- Dr. J. Stafleu,
TNO - Geological Survey of the Netherlands,
PO Box 80015,
3508 TA Utrecht,
The Netherlands
Visiting address
Princetonlaan 6,
3584 CB Utrecht - +31 88 866 46 67
Jan Stafleu
TNO - Geological Survey of the Netherlands, Geomodelling, Department Member
- From December 2006 to present: Developing three-dimensional geological subsurface models of the shallow subsurface o... moreFrom December 2006 to present:
Developing three-dimensional geological subsurface models of the shallow subsurface of the Netherlands - in particular the GeoTOP voxel model which provides a sound basis for subsurface related questions on, amongst others, groundwater extraction and management, land subsidence studies, aggregate resources and infrastructural issues.
From 1990 to 1995:
PhD Research involving seismic modelling of large outcrops. I produced seismic models of outcrops to study resolution problems in exploration seismic data, and to offer alternatives for traditional seismic interpretation techniquesedit
In a geological GIS-data recombination project, a digital map was produced that holds information on the Netherlands’ former coastal and delta plain landscapes in the last 14,000 years: the Holocene and the very end of the Pleistocene.... more
In a geological GIS-data recombination project, a digital map was produced that holds information on the Netherlands’ former coastal and delta plain landscapes in the last 14,000 years: the Holocene and the very end of the Pleistocene. The end product polygon maps are accompanied by a set of palaeoDEMs indicating the ‘attention depth’ for buried land surfaces and aquatic deposits; both for four time slices. This paper provides conceptual background on legend and construction principles of the polygon maps and the palaeoDEMs (‘decisions during the making off’) and a basic overview of the map product (‘landscape structure’, ‘burial depth’, ‘preservation’), visualised for the four time slices of RCE’s Archaeological Knowledge Kit. The text links the coastal plain buried landscape mapping for time slices T0, T1, T2 and T3, to the other Knowledge Kit activities described in this volume, notably that of the Archaeological Landscape map (for time slice T4 in the coastal plain part of The Netherlands, for time slice T0 to T4 in the Pleistocene uplands)
Research Interests:
Geographic decision support systems aim to integrate and process data originating from different sources and different data providers in order to create suitability models. A suitability model denotes how suitable geographic locations are... more
Geographic decision support systems aim to integrate and process data originating from different sources and different data providers in order to create suitability models. A suitability model denotes how suitable geographic locations are for a specific purpose on which decision-makers need to make a decision. Particularly in the presence of volunteered information, data quality assessment becomes an important aspect of a decision-making process. Geographic data are commonly prone to incompleteness, imprecision and uncertainty, and this is even more the case with volunteered data. To correctly inform the users, it is essential to communicate not only the suitability degrees highlighted in a suitability model, but also the confidence about these suitability degrees as can be derived from data quality assessment. In this chapter, a novel hierarchical approach for data quality assessment, supporting the computation of associated confidence degrees, is introduced. To illustrate its added value, aspects of the project Transnational and Integrated Long-term marine Exploitation Strategies (TILES) are used. Providing confidence information adds an extra dimension to the decision-making process and leads to more sound decisions.
Research Interests:
Practical and scientific knowledge related to groundwater research and innovation is scattered amongst various actors throughout Europe. KINDRA (Knowledge Inventory for Hydrogeology Research) is developing an inventory of this groundwater... more
Practical and scientific knowledge related to groundwater research and innovation is scattered amongst various actors throughout Europe. KINDRA (Knowledge Inventory for Hydrogeology Research) is developing an inventory of this groundwater knowledge-base, following a new Harmonised Research Classification System (HRC-SYS).
An European Inventory of Groundwater Research (EIGR) is being compiled, including survey results and research activities, projects and programmes, all of which are essential to identify and determine future trends, critical challenges and research gaps. The objective is to improve management and policy development for groundwater resources on a EU level coherently with the Water Framework Directive (WFD) and the Groundwater Directive (GWD).
KINDRA counts on the direct involvement of the European Federation of Geologists (EFG), which will provide the technical expertise of its national members actively cooperating within the project. In case of the Netherlands, the national member is KNGMG.
An important task in the KINDRA project is the organisation of a National Workshop on Hydrogeology in each of the 20 participating countries. KNGMG (Royal Geological and Mining Society of the Netherlands) and NHV (Hydrological Society of the Netherlands) co-organised the Dutch workshop on November 10, 2016. Venue was the office of TNO – Geological Survey of the Netherlands and Deltares in Utrecht.
The workshop was aimed at identifying research gaps in the field of hydrogeology. Research gaps may include missing scientific knowledge about the groundwater system, but also missing information or lack of knowledge of existing information. A second goal of the workshop was to discuss possible solutions to bridge the research gaps.
This report includes the programme of the workshop (Chapter 2), a summary of the presentations (Chapter 3) and a summary of the two discussion round on research gaps (Chapter 4). Chapter 5 lists the participants as well as the professionals who were interested in the workshop but were not able to attend.
An European Inventory of Groundwater Research (EIGR) is being compiled, including survey results and research activities, projects and programmes, all of which are essential to identify and determine future trends, critical challenges and research gaps. The objective is to improve management and policy development for groundwater resources on a EU level coherently with the Water Framework Directive (WFD) and the Groundwater Directive (GWD).
KINDRA counts on the direct involvement of the European Federation of Geologists (EFG), which will provide the technical expertise of its national members actively cooperating within the project. In case of the Netherlands, the national member is KNGMG.
An important task in the KINDRA project is the organisation of a National Workshop on Hydrogeology in each of the 20 participating countries. KNGMG (Royal Geological and Mining Society of the Netherlands) and NHV (Hydrological Society of the Netherlands) co-organised the Dutch workshop on November 10, 2016. Venue was the office of TNO – Geological Survey of the Netherlands and Deltares in Utrecht.
The workshop was aimed at identifying research gaps in the field of hydrogeology. Research gaps may include missing scientific knowledge about the groundwater system, but also missing information or lack of knowledge of existing information. A second goal of the workshop was to discuss possible solutions to bridge the research gaps.
This report includes the programme of the workshop (Chapter 2), a summary of the presentations (Chapter 3) and a summary of the two discussion round on research gaps (Chapter 4). Chapter 5 lists the participants as well as the professionals who were interested in the workshop but were not able to attend.
Research Interests:
Dit rapport beschrijft de hydraulische parameterisering van de holocene eenheden van het GeoTOP modelgebied Zeeland. De nadruk ligt daarbij op het opschalen van in het laboratorium aan monsters gemeten doorlatendheden naar het voxelmodel... more
Dit rapport beschrijft de hydraulische parameterisering van de holocene eenheden van het GeoTOP modelgebied Zeeland. De nadruk ligt daarbij op het opschalen van in het laboratorium aan monsters gemeten doorlatendheden naar het voxelmodel met voxels van 100 bij 100 bij 0,5 m.
Het rapport beschrijft twee opschalingsmethoden: de "simpele opschaling", bruikbaar voor relatief homogene geologische eenheden, en een nieuw ontwikkelde "complexe opschaling" die geschikt is voor heterogeen samengestelde eenheden. Daarnaast laat het rapport zien hoe GeoTOP met de opgeschaalde waarden wordt gevuld en gebruikt om een kaart van de weerstand (c-waardekaart) van de holocene eenheden te maken. In de discussie is aandacht voor een uitgebreide toets van de gemodelleerde weerstand aan een set van pompproeven in de provincie Zeeland.
Het rapport beschrijft twee opschalingsmethoden: de "simpele opschaling", bruikbaar voor relatief homogene geologische eenheden, en een nieuw ontwikkelde "complexe opschaling" die geschikt is voor heterogeen samengestelde eenheden. Daarnaast laat het rapport zien hoe GeoTOP met de opgeschaalde waarden wordt gevuld en gebruikt om een kaart van de weerstand (c-waardekaart) van de holocene eenheden te maken. In de discussie is aandacht voor een uitgebreide toets van de gemodelleerde weerstand aan een set van pompproeven in de provincie Zeeland.
Research Interests:
This product specification describes the 3D geological subsurface model GeoTOP, version 1.3, produced by TNO - Geological Survey of the Netherlands. On the basis of this specification the reader cab decide whether or not the GeoTOP model... more
This product specification describes the 3D geological subsurface model GeoTOP, version 1.3, produced by TNO - Geological Survey of the Netherlands. On the basis of this specification the reader cab decide whether or not the GeoTOP model is appropriate for his or her application.
Research Interests:
Deze productspecificatie beschrijft het ondergrondmodel GeoTOP, versie 1.3, van TNO – Geologische Dienst Nederland. Op basis van deze specificatie kan de lezer beslissen of, en zo ja hoe, het ondergrondmodel voor zijn of haar toepassing... more
Deze productspecificatie beschrijft het ondergrondmodel GeoTOP, versie 1.3, van TNO – Geologische Dienst Nederland. Op basis van deze specificatie kan de lezer beslissen of, en zo ja hoe, het ondergrondmodel voor zijn of haar toepassing gebruikt kan worden.
Research Interests:
The NAM is preparing a new "Winningsplan", to be submitted in 2016. For this new Winningsplan, a new generation of Ground Motion Prediction Equations (GMPEs) will be developed. The overall scope is to reduce uncertainties in the hazard... more
The NAM is preparing a new "Winningsplan", to be submitted in 2016. For this new Winningsplan, a new generation of Ground Motion Prediction Equations (GMPEs) will be developed. The overall scope is to reduce uncertainties in the hazard and risk analysis by improvement of input data, such as Groningen-specific data, and better GMPEs. In the current GMPE, only one value for shear wave velocity (Vs) is used for the entire Groningen field (Vs30 = 200 mIs). The shallow subsurface of Groningen, consisting of Holocene and Pleistocene sediments is heterogeneous, resulting in variations of shear wave velocity. It is expected that part of the uncertainties in the seismic hazard and risk analysis can be reduced by including Groningen-specific information and knowledge of the subsurface to improve quantification of the site response caused by earthquakes
Deltares has built a geological model for the Groningen field (+ 5 km buffer) for the purpose of the construction of Vs30 maps and as input for the calculations of site amplification. These results will feed into the new GMPEs. The Geological model for the ~ite response at the Groningen Field (GSG-model) is, among other data sources, based on the beta version of GeoTOP (a 3D geological model of the Netherlands), provided by TNO Geological Survey of the Netherlands. The GSG-model built by Deltares consists of a map defining geological areas and voxel stacks containing stratigraphy and lithological class with depth. Additionally, a state-of-the-art Vs30 map was derived for the Groningen field + 5 km buffer, taking into account Groningen-specific Vs relations and the geology from the GSG-model.
This report describes the method for the construction and the results of version 1 of the GSGmodel, the quality checks performed on the model and recommendations for future versions. When more data becomes available, updates of the GSG-model are anticipated.
Deltares has built a geological model for the Groningen field (+ 5 km buffer) for the purpose of the construction of Vs30 maps and as input for the calculations of site amplification. These results will feed into the new GMPEs. The Geological model for the ~ite response at the Groningen Field (GSG-model) is, among other data sources, based on the beta version of GeoTOP (a 3D geological model of the Netherlands), provided by TNO Geological Survey of the Netherlands. The GSG-model built by Deltares consists of a map defining geological areas and voxel stacks containing stratigraphy and lithological class with depth. Additionally, a state-of-the-art Vs30 map was derived for the Groningen field + 5 km buffer, taking into account Groningen-specific Vs relations and the geology from the GSG-model.
This report describes the method for the construction and the results of version 1 of the GSGmodel, the quality checks performed on the model and recommendations for future versions. When more data becomes available, updates of the GSG-model are anticipated.
Research Interests:
TNO Report (in Dutch) about a detailed 3D geological model of the shallow subsurface of a nature reserve in the southern Netherlands.
Research Interests:
Deze productspecificatie beschrijft het ondergrondmodel GeoTOP, versie 1.2, van TNO – Geologische Dienst Nederland. Op basis van deze specificatie kan de lezer beslissen of, en zo ja hoe, het ondergrondmodel voor zijn of haar toepassing... more
Deze productspecificatie beschrijft het ondergrondmodel GeoTOP, versie 1.2, van TNO – Geologische Dienst Nederland. Op basis van deze specificatie kan de lezer beslissen of, en zo ja hoe, het ondergrondmodel voor zijn of haar toepassing gebruikt kan worden.
Research Interests:
Dit rapport geeft een gedetailleerde beschrijving van GeoTOP: het beschrijft wat GeoTOP is, op welke brongegevens het is gebaseerd en hoe het gemaakt wordt. Ook worden de uit GeoTOP afgeleide producten beschreven die (vrijwel) direct... more
Dit rapport geeft een gedetailleerde beschrijving van GeoTOP: het beschrijft wat GeoTOP is, op welke brongegevens het is gebaseerd en hoe het gemaakt wordt. Ook worden de uit GeoTOP afgeleide producten beschreven die (vrijwel) direct toepasbaar zijn bij het analyseren en oplossen van ondergrondvraagstukken.
Het rapport start met een beschrijving van de verschillende onderdelen van het model: geïnterpreteerde boringen, rasters van toppen en basissen van stratigrafische eenheden en voxels met stratigrafische en lithologische kenmerken (hoofdstuk 2). Vervolgens wordt in hoofdstuk 3 een overzicht gegeven van de bij GeoTOP betrokken brongegevens, o.a. boringen, sonderingen en kaartmateriaal. Hoofdstuk 4 beslaat het grootste deel van het rapport en geeft een gedetailleerde beschrijving van het proces waarmee GeoTOP wordt gemaakt. Dit proces bestaat uit 5 werkprocessen: 1) voorbereiden basisgegevens; 2) indelen stratigrafie; 3) modelleren stratigrafie (lagenmodel); 4) modelleren lithoklassen (voxelmodel) en 5) maken afgeleide producten. Het rapport eindigt met een aantal bijlagen die uitleg geven over in GeoTOP gebruikte coderingen en bestandsformaten.
Het rapport start met een beschrijving van de verschillende onderdelen van het model: geïnterpreteerde boringen, rasters van toppen en basissen van stratigrafische eenheden en voxels met stratigrafische en lithologische kenmerken (hoofdstuk 2). Vervolgens wordt in hoofdstuk 3 een overzicht gegeven van de bij GeoTOP betrokken brongegevens, o.a. boringen, sonderingen en kaartmateriaal. Hoofdstuk 4 beslaat het grootste deel van het rapport en geeft een gedetailleerde beschrijving van het proces waarmee GeoTOP wordt gemaakt. Dit proces bestaat uit 5 werkprocessen: 1) voorbereiden basisgegevens; 2) indelen stratigrafie; 3) modelleren stratigrafie (lagenmodel); 4) modelleren lithoklassen (voxelmodel) en 5) maken afgeleide producten. Het rapport eindigt met een aantal bijlagen die uitleg geven over in GeoTOP gebruikte coderingen en bestandsformaten.
INTRODUCTION Seismic reflection profiling is the most powerful geophysical method of investigating the upper part of the Earth's crust. Modern two- and three-dimensional seismic surveys provide us with images that look so much like... more
INTRODUCTION
Seismic reflection profiling is the most powerful geophysical method of investigating the upper part of the Earth's crust. Modern two- and three-dimensional seismic surveys provide us with images that look so much like cross-sections through the subsurface, that it is tempting to interpret them as such. However, a seismic section is not the exact equivalent of a geologic cross-section. One of the reasons why such an one-to-one relationship between seismic records and geologic cross-sections does not exist is the limited resolution of seismic waves.
In areas of substantial well control, one-dimensional seismic models of wire line logs can be used to tie high-resolution log readings to the low-resolution seismic information. These models can serve as adequate ground control for identification and interpretation of individual seismic reflections. Understanding seismic sequences and unconformities, however, requires simulation of two-dimensional sections. This thesis presents seismic models of large-scale outcrops to study the seismic resolution of detailed stratigraphic cross-sections.
METHODS
The seismic models in this thesis were constructed using a standard methodology. It consists of the following five steps.
1) Construction of a geologic cross-section that shows the distribution of major lithologies. Large-scale stratal patterns observed on outcrop photos and photomosaics were combined with detailed field measurements. To study resolution problems, the vertical distance over which changes in acoustic properties occur has to be much smaller than the wavelength. 2) Determination of impedance by measuring petrophysical properties of major lithologies or by using published data. 3) Construction of an impedance model, i.e., a cross-section that shows the spatial distribution of velocity and density. The impedance models in this thesis are among the first in which the impedance boundaries mostly coincide with bedding planes. 4) Raytracing to compute a time- or depth section of reflectivity, using own software and commercially available programs. 5) Convolution of the reflectivity section with a source wavelet. Systematic comparisons of seismic models with different frequency contents reveal what frequency is needed to resolve complex stratigraphic features accurately.
CASE STUDIES
Chapters 2 to 7 present case-studies from a variety of areas and stratigraphic intervals (Part I).
Chapter 2 describes the acquisition and processing of shallow seismic surveys on Tertiary outcrops in the Sorbas basin (SE Spain). Seismic models based on outcrop observations, are used in the interpretation of the seismic data.
The seismic models in Chapters 3 to 7 are entirely from carbonate margins or carbonate platform-to-basin transitions. Carbonate platforms are characterized by rapid lateral variations in facies and geometry. The examples show how resolution problems can result from constructive and destructive interference in areas of such rapid lateral facies transitions or other zones of complex sediment geometry.
Examples include the platform-to-basin transition at the Picco di Vallandro and the platform margin of the Sella, both from the Triassic of the Dolomites (Chapters 3 and 4, respectively); the Early Jurassic Djebel Bou Dahar platform and basin-fill geometry (Morocco, Chapter 5); the Early Cretaceous of the Vercors platform (France, Chapter 6); and a mixed carbonate-siliciclastic shelf-margin from the Permian Guadalupe Mountains (New Mexico, USA, Chapter 7).
In some case studies, the seismic models were compared with real seismic records from the same stratigraphic setting (Chapters 2 and 7) or a similar situation (Chapters 5 and 6).
IMPEDANCE DISTRIBUTION
A crucial step in the construction of an outcrop-based seismic model is the conversion of the geologic cross-section into an impedance model showing the distribution of velocity and density (Part II). This can be done by directly measuring the acoustic properties of the rocks or by defining another variable, e.g. gamma-ray or resistivity, that follows the variation of impedance and can serve as a proxy of impedance. Chapter 8 shows how seismic models based on these measurements can be compared with seismic models based on sonic and density logs from boreholes. These comparisons will help to improve methods of converting outcrop data into realistic seismic models.
Erosional topography may be another possible proxy for impedance that is relatively easy to measure in outcrop. The underlying assumption is that resistance against erosion, "erosive hardness", is closely related to impedance, "acoustic hardness". In Chapter 9, photogrammetric techniques were used to establish the relationship between topography and impedance in the Vercors.
CONCLUSIONS
The lithologic detail modeled in the case studies lead to some striking results, particularly the discovery of pseudo-unconformities. Pseudo-unconformities are unconformities in seismics, but correspond to rapid changes of dip and facies in outcrop. In many case studies, lateral amplitude variations did not result from lateral variations in impedance contrasts, but from changes in depositional dip along carbonate platform slopes or from variable bed thickness.
Proxies of velocity, which can be more easily measured than velocity itself, include porosity (if over 10-15%), clay content (if over 10-15%), and bulk density (if both porosity and clay content are less than 10-15%). Another proxy of impedance is erosional relief, expressed as the slope angle.
Seismic reflection profiling is the most powerful geophysical method of investigating the upper part of the Earth's crust. Modern two- and three-dimensional seismic surveys provide us with images that look so much like cross-sections through the subsurface, that it is tempting to interpret them as such. However, a seismic section is not the exact equivalent of a geologic cross-section. One of the reasons why such an one-to-one relationship between seismic records and geologic cross-sections does not exist is the limited resolution of seismic waves.
In areas of substantial well control, one-dimensional seismic models of wire line logs can be used to tie high-resolution log readings to the low-resolution seismic information. These models can serve as adequate ground control for identification and interpretation of individual seismic reflections. Understanding seismic sequences and unconformities, however, requires simulation of two-dimensional sections. This thesis presents seismic models of large-scale outcrops to study the seismic resolution of detailed stratigraphic cross-sections.
METHODS
The seismic models in this thesis were constructed using a standard methodology. It consists of the following five steps.
1) Construction of a geologic cross-section that shows the distribution of major lithologies. Large-scale stratal patterns observed on outcrop photos and photomosaics were combined with detailed field measurements. To study resolution problems, the vertical distance over which changes in acoustic properties occur has to be much smaller than the wavelength. 2) Determination of impedance by measuring petrophysical properties of major lithologies or by using published data. 3) Construction of an impedance model, i.e., a cross-section that shows the spatial distribution of velocity and density. The impedance models in this thesis are among the first in which the impedance boundaries mostly coincide with bedding planes. 4) Raytracing to compute a time- or depth section of reflectivity, using own software and commercially available programs. 5) Convolution of the reflectivity section with a source wavelet. Systematic comparisons of seismic models with different frequency contents reveal what frequency is needed to resolve complex stratigraphic features accurately.
CASE STUDIES
Chapters 2 to 7 present case-studies from a variety of areas and stratigraphic intervals (Part I).
Chapter 2 describes the acquisition and processing of shallow seismic surveys on Tertiary outcrops in the Sorbas basin (SE Spain). Seismic models based on outcrop observations, are used in the interpretation of the seismic data.
The seismic models in Chapters 3 to 7 are entirely from carbonate margins or carbonate platform-to-basin transitions. Carbonate platforms are characterized by rapid lateral variations in facies and geometry. The examples show how resolution problems can result from constructive and destructive interference in areas of such rapid lateral facies transitions or other zones of complex sediment geometry.
Examples include the platform-to-basin transition at the Picco di Vallandro and the platform margin of the Sella, both from the Triassic of the Dolomites (Chapters 3 and 4, respectively); the Early Jurassic Djebel Bou Dahar platform and basin-fill geometry (Morocco, Chapter 5); the Early Cretaceous of the Vercors platform (France, Chapter 6); and a mixed carbonate-siliciclastic shelf-margin from the Permian Guadalupe Mountains (New Mexico, USA, Chapter 7).
In some case studies, the seismic models were compared with real seismic records from the same stratigraphic setting (Chapters 2 and 7) or a similar situation (Chapters 5 and 6).
IMPEDANCE DISTRIBUTION
A crucial step in the construction of an outcrop-based seismic model is the conversion of the geologic cross-section into an impedance model showing the distribution of velocity and density (Part II). This can be done by directly measuring the acoustic properties of the rocks or by defining another variable, e.g. gamma-ray or resistivity, that follows the variation of impedance and can serve as a proxy of impedance. Chapter 8 shows how seismic models based on these measurements can be compared with seismic models based on sonic and density logs from boreholes. These comparisons will help to improve methods of converting outcrop data into realistic seismic models.
Erosional topography may be another possible proxy for impedance that is relatively easy to measure in outcrop. The underlying assumption is that resistance against erosion, "erosive hardness", is closely related to impedance, "acoustic hardness". In Chapter 9, photogrammetric techniques were used to establish the relationship between topography and impedance in the Vercors.
CONCLUSIONS
The lithologic detail modeled in the case studies lead to some striking results, particularly the discovery of pseudo-unconformities. Pseudo-unconformities are unconformities in seismics, but correspond to rapid changes of dip and facies in outcrop. In many case studies, lateral amplitude variations did not result from lateral variations in impedance contrasts, but from changes in depositional dip along carbonate platform slopes or from variable bed thickness.
Proxies of velocity, which can be more easily measured than velocity itself, include porosity (if over 10-15%), clay content (if over 10-15%), and bulk density (if both porosity and clay content are less than 10-15%). Another proxy of impedance is erosional relief, expressed as the slope angle.
Research Interests:
Koster, K., Stafleu, J., Cohen, K.M., Stouthamer, E., Busschers, F.S. and Middelkoop, H., 2018. Three-dimensional distribution of organic matter in coastal-deltaic peat: Implications for subsidence and carbon dioxide emissions by... more
Koster, K., Stafleu, J., Cohen, K.M., Stouthamer, E., Busschers, F.S. and Middelkoop, H., 2018. Three-dimensional distribution of organic matter in coastal-deltaic peat: Implications for subsidence and carbon dioxide emissions by human-induced peat oxidation. Anthropocene, doi: 10.1016/j.ancene.2018.03.001
Human-induced groundwater level lowering in the Holocene coastal-deltaic plain of the Netherlands causes oxidation of peat organic matter, resulting in land subsidence and carbon dioxide (CO2) emissions. Here, a three-dimensional (3D) analysis of the distribution of the remaining peat organic matter is presented, to quantify the potential of this area to further subsidence and CO2 emissions by oxidation. Hereto, we established relations between dry mass ratios of organic matter and sediment in peat formed in different environmental settings. This was combined with a high-resolution 3D geological model of the subsurface of the Netherlands to map the proportions of organic matter, clastic sediment and void space in peat.
The 3D model indicates that c. 15 km3 of Holocene peat is embedded in the coastal-deltaic plain subsurface, of which c. 1.5 km3 consists of organic matter, 0.4 km3 of sediment, and 13.1 km3 of void space. During future human-induced oxidation, this peat has a volumetric loss potential of 14.6 km3, responsible for locally 0.4–6.0 m of subsidence, and a CO2 emission of 2.0 Gton.
The 3D modelling revealed that the amount of peat organic matter varies considerably between regions. Especially the subsurface of urban areas overlying back-barrier peat were identified as hot-spots accommodating the highest quantities of peat organic matter. The peat in agricultural areas contains less organic matter but is more prone to oxidation than peat underlying urban areas, because in the latter settings anthropogenic brought-up soil restricts oxidation. Future mitigation strategies should therefore focus on restricting peat oxidation in the agricultural areas of the coastal-deltaic plain.
Human-induced groundwater level lowering in the Holocene coastal-deltaic plain of the Netherlands causes oxidation of peat organic matter, resulting in land subsidence and carbon dioxide (CO2) emissions. Here, a three-dimensional (3D) analysis of the distribution of the remaining peat organic matter is presented, to quantify the potential of this area to further subsidence and CO2 emissions by oxidation. Hereto, we established relations between dry mass ratios of organic matter and sediment in peat formed in different environmental settings. This was combined with a high-resolution 3D geological model of the subsurface of the Netherlands to map the proportions of organic matter, clastic sediment and void space in peat.
The 3D model indicates that c. 15 km3 of Holocene peat is embedded in the coastal-deltaic plain subsurface, of which c. 1.5 km3 consists of organic matter, 0.4 km3 of sediment, and 13.1 km3 of void space. During future human-induced oxidation, this peat has a volumetric loss potential of 14.6 km3, responsible for locally 0.4–6.0 m of subsidence, and a CO2 emission of 2.0 Gton.
The 3D modelling revealed that the amount of peat organic matter varies considerably between regions. Especially the subsurface of urban areas overlying back-barrier peat were identified as hot-spots accommodating the highest quantities of peat organic matter. The peat in agricultural areas contains less organic matter but is more prone to oxidation than peat underlying urban areas, because in the latter settings anthropogenic brought-up soil restricts oxidation. Future mitigation strategies should therefore focus on restricting peat oxidation in the agricultural areas of the coastal-deltaic plain.
Research Interests:
Koster, K., Cohen, K.M., Stafleu, J. and Stouthamer, E., 2018. Using 14C-Dated Peat Beds for Reconstructing Subsidence by Compression in the Holland Coastal Plain of the Netherlands. Journal of Coastal Research, doi:... more
Koster, K., Cohen, K.M., Stafleu, J. and Stouthamer, E., 2018. Using 14C-Dated Peat Beds for Reconstructing Subsidence by Compression in the Holland Coastal Plain of the Netherlands. Journal of Coastal Research, doi: 10.2112/JCOASTRES-D-17-00093.1
Subsidence in the Holland coastal plain of the Netherlands was reconstructed from the vertical displacement of Holocene peat layers below their reference groundwater levels at the time of peat formation. This quantifies the part of subsidence that is due to compression processes and allows specification of the current state of peat compression in a map. 14C-dating of peat layers found intercalated in the Holocene sequence were used in the reconstruction. This dataset was combined with results from a recent coastal-deltaic plain wide three-dimensional (3D) interpolation of reference palaeo-groundwater levels, at which the intercalated peats are thought to have formed before they were buried, compressed, and vertically displaced. Empiric relations between reconstructed displacement and the thickness of overburden were determined and deployed in a national 3D geological subsurface model to establish a subsidence map with continuous cover of the coastal plain. The resulting maps show compressed peat layers under urbanized areas with 1 to 8 m of natural and anthropogenic overburden have subsided 1 to 5 m below the original level of formation. In the agricultural area of the coastal plain, where overburden is merely decimetres thick, consisting of fluvial flood- and sea-ingression deposits, peat generally experienced less than 1 m subsidence. The reference-level reconstruction method is deployable over large coastal plain areas to reconstruct subsidence caused by postdepositional vertical displacement of intercalated peat layers. It could therefore serve as an alternative approach for methods based on soil mechanics, which require input often not available for coastal plains on regional scales.
Subsidence in the Holland coastal plain of the Netherlands was reconstructed from the vertical displacement of Holocene peat layers below their reference groundwater levels at the time of peat formation. This quantifies the part of subsidence that is due to compression processes and allows specification of the current state of peat compression in a map. 14C-dating of peat layers found intercalated in the Holocene sequence were used in the reconstruction. This dataset was combined with results from a recent coastal-deltaic plain wide three-dimensional (3D) interpolation of reference palaeo-groundwater levels, at which the intercalated peats are thought to have formed before they were buried, compressed, and vertically displaced. Empiric relations between reconstructed displacement and the thickness of overburden were determined and deployed in a national 3D geological subsurface model to establish a subsidence map with continuous cover of the coastal plain. The resulting maps show compressed peat layers under urbanized areas with 1 to 8 m of natural and anthropogenic overburden have subsided 1 to 5 m below the original level of formation. In the agricultural area of the coastal plain, where overburden is merely decimetres thick, consisting of fluvial flood- and sea-ingression deposits, peat generally experienced less than 1 m subsidence. The reference-level reconstruction method is deployable over large coastal plain areas to reconstruct subsidence caused by postdepositional vertical displacement of intercalated peat layers. It could therefore serve as an alternative approach for methods based on soil mechanics, which require input often not available for coastal plains on regional scales.
Research Interests:
Koster, K., Stafleu, J. & Stouthamer, E., 2018. Differential subsidence in the urbanized coastal-deltaic plain of the Netherlands. Netherlands Journal of Geosciences, doi: 10.1017/njg.2018.11 The urbanised peat-rich coastal-deltaic... more
Koster, K., Stafleu, J. & Stouthamer, E., 2018. Differential subsidence in the urbanized coastal-deltaic plain of the Netherlands. Netherlands Journal of Geosciences, doi: 10.1017/njg.2018.11
The urbanised peat-rich coastal-deltaic plain of the Netherlands is severely subsiding due to human-induced phreatic groundwater level lowering, as this causes peat layers to compress and oxidise. To determine the potential susceptibility of this area to future subsidence by peat compression and oxidation, the effects of lowering present-day phreatic groundwater levels were quantitatively evaluated using a subsidence model. Input were a 3D geological subsurface voxel-model, modelled phreatic groundwater levels, and functions for peat compression and oxidation. Phreatic groundwater levels were lowered by 0.25 and 0.5 m, and the resulting peat compression and oxidation over periods of 15 and 30 years were determined. The model area comprised the major cities Amsterdam and Rotterdam, and their surrounding agricultural lands. The results revealed that for these scenarios agricultural areas may subside between 0.3 and 0.8 m; potential subsidence in Amsterdam and Rotterdam is considerably lower, less than 0.4 m. This is due to the presence of several metres thick anthropogenic brought-up soils overlying the peat below the urban areas, which has already compressed the peat to a depth below groundwater level, and thus minimises further compression and oxidation. In agricultural areas peat is often situated near the surface, and is therefore highly compressible and prone to oxidation. The averaged subsidence rates for the scenarios range between 7 and 13 mm a −1 , which is corresponds to present-day rates of subsidence in the peat areas of the Netherlands. These results contrast with the trend of coastal-deltaic subsidence in other deltas, with cities subsiding faster than agricultural areas. This difference is explained by the driver of subsidence: in other deltas, subsidence of urban areas is mainly due to deep aquifer extraction, whereas in the Netherlands subsidence is due to phreatic groundwater level lowering.
The urbanised peat-rich coastal-deltaic plain of the Netherlands is severely subsiding due to human-induced phreatic groundwater level lowering, as this causes peat layers to compress and oxidise. To determine the potential susceptibility of this area to future subsidence by peat compression and oxidation, the effects of lowering present-day phreatic groundwater levels were quantitatively evaluated using a subsidence model. Input were a 3D geological subsurface voxel-model, modelled phreatic groundwater levels, and functions for peat compression and oxidation. Phreatic groundwater levels were lowered by 0.25 and 0.5 m, and the resulting peat compression and oxidation over periods of 15 and 30 years were determined. The model area comprised the major cities Amsterdam and Rotterdam, and their surrounding agricultural lands. The results revealed that for these scenarios agricultural areas may subside between 0.3 and 0.8 m; potential subsidence in Amsterdam and Rotterdam is considerably lower, less than 0.4 m. This is due to the presence of several metres thick anthropogenic brought-up soils overlying the peat below the urban areas, which has already compressed the peat to a depth below groundwater level, and thus minimises further compression and oxidation. In agricultural areas peat is often situated near the surface, and is therefore highly compressible and prone to oxidation. The averaged subsidence rates for the scenarios range between 7 and 13 mm a −1 , which is corresponds to present-day rates of subsidence in the peat areas of the Netherlands. These results contrast with the trend of coastal-deltaic subsidence in other deltas, with cities subsiding faster than agricultural areas. This difference is explained by the driver of subsidence: in other deltas, subsidence of urban areas is mainly due to deep aquifer extraction, whereas in the Netherlands subsidence is due to phreatic groundwater level lowering.
Research Interests:
Kruiver, P.P., Wiersma, A., Kloosterman, F.H., De Lange, G., Korff, M., Stafleu, J., Busschers, F.S., Harting, R., Gunnink, J.L., Green, R.A., Van Elk, J. and Doornhof, D., 2017. Characterisation of the Groningen subsurface for seismic... more
Kruiver, P.P., Wiersma, A., Kloosterman, F.H., De Lange, G., Korff, M., Stafleu, J., Busschers, F.S., Harting, R., Gunnink, J.L., Green, R.A., Van Elk, J. and Doornhof, D., 2017. Characterisation of the Groningen subsurface for seismic hazard and risk modelling. Netherlands Journal of Geosciences, 96: 215-233, doi:10.1017/njg.2017.11
The shallow subsurface of Groningen, the Netherlands, is heterogeneous due to its formation in a Holocene tidal coastal setting on a periglacially and glacially inherited landscape with strong lateral variation in subsurface architecture. Soft sediments with low, small-strain shear wave velocities (V S30 around 200 m s −1) are known to amplify earthquake motions. Knowledge of the architecture and properties of the subsurface and the combined effect on the propagation of earthquake waves is imperative for the prediction of geohazards of ground shaking and liquefaction at the surface. In order to provide information for the seismic hazard and risk analysis, two geological models were constructed. The first is the 'Geological model for Site response in Groningen' (GSG model) and is based on the detailed 3D GeoTOP voxel model containing lithostratigraphy and lithoclass attributes. The GeoTOP model was combined with information from boreholes, cone penetration tests, regional digital geological and geohydrological models to cover the full range from the surface down to the base of the North Sea Supergroup (base Paleogene) at ∼800 m depth. The GSG model consists of a microzonation based on geology and a stack of soil stratigraphy for each of the 140,000 grid cells (100 m × 100 m) to which properties (V S and parameters relevant for nonlinear soil behaviour) were assigned. The GSG model serves as input to the site response calculations that feed into the Ground Motion Model. The second model is the 'Geological model for Liquefaction sensitivity in Groningen' (GLG). Generally, loosely packed sands might be susceptible to liquefaction upon earthquake shaking. In order to delineate zones of loosely packed sand in the first 40 m below the surface, GeoTOP was combined with relative densities inferred from a large cone penetration test database. The marine Naaldwijk and Eem Formations have the highest proportion of loosely packed sand (31% and 38%, respectively) and thus are considered to be the most vulnerable to liquefaction; other units contain 5–17% loosely packed sand. The GLG model serves as one of the inputs for further research on the liquefaction potential in Groningen, such as the development of region-specific magnitude scaling factors (MSF) and depth–stress reduction relationships (r d).
The shallow subsurface of Groningen, the Netherlands, is heterogeneous due to its formation in a Holocene tidal coastal setting on a periglacially and glacially inherited landscape with strong lateral variation in subsurface architecture. Soft sediments with low, small-strain shear wave velocities (V S30 around 200 m s −1) are known to amplify earthquake motions. Knowledge of the architecture and properties of the subsurface and the combined effect on the propagation of earthquake waves is imperative for the prediction of geohazards of ground shaking and liquefaction at the surface. In order to provide information for the seismic hazard and risk analysis, two geological models were constructed. The first is the 'Geological model for Site response in Groningen' (GSG model) and is based on the detailed 3D GeoTOP voxel model containing lithostratigraphy and lithoclass attributes. The GeoTOP model was combined with information from boreholes, cone penetration tests, regional digital geological and geohydrological models to cover the full range from the surface down to the base of the North Sea Supergroup (base Paleogene) at ∼800 m depth. The GSG model consists of a microzonation based on geology and a stack of soil stratigraphy for each of the 140,000 grid cells (100 m × 100 m) to which properties (V S and parameters relevant for nonlinear soil behaviour) were assigned. The GSG model serves as input to the site response calculations that feed into the Ground Motion Model. The second model is the 'Geological model for Liquefaction sensitivity in Groningen' (GLG). Generally, loosely packed sands might be susceptible to liquefaction upon earthquake shaking. In order to delineate zones of loosely packed sand in the first 40 m below the surface, GeoTOP was combined with relative densities inferred from a large cone penetration test database. The marine Naaldwijk and Eem Formations have the highest proportion of loosely packed sand (31% and 38%, respectively) and thus are considered to be the most vulnerable to liquefaction; other units contain 5–17% loosely packed sand. The GLG model serves as one of the inputs for further research on the liquefaction potential in Groningen, such as the development of region-specific magnitude scaling factors (MSF) and depth–stress reduction relationships (r d).
Research Interests:
Kruiver, P.P., Van Dedem, E., Romijn, R., De Lange, G., Korff, M., Stafleu, J., Gunnink, J.L., Rodriguez-Marek, A., Bommer, J.J., Van Elk, J., Doornhof, D., 2017. An integrated shear-wave velocity model for the Groningen gas field, The... more
Kruiver, P.P., Van Dedem, E., Romijn, R., De Lange, G., Korff, M., Stafleu, J., Gunnink, J.L., Rodriguez-Marek, A., Bommer, J.J., Van Elk, J., Doornhof, D., 2017. An integrated shear-wave velocity model for the Groningen gas field, The Netherlands. Bull. Earthquake Eng. 15: 3555-3580, doi: 10.1007/s10518-017-0105-y
A regional shear-wave velocity (VS) model has been developed for the Groningen gas field in the Netherlands as the basis for seismic microzonation of an area of more than 1000 km2. The VS model, extending to a depth of almost 1 km, is an essential input to the modelling of hazard and risk due to induced earthquakes in the region. The detailed VS profiles are constructed from a novel combination of three data sets covering different, partially overlapping depth ranges. The uppermost 50 m of the VS profiles are obtained from a high-resolution geological model with representative VS values assigned to the sediments. Field measurements of VS were used to derive representative VS values for the different types of sediments. The profiles from 50 to 120 m are obtained from inversion of surface waves recorded (as noise) during deep seismic reflection profiling of the gas reservoir. The deepest part of the profiles is obtained from sonic logging and VP–VS relationships based on measurements in deep boreholes. Criteria were established for the splicing of the three portions to generate continuous models over the entire depth range for use in site response calculations, for which an elastic half-space is assumed to exist below a clear stratigraphic boundary and impedance contrast encountered at about 800 m depth. In order to facilitate fully probabilistic site response analyses, a scheme for the randomisation of the VS profiles is implemented.
A regional shear-wave velocity (VS) model has been developed for the Groningen gas field in the Netherlands as the basis for seismic microzonation of an area of more than 1000 km2. The VS model, extending to a depth of almost 1 km, is an essential input to the modelling of hazard and risk due to induced earthquakes in the region. The detailed VS profiles are constructed from a novel combination of three data sets covering different, partially overlapping depth ranges. The uppermost 50 m of the VS profiles are obtained from a high-resolution geological model with representative VS values assigned to the sediments. Field measurements of VS were used to derive representative VS values for the different types of sediments. The profiles from 50 to 120 m are obtained from inversion of surface waves recorded (as noise) during deep seismic reflection profiling of the gas reservoir. The deepest part of the profiles is obtained from sonic logging and VP–VS relationships based on measurements in deep boreholes. Criteria were established for the splicing of the three portions to generate continuous models over the entire depth range for use in site response calculations, for which an elastic half-space is assumed to exist below a clear stratigraphic boundary and impedance contrast encountered at about 800 m depth. In order to facilitate fully probabilistic site response analyses, a scheme for the randomisation of the VS profiles is implemented.
Research Interests:
We present an interpolation model that describes Holocene groundwater level rise and the creation of accommodation space in 3D in the Rhine-Meuse delta – the Netherlands. The model area (ca. 12 400 km2) covers two palaeovalleys of Late... more
We present an interpolation model that describes Holocene groundwater level rise and the creation of accommodation space in 3D in the Rhine-Meuse delta – the Netherlands. The model area (ca. 12 400 km2) covers two palaeovalleys of Late Pleistocene age (each 30 km wide) and the overlying Holocene deposits of the Rhine-Meuse delta, the Holland coastal plain, and the Zuiderzee former lagoon. Water table rise is modelled from 10 800 to 1000 cal. BP, making use of age-depth relations based on 384 basal peat index points, and producing output in the form of stacked palaeo groundwater surfaces, groundwater age-depth curves, and voxel sets. These products allow to resolve (i) regional change and variations of inland water table slopes, (ii) spatial differences in the timing and pacing of transgression, and (iii) analysis of interplay of coastal, fluvial and subsidence controls on the provision of accommodation space. The interpolation model is a multi-parameter trend function, to which a 3D-kriging procedure of the residuals is added. This split design deploys a generic approach for modelling provision of accommodation space in deltas and coastal lowlands, aiming to work both in areas of intermediate data availability and in the most data-rich environments. Major provision of accommodation space occurred from 8500 cal BP onwards, but a different evolution occurred in each of the two palaeovalleys. In the northern valley, creation of accommodation space began to stall at 7500 cal BP, while in the southern valley provision of new accommodation space in considerable quantities continued longer. The latter is due to the floodplain gradient that was maintained by the Rhine, which distinguishes the fluvial deltaic environment from the rest of the back-barrier coastal plain. The interpolation results allow advanced mapping and investigation of apparent spatial differences in Holocene aggradation in larger coastal sedimentary systems. Furthermore, they provide a means to generate first-order age information with centennial precision for 3D geological subsurface models of Holocene deltas and valley fills. As such, the interpolation is of use in studies into past and present land subsidence and into low land sedimentation.
Research Interests:
Research Interests:
Aggregate resource assessments, derived from three subsequent generations of voxel models, were compared in a qualitative way to illustrate and discuss modelling progress. We compared the models in terms of both methodology and... more
Aggregate resource assessments, derived from three subsequent generations of voxel models, were compared in a qualitative way to illustrate and
discuss modelling progress. We compared the models in terms of both methodology and usability. All three models were produced by the Geological
Survey of the Netherlands. Aggregate is granular mineral material used in building and construction, and in this case consists of sand and gravel.
On each occasion ever-increasing computer power allowed us to model at a higher resolution and use more geological information to constrain
interpolations. The two oldest models, built in 2005 and 2007, were created specifically for aggregate resource assessments, the first as proof of
concept, the second for an online resource information system. The third model was derived from the ongoing multipurpose systematic 3D modelling
programme GeoTOP. We used a study area of 40 x 40 km located in the central Netherlands, which encompasses a section of the Rhine-Meuse delta
and adjacent glacial terrains to the north. Aggregate resource assessments rely on the extent to which the occurrence and grain size of sand and
gravel are resolved, and on proper representation of clay and peat layers (overburden and intercalations) that affect exploitability. Average model
properties (e.g. total aggregate content) are about the same in all three models, except for a difference resulting from converting older lithological
classifications to the current one. This difference illustrates that data selection and preparation are paramount, especially when dealing with quality
issues. Generally speaking the results of the aggregate resource assessments are consistent and satisfactory for all three models, provided that they
are judged at the appropriate scale. However, the assessments based on GeoTOP best approach the desired scale of use for the aggregates industry;
in that sense progress was significant and each model was a better fit for the purpose.
discuss modelling progress. We compared the models in terms of both methodology and usability. All three models were produced by the Geological
Survey of the Netherlands. Aggregate is granular mineral material used in building and construction, and in this case consists of sand and gravel.
On each occasion ever-increasing computer power allowed us to model at a higher resolution and use more geological information to constrain
interpolations. The two oldest models, built in 2005 and 2007, were created specifically for aggregate resource assessments, the first as proof of
concept, the second for an online resource information system. The third model was derived from the ongoing multipurpose systematic 3D modelling
programme GeoTOP. We used a study area of 40 x 40 km located in the central Netherlands, which encompasses a section of the Rhine-Meuse delta
and adjacent glacial terrains to the north. Aggregate resource assessments rely on the extent to which the occurrence and grain size of sand and
gravel are resolved, and on proper representation of clay and peat layers (overburden and intercalations) that affect exploitability. Average model
properties (e.g. total aggregate content) are about the same in all three models, except for a difference resulting from converting older lithological
classifications to the current one. This difference illustrates that data selection and preparation are paramount, especially when dealing with quality
issues. Generally speaking the results of the aggregate resource assessments are consistent and satisfactory for all three models, provided that they
are judged at the appropriate scale. However, the assessments based on GeoTOP best approach the desired scale of use for the aggregates industry;
in that sense progress was significant and each model was a better fit for the purpose.
Research Interests:
De carbonaatplatforms in de Dolomieten worden wel een “sedimentologische hemel op aarde” genoemd, en dat is niet zonder reden. Voor alpiene begrippen is er relatief weinig tektonische deformatie, en synsedimentaire breuken hebben in het... more
De carbonaatplatforms in de Dolomieten worden wel een “sedimentologische hemel op aarde” genoemd, en dat is niet zonder reden. Voor alpiene begrippen is er relatief weinig tektonische deformatie, en synsedimentaire breuken hebben in het Trias een veelheid aan kleine bekkens gecreëerd die zijn opgevuld met mergel en vulcanoklastisch materiaal dat veel makkelijker erodeert dan de gedolomitiseerde kalksteen van de carbonaatplatforms. De Triassische paleogeografie is door de erosie als het ware herschapen en je waant je op de bodem van de zee, omringd door carbonaatplatforms.
The Geological Survey of the Netherlands aims at building a 3D geological voxel model of the upper 30 m of the subsurface of the Netherlands in order to provide a sound basis for subsurface related questions on, amongst others,... more
The Geological Survey of the Netherlands aims at building a 3D geological voxel model of the upper 30 m of the subsurface of the Netherlands in order to provide a sound basis for subsurface related questions on, amongst others, groundwater extraction and management, land subsidence studies, aggregate resources and infrastructural issues. The Province of Zeeland (SW Netherlands, covering an area of approximately 70 by 75 km) was chosen as the starting point for this model due to an excellent dataset of 23,000 stratigraphically interpreted borehole descriptions.
The modelling procedure involved a number of steps. The first step is a geological schematisation of the borehole descriptions into units that have uniform sediment characteristics, using lithostratigraphical, lithofacies and lithological criteria. During the second modelling step, 2D bounding surfaces are constructed. These surfaces represent the top and base of the lithostratigraphical units and are used to place each voxel (100 by 100 by 0.5 metres) in the model within the correct lithostratigraphical unit. The lithological units in the borehole descriptions are used to perform a final 3D stochastic interpolation of lithofacies, lithology (clay, sand, peat) and if applicable, sand grain-size class within each lithostratigraphical unit. After this step, a three-dimensional geological model is obtained. The use of stochastic techniques such as Sequential Gaussian Simulation and Sequential Indicator Simulation, allowed us to compute probabilities for lithostratigraphy, lithofacies and lithology for each voxel, providing a measure of model uncertainty.
The procedures described above resulted in the first fully 3D regional-scale lithofacies model of the shallow subsurface in the Netherlands. The model provides important new insights on spatial connectivity of sediment units of, for example, sandy Holocene tidal channel systems. Our results represent a major step forward towards a fully 3D voxel model of the Netherlands.
The modelling procedure involved a number of steps. The first step is a geological schematisation of the borehole descriptions into units that have uniform sediment characteristics, using lithostratigraphical, lithofacies and lithological criteria. During the second modelling step, 2D bounding surfaces are constructed. These surfaces represent the top and base of the lithostratigraphical units and are used to place each voxel (100 by 100 by 0.5 metres) in the model within the correct lithostratigraphical unit. The lithological units in the borehole descriptions are used to perform a final 3D stochastic interpolation of lithofacies, lithology (clay, sand, peat) and if applicable, sand grain-size class within each lithostratigraphical unit. After this step, a three-dimensional geological model is obtained. The use of stochastic techniques such as Sequential Gaussian Simulation and Sequential Indicator Simulation, allowed us to compute probabilities for lithostratigraphy, lithofacies and lithology for each voxel, providing a measure of model uncertainty.
The procedures described above resulted in the first fully 3D regional-scale lithofacies model of the shallow subsurface in the Netherlands. The model provides important new insights on spatial connectivity of sediment units of, for example, sandy Holocene tidal channel systems. Our results represent a major step forward towards a fully 3D voxel model of the Netherlands.
Research Interests:
This paper corresponds to Chapter 12 of a report on the "current status of 3D geological modelling". This report was published by the Illinois and British Geological Surveys. The URL provides a link to the full report. The PDF contains... more
This paper corresponds to Chapter 12 of a report on the "current status of 3D geological modelling". This report was published by the Illinois and British Geological Surveys. The URL provides a link to the full report. The PDF contains the cover and Chapter 12 only.
Full reference:
Stafleu, J., Maljers, D., Busschers, F.S., Gunnink, J.L. and Vernes, R.W., 2011. TNO – Geological Survey of the Netherlands: 3-D Geological Modeling of the Upper 500 to 1,000 Meters of the Dutch Subsurface. In: Berg, R.C., Mathers, S.J., Kessler, H. & Keefer, D.A. (eds.): Synopsis of Current Three-dimensional Geological Mapping and Modeling in Geological Survey Organizations, Illinois State Geological Survey Circular 578, 64-68.
Full reference:
Stafleu, J., Maljers, D., Busschers, F.S., Gunnink, J.L. and Vernes, R.W., 2011. TNO – Geological Survey of the Netherlands: 3-D Geological Modeling of the Upper 500 to 1,000 Meters of the Dutch Subsurface. In: Berg, R.C., Mathers, S.J., Kessler, H. & Keefer, D.A. (eds.): Synopsis of Current Three-dimensional Geological Mapping and Modeling in Geological Survey Organizations, Illinois State Geological Survey Circular 578, 64-68.
Research Interests:
In the Sella platform of the Dolomite Alps, the horizontal beds of the Raibl Formation directly overlie the Upper Schlern Dolomite (Cassian Dolomite of some authors). The Schlern Dolomite comprises steep clinoforms, together with a few... more
In the Sella platform of the Dolomite Alps, the horizontal beds of the Raibl Formation directly overlie the Upper Schlern Dolomite (Cassian Dolomite of some authors). The Schlern Dolomite comprises steep clinoforms, together with a few tens of metres of horizontal topset beds in the platform interior.
Two-dimensional seismic modelling techniques were used to determine the seismic-response of this interesting situation. To perform this, two different lithological models were constructed based on outcrops of the Sella south face. The first model is that of a rapidly prograding platform with slow aggradation in the platform interior. The second model shows clinoforms toplapping against the topset beds of the platform interior.
P-wave velocities and bulk densities were assigned to the lithostratigraphical units in accordance with values from a similar study, involving the same formations. The vertical-incidence method was used to construct perfectly migrated time sections and depth sections of reflectivity. These were convolved with zero-phase Ricker wavelets of different peak frequencies to produce the final synthetic seismic sections.
Using conventional, low frequencies (e.g. 25 Hz), the seismic response of the two models is almost identical. The topset beds and the Schlern-Raibl contact appear as one event. In a real seismic survey, both sections would be interpreted as toplap of Schlern clinoforms against the Raibl Formation. At higher frequencies (75 Hz), however, differences are revealed. The angle of progradation in the progradation & aggradation model becomes visible, as opposed to the horizontal surface in the progradation & toplap model. Topset beds are resolved separate from the Raibl Formation, but still appear to form a single dipping pseudo-toplap surface.
Another modelling technique, simulating unmigrated sections, shows few differences between the two models even at high frequencies. In addition, the clinoforms are disturbed by the refraction of rays. This study demonstrates that, even under ideal acquisition and processing conditions, the seismic tool can introduce a pseudo-toplap. This implies that toplap in a seismic section is not necessarily toplap in outcrop.
Two-dimensional seismic modelling techniques were used to determine the seismic-response of this interesting situation. To perform this, two different lithological models were constructed based on outcrops of the Sella south face. The first model is that of a rapidly prograding platform with slow aggradation in the platform interior. The second model shows clinoforms toplapping against the topset beds of the platform interior.
P-wave velocities and bulk densities were assigned to the lithostratigraphical units in accordance with values from a similar study, involving the same formations. The vertical-incidence method was used to construct perfectly migrated time sections and depth sections of reflectivity. These were convolved with zero-phase Ricker wavelets of different peak frequencies to produce the final synthetic seismic sections.
Using conventional, low frequencies (e.g. 25 Hz), the seismic response of the two models is almost identical. The topset beds and the Schlern-Raibl contact appear as one event. In a real seismic survey, both sections would be interpreted as toplap of Schlern clinoforms against the Raibl Formation. At higher frequencies (75 Hz), however, differences are revealed. The angle of progradation in the progradation & aggradation model becomes visible, as opposed to the horizontal surface in the progradation & toplap model. Topset beds are resolved separate from the Raibl Formation, but still appear to form a single dipping pseudo-toplap surface.
Another modelling technique, simulating unmigrated sections, shows few differences between the two models even at high frequencies. In addition, the clinoforms are disturbed by the refraction of rays. This study demonstrates that, even under ideal acquisition and processing conditions, the seismic tool can introduce a pseudo-toplap. This implies that toplap in a seismic section is not necessarily toplap in outcrop.
Research Interests: Earth Sciences and Basin
Understanding the nature and formation of unconformities allows for better interpretations of the sediment architecture within a basin and, hence, a more accurate play and reservoir evaluation. Sequence stratigraphy assumes that 1)... more
Understanding the nature and formation of unconformities allows for better interpretations of the sediment architecture within a basin and, hence, a more accurate play and reservoir evaluation. Sequence stratigraphy assumes that 1) relative sea-level controls the generation of sequences and unconformities to the exclusion of all other mechanisms, and 2) all unconformities on seismic profiles are unconformities in the rock record.
Studies of the geometry of carbonate and siliciclastic shelves from seismic profiles showed that unconformities can form as the result/t of changes in the geometry of sediment dispersal systems and may be independent of sea-level. In addition, unconformities on seismic records may represent rapid transitions when studied in outcrop. Seismic modeling of carbonate platforms showed that, when using typical/ industrial/ frequencies, there are apparent truncations of the margin and significant basin ward shifts in the point of on/sp. The low resolution of the seismic tool also results in apparent pinch outs and pseudo-unconformities.
Unconformities on seismic profiles need not correspond to unconformities in the Iithological record. The seismic modeling of outcrops ultimately provides a means for evacuating the accuracy of unconformity interpretations based solely on seismic response. New constraints in the interpretation of unconformity geometry will/ lead not only to more accurate p/ay evacuations but possibly also to revision of the "Vail" sea-level curve which is based largely on the interpretation of unconformity geometries from industrial seismic profiles.
Studies of the geometry of carbonate and siliciclastic shelves from seismic profiles showed that unconformities can form as the result/t of changes in the geometry of sediment dispersal systems and may be independent of sea-level. In addition, unconformities on seismic records may represent rapid transitions when studied in outcrop. Seismic modeling of carbonate platforms showed that, when using typical/ industrial/ frequencies, there are apparent truncations of the margin and significant basin ward shifts in the point of on/sp. The low resolution of the seismic tool also results in apparent pinch outs and pseudo-unconformities.
Unconformities on seismic profiles need not correspond to unconformities in the Iithological record. The seismic modeling of outcrops ultimately provides a means for evacuating the accuracy of unconformity interpretations based solely on seismic response. New constraints in the interpretation of unconformity geometry will/ lead not only to more accurate p/ay evacuations but possibly also to revision of the "Vail" sea-level curve which is based largely on the interpretation of unconformity geometries from industrial seismic profiles.
The southern Vercors area (south-east France) displays superb exposures of a Lower Cretaceous prograding carbonate platform. These exposures allow a geometrical sequence analysis to be combined with detailed outcrop observations.... more
The southern Vercors area (south-east France) displays superb exposures of a Lower Cretaceous prograding carbonate platform. These exposures allow a geometrical sequence analysis to be combined with detailed outcrop observations. Two-dimensional seismic modelling techniques were used to determine the seismic response of three of these exposures: the Montagnette, the Archiane Valley and the Rocher de Combau. The outcrops display prograding and retreating series of clinoforms interfingering with fine-grained basinal sediments. Photographs from different angles of view, combined with detailed field observations, were used to construct lithological profiles with a resolution of f few metres. P-wave velocities and bulk densities were measured from cored hand specimens and selected values were assigned to lithostratigraphic units in each profile. The vertical incidence modelling technique was then used to compute migrated time sections of reflectivity. These were convolved with source wavelets of different frequencies to produce the final synthetic seismic profiles. None of the modelled outcrop geometries is correctly portrayed seismically at 25–50 Hz frequencies. Not only do the synthetic seismic profiles show less detail, they also show misleading geometries. In most seismic models, for instance, pseudo-unconformities are present that correspond to rapid changes in dip and in facies in outcrop. Furthermore, the seismic tool is not able to resolve between stratal patterns punctuated by unconformities and those with gradual shifts in facies belts accompanied by complex interfingering relationships. This implies that an unconformity recognized on a real seismic line should not automatically be assumed to represent a true stratal unconformity. Large outcrops are often used to show the validity of sequence stratigraphy, a concept mainly based on the analysis of seismic lines. This study, however, shows that there is no one to one relationship between geometries observed in outcrop and in seismic lines. Seismic modelling of outcrops therefore provides a means for evaluating outcrop geometries in terms of seismic stratigraphy.
Research Interests:
The seismic resolution of stratal geometries and facies distributions observed in San Andres Formation (Permian) outcrops in Last Chance Canyon, Guadalupe Mountains, New Mexico, is studied by seismic modeling of a published, detailed... more
The seismic resolution of stratal geometries and facies distributions observed in San Andres Formation (Permian) outcrops in Last Chance Canyon, Guadalupe Mountains, New Mexico, is studied by seismic modeling of a published, detailed stratigraphic cross section. The outcrops in Last Chance Canyon are composed of two fourth-order depositional sequences: an aggrading carbonate bank (upper San Andres 3; uSA3) followed by a strongly progradational, offlapping mixed carbonate-siliciclastic succession (upper San Andres 4; uSA4). Each sequence comprises a number of subsidiary high-frequency sequences (fifth-order). Two alternative impedance models were used: Model A, in which all facies transitions are reflecting boundaries, and Model B, in which only time-significant surfaces act as reflectors and lateral facies transitions are represented by horizontal velocity gradients. The vertical-incidence modeling technique was used to compute perfectly migrated time and depth sections with different frequencies. Using a low-frequency wavelet (25 Hz), the sequence boundary separating the two fourth-order cycles (uSA3 and uSA4) is poorly imaged. Instead, one is tempted to incorrectly interpret an onlap pattern generated by a high-frequency cycle within uSA4 as this major sequence boundary. In addition, the 25 Hz runs show toplap and downlap lap-out patterns in an overly oblique fashion, obscuring true asymptotic stratal relationships. Both at 35 Hz and 50 Hz, profiles based on Model B image the genetic structure of both uSA3 and uSA4 relatively well. At 50 Hz, Model A incorrectly shows a transition from a ramp to a rimmed margin within uSA4. The 35 Hz models are qualitatively compared with a published Exxon Production Research Co. seismic line, located approximately 50 km along depositional strike to the northeast. Model A shows an unexpected good match with the Exxon seismic line, whereas Model B comes much closer to the depositional anatomy observed in outcrop. Our results show that the resolution of stratal geometries and facies distributions in Last Chance Canyon is strongly related to carbonate-sandstone alternations and the way impedance contrasts at carbonate-sandstone transitions are represented.
Research Interests: Geology and Sedimentary
Synthetic seismograms at Hole 866 were derived from sonic velocity and neutron density logs and compared to the lithology and seismic reflection data. In addition, logs of neutron density, neutron porosity, resistivity, gamma-ray, and... more
Synthetic seismograms at Hole 866 were derived from sonic velocity and neutron density logs and compared to the lithology and seismic reflection data. In addition, logs of neutron density, neutron porosity, resistivity, gamma-ray, and discrete measurements were used to generate pseudo-velocity logs as input for synthetic seismograms to evaluate their potential as proxy for sonic velocity. The experiment has several implications for the study of seismic reflection profiles over Cretaceous Mid-Pacific guyots.
High-amplitude reflections in the synthetic seismograms derived from log velocity and density are generated at lithologic boundaries, possibly related to changes in sea level or Oceanographic events, at diagenetic boundaries (dolomitization), and by interference processes. The generally poor correlation between the synthetic seismogram and reflection seismic profile may be related to quality of recording, the quality of the well logs, rapid lateral changes in lithology or diagenetic overprinting, or changing interference patterns. The precise cause remains unclear, but the synthetic seismograms suggest that it is difficult to identify reflections in conventional seismic reflection profiles that are related to changes in sea level or Oceanographic events and to correlate these to other guyots. In addition, as the impedance contrasts between limestone and basalt in these guyots is smaller, or equal to, the impedance contrasts within the limestone succession, it is nearly impossible to identify a basement reflection based on amplitudes alone.
Synthetic seismograms calculated from sonic velocity, neutron density, neutron porosity, and resistivity logs produce similar results. Gamma-ray data are poorly correlated to impedance because the clay-content is not the primary source of gamma-ray activity. Resistivity, however, is an unexpectedly good proxy for impedance. Density shows a useful correlation because Gardner's equation works well for pure limestone, whereas Wyllie's equation underestimates velocity.
High-amplitude reflections in the synthetic seismograms derived from log velocity and density are generated at lithologic boundaries, possibly related to changes in sea level or Oceanographic events, at diagenetic boundaries (dolomitization), and by interference processes. The generally poor correlation between the synthetic seismogram and reflection seismic profile may be related to quality of recording, the quality of the well logs, rapid lateral changes in lithology or diagenetic overprinting, or changing interference patterns. The precise cause remains unclear, but the synthetic seismograms suggest that it is difficult to identify reflections in conventional seismic reflection profiles that are related to changes in sea level or Oceanographic events and to correlate these to other guyots. In addition, as the impedance contrasts between limestone and basalt in these guyots is smaller, or equal to, the impedance contrasts within the limestone succession, it is nearly impossible to identify a basement reflection based on amplitudes alone.
Synthetic seismograms calculated from sonic velocity, neutron density, neutron porosity, and resistivity logs produce similar results. Gamma-ray data are poorly correlated to impedance because the clay-content is not the primary source of gamma-ray activity. Resistivity, however, is an unexpectedly good proxy for impedance. Density shows a useful correlation because Gardner's equation works well for pure limestone, whereas Wyllie's equation underestimates velocity.
Conventional sequence-stratigraphic concepts relate the large-scale stratal architecture of sediment bodies to changes in relative sea level. This paper evaluates the relationship between stratal geometry and sea-level stand, based on a... more
Conventional sequence-stratigraphic concepts relate the large-scale stratal architecture of sediment bodies to changes in relative sea level. This paper evaluates the relationship between stratal geometry and sea-level stand, based on a study of large, semicontinuous outcrops of Cretaceous carbonate platform strata in the Vercors (southeastern France). Multiple lines of evidence for sea-level change are combined, including stratal geometry, detailed quantitative microfacies analyses, and diagenetic patterns at platform-top hardground surfaces. The studied outcrops of the Cirque d'Archiane show two main prograding platform tongues, both over 100 m thick. The stratal geometries at the boundary between these platform tongues, including an apparent pinchout of a wedge of slope sediments, suggest the presence of a major lowstand unconformity. However, this stratal boundary does not coincide with the horizon containing the most extensive meteoric alteration. Furthermore, detailed platform-to-basin correlation shows that the wedge of slope sediments is not basin-restricted, but makes a thin drape over the platform top. The sedimentologic and diagenetic evidence suggest incipient drowning of the platform at the boundary between the two main platform tongues, preceded by a minor exposure event only. Internally, the main platform tongues consist of smaller (10-30 m thick) units that prograde towards the basin and aggrade on the platform top, and which are interpreted as stacked highstand wedges. These wedges are usually topped by hardground surfaces with minor evidence for subaerial exposure. The platform-top horizon with the most extensive subaerial diagenesis and erosion correlates with a distinct but relatively thin unit of lithoclastic debris on the slope. A pronounced scour in the clinoforms of the Vercors does not correlate with a major exposure surface on the platform top. This study shows that stratal geometries alone are a rather ambiguous guide to sea-level history. Without the accompanying sedimentologic and diagenetic evidence for sea-level change, most of the stratal architecture of the Vercors platform can be explained by either changes in accommodation or changes in carbonate production.
Research Interests: Geology and Sedimentary
Traditionally, seismic modeling has concentrated on one-dimensional borehole modeling and two-dimensional forward modeling of basic structural-stratigraphic schemes, which are directly compared with real seismic data. Two-dimensional... more
Traditionally, seismic modeling has concentrated on one-dimensional borehole modeling and two-dimensional forward modeling of basic structural-stratigraphic schemes, which are directly compared with real seismic data. Two-dimensional seismic models based on outcrop observations may aid in bridging the gap between the detail of the outcrop and the low resolution of seismic lines. Examples include the Dolomites (North Italy), the Vercors (SE France), and the High Atlas (Morocco).
The seismic models are generally constructed using the following procedure: (a) construction of a detailed lithologic model based on direct outcrop observations; (b) division of the lithologic model into lithostratigraphic units; (c) assignment of petrophysical properties to these lithostratigraphic units; (d) ray tracing to compute time- or depth sections of reflectivity; (e) convolution of the reflectivity sections with source wavelets of different frequencies.
The lithologic detail modeled in the case studies led to some striking results, particularly the discovery of pseudo-unconformities. Pseudo-unconformities are unconformities in seismics, but correspond to rapid changes of dip and facies in outcrop. None of the outcrop geometries studied were correctly portrayed seismically at 25-Hz peak frequency. However, in some instances the true relationship would gradually emerge at peak frequencies of 50-100Hz. The examples given in this study demonstrate that detailed, outcrop-derived, seismic models can reveal what stratigraphic relationships and features are likely to be resolved under ideal or less-ideal conditions, and what pitfalls may befall the interpreter of real seismic data.
The seismic models are generally constructed using the following procedure: (a) construction of a detailed lithologic model based on direct outcrop observations; (b) division of the lithologic model into lithostratigraphic units; (c) assignment of petrophysical properties to these lithostratigraphic units; (d) ray tracing to compute time- or depth sections of reflectivity; (e) convolution of the reflectivity sections with source wavelets of different frequencies.
The lithologic detail modeled in the case studies led to some striking results, particularly the discovery of pseudo-unconformities. Pseudo-unconformities are unconformities in seismics, but correspond to rapid changes of dip and facies in outcrop. None of the outcrop geometries studied were correctly portrayed seismically at 25-Hz peak frequency. However, in some instances the true relationship would gradually emerge at peak frequencies of 50-100Hz. The examples given in this study demonstrate that detailed, outcrop-derived, seismic models can reveal what stratigraphic relationships and features are likely to be resolved under ideal or less-ideal conditions, and what pitfalls may befall the interpreter of real seismic data.
Research Interests:
Two-dimensional seismic models of geologic data are usually based on simplified impedance functions: large “seismic-scale” lithologic blocks exhibit uniform impedance values, and abrupt changes in impedance occur at the boundaries of... more
Two-dimensional seismic models of geologic data are usually based on simplified impedance functions: large “seismic-scale” lithologic blocks exhibit uniform impedance values, and abrupt changes in impedance occur at the boundaries of these lithologic blocks. For outcrop-based seismic models, erosional slope topography may be one possible proxy for impedance that is relatively easy to measure in outcrop. In this paper, we use terrestrial photogrammetric techniques to establish the relationship between outcrop topography, expressed as the rock slope angle, and impedance for a marl-limestone terrain in the Vercors, southeast France. The photogrammetric surveys were combined with sedimentologic descriptions and petrophysical measurements (including P-wave velocity, bulk-density, clay content, and porosity). The slope angle along a particular vertical profile was then converted into a pseudoimpedance log, which was subsequently used to construct 1-D synthetic seismograms. A comparison of these new seismograms with published seismic models of the same area revealed the benefits of the new approach, in particular for seismic modeling using high-frequency source wavelets.
Research Interests:
Kruiver, P.P., De Lange, G., Korff, M., Wiersma, A., Harting, R., Kloosterman, F.H., Stafleu, J., Gunnink, J.L., Van Elk, J. & Doornhof, D., 2018. Parameterization of Geological Models for Regional Site Response and Liquefaction Potential... more
Kruiver, P.P., De Lange, G., Korff, M., Wiersma, A., Harting, R., Kloosterman, F.H., Stafleu, J., Gunnink, J.L., Van Elk, J. & Doornhof, D., 2018. Parameterization of Geological Models for Regional Site Response and Liquefaction Potential Indicators (Extended Abstract, 12 pp). 16th European Conference on Earthquake Engineering, June 18 – 21, 2018, Thessaloniki, Greece.
We have built two regional geological models-covering over 1,000 km 2-that serve as input for the seismic hazard and risk analysis of the onshore gas field of the Groningen region, the Netherlands. The first model describes the liquefaction potential indicators and the second model contains the layer model and parameterization for site response analysis. Earlier published papers focused on the construction of the models. The emphasis of the current paper is on the parameterization of both models. The liquefaction potential indicator consists of the cumulative thickness of loosely, moderately and densely packed sand in the top 40 m. This parameter was derived from the cone resistance values in the database of ~ 5,700 Cone Penetration Test (CPT) soundings. The geological model for site response consists of vertical voxel stacks corresponding to the GeoTOP model and extended to ~ 800 m depth using scenarios. These voxel stacks serve as input for site response calculations which requires information about shear wave velocity, unit weight, overconsolidation ratio, plasticity index, undrained shear strength, median grain size and coefficient of uniformity. These parameters were either derived based on local data from Seismic CPTs, CPTs or grainsize analyses. The empirical relations from literature were modified to fit the local Groningen characteristics of the soil. The parameterization was derived for the combinations of stratigraphy and lithology that are present in the region. Although our approach to schematize geology and to parameterize the geological models was developed for the region of Groningen, the general approach can be applied to other regions.
We have built two regional geological models-covering over 1,000 km 2-that serve as input for the seismic hazard and risk analysis of the onshore gas field of the Groningen region, the Netherlands. The first model describes the liquefaction potential indicators and the second model contains the layer model and parameterization for site response analysis. Earlier published papers focused on the construction of the models. The emphasis of the current paper is on the parameterization of both models. The liquefaction potential indicator consists of the cumulative thickness of loosely, moderately and densely packed sand in the top 40 m. This parameter was derived from the cone resistance values in the database of ~ 5,700 Cone Penetration Test (CPT) soundings. The geological model for site response consists of vertical voxel stacks corresponding to the GeoTOP model and extended to ~ 800 m depth using scenarios. These voxel stacks serve as input for site response calculations which requires information about shear wave velocity, unit weight, overconsolidation ratio, plasticity index, undrained shear strength, median grain size and coefficient of uniformity. These parameters were either derived based on local data from Seismic CPTs, CPTs or grainsize analyses. The empirical relations from literature were modified to fit the local Groningen characteristics of the soil. The parameterization was derived for the combinations of stratigraphy and lithology that are present in the region. Although our approach to schematize geology and to parameterize the geological models was developed for the region of Groningen, the general approach can be applied to other regions.
Research Interests:
Van Lancker, V., Francken, F., Kapel, M., Kint, L., Terseleer, N., Van den Eynde, D., Degrendele, K., Roche, M., De Tré, G., De Mol, R., Missiaen, T., Hademenos, V., Stafleu, J., Van Heteren, S., Van Maanen P.-P.,, Van Schendel, J., 2017.... more
Van Lancker, V., Francken, F., Kapel, M., Kint, L., Terseleer, N., Van den Eynde, D., Degrendele, K., Roche, M., De Tré, G., De Mol, R., Missiaen, T., Hademenos, V., Stafleu, J., Van Heteren, S., Van Maanen P.-P.,, Van Schendel, J., 2017. Flexible querying of geological resource quantities and qualities, a sustainability perspective (Extended Abstract, 13 pp). Studiedag Zandwinning, June 9, 2017, Oostende (Ostend), Belgium.
To anticipate on future resource supplies and needs, long-term adaptive management strategies for the exploitation of geological resources are urgently needed (cf. EU's Maritime Policy, Marine Spatial Planning, Marine Strategy Framework Directive). These are based ideally on a geological knowledge base incorporating comprehensive knowledge on the distribution, composition and dynamics of geological resources.
Such a knowledge base is being built for the Belgian and southern Netherlands part of the North Sea (Belgian Science Policy 'TILES') with the aim of providing long-term predictions of geological resource quantity and quality (Van Lancker et al., 2017, for an overview). Therefore, the lithology or sediment composition of the subsurface needs quantification which is traditionally derived from borehole point data. First these data are classified into classes, e.g., following the Wentworth scale (i.e., clay, silt, fine, medium to coarse sand and gravel), but secondly their distribution needs interpolation. Since the data are prone to a high variability, both in space and in depth, it is important to constrain the lithological interpolation within the geological unit or stratigraphy the lithoclass belongs to. This information ideally comes from seismic line data. Combining both point and line data is most efficiently done in a voxel modelling approach of which 3D volume elements are the key component. Advantages are the suite of geostatistical interpolations that can incorporate various criteria, including expert knowledge, the unlimited information that can be added to the data cube in a later phase, and the easy calculation of resource volumes per geological unit or resource quality. Importantly, the geostatistical modelling allows for probabilistic instead of static mapping providing the user with a measure of uncertainty on the lithoclass that is interpolated.
To anticipate on future resource supplies and needs, long-term adaptive management strategies for the exploitation of geological resources are urgently needed (cf. EU's Maritime Policy, Marine Spatial Planning, Marine Strategy Framework Directive). These are based ideally on a geological knowledge base incorporating comprehensive knowledge on the distribution, composition and dynamics of geological resources.
Such a knowledge base is being built for the Belgian and southern Netherlands part of the North Sea (Belgian Science Policy 'TILES') with the aim of providing long-term predictions of geological resource quantity and quality (Van Lancker et al., 2017, for an overview). Therefore, the lithology or sediment composition of the subsurface needs quantification which is traditionally derived from borehole point data. First these data are classified into classes, e.g., following the Wentworth scale (i.e., clay, silt, fine, medium to coarse sand and gravel), but secondly their distribution needs interpolation. Since the data are prone to a high variability, both in space and in depth, it is important to constrain the lithological interpolation within the geological unit or stratigraphy the lithoclass belongs to. This information ideally comes from seismic line data. Combining both point and line data is most efficiently done in a voxel modelling approach of which 3D volume elements are the key component. Advantages are the suite of geostatistical interpolations that can incorporate various criteria, including expert knowledge, the unlimited information that can be added to the data cube in a later phase, and the easy calculation of resource volumes per geological unit or resource quality. Importantly, the geostatistical modelling allows for probabilistic instead of static mapping providing the user with a measure of uncertainty on the lithoclass that is interpolated.
Research Interests:
Stafleu, J., Maljers, D., Hummelman, J., Busschers, F.S., Schokker, J. and Van der Meulen, M.J., 2018. An integrated modelling approach at TNO – Geological Survey of the Netherlands. In: Berg, R.C., MacCormack, K., Russell, H.A.J. &... more
Stafleu, J., Maljers, D., Hummelman, J., Busschers, F.S., Schokker, J. and Van der Meulen, M.J., 2018. An integrated modelling approach at TNO – Geological Survey of the Netherlands. In: Berg, R.C., MacCormack, K., Russell, H.A.J. & Thorleifson, L.H. (eds.): Three-Dimensional Geological Mapping, Workshop Extended Abstracts, RFG2018 Resources for Future Generations, Premier Conference on Energy, Minerals, Water, The Earth, June 16-17 2018, Vancouver, BC, Canada, 84-87
TNO – Geological Survey of the Netherlands (TNO – GSN) defines digital geological models as estimates of both geometry and properties of the subsurface. In contrast to singular observations in boreholes and the projected information of traditional maps, models provide continuous representations of the subsurface built with all geological expertise available. The models are quantitative and user oriented, i.e., they are applicable for non-geologists in their own area of expertise. They are also stochastic in nature, which implies that model uncertainty can be quantified.
TNO – GSN systematically produces 3D models of the Netherlands. To date, we build and maintain two different types of nation-wide models: (1) layer-based models in which the subsurface is represented as a series of tops and bases of geological, hydrogeological units and (2) voxel models in which the subsurface is subdivided in a regular grid of voxels attributed with a number of geological properties. Layer-based models of the shallow subsurface include the national geological framework model DGM (Gunnink et al. 2013) and the geohydrological model REGIS II (Vernes and Van Doorn 2005). A third layer-based model is DGM-deep with Carboniferous to Neogene seismostratigraphical units up to a depth of 7 km. The two main voxel models are the aggregate resources model (Maljers et al. 2015) and the multi-purpose GeoTOP model (Stafleu et al. 2011).
Our models are disseminated free-of-charge via the DINO-web portal (www.dinoloket.nl/en/subsurface-models) in a number of ways, including an on-line map viewer with the option to create virtual boreholes and cross sections through the models, and as a series of downloadable GIS products. A freely downloadable Subsurface-Viewer® was added to the portal, allowing users to download and visualize the layer-based models as well as GeoTOP on their desktop computers.
This extended abstract explores the three main models of the shallow subsurface, with an emphasis on the GeoTOP voxel model, discusses how we are currently integrating the layer-based models of DGM and GeoTOP and gives some examples of applications.
TNO – Geological Survey of the Netherlands (TNO – GSN) defines digital geological models as estimates of both geometry and properties of the subsurface. In contrast to singular observations in boreholes and the projected information of traditional maps, models provide continuous representations of the subsurface built with all geological expertise available. The models are quantitative and user oriented, i.e., they are applicable for non-geologists in their own area of expertise. They are also stochastic in nature, which implies that model uncertainty can be quantified.
TNO – GSN systematically produces 3D models of the Netherlands. To date, we build and maintain two different types of nation-wide models: (1) layer-based models in which the subsurface is represented as a series of tops and bases of geological, hydrogeological units and (2) voxel models in which the subsurface is subdivided in a regular grid of voxels attributed with a number of geological properties. Layer-based models of the shallow subsurface include the national geological framework model DGM (Gunnink et al. 2013) and the geohydrological model REGIS II (Vernes and Van Doorn 2005). A third layer-based model is DGM-deep with Carboniferous to Neogene seismostratigraphical units up to a depth of 7 km. The two main voxel models are the aggregate resources model (Maljers et al. 2015) and the multi-purpose GeoTOP model (Stafleu et al. 2011).
Our models are disseminated free-of-charge via the DINO-web portal (www.dinoloket.nl/en/subsurface-models) in a number of ways, including an on-line map viewer with the option to create virtual boreholes and cross sections through the models, and as a series of downloadable GIS products. A freely downloadable Subsurface-Viewer® was added to the portal, allowing users to download and visualize the layer-based models as well as GeoTOP on their desktop computers.
This extended abstract explores the three main models of the shallow subsurface, with an emphasis on the GeoTOP voxel model, discusses how we are currently integrating the layer-based models of DGM and GeoTOP and gives some examples of applications.
Research Interests:
TNO Geological Survey of the Netherlands systematically produces 3D voxel models for answering subsurface related questions. The unique combination of vast amounts of borehole data and the voxel-based approach makes the models valuable... more
TNO Geological Survey of the Netherlands systematically produces 3D voxel models for answering subsurface related questions. The unique combination of vast amounts of borehole data and the voxel-based approach makes the models valuable new sources for exploring the Quaternary fluvial record. The latest generation of 3D voxel models (GeoTOP) schematises the shallow subsurface of the Netherlands in millions of voxels each measuring 100 by 100 by 0.5 m up to a depth of 50 m below sea level. The GeoTOP model was used to perform a 3D spatial trend analysis on channel belt lithology, sand grain-size and architectural characteristics in the Holocene Rhine-Meuse delta. An analysis of the coarse-sand and fine-sand fractions shows clear spatial trends that relate to downstream changes in gradient, reworking of older sediments and tidal influence. Channel deposit proportions show an almost linear downstream decrease with an average value of about 0.5% per km. Our data can act as an important constraint for hydrocarbon reservoir modelling where this type of information is often only sparsely available.
Research Interests:
The Geological Survey of the Netherlands maps its country systematically in 3D, putting out four models that each correspond with a particular application domain. Rather than the models themselves, we discuss the meaning and... more
The Geological Survey of the Netherlands maps its country systematically in 3D, putting out four models
that each correspond with a particular application domain. Rather than the models themselves, we discuss
the meaning and implementation of working systematically, focusing on quality assurance and model
versioning and maintenance. Our aims for quality assurance are to put a system in place that arranges for
independent and documented checks of all model output, according to well-defined quality standards,
finding a balance between rigorousness on the one hand, and user demands to deliver information faster
on the other. Regarding model versioning and maintenance, we aim to significantly shorten our release
cycles, publishing models after making specific improvements rather than full updates. These two aspects
of working systematically are particularly important in helping us to be accountable in terms of the value
and quality of our modeling work, which in its turn is vital to the continuity of our Survey.
that each correspond with a particular application domain. Rather than the models themselves, we discuss
the meaning and implementation of working systematically, focusing on quality assurance and model
versioning and maintenance. Our aims for quality assurance are to put a system in place that arranges for
independent and documented checks of all model output, according to well-defined quality standards,
finding a balance between rigorousness on the one hand, and user demands to deliver information faster
on the other. Regarding model versioning and maintenance, we aim to significantly shorten our release
cycles, publishing models after making specific improvements rather than full updates. These two aspects
of working systematically are particularly important in helping us to be accountable in terms of the value
and quality of our modeling work, which in its turn is vital to the continuity of our Survey.
Research Interests:
TNO Geological Survey of the Netherlands systematically produces 3D voxel models for answering subsurface related questions. One of these models (GeoTOP) schematizes the shallow subsurface of the Netherlands in millions of voxels each... more
TNO Geological Survey of the Netherlands systematically produces 3D voxel models for answering subsurface related questions. One of these models (GeoTOP) schematizes the shallow subsurface of the Netherlands in millions of voxels each measuring 100 by 100 by 0.5 m up to a depth of 50 m below sea level.
The GeoTOP model was used to perform a quantitative 3D spatial trend analysis on channel belt lithology, sand grain-size and architectural characteristics in the Holocene Rhine-Meuse delta. An analysis of the coarse-sand and fine-sand fractions shows clear spatial trends that relate to downstream changes in gradient, reworking of older sediments and tidal influence. Channel deposit proportions show an almost linear downstream decrease with an average value of about 0.5% per km. The analysis results can be used as input parameters for groundwater flow modeling studies in areas or at depths where this type of information is not available.
The GeoTOP model was used to perform a quantitative 3D spatial trend analysis on channel belt lithology, sand grain-size and architectural characteristics in the Holocene Rhine-Meuse delta. An analysis of the coarse-sand and fine-sand fractions shows clear spatial trends that relate to downstream changes in gradient, reworking of older sediments and tidal influence. Channel deposit proportions show an almost linear downstream decrease with an average value of about 0.5% per km. The analysis results can be used as input parameters for groundwater flow modeling studies in areas or at depths where this type of information is not available.
Research Interests:
TNO Geological Survey of the Netherlands systematically produces 3D voxel models for answering subsurface related questions. The unique combination of vast amounts of borehole data and the voxel-based approach makes the models valuable... more
TNO Geological Survey of the Netherlands systematically produces 3D voxel models for answering subsurface related questions. The unique combination of vast amounts of borehole data and the voxel-based approach makes the models valuable new sources for exploring the Quaternary fluvial record. The latest generation of 3D voxel models (GeoTOP) schematises the shallow subsurface of the Netherlands in millions of voxels each measuring 100 by 100 by 0.5 m up to a depth of 50 m below sea level. The GeoTOP model was used to perform a 3D spatial trend analysis on channel belt lithology, sand grain-size and architectural characteristics in the Holocene Rhine-Meuse delta. An analysis of the coarse-sand and fine-sand fractions shows clear spatial trends that relate to downstream changes in gradient, reworking of older sediments and tidal influence. Channel deposit proportions show an almost linear downstream decrease with an average value of about 0.5% per km. Our data can act as an important constraint for hydrocarbon reservoir modelling where this type of information is often only sparsely available.
"The Geological Survey of the Netherlands builds and maintains two different types of nation-wide models: (1) layer-based models in which the subsurface is represented as a series of tops and bases of geological or hydrogeological units... more
"The Geological Survey of the Netherlands builds and maintains two different types of nation-wide models: (1) layer-based models in which the subsurface is represented as a series of tops and bases of geological or hydrogeological units and (2) voxel models in which the subsurface is subdivided in a regular grid of voxels containing several geological properties. Layer-based models include the geological framework model DGM (Digital Geological Model, Gunnink et al., 2013) and the hydrogeological model REGIS II (Regional Geohydrological Information System, Vernes and Van Doorn, 2005). Voxel models include NL3D with voxels of 250 by 250 by 1 m, and the detailed GeoTOP model with voxels measuring 100 by 100 by 0.5 m (Stafleu et al., 2011).
Modeling typically starts with a geological framework and this is then further refined to include user-specific parameters. In geohydrological applications, the geological framework model is used to distinguish geological units that act either as aquifer or as aquitard and to further parameterize these units with hydrological parameters, like porosity and hydraulic conductivity.
This extended abstract describes the parameterization for geohydrological applications of both the layer-based model REGIS II and the voxel model GeoTOP. The main emphasis is on building spatially distributed models of hydraulic conductivity, which are consistent with the geological model and can be used in groundwater flow modeling.
Hydraulic conductivity is a key parameter in geohydrological modeling. Direct measurements of hydraulic conductivity at the model-scale are often not available. Instead, hydraulic conductivity measurements are derived from pump-tests (which are costly and often multi-interpretable), from empirically derived relationships with grain-size distributions or by measuring hydraulic conductivity of small volumes of sediments that are extracted from boreholes. This results in the concept of “the missing scale” (Tran, 1996), and upscaling is necessary to derive meaningful parameters at the model-scale.
"
Modeling typically starts with a geological framework and this is then further refined to include user-specific parameters. In geohydrological applications, the geological framework model is used to distinguish geological units that act either as aquifer or as aquitard and to further parameterize these units with hydrological parameters, like porosity and hydraulic conductivity.
This extended abstract describes the parameterization for geohydrological applications of both the layer-based model REGIS II and the voxel model GeoTOP. The main emphasis is on building spatially distributed models of hydraulic conductivity, which are consistent with the geological model and can be used in groundwater flow modeling.
Hydraulic conductivity is a key parameter in geohydrological modeling. Direct measurements of hydraulic conductivity at the model-scale are often not available. Instead, hydraulic conductivity measurements are derived from pump-tests (which are costly and often multi-interpretable), from empirically derived relationships with grain-size distributions or by measuring hydraulic conductivity of small volumes of sediments that are extracted from boreholes. This results in the concept of “the missing scale” (Tran, 1996), and upscaling is necessary to derive meaningful parameters at the model-scale.
"
At TNO – Geological Survey of the Netherlands we have a high-resolution 3D model of the subsurface of the Netherlands, to a depth of about 30 m (Stafleu et al., 2011). The voxels of this model measure 100 x 100 x 0.5 m and have a variety... more
At TNO – Geological Survey of the Netherlands we have a high-resolution 3D model of the subsurface of the Netherlands, to a depth of about 30 m (Stafleu et al., 2011). The voxels of this model measure 100 x 100 x 0.5 m and have a variety of geological parameters attached to them. Contained in that model is the 3D architecture of the Rhine-Meuse delta (Fig.1). The geometry of the channel bodies in the delta is known in unrivalled detail based on more than 200,000 boreholes, mainly due to the work by Utrecht University (Berendsen & Stouthamer, 2001; Cohen et al., 2012).
In contrast to the detailed knowledge of the 3D architecture of the Rhine-Meuse delta, little is known of the architecture of the Late Jurassic-Early Cretaceous deltaic system in the West Netherlands Basin at about 2000 m depth (Fig. 2). After having been explored for hydrocarbons during the last century, that basin is now receiving more and more attention for geothermal energy. As for hydrocarbon production, a key element for geothermal energy is an aquifer/reservoir with optimal connectivity.
Related to the topic of connectivity of fluvial channel deposits, we have started a pilot-study to test the applicability of the wealth of information contained in the detailed 3D model of the Rhine-Meuse delta for a better understanding of the distribution of fluvial bodies in general and in the Late Jurassic-Early Cretaceous deltaic system specifically.
In contrast to the detailed knowledge of the 3D architecture of the Rhine-Meuse delta, little is known of the architecture of the Late Jurassic-Early Cretaceous deltaic system in the West Netherlands Basin at about 2000 m depth (Fig. 2). After having been explored for hydrocarbons during the last century, that basin is now receiving more and more attention for geothermal energy. As for hydrocarbon production, a key element for geothermal energy is an aquifer/reservoir with optimal connectivity.
Related to the topic of connectivity of fluvial channel deposits, we have started a pilot-study to test the applicability of the wealth of information contained in the detailed 3D model of the Rhine-Meuse delta for a better understanding of the distribution of fluvial bodies in general and in the Late Jurassic-Early Cretaceous deltaic system specifically.
"(1) Introduction - TNO Geological Survey of the Netherlands systematically produces 3D voxel models for answering applied subsurface related questions. The unique combination of vast amounts of borehole data and the voxel-based approach... more
"(1) Introduction - TNO Geological Survey of the Netherlands systematically produces 3D voxel models for answering applied subsurface related questions. The unique combination of vast amounts of borehole data and the voxel-based approach of capturing geological heterogeneity makes the models valuable new sources for exploring the Quaternary fluvial record. GeoTOP is the latest generation of 3D voxel models. This model describes the 3D lithological variability of the subsurface of the upper 50 m using voxels of 100*100*0.5 m (Stafleu et al., 2011a, 2011b). The recently completed GeoTOP model of the Rhine-Meuse delta allows an in depth-analysis of its 3D variability, including spatial trends in both lithology and sand grain-size.
(2) Modelling of 3D Rhine-Meuse channel belts - The GeoTOP model of the Rhine-Meuse delta was constructed using ~225.000 borehole descriptions from the DINO and Utrecht University databases. The location of the channel belts was derived from detailed maps published by the Geological Survey and the Utrecht University (Berendsen and Stouthamer, 2001). Newly developed software was used to determine the top and base of the belts within the boreholes. Finally, the use of stochastic interpolation techniques allowed us to predict lithology and sand grain-size for each voxel in the model.
(3) 3D lithology and grain-size trends - A preliminary 3D analysis of a single channel belt in the western part of the Rhine-Meuse delta (Figure 1) shows a clear downstream increase in percentages of fine-grained sand and a decrease in percentages of the coarser fractions. This observation, which illustrates the potential of the GeoTOP model to identify grain-size trends in sandy lowland rivers, initiated a full scale analysis of the entire delta in 3D. At ICFS10 we will present this delta-scale analysis and discuss the results in relation to other field- and model studies.
"
(2) Modelling of 3D Rhine-Meuse channel belts - The GeoTOP model of the Rhine-Meuse delta was constructed using ~225.000 borehole descriptions from the DINO and Utrecht University databases. The location of the channel belts was derived from detailed maps published by the Geological Survey and the Utrecht University (Berendsen and Stouthamer, 2001). Newly developed software was used to determine the top and base of the belts within the boreholes. Finally, the use of stochastic interpolation techniques allowed us to predict lithology and sand grain-size for each voxel in the model.
(3) 3D lithology and grain-size trends - A preliminary 3D analysis of a single channel belt in the western part of the Rhine-Meuse delta (Figure 1) shows a clear downstream increase in percentages of fine-grained sand and a decrease in percentages of the coarser fractions. This observation, which illustrates the potential of the GeoTOP model to identify grain-size trends in sandy lowland rivers, initiated a full scale analysis of the entire delta in 3D. At ICFS10 we will present this delta-scale analysis and discuss the results in relation to other field- and model studies.
"
"The Geological Survey of the Netherlands aims at building a 3D geological property model of the upper 30 meters of the Dutch subsurface. The model schematises the subsurface in millions of grid cells each measuring 100 by 100 meters in... more
"The Geological Survey of the Netherlands aims at building a 3D geological property model of the upper 30 meters of the Dutch subsurface. The model schematises the subsurface in millions of grid cells each measuring 100 by 100 meters in the horizontal directions and 0.5 meters in the vertical direction. Each grid cell of the model includes estimates of stratigraphy, lithofacies and lithology (clay, sand, peat) and if applicable, sand-grain size class data. Stochastic interpolation techniques are used to compute probabilities for these parameters, providing a quantification of model uncertainty. The model provides a sound framework for subsurface related questions on, amongst others, groundwater
management, land subsidence, natural resources and infrastructural issues."
management, land subsidence, natural resources and infrastructural issues."
A recent development in the Netherlands is the implementation of a Key Register Subsurface (“Basisregistratie Ondergrond”). Part of this Key Register Subsurface is a new generation of 3D subsurface models that provide estimates of... more
A recent development in the Netherlands is the implementation of a Key Register Subsurface (“Basisregistratie Ondergrond”). Part of this Key Register Subsurface is a new generation of 3D subsurface models that provide estimates of stratigraphy, lithology (clay, sand, peat) and sand-grain size class data at voxel-resolutions of 100*100*0.5m (referred to as GeoTOP models). These regional-scale models can be used as a starting point for detailed investigations of risks and opportunities that may evolve from intensive and multiple uses of the subsurface. An example of this is the planning of a new subway in the city of Rotterdam.
Creating 3D voxel models is as easy as assembling IKEA furniture (or isn't that so simple?). All you need is some 430,000 borehole descriptions, 35 geological layers and 250,000,000 empty voxels. Step 1 - Interpretation of borehole... more
Creating 3D voxel models is as easy as assembling IKEA furniture (or isn't that so simple?). All you need is some 430,000 borehole descriptions, 35 geological layers and 250,000,000 empty voxels. Step 1 - Interpretation of borehole descriptions in terms of geological units; Step 2 - Create the layer model using 2D interplation techniques; Step 3 - Build the voxel model by interpolating lithology from the boreholes within each geological layer using 3D simulation algorithms. Have fun!
Research Interests:
The 3D voxel model GeoTOP schematises onshore Netherlands in millions of voxels (grid cells), each measuring 100 x 100 x 0.5 m, to a depth of 50 m below NAP (Dutch Ordnance Datum). Each voxel in the model contains information on the... more
The 3D voxel model GeoTOP schematises onshore Netherlands in millions of voxels (grid cells), each measuring 100 x 100 x 0.5 m, to a depth of 50 m below NAP (Dutch Ordnance Datum). Each voxel in the model contains information on the lithostratigraphy and lithological classes (lithoclasses), including the probability of occurrence for each lithoclass. Other parameters, such as hydraulic conductivity and chloride content can also be linked to the voxels in the model. Using the lithostratigraphical framework as a base for physical and chemical parameters, GeoTOP provides the user with a reliable image of the spatial variability of those parameters.
Research Interests:
""Since the early nineties digital geological and hydrogeological models have been developed by TNO Geological Survey of the Netherlands. Three national geological models provide information on the subsurface, each differing in depth... more
""Since the early nineties digital geological and hydrogeological models have been developed by TNO Geological Survey of the Netherlands. Three national geological models provide information on the subsurface, each differing in depth range and scale:
- GeoTOP-model covering the uppermost 30 meters;
- Digital Geological Model - shallow for the shallow sub surface to about 500 meters;
- Digital Geological Model - deep covering the deep subsurface to about 5000 meters.
These models in turn form the basis for the development of property models, like for example the national hydrogeological model REGIS II. All of these models are based on data from DINO, the central database for geoscientific data on the shallow and deep Dutch subsurface. See www.dinoloket.nl for more information.""
- GeoTOP-model covering the uppermost 30 meters;
- Digital Geological Model - shallow for the shallow sub surface to about 500 meters;
- Digital Geological Model - deep covering the deep subsurface to about 5000 meters.
These models in turn form the basis for the development of property models, like for example the national hydrogeological model REGIS II. All of these models are based on data from DINO, the central database for geoscientific data on the shallow and deep Dutch subsurface. See www.dinoloket.nl for more information.""
Voor een duurzaam gebruik en beheer van de ondergrond is informatie over de opbouw en eigenschappen van de ondergrond essentieel. De Geologische Dienst Nederland levert deze informatie in de vorm van computermodellen. Het model GeoTOP... more
Voor een duurzaam gebruik en beheer van de ondergrond is informatie over de opbouw en eigenschappen van de ondergrond essentieel. De Geologische Dienst Nederland levert deze informatie in de vorm van computermodellen. Het model GeoTOP geeft een gedetailleerd driedimensionaal beeld van de ondergrond tot een diepte van 30 meter onder maaiveld: het deel van de bodem dat door ons het meest intensief wordt benut. Dit productblad verstrekt algemene informatie over de GeoTOP modellering en de gehanteerde werkwijze. Er wordt ingegaan op het raamwerk van de lithostratigrafie, de indeling in lithoklassen en de koppeling met fysisch-chemische parameters. Ook wordt een voorbeeld gege-ven van de onzekerheden in het model. Modelresultaten van GeoTOP en nadere info over de deelmodellen Zeeland, Zuid-Holland, Noord-Holland en het Rivierengebied vindt u op de website www.DINOloket.nl.
GeoTOP is a detailed three-dimensional model of the upper 30 meters of the subsurface of the Netherlands. It provides the user with a cell-based description of the spatial variability of geological, physical and chemical parameters in the... more
GeoTOP is a detailed three-dimensional model of the upper 30 meters of the subsurface of the Netherlands. It provides the user with a cell-based description of the spatial variability of geological, physical and chemical parameters in the subsurface. In this way, GeoTOP provides a sound framework for subsurface related questions on groundwater management, land subsidence, natural resources, and infrastructural projects.
The shallow subsurface of the Province of Zuid-Holland is characterised by strong geological heterogeneity. Overlying a coarse-grained Pleistocene substratum, a 5-20m thick sequence of Holocene age fluvial-estuarine sediment and... more
The shallow subsurface of the Province of Zuid-Holland is characterised by strong geological heterogeneity. Overlying a coarse-grained Pleistocene substratum, a 5-20m thick sequence of Holocene age fluvial-estuarine sediment and peatlayers occur. Rhine-Meuse channel belts and coastal barriers form an important part of this sequence, causing short range variability of lithology and grain-size.
Kint, L., De Mol, R., Hademenos, V., Stafleu, J., van Heteren, S., Van Lancker, V., 2018. Incorporating data uncertainty in 3D voxel modelling and the importance in decision making. NCK Days, March 21-23, 2018, Haarlem, the Netherlands.... more
Kint, L., De Mol, R., Hademenos, V., Stafleu, J., van Heteren, S., Van Lancker, V., 2018. Incorporating data uncertainty in 3D voxel modelling and the importance in decision making. NCK Days, March 21-23, 2018, Haarlem, the Netherlands.
Geological databases resulting from the merging of various data sources and time periods jeopardize harmonization of data products. Data standardization is already common practice and a first step in avoiding semantic overlap. European marine data-management infrastructures provide such standards, e.g., Geo-Seas (http://www.geo-seas.eu/) for geological data and SeaDataNet (https://www.seadatanet.org/) for marine metadata in general. In addition, metadata quality control is important, though data uncertainty is seldom quantified and yet to be used in modeling. Preliminary uncertainty analyses were worked out to provide an extra dimension to the cross-border 3D voxel models of the geological subsurface of the Belgian and southern Netherlands part of the North Sea (http://odnature.naturalsciences.be/tiles/). Starting from simple quality flagging in geological databases and model-uncertainty calculations (probability and entropy) in the 3D modelling, data uncertainty (e.g., related to qualities in positioning, sampling and vintage) is now quantified. Combining all uncertainties remains a challenge, as is communicating their importance in decision making. A demonstration will be given on the status of the uncertainty analyses and on the way these are incorporated into a newly developed decision support tool allowing interactive querying of the 3D voxel model, now comprising geological parameters as well as entropy, probability and data-uncertainty attributes (Figure 1).
Figure 1. Interactive querying of the 3D geological voxel model in the newly developed 2D Decision Support System (DSS).
Geological databases resulting from the merging of various data sources and time periods jeopardize harmonization of data products. Data standardization is already common practice and a first step in avoiding semantic overlap. European marine data-management infrastructures provide such standards, e.g., Geo-Seas (http://www.geo-seas.eu/) for geological data and SeaDataNet (https://www.seadatanet.org/) for marine metadata in general. In addition, metadata quality control is important, though data uncertainty is seldom quantified and yet to be used in modeling. Preliminary uncertainty analyses were worked out to provide an extra dimension to the cross-border 3D voxel models of the geological subsurface of the Belgian and southern Netherlands part of the North Sea (http://odnature.naturalsciences.be/tiles/). Starting from simple quality flagging in geological databases and model-uncertainty calculations (probability and entropy) in the 3D modelling, data uncertainty (e.g., related to qualities in positioning, sampling and vintage) is now quantified. Combining all uncertainties remains a challenge, as is communicating their importance in decision making. A demonstration will be given on the status of the uncertainty analyses and on the way these are incorporated into a newly developed decision support tool allowing interactive querying of the 3D voxel model, now comprising geological parameters as well as entropy, probability and data-uncertainty attributes (Figure 1).
Figure 1. Interactive querying of the 3D geological voxel model in the newly developed 2D Decision Support System (DSS).
Research Interests:
Stafleu, J., 2018. Sand-resource accounting is ideally done using 3D voxel models (Abstract). TILES - Transnational and Integrated Long-term Marine Exploitation Strategies, Final Conference, 1 June 2018, Brussels, Belgium. Sand-stock... more
Stafleu, J., 2018. Sand-resource accounting is ideally done using 3D voxel models (Abstract). TILES - Transnational and Integrated Long-term Marine Exploitation Strategies, Final Conference, 1 June 2018, Brussels, Belgium.
Sand-stock assessments should include the quality of the resource. 3D pixel (voxel) models incorporate multiple properties and allow in-depth analyses of their interrelationships. Because of the structured geometry, voxels capture the 3D-spatial heterogeneity within a resource layer better than maps.
Sand-stock assessments should include the quality of the resource. 3D pixel (voxel) models incorporate multiple properties and allow in-depth analyses of their interrelationships. Because of the structured geometry, voxels capture the 3D-spatial heterogeneity within a resource layer better than maps.
Research Interests:
Stafleu, J., D. Maljers. J.L. Gunnink, F.S. Busschers, K. Koster, V. Hademenos, 2018. Putting our models to work: Applications of 3D voxel models in real life situations (Abstract). 4th European Meeting on 3D Geological Modelling, 21-23... more
Stafleu, J., D. Maljers. J.L. Gunnink, F.S. Busschers, K. Koster, V. Hademenos, 2018. Putting our models to work: Applications of 3D voxel models in real life situations (Abstract). 4th European Meeting on 3D Geological Modelling, 21-23 February 2018, Orléans, France.
Geological voxel models subdivide the subsurface in a regular grid of rectangular blocks ('voxels', 'tiles' or '3D cells') in a Cartesian coordinate system. Each voxel contains multiple properties that describe the geometry of stratigraphical units and the spatial variation of lithology within these units. Using voxel models, the architecture and internal heterogeneity of stratigraphical units in the subsurface can be modelled in great detail. By assigning physical properties to the voxels we are able to turn the models into powerful instruments for a wide range of applications such as: groundwater management, risk assessments, the planning of infrastructural works and aggregate resource assessments. The underlying assumption is that the spatial variation of many subsurface properties, such as hydraulic conductivity and shear-wave velocity, strongly depends on the two main geological properties in the model: stratigraphy and lithology (Figure 1). Fig. 1: Putting geological voxel models to work by adding properties related to the application at hand. In this presentation, we will show the following real life applications of geological voxel models attributed with physical properties: 1) the Netherland's nationwide mapping programme GeoTOP, 2) a detailed model of the subsurface of Tokyo Lowland, Japan, and 3) a voxel model of the Belgian Continental Shelf. These models cover the upper 50 m of the subsurface. The GeoTOP model covers 23,325 km 2 (57%) of the surface area of the Netherlands. It is a multipurpose model that has already been used in a number of different applications. A recent application is the risk-assessment of damage caused by human induced earthquakes in the Groningen gas field (Figure 1). Another GeoTOP-application is the long-term prediction of land subsidence due to the oxidation and compression of peat layers. The model of the Tokyo Lowland was used to study the relation between the accumulated thickness of soft Holocene mud and the amount of damage caused by natural earthquakes. The Quaternary sands of the Belgian Continental Shelf are a resource for the construction industry and for the reinforcement of the Belgian coast. A voxel model based on shallow seismic profiles and a limited amount of boreholes was developed and subsequently complemented with an online query-tool. This tool enables the users to perform volume calculations, which are crucial for the management of raw materials in the marine environment. These case studies exemplify the value of geological voxel models in real life applications. Furthermore, they show that voxel models attributed with physical properties are deployable in a wide range of geological settings.
Geological voxel models subdivide the subsurface in a regular grid of rectangular blocks ('voxels', 'tiles' or '3D cells') in a Cartesian coordinate system. Each voxel contains multiple properties that describe the geometry of stratigraphical units and the spatial variation of lithology within these units. Using voxel models, the architecture and internal heterogeneity of stratigraphical units in the subsurface can be modelled in great detail. By assigning physical properties to the voxels we are able to turn the models into powerful instruments for a wide range of applications such as: groundwater management, risk assessments, the planning of infrastructural works and aggregate resource assessments. The underlying assumption is that the spatial variation of many subsurface properties, such as hydraulic conductivity and shear-wave velocity, strongly depends on the two main geological properties in the model: stratigraphy and lithology (Figure 1). Fig. 1: Putting geological voxel models to work by adding properties related to the application at hand. In this presentation, we will show the following real life applications of geological voxel models attributed with physical properties: 1) the Netherland's nationwide mapping programme GeoTOP, 2) a detailed model of the subsurface of Tokyo Lowland, Japan, and 3) a voxel model of the Belgian Continental Shelf. These models cover the upper 50 m of the subsurface. The GeoTOP model covers 23,325 km 2 (57%) of the surface area of the Netherlands. It is a multipurpose model that has already been used in a number of different applications. A recent application is the risk-assessment of damage caused by human induced earthquakes in the Groningen gas field (Figure 1). Another GeoTOP-application is the long-term prediction of land subsidence due to the oxidation and compression of peat layers. The model of the Tokyo Lowland was used to study the relation between the accumulated thickness of soft Holocene mud and the amount of damage caused by natural earthquakes. The Quaternary sands of the Belgian Continental Shelf are a resource for the construction industry and for the reinforcement of the Belgian coast. A voxel model based on shallow seismic profiles and a limited amount of boreholes was developed and subsequently complemented with an online query-tool. This tool enables the users to perform volume calculations, which are crucial for the management of raw materials in the marine environment. These case studies exemplify the value of geological voxel models in real life applications. Furthermore, they show that voxel models attributed with physical properties are deployable in a wide range of geological settings.
Research Interests:
Maljers, D., Van der Meulen, M.J., Stafleu, J., Vernes, R.W., Ten Veen, J., 2018. Yes, we need to integrate our subsurface models! (Abstract). 4th European Meeting on 3D Geological Modelling, 21-23 February 2018, Orléans, France.... more
Maljers, D., Van der Meulen, M.J., Stafleu, J., Vernes, R.W., Ten Veen, J., 2018. Yes, we need to integrate our subsurface models! (Abstract). 4th European Meeting on 3D Geological Modelling, 21-23 February 2018, Orléans, France.
TNO-Geological Survey of the Netherlands (GSN) develops and maintains a suite of four subsurface models. These models each have their own historical background, use different data, different modelling techniques and serve different user groups. However, today more and more the call for integration of these subsurface models is heard. Therefore at GSN we are currently working on the integration of two of these models covering the shallow subsurface. The result is a single, integrated and multiresolution model that displays a great amount of detail in the upper tens of meters, but at the same time reaches, albeit with less detail, depths of several hundreds of meters. In doing so we eliminate differences between realizations of the same geological units. The integration of the shallow framework models appear to be a relatively straightforward step, mainly because they are constructed using comparable datasets (mainly boreholes) and the same modelling software, but is nevertheless time-consuming. The new integrated model will serve as the future carrier of our voxel models with detailed lithological information as well as our hydrogeological information on aquifers and aquitards. In recent years, progress has been made in the integration of our shallow and deep subsurface models in the context of H3O projects. These projects, carried out in close collaboration with our Belgian and German partners, deliver cross-border hydrogeological models. The main challenges in these projects are the harmonisation of the stratigraphic nomenclatures used on either side of the border, the integrated interpretation of data from boreholes as well as from seismic lines, the handling of faults, and the use of different software. In the Netherlands, due to the energy transition, geothermal energy receives more and more attention. At greater depths, this energy source often come from reservoir rocks that are already modelled in detail for hydrocarbon exploration. However, the recent shift of focus to more shallow reservoirs in the Netherlands has, to date, received little attention from the geomodelling community. The main reason is that these shallow reservoirs fall outside the depth ranges of the shallow models and lack detail in the deep models, because they were irrelevant for hydrocarbon exploitation (Figure 1). Although here only one example underpinning the needs for integration is mentioned, the increased use of the subsurface in providing essential resources and storage capacities (and the associated synergies) asks for better integration of subsurface models. Although we do not have all the answers to the way ahead yet, we look forward to discuss the possible approaches for model integration with the audience. Fig. 1: Example of a cross-section of a shallow subsurface model (upper panel) and a deep subsurface model (lower panel). Interest is currently focussed on the depth range of 600-1200 m below reference level, which is not modelled in the shallow model and has received little attention in the deep model.
TNO-Geological Survey of the Netherlands (GSN) develops and maintains a suite of four subsurface models. These models each have their own historical background, use different data, different modelling techniques and serve different user groups. However, today more and more the call for integration of these subsurface models is heard. Therefore at GSN we are currently working on the integration of two of these models covering the shallow subsurface. The result is a single, integrated and multiresolution model that displays a great amount of detail in the upper tens of meters, but at the same time reaches, albeit with less detail, depths of several hundreds of meters. In doing so we eliminate differences between realizations of the same geological units. The integration of the shallow framework models appear to be a relatively straightforward step, mainly because they are constructed using comparable datasets (mainly boreholes) and the same modelling software, but is nevertheless time-consuming. The new integrated model will serve as the future carrier of our voxel models with detailed lithological information as well as our hydrogeological information on aquifers and aquitards. In recent years, progress has been made in the integration of our shallow and deep subsurface models in the context of H3O projects. These projects, carried out in close collaboration with our Belgian and German partners, deliver cross-border hydrogeological models. The main challenges in these projects are the harmonisation of the stratigraphic nomenclatures used on either side of the border, the integrated interpretation of data from boreholes as well as from seismic lines, the handling of faults, and the use of different software. In the Netherlands, due to the energy transition, geothermal energy receives more and more attention. At greater depths, this energy source often come from reservoir rocks that are already modelled in detail for hydrocarbon exploration. However, the recent shift of focus to more shallow reservoirs in the Netherlands has, to date, received little attention from the geomodelling community. The main reason is that these shallow reservoirs fall outside the depth ranges of the shallow models and lack detail in the deep models, because they were irrelevant for hydrocarbon exploitation (Figure 1). Although here only one example underpinning the needs for integration is mentioned, the increased use of the subsurface in providing essential resources and storage capacities (and the associated synergies) asks for better integration of subsurface models. Although we do not have all the answers to the way ahead yet, we look forward to discuss the possible approaches for model integration with the audience. Fig. 1: Example of a cross-section of a shallow subsurface model (upper panel) and a deep subsurface model (lower panel). Interest is currently focussed on the depth range of 600-1200 m below reference level, which is not modelled in the shallow model and has received little attention in the deep model.
Research Interests:
Van der Meulen, M.J., Maljers, D., Stafleu, J., Vernes, R.W., Doornenbal, J.C., Gunnink, J.L., 2018. Systematic 3D modelling at the Geological Survey of the Netherlands – country update (Abstract). 4th European Meeting on 3D Geological... more
Van der Meulen, M.J., Maljers, D., Stafleu, J., Vernes, R.W., Doornenbal, J.C., Gunnink, J.L., 2018. Systematic 3D modelling at the Geological Survey of the Netherlands – country update (Abstract). 4th European Meeting on 3D Geological Modelling, 21-23 February 2018, Orléans, France.
The Geological Survey of the Netherlands maintains a portfolio of four national subsurface models. Layer-based models include the geological framework models DGM (Digital Geological Model) and DGM-deep, and the hydrogeological model REGIS-II. The distinction between deep and shallow modelling relates to both the application of the model and modelling methods. Shallow modelling, having evolved from traditional geologic mapping, is primarily based on the correlation of boreholes and covers depths that are relevant to geotechnical and groundwater studies (generally down to about 500 m below the surface). Deep modelling, originally targeted at hydrocarbon resources, primarily uses seismic data down to about 5 km below the surface. Voxel (i.e. 3D raster) models of the upper tens of meters of the subsurface include GeoTOP, a high-resolution model that is in the process of being built and covers about half of the country, and NL3D, a lower-resolution model that already has national coverage. Developments in Dutch geomodelling after the previous status update (Wiesbaden, 2016) include the following highlights: (1) GeoTOP now includes all coastal provinces and the Rhine-Meuse delta, serving the areas that are most vulnerable to adverse ground conditions and flooding. Research preparing for geochemical and hydraulic parametrisation of GeoTOP is well underway, to be eventually followed by geotechnical parametrisation. (2) A new version of REGIS-II has been released, which is geometrically compatible with the last release of DGM (2014). (3) The layer modelling step of GeoTOP has been integrated with that of DGM, in order to enhance geometrical consistency. (4) Following on a first project that started in 2014, two more transboundary hydrogeological models are being constructed together with counterpart organisations in Belgium and Germany. The results will present water managers in the border areas with better (seamless) information, and the exchange of knowledge between project partners boosted our collective understanding of the regional (hydro)strati-graphy. The results of the individual projects will be fed back in the DGM, REGIS-II and DGM-deep programmes. Beyond technical-scientific progress, pending developments in Dutch geomodelling primary relate to a new law on subsurface information. Since 2010, our Survey has been preparing for a transformation of our databases to a 'key register for the subsurface' (further referred by its Dutch acronym BRO). A key register is legally defined register containing high-quality data that the government is obliged to use for its public tasks, existing ones containing personally identifiable information; identification and ownership of real estate, companies and vehicles; real-estate value; income, employment relations and social-security benefits; addresses and buildings; and base topography. The BRO recognises the government's reliance on subsurface data and information for a number important planning and permitting procedures, e.g., for land use planning; exploration and production of hydrocarbons, minerals and geothermal heat; storage of CO2 and natural gas; and groundwater management. Beyond that, it is expected to help reduce the considerable societal risks and costs associated with adverse ground conditions in public works, especially infrastructure projects. The BRO law is now in a process of stepwise implementation, i.e., datatype by datatype, which will take several years. For systematic geomodelling, the BRO law is crucial: it is the only way in which we can substantially increase the inflow of data to our survey. In this way, we expect the law to be instrumental in achieving higher model resolutions at lower uncertainties.
The Geological Survey of the Netherlands maintains a portfolio of four national subsurface models. Layer-based models include the geological framework models DGM (Digital Geological Model) and DGM-deep, and the hydrogeological model REGIS-II. The distinction between deep and shallow modelling relates to both the application of the model and modelling methods. Shallow modelling, having evolved from traditional geologic mapping, is primarily based on the correlation of boreholes and covers depths that are relevant to geotechnical and groundwater studies (generally down to about 500 m below the surface). Deep modelling, originally targeted at hydrocarbon resources, primarily uses seismic data down to about 5 km below the surface. Voxel (i.e. 3D raster) models of the upper tens of meters of the subsurface include GeoTOP, a high-resolution model that is in the process of being built and covers about half of the country, and NL3D, a lower-resolution model that already has national coverage. Developments in Dutch geomodelling after the previous status update (Wiesbaden, 2016) include the following highlights: (1) GeoTOP now includes all coastal provinces and the Rhine-Meuse delta, serving the areas that are most vulnerable to adverse ground conditions and flooding. Research preparing for geochemical and hydraulic parametrisation of GeoTOP is well underway, to be eventually followed by geotechnical parametrisation. (2) A new version of REGIS-II has been released, which is geometrically compatible with the last release of DGM (2014). (3) The layer modelling step of GeoTOP has been integrated with that of DGM, in order to enhance geometrical consistency. (4) Following on a first project that started in 2014, two more transboundary hydrogeological models are being constructed together with counterpart organisations in Belgium and Germany. The results will present water managers in the border areas with better (seamless) information, and the exchange of knowledge between project partners boosted our collective understanding of the regional (hydro)strati-graphy. The results of the individual projects will be fed back in the DGM, REGIS-II and DGM-deep programmes. Beyond technical-scientific progress, pending developments in Dutch geomodelling primary relate to a new law on subsurface information. Since 2010, our Survey has been preparing for a transformation of our databases to a 'key register for the subsurface' (further referred by its Dutch acronym BRO). A key register is legally defined register containing high-quality data that the government is obliged to use for its public tasks, existing ones containing personally identifiable information; identification and ownership of real estate, companies and vehicles; real-estate value; income, employment relations and social-security benefits; addresses and buildings; and base topography. The BRO recognises the government's reliance on subsurface data and information for a number important planning and permitting procedures, e.g., for land use planning; exploration and production of hydrocarbons, minerals and geothermal heat; storage of CO2 and natural gas; and groundwater management. Beyond that, it is expected to help reduce the considerable societal risks and costs associated with adverse ground conditions in public works, especially infrastructure projects. The BRO law is now in a process of stepwise implementation, i.e., datatype by datatype, which will take several years. For systematic geomodelling, the BRO law is crucial: it is the only way in which we can substantially increase the inflow of data to our survey. In this way, we expect the law to be instrumental in achieving higher model resolutions at lower uncertainties.
Research Interests:
Erkens, G., Van den Akker, J., Stafleu, J. and De Lange, G., 2018. New predictive maps of land subsidence in the Netherlands. 14th Nederlands Aardwetenschappelijk Congres (NAC2018), 15-16 March 2018, Veldhoven, The Netherlands. Already... more
Erkens, G., Van den Akker, J., Stafleu, J. and De Lange, G., 2018. New predictive maps of land subsidence in the Netherlands. 14th Nederlands Aardwetenschappelijk Congres (NAC2018), 15-16 March 2018, Veldhoven, The Netherlands.
Already for 1000 years, the Netherlands has seen steady human-induced subsidence. There is no reason why subsidence would not continue the coming decades, as the root causes are still active. Subsidence causes an increased flood risk, which has to be compensated by continuous investments in water management, and it also may cause damage to infrastructure and constructions.
The resulting costs are accumulating to billions of euros per year, and these costs will rise in the future, as the exposure and vulnerability of society to land subsidence increases. Predictive maps of land subsidence are used in policy to mitigate subsidence and its effects, or are used in efforts to become more adaptive.
The results encouraged us to start further improvement of national subsidence modelling, in terms of the capability to deal with large datasets, and the subsidence model code.
Already for 1000 years, the Netherlands has seen steady human-induced subsidence. There is no reason why subsidence would not continue the coming decades, as the root causes are still active. Subsidence causes an increased flood risk, which has to be compensated by continuous investments in water management, and it also may cause damage to infrastructure and constructions.
The resulting costs are accumulating to billions of euros per year, and these costs will rise in the future, as the exposure and vulnerability of society to land subsidence increases. Predictive maps of land subsidence are used in policy to mitigate subsidence and its effects, or are used in efforts to become more adaptive.
The results encouraged us to start further improvement of national subsidence modelling, in terms of the capability to deal with large datasets, and the subsidence model code.
Research Interests:
Hademenos, V., Van Lancker, V., Missiaen, T., Stafleu, J., 2015. Preliminary results on the 3D voxel model of the subsurface of the Belgian Continental Shelf. In: Mees, J. et al. (Ed.) Book of abstracts – VLIZ Young Scientists’ Day.... more
Hademenos, V., Van Lancker, V., Missiaen, T., Stafleu, J., 2015. Preliminary results on the 3D voxel model of the subsurface of the Belgian Continental Shelf. In: Mees, J. et al. (Ed.) Book of abstracts – VLIZ Young Scientists’ Day. Brugge, Belgium, 20 February 2015. VLIZ Special Publication 268654, 71: pp. 69
The BCS until recently regarded as one of the most well-studied areas of the North Sea has more to show than originally thought. Buried valleys, deltaic units, tidal channels, and erosional unconformities provide a challenging environment for 3D modelling. Within the frame of the Belspo Brain-be project TILES (Transnational and Integrated Long-term Marine Exploitation Strategies), a
3D voxel model of the subsurface of the North Sea will be created. The borehole and 2D seismic database of Belgium and Holland were combined to create the geological scheme of the area, unified borehole lithological descriptions and 2d bounding surfaces determining lithostratigraphical units. The previously mentioned data were interpolated using ISATIS to create the 3D voxel model.
Each voxel is describing either a unique value of a lithological feature (fine sand, gravel, etc.) or the occurrence probability of it. Results from the probability voxel model, showed a more detailed distribution of Pleistocene to Holocene stratigrafical units, outlined the deltaic fan of the Schelde River and aiso provided a preliminary model that can be used to determine resources volumes and their sustainable exploitation and in planning coastal zone and offshore area development.
The BCS until recently regarded as one of the most well-studied areas of the North Sea has more to show than originally thought. Buried valleys, deltaic units, tidal channels, and erosional unconformities provide a challenging environment for 3D modelling. Within the frame of the Belspo Brain-be project TILES (Transnational and Integrated Long-term Marine Exploitation Strategies), a
3D voxel model of the subsurface of the North Sea will be created. The borehole and 2D seismic database of Belgium and Holland were combined to create the geological scheme of the area, unified borehole lithological descriptions and 2d bounding surfaces determining lithostratigraphical units. The previously mentioned data were interpolated using ISATIS to create the 3D voxel model.
Each voxel is describing either a unique value of a lithological feature (fine sand, gravel, etc.) or the occurrence probability of it. Results from the probability voxel model, showed a more detailed distribution of Pleistocene to Holocene stratigrafical units, outlined the deltaic fan of the Schelde River and aiso provided a preliminary model that can be used to determine resources volumes and their sustainable exploitation and in planning coastal zone and offshore area development.
Research Interests:
Hademenos, V., Kint, L., Missiaen, T., Stafleu, J. & Van Lancker, V., 2017. 3D voxel modelling of the marine subsurface: the Belgian Continental Shelf case (Abstract). EGU General Assembly, 23 – 28 April 2017, Vienna, Austria. The need... more
Hademenos, V., Kint, L., Missiaen, T., Stafleu, J. & Van Lancker, V., 2017. 3D voxel modelling of the marine subsurface: the Belgian Continental Shelf case (Abstract). EGU General Assembly, 23 – 28 April 2017, Vienna, Austria.
The need for marine space grows bigger by the year. Dredging, wind farms, aggregate extraction and many other activities take up more space than ever before. As a result, the need for an accurate model that describes the properties of the areas in use is a priority. To address this need a 3D voxel model of the subsurface of the Belgian part of the North Sea has been created in the scope of the Belgian Science Policy project TILES ('Transnational and Integrated Long-term Marine Exploitation Strategies'). Since borehole data in the marine environment are a costly endeavour and therefore relatively scarce, seismic data have been incorporated in order to improve the data coverage. Lithostratigraphic units have been defined and lithoclasses are attributed to the voxels using a stochastic interpolation. As a result each voxel contains a unique value of one of 7 lithological classes (spanning in grain size from clay to gravel) in association with the geological layer it belongs to. In addition other forms of interpolation like sequential indicator simulation have allowed us to calculate the probability occurrence of each lithoclass, thus providing additional info from which the uncertainty of the model can be derived. The resulting 3D voxel model gives a detailed image of the distribution of different sediment types and provides valuable insight on the different geological settings. The voxel model also allows to estimate resource volumes (e.g. the availability of particular sand classes), enabling a more targeted exploitation. The primary information of the model is related to geology, but the model can additionally host any type of information.
The need for marine space grows bigger by the year. Dredging, wind farms, aggregate extraction and many other activities take up more space than ever before. As a result, the need for an accurate model that describes the properties of the areas in use is a priority. To address this need a 3D voxel model of the subsurface of the Belgian part of the North Sea has been created in the scope of the Belgian Science Policy project TILES ('Transnational and Integrated Long-term Marine Exploitation Strategies'). Since borehole data in the marine environment are a costly endeavour and therefore relatively scarce, seismic data have been incorporated in order to improve the data coverage. Lithostratigraphic units have been defined and lithoclasses are attributed to the voxels using a stochastic interpolation. As a result each voxel contains a unique value of one of 7 lithological classes (spanning in grain size from clay to gravel) in association with the geological layer it belongs to. In addition other forms of interpolation like sequential indicator simulation have allowed us to calculate the probability occurrence of each lithoclass, thus providing additional info from which the uncertainty of the model can be derived. The resulting 3D voxel model gives a detailed image of the distribution of different sediment types and provides valuable insight on the different geological settings. The voxel model also allows to estimate resource volumes (e.g. the availability of particular sand classes), enabling a more targeted exploitation. The primary information of the model is related to geology, but the model can additionally host any type of information.
Research Interests:
Cohen, K.M., Koster, K., Pierik, H.J., Van der Meulen, B., Hijma, M., Schokker, J. & Stafleu, J., 2017. Holocene palaeoDEMs for lowland coastal and delta plain landscape Reconstructions (Abstract). EGU General Assembly, 23 – 28 April... more
Cohen, K.M., Koster, K., Pierik, H.J., Van der Meulen, B., Hijma, M., Schokker, J. & Stafleu, J., 2017. Holocene palaeoDEMs for lowland coastal and delta plain landscape Reconstructions (Abstract). EGU General Assembly, 23 – 28 April 2017, Vienna, Austria.
Geological mapping of Holocene deposits of coastal plains, such as that of The Netherlands can reach high resolution (dense population, diverse applied usage) and good time control (14C dating, archaeology). The next step is then to create time sliced reconstructions for stages in the Holocene, peeling of the subrecent and exposing past relief situation. This includes winding back the history of sea-level rise and delta progradation etc. etc. So far, this has mainly be done as 2D series of landscape maps, or as sea-level curve age-depth plots.
In the last decade, academic and applied projects at Utrecht University, TNO Geological Survey of The Netherlands and Deltares have developed palaeoDEMs for the Dutch low lands, that are a third main way of showing coastal plain evolution. Importantly, we produce two types of palaeoDEMs: (1) geological surface mapping using deposit contacts from borehole descriptions (and scripted 3D processing techniques – e.g. Van der Meulen et al. 2013) and (2) palaeogroundwater surfaces, using sea-level and inland water-level index-points (and 3D kriging interpolations – e.g. Koster et al. 2016). The applications for the combined palaeoDEMs range from relative sea-level rise mapping and assessment of variation in rate of GIA across the coastal plain, to quantification of soft soil deformation, to analysis of pre-embankment extreme flood levels.
Koster, K., Stafleu, J., & Cohen, K.M. (2016). Generic 3D interpolation of Holocene base-level rise and provision of accommodation space, developed for the Netherlands coastal plain and infilled palaeovalleys. Basin Research. DOI 10.1111/bre.12202
Van der Meulen, M.J., Doornenbal, J.C., Gunnink, J.L., Stafleu, J., Schokker, J., Vernes, R.W., Van Geer, F.C., Van Gessel, S.F., Van Heteren, S., Van Leeuwen, R.J.W. & Bakker, M.A.J. (2013). 3D geology in a 2D country: perspectives for geological surveying in the Netherlands. Netherlands Journal of Geosciences, 92, 217-241. DOI 10.1017/S0016774600000184
Geological mapping of Holocene deposits of coastal plains, such as that of The Netherlands can reach high resolution (dense population, diverse applied usage) and good time control (14C dating, archaeology). The next step is then to create time sliced reconstructions for stages in the Holocene, peeling of the subrecent and exposing past relief situation. This includes winding back the history of sea-level rise and delta progradation etc. etc. So far, this has mainly be done as 2D series of landscape maps, or as sea-level curve age-depth plots.
In the last decade, academic and applied projects at Utrecht University, TNO Geological Survey of The Netherlands and Deltares have developed palaeoDEMs for the Dutch low lands, that are a third main way of showing coastal plain evolution. Importantly, we produce two types of palaeoDEMs: (1) geological surface mapping using deposit contacts from borehole descriptions (and scripted 3D processing techniques – e.g. Van der Meulen et al. 2013) and (2) palaeogroundwater surfaces, using sea-level and inland water-level index-points (and 3D kriging interpolations – e.g. Koster et al. 2016). The applications for the combined palaeoDEMs range from relative sea-level rise mapping and assessment of variation in rate of GIA across the coastal plain, to quantification of soft soil deformation, to analysis of pre-embankment extreme flood levels.
Koster, K., Stafleu, J., & Cohen, K.M. (2016). Generic 3D interpolation of Holocene base-level rise and provision of accommodation space, developed for the Netherlands coastal plain and infilled palaeovalleys. Basin Research. DOI 10.1111/bre.12202
Van der Meulen, M.J., Doornenbal, J.C., Gunnink, J.L., Stafleu, J., Schokker, J., Vernes, R.W., Van Geer, F.C., Van Gessel, S.F., Van Heteren, S., Van Leeuwen, R.J.W. & Bakker, M.A.J. (2013). 3D geology in a 2D country: perspectives for geological surveying in the Netherlands. Netherlands Journal of Geosciences, 92, 217-241. DOI 10.1017/S0016774600000184
Research Interests:
Van Lancker, V., Kint, L., Montereale-Gavazzi, G., Terseleer, N., Chademenos, V., Missiaen, T., De Mol, R., De Tré, G., Van Heteren, S., Van Maanen, P.-P., Stafleu, J., 2017. How Subsurface Voxel Modelling and Uncertainty Analysis... more
Van Lancker, V., Kint, L., Montereale-Gavazzi, G., Terseleer, N., Chademenos, V., Missiaen, T., De Mol, R., De Tré, G., Van Heteren, S., Van Maanen, P.-P., Stafleu, J., 2017. How Subsurface Voxel Modelling and Uncertainty Analysis Contribute to Habitat-Change Prediction and Monitoring (Abstract). GeoHAB17 – Marine Geological & Biological Habitat Mapping, May 1 – 5, 2017, Nova Scotia, Canada.
For long-term predictions of geological resource quantity and quality, a voxel model was built for the subsurface of the Belgian part of the North Sea (Belgian Science Policy ‘TILES’). The 3D voxels contain lithostratigraphic information over the entire data volume (up to -70 m), but also sediment characteristics and a suite of sediment-dynamic parameters in the upper voxel (i.e., the seabed). Derivative data products include probability maps of sediment type and resource-suitability maps that reflect a combination of user-specific criteria.
From stakeholder consultation, it became clear that the model has numerous potential applications, provided that resolution requirements from very small-scale to large-scale can be met (e.g., assessing local aggregate quality, but also decision-making on long-term resource use). To accommodate these varying needs, and also to enhance computational speed, voxel models were post-processed to vary the size of the voxels dependent on user demand. As such, data density, but also geological heterogeneity can steer the voxel size.
Uncertainty is parameterised to generate data products with confidence limits. Uniquely, the quality of each of the data fields in the databases is quantified in order to be propagated in the voxel model. Additionally, interpolation-related uncertainty, as well as uncertainty in the mapping of the lithological class and stratigraphic uncertainty (i.e. the geological layer to which a so-called lithoclass belongs) is incorporated. Visualisation of these uncertainties is highly challenging, and is addressed through variation in the sizes of the voxels or through transparency.
An ample spectrum of benefits exists for habitat mapping. Firstly, the geology of the shallow subsurface is accounted for, being highly relevant in predicting and constraining habitat change in long-term projections of resource use. The approach is also pertinent to assist present-day seabed mapping. Uncertainty mapping is critical to judge on the accuracy of seabed maps, and it assists in interpreting habitat changes within an envelope of natural variability, imposed by both the geological nature of the seabed and the highly dynamic sedimentary environment.
For long-term predictions of geological resource quantity and quality, a voxel model was built for the subsurface of the Belgian part of the North Sea (Belgian Science Policy ‘TILES’). The 3D voxels contain lithostratigraphic information over the entire data volume (up to -70 m), but also sediment characteristics and a suite of sediment-dynamic parameters in the upper voxel (i.e., the seabed). Derivative data products include probability maps of sediment type and resource-suitability maps that reflect a combination of user-specific criteria.
From stakeholder consultation, it became clear that the model has numerous potential applications, provided that resolution requirements from very small-scale to large-scale can be met (e.g., assessing local aggregate quality, but also decision-making on long-term resource use). To accommodate these varying needs, and also to enhance computational speed, voxel models were post-processed to vary the size of the voxels dependent on user demand. As such, data density, but also geological heterogeneity can steer the voxel size.
Uncertainty is parameterised to generate data products with confidence limits. Uniquely, the quality of each of the data fields in the databases is quantified in order to be propagated in the voxel model. Additionally, interpolation-related uncertainty, as well as uncertainty in the mapping of the lithological class and stratigraphic uncertainty (i.e. the geological layer to which a so-called lithoclass belongs) is incorporated. Visualisation of these uncertainties is highly challenging, and is addressed through variation in the sizes of the voxels or through transparency.
An ample spectrum of benefits exists for habitat mapping. Firstly, the geology of the shallow subsurface is accounted for, being highly relevant in predicting and constraining habitat change in long-term projections of resource use. The approach is also pertinent to assist present-day seabed mapping. Uncertainty mapping is critical to judge on the accuracy of seabed maps, and it assists in interpreting habitat changes within an envelope of natural variability, imposed by both the geological nature of the seabed and the highly dynamic sedimentary environment.
Research Interests:
Van Lancker, V., Kint, L., Terseleer, N., Hademenos, V., Missiaen, T., De Mol, R., De Tré, G., van Heteren, S., Stafleu, J., Degrendele, K., & Roche, M., 2018. Transnational Belgian-Dutch geological knowledge base on marine aggregates.... more
Van Lancker, V., Kint, L., Terseleer, N., Hademenos, V., Missiaen, T., De Mol, R., De Tré, G., van Heteren, S., Stafleu, J., Degrendele, K., & Roche, M., 2018. Transnational Belgian-Dutch geological knowledge base on marine aggregates. From 3D voxel modelling to 4D cross-border environmental assessments. RFG2018 Resources for Future Generations, Premier Conference on Energy, Minerals, Water, The Earth, June 16-21, Vancouver, Canada.
Mineral and geological resources are non-renewable on time scales relevant for decision makers. Once exhausted by humans, they are not replenished rapidly enough by nature, meaning that truly sustainable resource exploitation is not possible. Comprehensive knowledge on the distribution, composition and dynamics of geological resources and on the environmental impact of extraction is therefore critical. Anticipating on this, a geological knowledge base has been developed as a platform for resource management (Belspo Brain-be TILES, 2014-2018). Backbone of the knowledge base is a 3D voxel model (volume pixels) of the surface and subsurface of the Belgian and southern part of the North Sea. Standardized and harmonized databases have been created and a methodological workflow for the 3D modelling of offshore aggregates published. Data were added to the highest detail as to maximize their classification to any application (e.g., aggregate industry). Metadata were carefully added to estimate data-related uncertainty. The 3D geological models were further coupled to 4D numerical environmental impact models as to quantify environmental impact under various scenarios of exploitation. Furthermore, the voxels were filled with decadal sediment transport calculations allowing assessing seabed recovery estimations after extraction, an important asset in many environment-related European Directives. Data, models, and their uncertainties, are embedded in an end-user driven decision support system (DSS) that uniquely allows querying the full 3D resource volume, and integrating it with any third-party data. Visualization is an inherent part of the DSS, but to maximize impact towards a broader user community, a virtual reality application has been built too. From a management perspective, the DSS allows long-term resource predictions, balancing aggregate quality and quantity against various applications, and whilst minimizing environmental impact. Finally, a vision will be presented on how incorporating the geological knowledge base into a future national seabed mapping programme.
Mineral and geological resources are non-renewable on time scales relevant for decision makers. Once exhausted by humans, they are not replenished rapidly enough by nature, meaning that truly sustainable resource exploitation is not possible. Comprehensive knowledge on the distribution, composition and dynamics of geological resources and on the environmental impact of extraction is therefore critical. Anticipating on this, a geological knowledge base has been developed as a platform for resource management (Belspo Brain-be TILES, 2014-2018). Backbone of the knowledge base is a 3D voxel model (volume pixels) of the surface and subsurface of the Belgian and southern part of the North Sea. Standardized and harmonized databases have been created and a methodological workflow for the 3D modelling of offshore aggregates published. Data were added to the highest detail as to maximize their classification to any application (e.g., aggregate industry). Metadata were carefully added to estimate data-related uncertainty. The 3D geological models were further coupled to 4D numerical environmental impact models as to quantify environmental impact under various scenarios of exploitation. Furthermore, the voxels were filled with decadal sediment transport calculations allowing assessing seabed recovery estimations after extraction, an important asset in many environment-related European Directives. Data, models, and their uncertainties, are embedded in an end-user driven decision support system (DSS) that uniquely allows querying the full 3D resource volume, and integrating it with any third-party data. Visualization is an inherent part of the DSS, but to maximize impact towards a broader user community, a virtual reality application has been built too. From a management perspective, the DSS allows long-term resource predictions, balancing aggregate quality and quantity against various applications, and whilst minimizing environmental impact. Finally, a vision will be presented on how incorporating the geological knowledge base into a future national seabed mapping programme.
Research Interests:
Hademenos, V., Missiaen, T., Kapel, M., Kint, L., Terseleer, N, De Tré, G., De Mol, R., Stafleu, J., Van Maanen, P.-P., Rick Appleton, R. & Van Lancker, V., 2018. Mapping offshore resources of the Belgian Continental Shelf using 3D voxel... more
Hademenos, V., Missiaen, T., Kapel, M., Kint, L., Terseleer, N, De Tré, G., De Mol, R., Stafleu, J., Van Maanen, P.-P., Rick Appleton, R. & Van Lancker, V., 2018. Mapping offshore resources of the Belgian Continental Shelf using 3D voxel modelling. RFG2018 Resources for Future Generations, Premier Conference on Energy, Minerals, Water, The Earth, June 16-21, Vancouver, Canada.
Sustainable management of marine geological resources starts with a deep understanding of their diverse qualities and quantities. To facilitate comprehension of these variables a 3D voxel model of the subsurface of the Belgian part of the North Sea has been created in the scope of the Belgian Science Policy project TILES ('Transnational and Integrated Long-term Marine Exploitation Strategies'). The construction of the model follows a standardised methodological approach that is versatile in the addition of data that comes from different sources. In this case the voxels are filled with geological data originating from boreholes and seismic lines. The resulting 3D voxel model gives a detailed image of the distribution of different sediment types and provides valuable insight on the different geological settings. The voxel model also allows estimating resource volumes (e.g. availability of particular sand classes), enabling a more targeted exploitation. The primary information of the model is related to geology, but the model can additionally host any type of information, e.g., relevant from an industry perspective. Web querying tools have been developed of which the functionalities were mainly driven by end-users. Furthermore, a virtual reality application was built projecting the 3D models in their true dimensions and allowing more comprehensive interaction with the viewer.
Sustainable management of marine geological resources starts with a deep understanding of their diverse qualities and quantities. To facilitate comprehension of these variables a 3D voxel model of the subsurface of the Belgian part of the North Sea has been created in the scope of the Belgian Science Policy project TILES ('Transnational and Integrated Long-term Marine Exploitation Strategies'). The construction of the model follows a standardised methodological approach that is versatile in the addition of data that comes from different sources. In this case the voxels are filled with geological data originating from boreholes and seismic lines. The resulting 3D voxel model gives a detailed image of the distribution of different sediment types and provides valuable insight on the different geological settings. The voxel model also allows estimating resource volumes (e.g. availability of particular sand classes), enabling a more targeted exploitation. The primary information of the model is related to geology, but the model can additionally host any type of information, e.g., relevant from an industry perspective. Web querying tools have been developed of which the functionalities were mainly driven by end-users. Furthermore, a virtual reality application was built projecting the 3D models in their true dimensions and allowing more comprehensive interaction with the viewer.
Research Interests:
Stafleu, J., Maljers, D., Gunnink, J.L., Busschers, F.S., Koster, K. & Hademenos, V., 2018. What would we do without them? 3D geological voxel models for assessing resources and risks. RFG2018 Resources for Future Generations, Premier... more
Stafleu, J., Maljers, D., Gunnink, J.L., Busschers, F.S., Koster, K. & Hademenos, V., 2018. What would we do without them? 3D geological voxel models for assessing resources and risks. RFG2018 Resources for Future Generations, Premier Conference on Energy, Minerals, Water, The Earth, June 16-21, Vancouver, Canada.
Geological voxel models subdivide the subsurface in a regular grid of rectangular 3D cells in a Cartesian coordinate system. Each voxel contains multiple properties that describe the geometry of stratigraphical units and the spatial variation of lithology within these units. The addition of physical properties to voxels enables the deployment of these models for a wide range of applications such as: groundwater management, risk assessments, the planning of infrastructural works and aggregate resource assessments. In this presentation, we show real life applications of the following three geological voxel models attributed with physical properties: 1) the Netherland's nationwide mapping programme GeoTOP, 2) a detailed model of the subsurface of Tokyo Lowland, Japan, and 3) a voxel model of the Belgian Continental Shelf. These models cover the upper 50 m of the subsurface. 1) A recent application of the GeoTOP model is the risk-assessment of damage caused by human induced earthquakes in the Groningen gas field. Another GeoTOP application is the long-term prediction of land subsidence due to the oxidation and compression of peat layers. 2) The model of the Tokyo Lowland was used to study the relation between the accumulated thickness of soft Holocene mud and the amount of damage caused by natural earthquakes. 3) The Quaternary sands of the Belgian Continental Shelf are a resource for the construction industry and for the reinforcement of the Belgian coast. A voxel model of this area was developed and subsequently complemented with an online query-tool. This tool enables users to perform volume calculations, which are crucial for the management of raw materials in the marine environment. These case studies exemplify the value of geological voxel models in real life applications. Furthermore, they show that voxel models attributed with physical properties are deployable in a wide range of geological settings.
Geological voxel models subdivide the subsurface in a regular grid of rectangular 3D cells in a Cartesian coordinate system. Each voxel contains multiple properties that describe the geometry of stratigraphical units and the spatial variation of lithology within these units. The addition of physical properties to voxels enables the deployment of these models for a wide range of applications such as: groundwater management, risk assessments, the planning of infrastructural works and aggregate resource assessments. In this presentation, we show real life applications of the following three geological voxel models attributed with physical properties: 1) the Netherland's nationwide mapping programme GeoTOP, 2) a detailed model of the subsurface of Tokyo Lowland, Japan, and 3) a voxel model of the Belgian Continental Shelf. These models cover the upper 50 m of the subsurface. 1) A recent application of the GeoTOP model is the risk-assessment of damage caused by human induced earthquakes in the Groningen gas field. Another GeoTOP application is the long-term prediction of land subsidence due to the oxidation and compression of peat layers. 2) The model of the Tokyo Lowland was used to study the relation between the accumulated thickness of soft Holocene mud and the amount of damage caused by natural earthquakes. 3) The Quaternary sands of the Belgian Continental Shelf are a resource for the construction industry and for the reinforcement of the Belgian coast. A voxel model of this area was developed and subsequently complemented with an online query-tool. This tool enables users to perform volume calculations, which are crucial for the management of raw materials in the marine environment. These case studies exemplify the value of geological voxel models in real life applications. Furthermore, they show that voxel models attributed with physical properties are deployable in a wide range of geological settings.
Research Interests:
The process and the timing of Holocene groundwater level rise in the Rhine-Meuse delta and coastal plain of Holland is well understood. From sea-level and groundwater level rise studies, several hundreds of basal peat index points have... more
The process and the timing of Holocene groundwater level rise in the Rhine-Meuse delta and coastal plain of Holland is well understood. From sea-level and groundwater level rise studies, several hundreds of basal peat index points have been gathered and 14 C dated that document regional groundwater changes. Although they show a general rising trend, variability in rates and timing of inundation exists between regions, caused by changing interplay of marine and fluvial dominated groundwater regimes and differential subsidence of the substrate. We present an interpolation model that describes Holocene groundwater level rise and creation of accommodation space in full 3D, based on 384 basal peat index points. The model area covers two palaeovalleys of Late Pleistocene age and overlying coastal-deltaic sequences. The results show synchronous drowning and creation of accommodation space of the two palaeovalleys prior to 8,000 cal. BP, explained by the great rates of sea-level rise and comparable valley configurations. Considerable differences are seen after this period, because the Rhine river discharge affected groundwater levels in the southern valley only. Inland, the slopes of the two valleys differ, affecting the pacing of transgression. Between the north and south of the area, subtle differences in substrate subsidence are seen.
Research Interests:
The increasing demand of marine aggregates for coastal safety plans and industrial use poses new challenges for the management of sand extraction on the Belgian Continental Shelf. To anticipate on this, a 3D voxel model of the subsurface... more
The increasing demand of marine aggregates for coastal safety plans and industrial use poses new challenges for the management of sand extraction on the Belgian Continental Shelf. To anticipate on this, a 3D voxel model of the subsurface has been created (Belspo Brain-be project TILES on Transnational and Integrated Long-term Marine Exploitation Strategies). Available geological knowledge has been incorporated (cores and seismic profiles) resulting in voxels having a unique value of one of 7 lithological classes spanning in grain size from clay to gravel, together with the probability occurrence of each class derived from data and statistical calculations. Results from the voxel model gave a detailed image of the distribution of different sediment types and provided an insight on the different geological settings that are used or can be used for sand extraction. Estimates on volumes and availability of particular sand resources can be given, enabling more targeted exploitation. The information provided is critical to assess potential habitat changes in depth and time.
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With increasing exploitation of marine aggregates, the need for dedicated resource estimations becomes urgent. This is also the case for the North Sea, where sand extraction already takes place for more than 30 years. To enable long-term... more
With increasing exploitation of marine aggregates, the need for dedicated resource estimations becomes urgent. This is also the case for the North Sea, where sand extraction already takes place for more than 30 years. To enable long-term predictions of the availability of the main resource qualities in the Belgian and southern Netherlands part of the North Sea, a 3D voxel modelling approach was followed. Focus is on the unconsolidated sediments of the Quaternary of which only the most modern deposits are suitable for exploitation. Therefore, Holocene and Pleistocene stratigraphic units were defined, based on bathymetric, borehole and 2D seismic data. The resulting 2 layers were then used in a geostatistical interpolation, for which a voxel resolution of 200 m x 200 m x 1 m was chosen. First results will be presented starting with a high-resolution model of the Top Paleogene (De Clercq et al., in review). Next, for both Holocene and Pleistocene units, the distribution of up to 7 lithological classes (clay to gravel) will be shown, as also their probabilities of occurrence based on 100 renditions of the interpolation. Additionally, first volume calculations were made providing insight into expected resource quantities. The presentation contributes to the BELSPO Brain-be project TILES (Transnational and Integrated Long-term Marine Exploitation Strategies; www.odnature.be/tiles).
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Within the framework of the BELSPO Brain-be project TILES (Transnational and Integrated Long-term Marine Exploitation Strategies) 3D geological voxel models of the subsurface (up to-30m) of the southern part of the North Sea are being... more
Within the framework of the BELSPO Brain-be project TILES (Transnational and Integrated Long-term Marine Exploitation Strategies) 3D geological voxel models of the subsurface (up to-30m) of the southern part of the North Sea are being developed. Voxels are 3D pixels or cuboids, which are here filled primarily with geological data from boreholes and seismic lines. Each voxel in the model describes a unique value of one of 7 lithological classes ranging from clay to gravel, or the occurrence probability of it. As such, detailed information on the availability of different sediment types is provided, including their volumes, e.g., in blocks of 200*200*1m, or even 100*100*0.5m for local case studies. Additionally, uncertainties in the data sources are classified, and major data and knowledge gaps identified. Such a geological framework is the fundament of a more sustainable use of marine resources. Examples relate to determining the depths of major substrate-bound habitat changes, as well as optimal selection of areas where sufficient material can be found for a specific purpose (e.g., for beach nourishment or industrial use).
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, 2016. A continuum of knowledge from measurements to modelling as management support for the exploitation of marine aggregates, Belgian part of the North Sea (Abstract). ECSA 56 Conference on coastal systems in transition: from a... more
, 2016. A continuum of knowledge from measurements to modelling as management support for the exploitation of marine aggregates, Belgian part of the North Sea (Abstract). ECSA 56 Conference on coastal systems in transition: from a 'natural' to an 'anthropogenically-modified' state, September 4 – The ever-increasing demand of marine aggregates in the Belgian part of the North Sea leads to two unresolved questions: what is the extent and sustainability of the resource, and what are the effects of exploitation on the system? To provide an overall assessment framework, we exploit the continuum of knowledge from in-situ geological measurements to a complex numerical modelling suite. Measurements include historically available cores, seismic profiles and sediment size distributions, and have been incorporated into a 3D geological 'voxel' model of the resource. Innovatively, this model is fed into a numerical modelling suite that simulates hydrodynamics, sediment transport and seabed morphology over time. Regarding aggregate resources, the voxel model emphasizes the scarcity of the heavily sought-after medium to coarse sands and the need for additional measurements in order to reduce the uncertainty of resource assessments. When coupled to the numerical modelling suite, which is done for the first time in the marine realm, new insights into impact quantifications undoubtedly emerge: while existing studies assume an infinite amount of sediment available for transport and regeneration after extraction, or are only able to crudely initialize the seabed in the absence of information, the current strategy uses a more realistic parametrization of the seabed nature both horizontally and vertically. Scenarios over time can now be run to estimate the sustainability and effects of marine aggregate extraction, e.g. through elaborating on the threshold for habitat changes or changes in bed shear stress, being two indicators that Belgium proposed for the descriptors seafloor integrity and hydrodynamic conditions in the context of the European Marine Strategy Framework Directive.
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Kruiver, P.P., De Lange, G.L., Meijers, P., Korff, M., Stafleu, J., Van Elk, J., Bommer, J.J., Rodriguez-Marek, A. & Edwards, B., 2016. Regional site response characterization for the seismic hazard and risk analysis for induced... more
Kruiver, P.P., De Lange, G.L., Meijers, P., Korff, M., Stafleu, J., Van Elk, J., Bommer, J.J., Rodriguez-Marek, A. & Edwards, B., 2016. Regional site response characterization for the seismic hazard and risk analysis for induced earthquakes in Groningen, the Netherlands (Abstract). 6th International Conference on Geotechnical Earthquake Engineering & Soil Dynamics, August 1 – 6, 2016, Greater NOIDA, India.
Regional site response characterization for the seismic hazard and risk analysis for induced earthquakes in Groningen, the Netherlands (Abstract). 6th International The province of Groningen, the Netherlands, is experiencing induced earthquakes due to the exploitation of a large gas field. An increase of the annual rate of induced earthquakes is associated with the progressive depletion of the reservoir. The largest induced earthquake to date had a magnitude of 3.6 and occurred in 2012. To manage the related risks, a probabilistic seismic hazard and risk analysis has been carried out for the area. Site specific ground motion prediction equations (GMPEs) have been derived, which are calibrated with records of earthquake observations at ground stations in Groningen. The overall aim of the site response characterization is to reflect as clearly as possible the dynamic behavior of local ground conditions and also reduce the aleatory variability by invoking single-station sigma. Rather than using surrogate parameters such as VS30, the site amplification factors are modelled explicitly for zones over the entire region (40 x 50 km). Since the shallow subsurface of the area of interest consists of relatively soft to medium stiff Holocene and Pleistocene sediments, severe amplification of the earthquake shaking can occur. To estimate the local site response, the province was subdivided in zones of similar geology, reflected in comparable successions of soil composition. The geological zonation was based on a detailed 3D voxel-model of the subsurface up to a depth of 50 m, consisting of voxels of 100 m x 100 m x 0.5 m (x,y,z). For the site response, the voxel-model was extended to larger depths using borehole data and another less detailed geological subsurface model. As a first proxy for site response, we calculated average VS30 values for each of the geological zones. The distinction between thick, soft Holocene sediment layers in the northern part and thinner Holocene layers on top of stiffer Pleistocene sand in the southern part is reflected in the VS30 map, which shows lower VS30 values in the north and higher VS30 values in the south. Additionally, peat occurrences (low VS) and infills of tidal channels can be recognized in the VS30 map. As a next step, a more advanced measure of site response is developed using 1D calculation of amplification factors. To capture the influence of the thick sequence of unconsolidated sediment the reference baserock is selected as the base of the Upper North Sea Group. This reference baserock horizon has an average depth of 340 m. Spectral amplifications of 1D columns down to the reference baserock horizon were determined for each 100x100m voxel stack within the region using equivalent linear analyses. The resulting spectral amplification factors were grouped into distributions for each of the geological zones. By combining these amplification distributions per zone with the Groningen-specific GMPE for motions at the selected baserock horizon, surface motions are estimated in the hazard and risk calculations that reliably capture local effects and thus reduce epistemic uncertainty in the estimates.
Regional site response characterization for the seismic hazard and risk analysis for induced earthquakes in Groningen, the Netherlands (Abstract). 6th International The province of Groningen, the Netherlands, is experiencing induced earthquakes due to the exploitation of a large gas field. An increase of the annual rate of induced earthquakes is associated with the progressive depletion of the reservoir. The largest induced earthquake to date had a magnitude of 3.6 and occurred in 2012. To manage the related risks, a probabilistic seismic hazard and risk analysis has been carried out for the area. Site specific ground motion prediction equations (GMPEs) have been derived, which are calibrated with records of earthquake observations at ground stations in Groningen. The overall aim of the site response characterization is to reflect as clearly as possible the dynamic behavior of local ground conditions and also reduce the aleatory variability by invoking single-station sigma. Rather than using surrogate parameters such as VS30, the site amplification factors are modelled explicitly for zones over the entire region (40 x 50 km). Since the shallow subsurface of the area of interest consists of relatively soft to medium stiff Holocene and Pleistocene sediments, severe amplification of the earthquake shaking can occur. To estimate the local site response, the province was subdivided in zones of similar geology, reflected in comparable successions of soil composition. The geological zonation was based on a detailed 3D voxel-model of the subsurface up to a depth of 50 m, consisting of voxels of 100 m x 100 m x 0.5 m (x,y,z). For the site response, the voxel-model was extended to larger depths using borehole data and another less detailed geological subsurface model. As a first proxy for site response, we calculated average VS30 values for each of the geological zones. The distinction between thick, soft Holocene sediment layers in the northern part and thinner Holocene layers on top of stiffer Pleistocene sand in the southern part is reflected in the VS30 map, which shows lower VS30 values in the north and higher VS30 values in the south. Additionally, peat occurrences (low VS) and infills of tidal channels can be recognized in the VS30 map. As a next step, a more advanced measure of site response is developed using 1D calculation of amplification factors. To capture the influence of the thick sequence of unconsolidated sediment the reference baserock is selected as the base of the Upper North Sea Group. This reference baserock horizon has an average depth of 340 m. Spectral amplifications of 1D columns down to the reference baserock horizon were determined for each 100x100m voxel stack within the region using equivalent linear analyses. The resulting spectral amplification factors were grouped into distributions for each of the geological zones. By combining these amplification distributions per zone with the Groningen-specific GMPE for motions at the selected baserock horizon, surface motions are estimated in the hazard and risk calculations that reliably capture local effects and thus reduce epistemic uncertainty in the estimates.
Research Interests:
TNO - Geological Survey of the Netherlands (GSN) develops several subsurface models. Most of the published models are 'layer-based' models with national coverage, consisting of stratigraphical or hydrogeological layers with uniform... more
TNO - Geological Survey of the Netherlands (GSN) develops several subsurface models. Most of the published models are 'layer-based' models with national coverage, consisting of stratigraphical or hydrogeological layers with uniform properties. One of the models (GeoTOP) describes the upper 30m of the subsurface in millions of voxels (100 x 100 x 0.5m) each containing information on stratigraphy, lithology and the probability of occurrence for the different lithological classes. The GeoTOP modelling program was initiated in 2007 starting in the southwestern part of the Netherlands and has a regional approach, covering 13 areas. More than 90% of the available borehole data in DINO (a relational database containing ~525.000 bore holes maintained by GSN) is used and focus has been on the Holocene sequence, which has less detail in all other published models. Seven regions have been released covering around 55% of the country by the end of May 2016.
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In support of a sustainable management of marine geological resources, a geological knowledge base is being built for the Belgian and southernmost Dutch part of the North Sea. Various voxel models of the subsurface are created to... more
In support of a sustainable management of marine geological resources, a geological knowledge base is being built for the Belgian and southernmost Dutch part of the North Sea. Various voxel models of the subsurface are created to understand and predict changing sand and gravel quantities and qualities, and thus to ensure their long-term use. Each voxel is attributed with geological data from boreholes and seismic lines. By generating data products that also include various aspects of model uncertainty, scientists will optimize policy-related decision making. In a key step to increase transparency, issues related to low and high model uncertainty are being addressed by generating irregular grids, composed of voxels of differing resolution. Creating smaller voxels where uncertainty is low and larger voxels where uncertainty is high provides more model detail only where appropriate. Many interpolation algorithms, as well as their implementations in geostatistical software packages, do not support irregular grids. In a temporary solution, such grids are generated by post-processing model output (see Figure). When proven successful, irregular-sized voxel models may be integrated in a decision-support system optimized for user-friendliness and online visualization. Comparison between a standard-(left) and irregular-sized voxel model (right).
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Peat is abundantly present within the Holocene coastal-deltaic sequence of the Netherlands, where it is alternating with clastic fluvial, estuarine and lagoonal deposits. The areas that are rich in peat are vulnerable to land subsidence,... more
Peat is abundantly present within the Holocene coastal-deltaic sequence of the Netherlands, where it is alternating with clastic fluvial, estuarine and lagoonal deposits. The areas that are rich in peat are vulnerable to land subsidence, resulting from consolidation and oxidation, due to loading by overlying deposits, infrastructure and buildings, as well as excessive artificial drainage. The physical properties of the peat are very heterogeneous, with variable clastic admixture up to 80% of its mass and rapid decrease in porosity with increasing effective stress. Mapping the spatial distribution of the peat properties is essential for identifying areas most susceptible to future land subsidence, as mineral content determines volume loss by oxidation, and porosity influences the rate of consolidation. Here we present the outline of a study focusing on mapping mechanical peat properties in relation to density and amount of admixed clastic constituents of Holocene peat layers (in 3D). In this study we use a staged approach: 1) Identifying soil mechanical properties in two large datasets that are managed by Utrecht University and the Geological Survey. 2) Determining relations between these properties and palaeogeographical development of the area by evaluating these properties against known geological concepts such as distance to clastic source (river, estuary etc.). 3) Implementing the obtained relations in GeoTOP, which is a 3D geological subsurface model of the Netherlands developed by the Geological Survey. The model will be used, among others, to assess the susceptibility of different areas to peat related land subsidence and load bearing capacity of the subsurface. So far, our analysis has focused stage 1, by establishing empirical relations between mechanical peat properties in ∼70 paired (piezometer) cone penetration tests and continuously cored boreholes with LOI measurements. Results show strong correlations between net cone resistance (qn), excess pore water (u1-u0), and total vertical stress (σvo), suggesting that the overburden strongly controls the vertical differential susceptibility of peat layers to consolidation.
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The Groningen gas field in the Netherlands is one of the largest gas fields of Europe and has been in production since the 1960's. Due to the progressive depletion of the reservoir, induced seismic activity has increased in recent years.... more
The Groningen gas field in the Netherlands is one of the largest gas fields of Europe and has been in production since the 1960's. Due to the progressive depletion of the reservoir, induced seismic activity has increased in recent years. In 2012, an earthquake of magnitude 3.6 initiated further research in prediction and management of risks related to man-induced earthquakes. Last year the government decided to reduce the gas extraction for this reason. One of the topics of concern is the large difference in earthquake-related damage to buildings which, in addition to the distance to the epicenter, appears to be also related to the composition of the shallow subsurface. To improve the spatial distribution of Shear Wave Velocities (Vs) in the shallow subsurface, used for hazard prediction , the Geological Survey of the Netherlands and Deltares constructed a Vs 30 map of the upper 30 m of the gas field. In this map a high-resolution geological model (GeoTOP) is combined with seismic cone penetration tests (SCPT) from the area. The GeoTOP model is a 3D voxel model of the upper 50 m, in which each voxel (100x100x0.5 m) is attributed with lithostratigraphy and the most likely lithological class (peat, clay, fine sand, etc.). To obtain statistical distributions (with mean and standard deviation) of Vs for each combination of lithos-tratigraphical unit and lithoclass, 60 SCPTs were analyzed. In this way, it was possible to assign a specific Vs to each voxel in the model. For each voxel in the stack of voxels that covers the upper 30 m (i.e. 60 voxels), a Vs value was randomly drawn from the statistical distribution of the lithostratigraphical – lithoclass combination it belongs to. The Vs 30 for each voxelstack is then calculated using the harmonic mean of the Vs of the 60 voxels. By repeating this procedure 100 times, an (average) Vs 30 map and the uncertainty in Vs 30 has been constructed. Using the procedure described above we were able to delineate zones with distinct Vs 30 characteristics: areas containing predominantly soft Holocene deposits with low Vs 30 and areas with predominantly stiff Pleistocene deposits with high Vs 30 , complemented with the uncertainty in Vs 30. The incorporation of the high resolution geological model resulted in a large improvement compared to the previously used Vs 30 , which was a simple interpolation of Vs30 from a limited number of CPTs and SCPTs. This new procedure also gives the opportunity to study the role of the upper subsurface in site amplification predictions. Using this new method, risks related to gas extraction in urban areas can be better managed and predicted.
Research Interests:
The Tokyo Lowland is situated in a Neogene sedimentary basin near the triple junction of the North American, Pacific, and Philippine tectonic plates. The basin is filled with Neogene and Quaternary sediments up to a thickness of 3 km. In... more
The Tokyo Lowland is situated in a Neogene sedimentary basin near the triple junction of the North American, Pacific, and Philippine tectonic plates. The basin is filled with Neogene and Quaternary sediments up to a thickness of 3 km. In the upper 70 m of the basin, thick sequences of soft Holocene sediments occur which are assumed to have played a key role in the spatial variation of damage intensity during the 1923 Kanto earthquake (Magnitude 7.9 to 8.3). Historical records show this earthquake destroyed large parts of the Tokyo urban area which in that time was largely made up by wooden houses. Although the epicentre was 70 km to the southwest of Tokyo, severe damage occurred north of the city centre, presumably due to ground motion amplification in the soft Holocene sediments in the shallow subsurface. In order to assess the presumed relation between the damage pattern of the 1923 earthquake and the occurrence of soft Holocene sediments in the shallow subsurface, we constructed a 3D geological voxel model of the central part of the Tokyo Lowland. The model was constructed using a methodology originally developed for the lowlands of the Netherlands. The modelling workflow basically consists of three steps. First, some 10,000 borehole descriptions (gathered for geomechanical purposes), were subdivided into geological units that have uniform sediment characteristics, using both lithological and geomechanical (N-value) criteria. Second, 2D bounding surfaces were constructed, representing tops and bases of the geological units. These surfaces were used to place each voxel (100 by 100 by 1 m) within the correct geological unit. The N-values and lithological units in the borehole descriptions were subsequently used to perform a 3D stochastic interpolation of N-value and lithological class within each geological unit. Using a vertical voxel stack analysis, we were able to create a map showing the accumulated thickness of soft muds in the Holocene succession. A comparison of this map with a published map of the damage-ratio of wooden houses that were destroyed during the Kanto earthquake in 1923, shows a remarkable relation between zones of maximum destruction and the occurrence of the so-called 'zero' muds, the latter representing the sediments most sensitive for ground motion amplification. Our results show that the 3D geological voxel modelling approach presented here is able to make a spatial analysis of earth quake damage sensitivity in the Tokyo Lowland. This makes our workflow also is a promising tool for seismic hazard assessments in other areas in Japan were detailed insights in earth quake damage from historical records are absent.
Research Interests:
The Groningen gas field in the Netherlands is one of the largest gas fields of Europe and has been in production since the 60’s. Due to the progressive depletion of the reservoir, induced seismic activity has increased in recent years. In... more
The Groningen gas field in the Netherlands is one of the largest gas fields of Europe and has been in production since the 60’s. Due to the progressive depletion of the reservoir, induced seismic activity has increased in recent years. In 2012, an earthquake of magnitude 3.6 initiated further research in prediction and management of risks related to man-induced earthquakes.
The work reported here deals with the derivation of spatially distributed Shear Wave Velocity (Vs) for the upper 30 m of the subsurface column (Vs30). The Geological Survey of the Netherlands and Deltares combined a beta version of the GeoTOP model of the area and seismic cone penetration tests (SECPT) into a Vs30 model of the area covering the gas field. The GeoTOP model is a 3D voxel model, in which each voxel is attributed with lithostratigraphy and lithological classes (peat, clay, fine sand, etc.). The modelling procedure of GeoTOP starts with the modelling of top and bottom of each stratigraphical unit. Next, the 3D volume in between top and bottom (voxels) is filled with lithoclasses using geostatistical indicator simulation routines. This results in a 3D model in which each voxel has attributes describing the lithostratigraphial unit and the most likely lithoclass.
60 SECPT’s were used to derive statistical distributions (with mean and standard deviation) of Vs for each combination of lithostratigraphical unit and lithoclass. In this way it was possible to assign a specific Vs to each voxel in the model.
For each voxel in the stack of voxels that covers the upper 30 m (i.e. 60 voxels), a Vs value was randomly drawn from the statistical distribution of the lithostratigraphical – lithoclass combination it belongs to. The Vs30 for each voxelstack is then calculated using the harmonic mean of the Vs of the 60 voxels. By repeating this procedure 100 times, the uncertainty in Vs30 was determined.
Using the above described procedure we were able to delineate zones with distinct Vs30 characteristics: areas containing predominantly soft Holocene deposits with low Vs30 and areas with predominantly stiff Pleistocene deposits with high Vs30. Also the uncertainty in Vs30 could be quantified. This is a huge improvement compared to the previously used Vs30, which was one value for the entire gas field. The Vs30 will be used as input for site amplification predictions.
The work reported here deals with the derivation of spatially distributed Shear Wave Velocity (Vs) for the upper 30 m of the subsurface column (Vs30). The Geological Survey of the Netherlands and Deltares combined a beta version of the GeoTOP model of the area and seismic cone penetration tests (SECPT) into a Vs30 model of the area covering the gas field. The GeoTOP model is a 3D voxel model, in which each voxel is attributed with lithostratigraphy and lithological classes (peat, clay, fine sand, etc.). The modelling procedure of GeoTOP starts with the modelling of top and bottom of each stratigraphical unit. Next, the 3D volume in between top and bottom (voxels) is filled with lithoclasses using geostatistical indicator simulation routines. This results in a 3D model in which each voxel has attributes describing the lithostratigraphial unit and the most likely lithoclass.
60 SECPT’s were used to derive statistical distributions (with mean and standard deviation) of Vs for each combination of lithostratigraphical unit and lithoclass. In this way it was possible to assign a specific Vs to each voxel in the model.
For each voxel in the stack of voxels that covers the upper 30 m (i.e. 60 voxels), a Vs value was randomly drawn from the statistical distribution of the lithostratigraphical – lithoclass combination it belongs to. The Vs30 for each voxelstack is then calculated using the harmonic mean of the Vs of the 60 voxels. By repeating this procedure 100 times, the uncertainty in Vs30 was determined.
Using the above described procedure we were able to delineate zones with distinct Vs30 characteristics: areas containing predominantly soft Holocene deposits with low Vs30 and areas with predominantly stiff Pleistocene deposits with high Vs30. Also the uncertainty in Vs30 could be quantified. This is a huge improvement compared to the previously used Vs30, which was one value for the entire gas field. The Vs30 will be used as input for site amplification predictions.
Research Interests:
The Geological Survey of the Netherlands (GSN) develops several shallow subsurface models with regional to national coverage. The models are made publically available through the Survey’s web portal (www.dinoloket.nl). One of the models... more
The Geological Survey of the Netherlands (GSN) develops several shallow subsurface models with regional to national coverage. The models are made publically available through the Survey’s web portal (www.dinoloket.nl). One of the models (GeoTOP) describes the subsurface in millions of voxels (100 x 100 x 0.5 m) each containing information on stratigraphy, lithology and the probability of occurrence of the different lithological classes. In addition to a range of academic applications that create new geological insights, GeoTOP is very suitable to create customized maps for our users. These maps are used for, amongst other applications, assessments of subsurface composition and properties such as consolidation or hydraulic conductivity, solving spatial planning issues or revealing geotechnical risks.
Relatively simple calculations on vertical voxel stacks in the model result in 2D raster maps, of which the design and information can be easily adapted to the user’s needs. The method is demonstrated using two examples: (1) a risk map for highway construction on soft soil linked to the risk of exceptionally slow consolidation. In this example, the geological information in the 3D model is translated to six risk categories displayed in a 2D map.; (2) a generalized soil composition map used by municipalities in estimating maintenance costs of their subsurface sewage-network. For this map the vertical succession of lithological classes in the upper 8 m of GeoTOP is summarized into five different map classes.
The maps from both examples show how smart selections and combinations of stratigraphy and lithological classes up to a chosen depth result in maps that are tailor-made to the user requirements. When needed additional maps can be created relatively easy, bringing geological information one step closer to the user’s own area of expertise.
In the near future we will incorporate more parameters in GeoTOP, making the model suitable for other applications. For the long term perspective we envision to create more flexible models; incorporating time (4D) and scaling. These models allow for, for example, detailed maps in urban areas and the creation of maps for a certain time period. With these perspectives the amount of information in the models increases rapidly, making tailor-made dissemination even more important.
Relatively simple calculations on vertical voxel stacks in the model result in 2D raster maps, of which the design and information can be easily adapted to the user’s needs. The method is demonstrated using two examples: (1) a risk map for highway construction on soft soil linked to the risk of exceptionally slow consolidation. In this example, the geological information in the 3D model is translated to six risk categories displayed in a 2D map.; (2) a generalized soil composition map used by municipalities in estimating maintenance costs of their subsurface sewage-network. For this map the vertical succession of lithological classes in the upper 8 m of GeoTOP is summarized into five different map classes.
The maps from both examples show how smart selections and combinations of stratigraphy and lithological classes up to a chosen depth result in maps that are tailor-made to the user requirements. When needed additional maps can be created relatively easy, bringing geological information one step closer to the user’s own area of expertise.
In the near future we will incorporate more parameters in GeoTOP, making the model suitable for other applications. For the long term perspective we envision to create more flexible models; incorporating time (4D) and scaling. These models allow for, for example, detailed maps in urban areas and the creation of maps for a certain time period. With these perspectives the amount of information in the models increases rapidly, making tailor-made dissemination even more important.
Research Interests:
We present a full 3D interpolation describing groundwater rise in two neighbouring river valleys based on age-depth relations of basal peat index points for GW levels through the Holocene. Rapid drowning 9000 to 8000 cal BP occurred... more
We present a full 3D interpolation describing groundwater rise in two neighbouring river valleys based on age-depth relations of basal peat index points for GW levels through the Holocene.
Rapid drowning 9000 to 8000 cal BP occurred relatively synchronous in the two valleys, explained by strong sea-level rise control and similar valley gradients and dimensions of the inundated valley sections. After 8000 the drowning history diversifies. From then on a strong river gradient is in effect in the Rhine delta (valley 1), and absence of a larger river keeps gradients near sea-level far inland in the northern valley (valley 2). Valley slope differences explain further differences. Via GW rise effects, the palaeovalley dimensions are an important control on Holocene transgressive landscape development.
Rapid drowning 9000 to 8000 cal BP occurred relatively synchronous in the two valleys, explained by strong sea-level rise control and similar valley gradients and dimensions of the inundated valley sections. After 8000 the drowning history diversifies. From then on a strong river gradient is in effect in the Rhine delta (valley 1), and absence of a larger river keeps gradients near sea-level far inland in the northern valley (valley 2). Valley slope differences explain further differences. Via GW rise effects, the palaeovalley dimensions are an important control on Holocene transgressive landscape development.
Peat is abundantly present in the Holocene Rhine-Meuse delta and coastal plain of the Netherlands, where it occurs intercalated with fluvial and marine deposits. Due to its susceptibility to oxidation and compaction, peat had a major... more
Peat is abundantly present in the Holocene Rhine-Meuse delta and coastal plain of the Netherlands, where it occurs intercalated with fluvial and marine deposits. Due to its susceptibility to oxidation and compaction, peat had a major influence on deltaic and coastal sedimentary processes. At present peat is a major contributor to land subsidence. A research outline will be presented on 3D modeling of peat characteristics in the Holocene Rhine-Meuse delta, in order to assess its control on past and present landscape dynamics. Modeling will be executed in the GeoTop domain of TNO – Geological Survey of the Netherlands and will cover the delta and adjacent peaty coastal plain areas of Zuid-Holland, Noord-Holland and Flevoland. Input data will be derived from the DINO and Utrecht University borehole and CPT databases, mapping products and 14C data. The modeling procedure comprises four stages: 1) palaeo-groundwater rise, 2) peat-related land subsidence, 3) organic-facies distribution and 4) compaction, oxidation and mechanical properties of peat. The modeling results will eventually be integrated in a generic 3D map product, describing present day peat characteristics in relation to Holocene dynamics of peat formation and Rhine-Meuse sedimentary development.
The Geological Survey of the Netherlands (GSN) systematically produces 3D geological property models of the upper 30 meters of the Dutch subsurface. These 3D models provide a basis for answering subsurface related questions on, amongst... more
The Geological Survey of the Netherlands (GSN) systematically produces 3D geological property models of the upper 30 meters of the Dutch subsurface. These 3D models provide a basis for answering subsurface related questions on, amongst others, groundwater extraction and infrastructural issues. Modelling is carried out per province using a digital borehole database containing several hundreds of thousands of borehole descriptions and using geological maps created during the last few decades. The models are quantitative and user oriented which means they can be used by non-geologists within their own area of expertise. The models are produced using stochastic simulation techniques.
GeoTOP is the latest generation of 3D subsurface models produced at the GSN. This model schematises the shallow subsurface of the Netherlands in voxels of 100 by 100 by 0.5 meters up to a depth of 30 meters. The model provides estimates of lithostratigraphy and lithology (including grain-size classes), as well as physical parameters like hydraulic conductivity. The estimates are calculated using Sequential Gaussian Simulation (SGS) and Sequential Indicator Simulation (SIS). These stochastic techniques allow the construction of multiple, equally probable 3D subsurface models as well as the evaluation of model uncertainty.
Construction of the GeoTOP model is performed in a workflow that consists of four consecutive steps. In the first step all borehole data is interpreted stratigraphically using the lithological information within the borehole and available geological maps. In the second step (basal) stratigraphic surfaces are simulated using SGS, allowing calculation of a mean depth estimate of each surface and its standard deviation. Subsequently, all surfaces are stacked according to their stratigraphical position, resulting in a consistent layer-based model with estimates of top and base of each stratigraphical unit. The surfaces are then used to place each voxel in the model within the correct lithostratigraphical unit. During the third step, 3D simulation is performed using SIS which results in 100 realisations of lithology and sand grain-size for each voxel. Post-processing of the realisations results in a most probable estimate of lithology and sand grain-size. After a thorough quality check, all results are published via our web portal (www.dinoloket.nl). This website includes an online map viewer with the option to create vertical cross-sections through the models, a series of downloadable GIS products and a freely downloadable 3D SubsurfaceViewer.
The multiple, equally probable realisations of the model can be applied in multiple runs of a groundwater flow model, allowing better assessment of uncertainty associated with, for instance, groundwater head predictions. In addition, the stochastic simulation results are used to calculate probabilities for each lithology and sand grain-size in the model. The probabilities facilitate costs assessments during large infrastructural projects, where zones with high probabilities of peat and clay potentially are areas of higher construction costs.
GeoTOP is the latest generation of 3D subsurface models produced at the GSN. This model schematises the shallow subsurface of the Netherlands in voxels of 100 by 100 by 0.5 meters up to a depth of 30 meters. The model provides estimates of lithostratigraphy and lithology (including grain-size classes), as well as physical parameters like hydraulic conductivity. The estimates are calculated using Sequential Gaussian Simulation (SGS) and Sequential Indicator Simulation (SIS). These stochastic techniques allow the construction of multiple, equally probable 3D subsurface models as well as the evaluation of model uncertainty.
Construction of the GeoTOP model is performed in a workflow that consists of four consecutive steps. In the first step all borehole data is interpreted stratigraphically using the lithological information within the borehole and available geological maps. In the second step (basal) stratigraphic surfaces are simulated using SGS, allowing calculation of a mean depth estimate of each surface and its standard deviation. Subsequently, all surfaces are stacked according to their stratigraphical position, resulting in a consistent layer-based model with estimates of top and base of each stratigraphical unit. The surfaces are then used to place each voxel in the model within the correct lithostratigraphical unit. During the third step, 3D simulation is performed using SIS which results in 100 realisations of lithology and sand grain-size for each voxel. Post-processing of the realisations results in a most probable estimate of lithology and sand grain-size. After a thorough quality check, all results are published via our web portal (www.dinoloket.nl). This website includes an online map viewer with the option to create vertical cross-sections through the models, a series of downloadable GIS products and a freely downloadable 3D SubsurfaceViewer.
The multiple, equally probable realisations of the model can be applied in multiple runs of a groundwater flow model, allowing better assessment of uncertainty associated with, for instance, groundwater head predictions. In addition, the stochastic simulation results are used to calculate probabilities for each lithology and sand grain-size in the model. The probabilities facilitate costs assessments during large infrastructural projects, where zones with high probabilities of peat and clay potentially are areas of higher construction costs.
"The Geological Survey of the Netherlands systematically produces both shallow (< 500 m) and deep 3D geological models of the Netherlands. These models are predictions of geometry and properties of the subsurface, and are used in applied... more
"The Geological Survey of the Netherlands systematically produces both shallow (< 500 m) and deep 3D geological models of the Netherlands. These models are predictions of geometry and properties of the subsurface, and are used in applied research. One of the geological models for the shallow subsurface (GeoTOP) consists of voxels of 100 x 100 x 0.5 m to a depth of 30 m. For each voxel, lithostratigraphy, facies, lithology and sand grain-size classes are modeled using stochastic simulation techniques. These simulation techniques allow for the spatial uncertainty of the model results to be calculated.
One of the parameters that is subsequently assigned to the voxels in the GeoTOP model, is hydraulic conductivity (both horizontal and vertical). Hydraulic conductivities are measured on samples taken from high-quality drillings, which are subjected to falling head hydraulic conductivity tests. Samples are taken for all combinations of lithostratigraphy, facies and lithology that are present in the GeoTOP model. However, the volume of the samples is orders of magnitude smaller than the volume of a voxel in the GeoTOP model. In addition, the heterogeneity that occurs within a voxel is not accounted for in the GeoTOP model, since every voxel is assigned a single lithology that is representative for the entire voxel. To account for both the difference in volume and the intra-voxel heterogeneity, an upscaling procedure is developed to produce upscaled hydraulic conductivities for each GeoTOP voxel. A very fine 3D grid of voxels measuring 0.5 x 0.5 x 0.05 m is created that covers the GeoTOP voxel size (100 x 100 x 0.5 m) plus half of the dimensions of the GeoTOP voxel to counteract undesired edge-effects. It is assumed that the scale of the samples is comparable to the voxel size of this fine grid. For each lithostratigraphy and facies combination the spatial correlation structure (variogram) of the lithological classes is used to create 50 equally probable distributions of lithology for the fine grid using Sequential Indicator Simulation. Then, for each of the lithology realizations, a hydraulic conductivity is assigned to the simulated lithology class, using Sequential Gaussian Simulation, again with the appropriate variogram. This procedure results in 50 3D models of hydraulic conductivities in the fine grid. For each of these hydraulic conductivity models, a hydraulic head difference of 1 m between top and bottom of the model is used to calculate the flux at the bottom. In this way, difference in volume between sample-size and GeoTOP voxels and the internal heterogeneity within a GeoTOP voxel are accounted for.
An important application of the upscaled hydraulic conductivities in the GeoTOP model is the calculation of a detailed hydraulic resistance map of the Holocene confining layer. Comparison with results from pumping-tests and experiences from groundwater flow modellers indicate that the upscaled hydraulic conductivities yield reasonable results.
"
One of the parameters that is subsequently assigned to the voxels in the GeoTOP model, is hydraulic conductivity (both horizontal and vertical). Hydraulic conductivities are measured on samples taken from high-quality drillings, which are subjected to falling head hydraulic conductivity tests. Samples are taken for all combinations of lithostratigraphy, facies and lithology that are present in the GeoTOP model. However, the volume of the samples is orders of magnitude smaller than the volume of a voxel in the GeoTOP model. In addition, the heterogeneity that occurs within a voxel is not accounted for in the GeoTOP model, since every voxel is assigned a single lithology that is representative for the entire voxel. To account for both the difference in volume and the intra-voxel heterogeneity, an upscaling procedure is developed to produce upscaled hydraulic conductivities for each GeoTOP voxel. A very fine 3D grid of voxels measuring 0.5 x 0.5 x 0.05 m is created that covers the GeoTOP voxel size (100 x 100 x 0.5 m) plus half of the dimensions of the GeoTOP voxel to counteract undesired edge-effects. It is assumed that the scale of the samples is comparable to the voxel size of this fine grid. For each lithostratigraphy and facies combination the spatial correlation structure (variogram) of the lithological classes is used to create 50 equally probable distributions of lithology for the fine grid using Sequential Indicator Simulation. Then, for each of the lithology realizations, a hydraulic conductivity is assigned to the simulated lithology class, using Sequential Gaussian Simulation, again with the appropriate variogram. This procedure results in 50 3D models of hydraulic conductivities in the fine grid. For each of these hydraulic conductivity models, a hydraulic head difference of 1 m between top and bottom of the model is used to calculate the flux at the bottom. In this way, difference in volume between sample-size and GeoTOP voxels and the internal heterogeneity within a GeoTOP voxel are accounted for.
An important application of the upscaled hydraulic conductivities in the GeoTOP model is the calculation of a detailed hydraulic resistance map of the Holocene confining layer. Comparison with results from pumping-tests and experiences from groundwater flow modellers indicate that the upscaled hydraulic conductivities yield reasonable results.
"
Van Lancker, V., De Mol, L., De Tré, G., Maljers, D., Missiaen, T., Stafleu, J., Van den Eynde, D., & van Heteren, S., 2014. Exploring our marine geological resources in the fifth dimension: About 3D voxels, 4D impact models and... more
Van Lancker, V., De Mol, L., De Tré, G., Maljers, D., Missiaen, T., Stafleu, J., Van den Eynde, D., & van Heteren, S., 2014. Exploring our marine geological resources in the fifth dimension: About 3D voxels, 4D impact models and uncertainty. in: Mees, J. et al. (Ed.). Book of abstracts – VLIZ Young Scientists’ Day. Brugge, Belgium, 7 March 2014. VLIZ Special Publication 67, 111.
ABSTRACT
Mineral and geological resources such as sand and gravel, ores and hydrocarbons can be considered to be non-renewable on time scales relevant for decision makers. Once exhausted by humans, they are not replenished rapidly enough by nature, meaning that truly sustainable management of these invaluable and sought-after resources is not possible. Using them wisely and sparingly requires a thorough and careful balancing of available quantity and quality versus rapidly changing societal and economical needs. The need for such an approach is recognized in the EU’s Raw Materials Initiative, which highlights the optimization of the geological knowledge base as a key element in ensuring enduring supplies from within the EU borders. Comprehensive knowledge on the distribution, composition and dynamics of geological resources therefore is critical for developing long-term strategies for resource use in our changing world.
To help ensure the optimal use of finite quantities of sand and gravel in the Belgian and southern Dutch parts of the North Sea, the new Belspo Brain-be project TILES will develop cross-border and integrated strategies for their long-term extraction. TILES has the ambition of:
(1) Developing a decision support system (DSS) for resource use. This DSS contains tools that link 3D geological models, knowledge and concepts, providing information on present-day resource quantities and distribution, to numerical models of extraction-related environmental impact through time. Together they quantify natural and man-made boundary conditions and changes to define exploitation thresholds that safeguard sustainability on a multi-decadal time scale. These thresholds need to be respected to ensure that geomorphological and habitat recovery from perturbations is rapid and secure, a prerequisite stated in Europe’s Marine Strategy Framework Directive, the environmental pillar of Europe’s Maritime Policy.
(2) Providing long-term adaptive management strategies that have generic value and can be used for all non-hydrocarbon geological resources in the marine environment, locally and more globally.
(3) Proposing legally binding measures to optimize and maximize long-term exploitation of aggregate resources within sustainable environmental limits. These proposed measures feed into policy and associated monitoring plans that are periodically evaluated and adapted (e.g. Marine Spatial Planning and the Marine Strategy Framework Directive).
Extensive analyses of data- and interpolation-related uncertainties, and of the propagation of these uncertainties in data products such as maps and GIS layers, form the backbone of the DSS. This is a necessary step in producing data products with confidence limits, and critical to detecting ‘true’ seabed changes in environmental monitoring. Using a dedicated subsurface viewer, a suite of data products will be viewable online. They can be extracted on demand from an underlying voxel (3D pixel) model. Each voxel will be assigned with values for geological, environmental and decisionrelated parameters, including uncertainty. The flexible 3D interaction and querying, enabled by TILES, will be invaluable for professionals, but also for the public at large and for students in particular. It will herald a new age in assessing cross-border impacts of marine exploitation activities.
ABSTRACT
Mineral and geological resources such as sand and gravel, ores and hydrocarbons can be considered to be non-renewable on time scales relevant for decision makers. Once exhausted by humans, they are not replenished rapidly enough by nature, meaning that truly sustainable management of these invaluable and sought-after resources is not possible. Using them wisely and sparingly requires a thorough and careful balancing of available quantity and quality versus rapidly changing societal and economical needs. The need for such an approach is recognized in the EU’s Raw Materials Initiative, which highlights the optimization of the geological knowledge base as a key element in ensuring enduring supplies from within the EU borders. Comprehensive knowledge on the distribution, composition and dynamics of geological resources therefore is critical for developing long-term strategies for resource use in our changing world.
To help ensure the optimal use of finite quantities of sand and gravel in the Belgian and southern Dutch parts of the North Sea, the new Belspo Brain-be project TILES will develop cross-border and integrated strategies for their long-term extraction. TILES has the ambition of:
(1) Developing a decision support system (DSS) for resource use. This DSS contains tools that link 3D geological models, knowledge and concepts, providing information on present-day resource quantities and distribution, to numerical models of extraction-related environmental impact through time. Together they quantify natural and man-made boundary conditions and changes to define exploitation thresholds that safeguard sustainability on a multi-decadal time scale. These thresholds need to be respected to ensure that geomorphological and habitat recovery from perturbations is rapid and secure, a prerequisite stated in Europe’s Marine Strategy Framework Directive, the environmental pillar of Europe’s Maritime Policy.
(2) Providing long-term adaptive management strategies that have generic value and can be used for all non-hydrocarbon geological resources in the marine environment, locally and more globally.
(3) Proposing legally binding measures to optimize and maximize long-term exploitation of aggregate resources within sustainable environmental limits. These proposed measures feed into policy and associated monitoring plans that are periodically evaluated and adapted (e.g. Marine Spatial Planning and the Marine Strategy Framework Directive).
Extensive analyses of data- and interpolation-related uncertainties, and of the propagation of these uncertainties in data products such as maps and GIS layers, form the backbone of the DSS. This is a necessary step in producing data products with confidence limits, and critical to detecting ‘true’ seabed changes in environmental monitoring. Using a dedicated subsurface viewer, a suite of data products will be viewable online. They can be extracted on demand from an underlying voxel (3D pixel) model. Each voxel will be assigned with values for geological, environmental and decisionrelated parameters, including uncertainty. The flexible 3D interaction and querying, enabled by TILES, will be invaluable for professionals, but also for the public at large and for students in particular. It will herald a new age in assessing cross-border impacts of marine exploitation activities.
"The Geological Survey of the Netherlands (GSN) systematically produces 3D stochastic voxel models of the upper 50 m of the subsurface. Each voxel contains the following properties: (1) the geological unit the voxel belongs to; (2) the... more
"The Geological Survey of the Netherlands (GSN) systematically produces 3D stochastic voxel models of the upper 50 m of the subsurface. Each voxel contains the following properties: (1) the geological unit the voxel belongs to; (2) the lithological class (including grain-size classes for sand) that is representative for the voxel; and (3) a set of probabilities of occurrence for each of the lithological classes that may be present in the voxel.
The probabilities of occurrence provide us with a measure of model uncertainty. The probabilities of an individual voxel can be displayed in a single bar graph, thus showing its probability distribution and hence model uncertainty. Similar displays are possible in visualizations of virtual boreholes (i.e. vertical stacks of voxels). However in 2D visualizations, for instance a vertical cross-sections, it is no longer possible to show all probabilities in a single view: the user will always be presented with one of the probabilities at a time.
To solve this problem, Wellmann & Regenauer-Lieb (2012) proposed to use information entropy as a measure of uncertainty in 3D models. The information entropy of a voxel is a single value ranging from 0 to 1 that can easily be calculated from each of the probabilities of lithological class. An entropy value of 0 means that there is no uncertainty, whereas a value of 1 occurs when all lithological classes have the same probability. Values in between 0 and 1 account for both the number of lithological classes with a probability higher than 0 (the more classes, the higher the entropy) and the differences amongst the probabilities (the greater the differences, the lower the entropy).
Another approach to visualizing uncertainty is to use borehole density. Many users assume a one-to-one relationship between borehole density and reliability of the model. Although this relationship not always exists (for example, a homogeneous unit may be fully characterized by a single borehole), it adheres to common sense and is therefore easily understood. Borehole density was calculated for horizontal slices through the model, each at a certain height with respect to Dutch Ordnance Datum. For each of these horizontal slices, we used standard 2D GIS logic to count the number of boreholes available in cells of 5 by 5 km at the depth of the slice. The result was then converted to the voxel model.
The uncertainty measures described above are or will be disseminated through our webportal (www.dinoloket.nl) in a number of ways, including an on-line map viewer with the option to create virtual boreholes and vertical cross-sections, a series of downloadable GIS products and datasets to be used in the freely available 3D SubsurfaceViewer software.
"
The probabilities of occurrence provide us with a measure of model uncertainty. The probabilities of an individual voxel can be displayed in a single bar graph, thus showing its probability distribution and hence model uncertainty. Similar displays are possible in visualizations of virtual boreholes (i.e. vertical stacks of voxels). However in 2D visualizations, for instance a vertical cross-sections, it is no longer possible to show all probabilities in a single view: the user will always be presented with one of the probabilities at a time.
To solve this problem, Wellmann & Regenauer-Lieb (2012) proposed to use information entropy as a measure of uncertainty in 3D models. The information entropy of a voxel is a single value ranging from 0 to 1 that can easily be calculated from each of the probabilities of lithological class. An entropy value of 0 means that there is no uncertainty, whereas a value of 1 occurs when all lithological classes have the same probability. Values in between 0 and 1 account for both the number of lithological classes with a probability higher than 0 (the more classes, the higher the entropy) and the differences amongst the probabilities (the greater the differences, the lower the entropy).
Another approach to visualizing uncertainty is to use borehole density. Many users assume a one-to-one relationship between borehole density and reliability of the model. Although this relationship not always exists (for example, a homogeneous unit may be fully characterized by a single borehole), it adheres to common sense and is therefore easily understood. Borehole density was calculated for horizontal slices through the model, each at a certain height with respect to Dutch Ordnance Datum. For each of these horizontal slices, we used standard 2D GIS logic to count the number of boreholes available in cells of 5 by 5 km at the depth of the slice. The result was then converted to the voxel model.
The uncertainty measures described above are or will be disseminated through our webportal (www.dinoloket.nl) in a number of ways, including an on-line map viewer with the option to create virtual boreholes and vertical cross-sections, a series of downloadable GIS products and datasets to be used in the freely available 3D SubsurfaceViewer software.
"
Over the past 20 years, TNO - Geological Survey of the Netherlands (GSN) has moved from the systematic production of geological map sheets to 3D subsurface modelling. GeoTOP comprises the latest generation of subsurface models at GSN.... more
Over the past 20 years, TNO - Geological Survey of the Netherlands (GSN) has moved from the systematic production of geological map sheets to 3D subsurface modelling. GeoTOP comprises the latest generation of subsurface models at GSN. GeoTOP schematises the shallow subsurface in millions of voxels of 100 by 100 by 0.5 m (x,y,z) up to a depth of 50 m, which is the main zone of current subsurface activity. The model provides estimates of lithostratigraphy and lithology (including grain-size classes), as well as physical and chemical parameters, such as hydraulic conductivity and chemical element concentrations.
With the continuing expansion of the area for which GeoTOP is available, the geological modelling workflow is fully established and the 3D models are being used by a diverse array of customers. Up-to-now however, this usage is mainly concentrated in more rural areas. One of the main challenges lying ahead is to improve the applicability of geological subsurface models in urbanised regions. The urban subsurface is heavily used nowadays. The heavy use not only relates to the presence of a dense network of underground infrastructure, including tunnels, car parks, sewage systems, etc., but also to the subsurface as a resource for energy and water. Combined with the presence of zones rich in archaeological heritage and diverse pollution sources, this heavy use increasingly leads to conflicting claims on the scarce subsurface space. Furthermore, the shallow urban subsurface is often characterised by the presence of a thick layer of man-made ground, which is not represented in great detail in current models. Many questions are associated with the lithological, hydrological and geochemical properties of this very heterogeneous layer.
In a pilot project together with the City of Rotterdam, GSN is improving the 3D geological modelling workflow, aiming at a model that is suited to deal with the peculiarities of the urban subsurface. The City of Rotterdam is actively working on 3D subsurface spatial planning and to facilitate this, the city has integrated all known information on its subsurface, including borehole data, cone penetration test data, underground infrastructure and spatial claims, in a single geospatial database. The improved 3D subsurface model of the city centre will include a large part of this information. Modelling focus is particularly on:
- Improved model resolution (i.e. smaller voxels) by incorporating as much local information on the build-up of the subsurface as possible, including historical and geotechnical data
- More detailed mapping and modelling of the man-made deposits and their characteristics
- Combined visualisation of the geological subsurface model and detailed information on underground infrastructure and spatial use.
We expect the resulting model of the city centre to better meet the challenges an urban area is facing with regard to its subsurface. It will ultimately enable the City of Rotterdam to fully integrate its subsurface characteristics in the process of 3D spatial planning.
With the continuing expansion of the area for which GeoTOP is available, the geological modelling workflow is fully established and the 3D models are being used by a diverse array of customers. Up-to-now however, this usage is mainly concentrated in more rural areas. One of the main challenges lying ahead is to improve the applicability of geological subsurface models in urbanised regions. The urban subsurface is heavily used nowadays. The heavy use not only relates to the presence of a dense network of underground infrastructure, including tunnels, car parks, sewage systems, etc., but also to the subsurface as a resource for energy and water. Combined with the presence of zones rich in archaeological heritage and diverse pollution sources, this heavy use increasingly leads to conflicting claims on the scarce subsurface space. Furthermore, the shallow urban subsurface is often characterised by the presence of a thick layer of man-made ground, which is not represented in great detail in current models. Many questions are associated with the lithological, hydrological and geochemical properties of this very heterogeneous layer.
In a pilot project together with the City of Rotterdam, GSN is improving the 3D geological modelling workflow, aiming at a model that is suited to deal with the peculiarities of the urban subsurface. The City of Rotterdam is actively working on 3D subsurface spatial planning and to facilitate this, the city has integrated all known information on its subsurface, including borehole data, cone penetration test data, underground infrastructure and spatial claims, in a single geospatial database. The improved 3D subsurface model of the city centre will include a large part of this information. Modelling focus is particularly on:
- Improved model resolution (i.e. smaller voxels) by incorporating as much local information on the build-up of the subsurface as possible, including historical and geotechnical data
- More detailed mapping and modelling of the man-made deposits and their characteristics
- Combined visualisation of the geological subsurface model and detailed information on underground infrastructure and spatial use.
We expect the resulting model of the city centre to better meet the challenges an urban area is facing with regard to its subsurface. It will ultimately enable the City of Rotterdam to fully integrate its subsurface characteristics in the process of 3D spatial planning.
"The Geological Survey of the Netherlands (GSN) develops nation-wide, multi-purpose 3D voxel models of the shallow subsurface. The models are available free-of-charge through the Survey’s interactive webportal (www.dinoloket.nl). One of... more
"The Geological Survey of the Netherlands (GSN) develops nation-wide, multi-purpose 3D voxel models of the shallow subsurface. The models are available free-of-charge through the Survey’s interactive webportal (www.dinoloket.nl). One of the models (GeoTOP) describes the subsurface in millions of voxels (100 x 100 x 0.5 m) each containing information on stratigraphy and lithology.
A reliable assessment of subsurface composition and properties can make an important contribution to solving spatial planning issues. A quick and easy step is an online assessment of subsurface characteristics using the available web tools, including an online map viewer with the option to create virtual boreholes and vertical cross-sections. In addition, the model can be downloaded from the webportal for detailed analyses in 2D or 3D.
We will show how relatively simple calculations on vertical voxel stacks in the model can result in customised 2D raster maps. Examples include a generalised soil composition map, a cumulative thickness map of Holocene peat, and the depth below land surface of the first thick sand layer. Additional maps can be created relatively easy, bringing geological information one step closer to the user’s own area of expertise."
A reliable assessment of subsurface composition and properties can make an important contribution to solving spatial planning issues. A quick and easy step is an online assessment of subsurface characteristics using the available web tools, including an online map viewer with the option to create virtual boreholes and vertical cross-sections. In addition, the model can be downloaded from the webportal for detailed analyses in 2D or 3D.
We will show how relatively simple calculations on vertical voxel stacks in the model can result in customised 2D raster maps. Examples include a generalised soil composition map, a cumulative thickness map of Holocene peat, and the depth below land surface of the first thick sand layer. Additional maps can be created relatively easy, bringing geological information one step closer to the user’s own area of expertise."
The Geological Survey of the Netherlands (GSN) systematically produces 3D geological models of the Netherlands. To date, we build and maintain two different types of nation-wide models: (1) layer-based models in which the subsurface is... more
The Geological Survey of the Netherlands (GSN) systematically produces 3D geological models of the Netherlands. To date, we build and maintain two different types of nation-wide models: (1) layer-based models in which the subsurface is represented by a series of tops and bases of geological or hydrogeological units, and (2) voxel models in which the subsurface is subdivided in a regular grid of voxels that can contain different properties.
Our models are disseminated free-of-charge through the DINO-webportal in a number of ways, including in an on-line map viewer with the option to create vertical cross-sections through the models, and as a series of downloadable GIS products. A recent addition to the portal is the freely downloadable SubsurfaceViewer software (developed by INSIGHT GmbH), allowing users to download and visualize both the layer-based models and the voxel models on their desktop computers.
The SubsurfaceViewer includes both a classical map view and an interactive 3D view. In addition, the SubsurfaceViewer offers synthetic boreholes as well as vertical cross-sections through the models.
A recent development in the SubsurfaceViewer is the introduction of a data structure supporting irregular voxels (i.e. rectangular voxels of different dimensions combined in a single grid). We have chosen a simple data structure consisting of a plain ASCII-file containing the x,y,z -coordinates of the lower left and upper right corner of each voxel followed by a list of property values (e.g. the geological unit the voxel belongs to, the lithological composition and the hydraulic conductivity).
Irregular voxels are used to deliver voxel models that display more detail (i.e. smaller voxels) where data density is high, and less detail where data density is low. In general, data density in the Netherlands allows the construction of detailed voxel models with a resolution of 100 x 100 x 0.5 m for the upper 30 m. The incorporation of soil data allows an even higher resolution (25 x 25 x 0.1 m) in the upper 2 m.
An interesting spin-off of the irregular voxels is that they allow the efficient storage and analysis of layer-based models. Using irregular voxels, a layer-based model can be stored in a single file rather than in a large set of separate raster-files of tops and bases of the layers in the model.
Our models are disseminated free-of-charge through the DINO-webportal in a number of ways, including in an on-line map viewer with the option to create vertical cross-sections through the models, and as a series of downloadable GIS products. A recent addition to the portal is the freely downloadable SubsurfaceViewer software (developed by INSIGHT GmbH), allowing users to download and visualize both the layer-based models and the voxel models on their desktop computers.
The SubsurfaceViewer includes both a classical map view and an interactive 3D view. In addition, the SubsurfaceViewer offers synthetic boreholes as well as vertical cross-sections through the models.
A recent development in the SubsurfaceViewer is the introduction of a data structure supporting irregular voxels (i.e. rectangular voxels of different dimensions combined in a single grid). We have chosen a simple data structure consisting of a plain ASCII-file containing the x,y,z -coordinates of the lower left and upper right corner of each voxel followed by a list of property values (e.g. the geological unit the voxel belongs to, the lithological composition and the hydraulic conductivity).
Irregular voxels are used to deliver voxel models that display more detail (i.e. smaller voxels) where data density is high, and less detail where data density is low. In general, data density in the Netherlands allows the construction of detailed voxel models with a resolution of 100 x 100 x 0.5 m for the upper 30 m. The incorporation of soil data allows an even higher resolution (25 x 25 x 0.1 m) in the upper 2 m.
An interesting spin-off of the irregular voxels is that they allow the efficient storage and analysis of layer-based models. Using irregular voxels, a layer-based model can be stored in a single file rather than in a large set of separate raster-files of tops and bases of the layers in the model.
The Geological Survey of the Netherlands (GSN) systematically produces 3D geological models of the Netherlands. To date, we build and maintain two different types of nation-wide models: (1) layer-based models in which the subsurface is... more
The Geological Survey of the Netherlands (GSN) systematically produces 3D geological models of the Netherlands. To date, we build and maintain two different types of nation-wide models: (1) layer-based models in which the subsurface is represented by a series of tops and bases of geological or hydrogeological units, and (2) voxel models in which the subsurface is subdivided in a regular grid of voxels that can contain different properties.
Our models are disseminated free-of-charge through the DINO-portal (www.dinoloket.nl) in a number of ways, including in an on-line map viewer with the option to create vertical cross-sections through the models, and as a series of downloadable GIS products. A recent addition to the portal is the freely downloadable SubsurfaceViewer software (developed by INSIGHT GmbH), allowing users to download and visualize both the layer-based models and the voxel models on their desktop computers.
The SubsurfaceViewer allows visualization and analysis of geological layer-based and voxel models of different data structures and origin and includes a selection of data used to construct the respective model (maps, cross-sections, borehole data, etc.). The user is presented both a classical map view and an interactive 3D view. In addition, the SubsurfaceViewer offers a one dimensional vertical view as a synthetic borehole as well as a vertical cross-section view. The data structure is based on XML and linked ASCII-files and allows the hybrid usage of layers (tin and 2D raster) and voxels (3D raster).
A recent development in the SubsurfaceViewer is the introduction of a data structure supporting irregular voxels. We have chosen a simple data structure consisting of a plain ASCII-file containing the x,y,z –coordinates of the lower left and upper right corner of each voxel followed by a list of property values (e.g. the geological unit the voxel belongs to, the lithological composition and the hydraulic conductivity).
Irregular voxels are used to deliver voxel models that display more detail (i.e. smaller voxels) where data density is high, and less detail where data density is low. In general, data density in the Netherlands allows the construction of detailed voxel models with a resolution of 100 x 100 x 0.5 m for the upper 30 m. The incorporation of soil data (both maps and boreholes) allows an even higher resolution (25 x 25 x 0.1 m) in the upper 2 m.
An interesting spin-off of the irregular voxels is that they allow the efficient storage and analysis of layerbased models. Using irregular voxels, the layer-based hydrogeological model of the Netherlands, for instance, can be stored in a single file rather than in a large set of separate raster-files of top, base, thickness and hydraulic conductivity for each of the 128 hydrogeological layers in the model.
Our models are disseminated free-of-charge through the DINO-portal (www.dinoloket.nl) in a number of ways, including in an on-line map viewer with the option to create vertical cross-sections through the models, and as a series of downloadable GIS products. A recent addition to the portal is the freely downloadable SubsurfaceViewer software (developed by INSIGHT GmbH), allowing users to download and visualize both the layer-based models and the voxel models on their desktop computers.
The SubsurfaceViewer allows visualization and analysis of geological layer-based and voxel models of different data structures and origin and includes a selection of data used to construct the respective model (maps, cross-sections, borehole data, etc.). The user is presented both a classical map view and an interactive 3D view. In addition, the SubsurfaceViewer offers a one dimensional vertical view as a synthetic borehole as well as a vertical cross-section view. The data structure is based on XML and linked ASCII-files and allows the hybrid usage of layers (tin and 2D raster) and voxels (3D raster).
A recent development in the SubsurfaceViewer is the introduction of a data structure supporting irregular voxels. We have chosen a simple data structure consisting of a plain ASCII-file containing the x,y,z –coordinates of the lower left and upper right corner of each voxel followed by a list of property values (e.g. the geological unit the voxel belongs to, the lithological composition and the hydraulic conductivity).
Irregular voxels are used to deliver voxel models that display more detail (i.e. smaller voxels) where data density is high, and less detail where data density is low. In general, data density in the Netherlands allows the construction of detailed voxel models with a resolution of 100 x 100 x 0.5 m for the upper 30 m. The incorporation of soil data (both maps and boreholes) allows an even higher resolution (25 x 25 x 0.1 m) in the upper 2 m.
An interesting spin-off of the irregular voxels is that they allow the efficient storage and analysis of layerbased models. Using irregular voxels, the layer-based hydrogeological model of the Netherlands, for instance, can be stored in a single file rather than in a large set of separate raster-files of top, base, thickness and hydraulic conductivity for each of the 128 hydrogeological layers in the model.
The Geological Survey of the Netherlands systematically produces both shallow (< 500 m) and deep 3D geological models of the Netherlands. These models are predictions of geometry and properties of the subsurface, and are used in applied... more
The Geological Survey of the Netherlands systematically produces both shallow (< 500 m) and deep 3D geological models of the Netherlands. These models are predictions of geometry and properties of the subsurface, and are used in applied research. One of the geological models for the shallow subsurface (GeoTOP) consists of voxels of 100 x 100 x 0.5 m to a depth of 30-50 m below surface. For each voxel, lithostratigraphy, facies and lithological classes are modeled with geostatistical simulation techniques. These simulation techniques allow for the spatial uncertainty of the model results to be calculated.
One of the parameters that is subsequently assigned to the voxels in the GeoTOP model, is hydraulic conductivity (both horizontal and vertical).
Hydraulic conductivities are measured on samples taken from high-quality drillings, which are subjected to falling head hydraulic conductivity tests. Samples are taken for all combinations of lithostratigraphy, facies and lithology that are present in the GeoTOP model. The volume of the samples is orders of magnitude smaller than the volume of a voxel in the GeoTOP model. Apart from that, the heterogeneity that occurs within a voxel is not accounted for in the GeoTOP model, since every voxel gets a single lithology that is deemed representative for the entire voxel.
To account for both the difference in volume and the within-voxel heterogeneity, an upscaling procedure is developed to produce up-scaled hydraulic conductivities for each GeoTOP voxel. A very fine 3D grid of 0.5 x 0.5 x 0.05 m is created that covers the GeoTOP voxel size (100 x 100 x 0.5 m) plus half of the dimensions of the GeoTOP voxel to counteract undesired edge-effects. It is assumed that the scale of the samples is comparable to the voxel size of this fine grid. For each lithostratigraphy and facies combination the spatial correlation structure (variogram) of the lithological classes is used to create 50 equiprobable distributions of lithology for the fine grid with sequential indicator simulation. Then, for each of the lithology realizations, a hydraulic conductivity is assigned to the simulated lithology class, using Sequential Gaussian Simulation, again with the appropriate variogram This results in 50 3D models of hydraulic conductivities on the fine grid. For each of these hydraulic conductivity models, a hydraulic head difference of 1m between top and bottom of the model is used to calculate the flux at the bottom of the model. No-flow boundaries is used on the sides of the model. In this way, difference in volume between sample-size and GeoTOP voxels and the internal heterogeneity within a GeoTOP voxel are accounted for.
An important product derived from assigning the upscaled hydraulic conductivities to the GeoTOP model is the hydraulic resistance of the Holocene confining layer. An example is presented, in which the calculation of the hydraulic resistance takes the uncertainty of the geological modelling into account. Comparison with results from pump-tests and experiences from users indicate that the upscaling and the subsequent calculation of hydraulic resistance of the Holocene layer yields reasonable results.
One of the parameters that is subsequently assigned to the voxels in the GeoTOP model, is hydraulic conductivity (both horizontal and vertical).
Hydraulic conductivities are measured on samples taken from high-quality drillings, which are subjected to falling head hydraulic conductivity tests. Samples are taken for all combinations of lithostratigraphy, facies and lithology that are present in the GeoTOP model. The volume of the samples is orders of magnitude smaller than the volume of a voxel in the GeoTOP model. Apart from that, the heterogeneity that occurs within a voxel is not accounted for in the GeoTOP model, since every voxel gets a single lithology that is deemed representative for the entire voxel.
To account for both the difference in volume and the within-voxel heterogeneity, an upscaling procedure is developed to produce up-scaled hydraulic conductivities for each GeoTOP voxel. A very fine 3D grid of 0.5 x 0.5 x 0.05 m is created that covers the GeoTOP voxel size (100 x 100 x 0.5 m) plus half of the dimensions of the GeoTOP voxel to counteract undesired edge-effects. It is assumed that the scale of the samples is comparable to the voxel size of this fine grid. For each lithostratigraphy and facies combination the spatial correlation structure (variogram) of the lithological classes is used to create 50 equiprobable distributions of lithology for the fine grid with sequential indicator simulation. Then, for each of the lithology realizations, a hydraulic conductivity is assigned to the simulated lithology class, using Sequential Gaussian Simulation, again with the appropriate variogram This results in 50 3D models of hydraulic conductivities on the fine grid. For each of these hydraulic conductivity models, a hydraulic head difference of 1m between top and bottom of the model is used to calculate the flux at the bottom of the model. No-flow boundaries is used on the sides of the model. In this way, difference in volume between sample-size and GeoTOP voxels and the internal heterogeneity within a GeoTOP voxel are accounted for.
An important product derived from assigning the upscaled hydraulic conductivities to the GeoTOP model is the hydraulic resistance of the Holocene confining layer. An example is presented, in which the calculation of the hydraulic resistance takes the uncertainty of the geological modelling into account. Comparison with results from pump-tests and experiences from users indicate that the upscaling and the subsequent calculation of hydraulic resistance of the Holocene layer yields reasonable results.
The Geological Survey of the Netherlands (GSN) defines digital geological models as predictions of both geometry and properties of the subsurface. In contrast to singular observations in boreholes and the projected information of... more
The Geological Survey of the Netherlands (GSN) defines digital geological models as predictions of both geometry and properties of the subsurface. In contrast to singular observations in boreholes and the projected information of traditional maps, models provide continuous representations of the subsurface built with all geological expertise available. The GSN systematically produces 3D models of the upper 500 m of the Netherlands. To date, we build and maintain two different types of nation-wide models: (1)layer-based models in which the subsurface is represented as a series of tops and bases of geological or hydrogeological units, and (2) voxel models in which the subsurface is subdivided in a regular grid of voxels. The models are quantitative and user-oriented, i.e. they are applicable for non-geologists in their own area of expertise. They are also stochastic in nature, which implies that
model uncertainty can be quantified.
GeoTOP is the latest generation of Dutch subsurface models at TNO – Geological Survey of the Netherlands. GeoTOP schematises the shallow subsurface in millions of voxels of 100 by 100 by 0.5 m up to a depth of 30-50 m, which is the main zone of current subsurface activity. The model provides estimates of lithostratigraphy and lithology (including grain-size classes), as well as physical and chemical parameters, such as hydraulic conductivity and chemical element concentrations. Modelling is performed per province using all available digital borehole descriptions, components of the layer-based DGM model and a context of geological maps created during the last few decades (e.g. 1:50,000 map sheets and channel belt mapping). An important component of the GeoTOP model workflow is that all digital borehole descriptions are stratigraphically interpreted using automated procedures. These procedures deliver a set of uniformly and consistently interpreted boreholes that are used in the subsequent modelling stages.
GeoTOP provides a base for answering subsurface-related questions about, amongst others, groundwater management and infrastructural issues. Current applications include:
- Modelling groundwater flow, using the architecture and sediment composition of glacially deformed sediments to assign hydraulic parameters.
- Modelling solute transport, using the distribution of lithology and sand grain-size classes to assign hydraulic parameters.
- Forecasting long-term (up to 200 y) land subsidence in the western part of the country, using the distribution of soft sediments (peat and clay) to model subsidence rates.
- Constructing risk maps for surface water-groundwater interaction in a river-deepening project, based on the architecture and sediment composition of fluvial channel belts.
Our models are disseminated free-of-charge through the DINO web portal (www.dinoloket.nl) in a number of ways, including in an on-line map viewer with the option to create vertical cross-sections through the models, and as a series of downloadable GIS products. In co-operation with INSIGHT Geologische Softwaresysteme GmbH, the freely downloadable Subsurface Viewer was recently added to the portal, allowing users to download and visualise the layer-based models as well as GeoTOP on their desktop computers.
model uncertainty can be quantified.
GeoTOP is the latest generation of Dutch subsurface models at TNO – Geological Survey of the Netherlands. GeoTOP schematises the shallow subsurface in millions of voxels of 100 by 100 by 0.5 m up to a depth of 30-50 m, which is the main zone of current subsurface activity. The model provides estimates of lithostratigraphy and lithology (including grain-size classes), as well as physical and chemical parameters, such as hydraulic conductivity and chemical element concentrations. Modelling is performed per province using all available digital borehole descriptions, components of the layer-based DGM model and a context of geological maps created during the last few decades (e.g. 1:50,000 map sheets and channel belt mapping). An important component of the GeoTOP model workflow is that all digital borehole descriptions are stratigraphically interpreted using automated procedures. These procedures deliver a set of uniformly and consistently interpreted boreholes that are used in the subsequent modelling stages.
GeoTOP provides a base for answering subsurface-related questions about, amongst others, groundwater management and infrastructural issues. Current applications include:
- Modelling groundwater flow, using the architecture and sediment composition of glacially deformed sediments to assign hydraulic parameters.
- Modelling solute transport, using the distribution of lithology and sand grain-size classes to assign hydraulic parameters.
- Forecasting long-term (up to 200 y) land subsidence in the western part of the country, using the distribution of soft sediments (peat and clay) to model subsidence rates.
- Constructing risk maps for surface water-groundwater interaction in a river-deepening project, based on the architecture and sediment composition of fluvial channel belts.
Our models are disseminated free-of-charge through the DINO web portal (www.dinoloket.nl) in a number of ways, including in an on-line map viewer with the option to create vertical cross-sections through the models, and as a series of downloadable GIS products. In co-operation with INSIGHT Geologische Softwaresysteme GmbH, the freely downloadable Subsurface Viewer was recently added to the portal, allowing users to download and visualise the layer-based models as well as GeoTOP on their desktop computers.
De andere helft van Rotterdam. Hoe ziet Rotterdam er onder de grond uit en wat kom je er allemaal tegen? TNO zal het 3D model GeoTOP laten zien waarmee de ondergrond van Rotterdam tot tientallen meters diep in beeld is gebracht.
""In cooperation with Rijkswaterstaat, the executive body of the Dutch Ministry of Infrastructure and the Environment, the Geological Survey of the Netherlands and Deltares have developed an innovative way to estimate available and... more
""In cooperation with Rijkswaterstaat, the executive body of the Dutch Ministry of Infrastructure and the Environment, the Geological Survey of the Netherlands and Deltares have developed an innovative way to estimate available and exploitable sand reserves in the North Sea, between the smoothed 20-meter depth line and the seaward limit of the 12-mile zone. The reserves are determined using a 3D model consisting of voxels (“volume cells” or “3D pixels”).
The model is constructed using borehole data, estimates of sand grain size and geologically interpreted shallow 2D seismics and assigns values of lithology, shell percentages and silt percentages to every voxel (250 • 250 • 0.5m). Using combinations of various criteria, such as overburden thickness and thickness of non-sandy intercalations, exploitable sand reserves can be deduced. The reserves are visualised in maps and presented as volumes.
Traditional 2D or map-based studies use the same data and produce comparable volumes when the same criteria are applied. The expert knowledge incorporated in these maps is also included in the new 3D model. The innovative aspect of the voxel model is that it allows us to update the reserve estimates when new data become available, and to vary the search criteria on demand without the need to perform recalculations. This flexibility will maximize the applicability of the geological information and provide end users with the tools to make informed decisions on for example extraction strategy.
As a step-up to a fully operational information system, multiple grids from an extensive series of queries on the 3D model in combination with grids representing economic aspects, have been assembled in a GIS file. The layers created in the GIS file are used as an automated first-order decision-support system. As part of this approach, penalty points are assigned to several aspects such as the geological complexity, availability of knowledge (or the lack of it) and to economic aspects such as the recoverability of the sand and navigable distance. The latter is important as extraction areas proximal to the location with sand demand are in favour.
The resulting grids, produced to answer some immediate questions on data gaps and optimal extraction strategy, use an easily understandable color scheme, with green as favorable and red as unfavorable. With this system, the decision to extract sand volumes for the use of for instance sand nourishments in an unfavourable area, can be well-founded by assigning or changing the priorities to the mentioned aspects. The system points out consequences of today’s policies, but as it is flexible, future changes in knowledge and policy can be accommodated.""
The model is constructed using borehole data, estimates of sand grain size and geologically interpreted shallow 2D seismics and assigns values of lithology, shell percentages and silt percentages to every voxel (250 • 250 • 0.5m). Using combinations of various criteria, such as overburden thickness and thickness of non-sandy intercalations, exploitable sand reserves can be deduced. The reserves are visualised in maps and presented as volumes.
Traditional 2D or map-based studies use the same data and produce comparable volumes when the same criteria are applied. The expert knowledge incorporated in these maps is also included in the new 3D model. The innovative aspect of the voxel model is that it allows us to update the reserve estimates when new data become available, and to vary the search criteria on demand without the need to perform recalculations. This flexibility will maximize the applicability of the geological information and provide end users with the tools to make informed decisions on for example extraction strategy.
As a step-up to a fully operational information system, multiple grids from an extensive series of queries on the 3D model in combination with grids representing economic aspects, have been assembled in a GIS file. The layers created in the GIS file are used as an automated first-order decision-support system. As part of this approach, penalty points are assigned to several aspects such as the geological complexity, availability of knowledge (or the lack of it) and to economic aspects such as the recoverability of the sand and navigable distance. The latter is important as extraction areas proximal to the location with sand demand are in favour.
The resulting grids, produced to answer some immediate questions on data gaps and optimal extraction strategy, use an easily understandable color scheme, with green as favorable and red as unfavorable. With this system, the decision to extract sand volumes for the use of for instance sand nourishments in an unfavourable area, can be well-founded by assigning or changing the priorities to the mentioned aspects. The system points out consequences of today’s policies, but as it is flexible, future changes in knowledge and policy can be accommodated.""
TNO - Geological Survey of the Netherlands produces nation wide 3D voxel models up to a depth of 50m below the land surface. The models are integrations of several hundred thousands of database stored borehole descriptions with existing... more
TNO - Geological Survey of the Netherlands produces nation wide 3D voxel models up to a depth of 50m below the land surface. The models are integrations of several hundred thousands of database stored borehole descriptions with existing geological mapping and geological expertise. They contain estimates of stratigraphy, lithology (clay, sand, peat) and, where applicable, sand-grain size class data at voxel-resolutions up-to 100*100*0.5m.
Besides serving as a source of subsurface information for the applied geosciences, the models also give new insights in the geological development of the Netherlands throughout the Quaternary. The combination of large amounts of borehole data and the use of powerful new visualization software (INSIGHT GmbH Subsurface Viewer) reveals new geological patterns that were not known from (classic) geological studies.
An example of this is the distribution of peats below the late Saalian (MIS6) glacial till in the northern Netherlands. Borehole data and transects from earlier geological studies already indicated the presence of peat below the till. The 3D distribution of peat in our NL3D voxel model however revealed that the peat occurs in a narrow SE-NW oriented zone. This remarkable spatial distribution suggests that the peats represent the infill of a large incised palaeovalley of the Rhine River that flowed in the area just before progradation of the late Saalian ice sheet into the northern Netherlands. It is important to note that these findings ‘emerged’ from the models without direct geological steering.
The example illustrates the potential of the 3D voxel models in deciphering the Quaternary fluvial record. Future analysis should test the power of the voxel models in other areas and/or sedimentary environments.
Besides serving as a source of subsurface information for the applied geosciences, the models also give new insights in the geological development of the Netherlands throughout the Quaternary. The combination of large amounts of borehole data and the use of powerful new visualization software (INSIGHT GmbH Subsurface Viewer) reveals new geological patterns that were not known from (classic) geological studies.
An example of this is the distribution of peats below the late Saalian (MIS6) glacial till in the northern Netherlands. Borehole data and transects from earlier geological studies already indicated the presence of peat below the till. The 3D distribution of peat in our NL3D voxel model however revealed that the peat occurs in a narrow SE-NW oriented zone. This remarkable spatial distribution suggests that the peats represent the infill of a large incised palaeovalley of the Rhine River that flowed in the area just before progradation of the late Saalian ice sheet into the northern Netherlands. It is important to note that these findings ‘emerged’ from the models without direct geological steering.
The example illustrates the potential of the 3D voxel models in deciphering the Quaternary fluvial record. Future analysis should test the power of the voxel models in other areas and/or sedimentary environments.
The Geological Survey of the Netherlands (TNO) delivers a suite of geological models. They are predictions of geometry and properties of the subsurface, for sustainable management of earth resources, safe living in subsiding lowlands, and... more
The Geological Survey of the Netherlands (TNO) delivers a suite of geological models. They are predictions of geometry and properties of the subsurface, for sustainable management of earth resources, safe living in subsiding lowlands, and the reduction of risks and costs related to ground conditions.
Following the needs of our users, traditional geologic surveying and mapping evolved into our current systematic mapping programme. The information we supply has become more quantitative and application-oriented. Progress has also been made in the extent to which geological knowledge is incorporated in geomodels. We will discuss the state-of-the-art in geomodelling, and provide a Dutch perspective on the future of information delivery by geological surveys. Following the evolution from 2D to 3D information products, our next important step will be towards building 4D models, which represent not only geological conditions, but also processes such as subsidence, anthropogenic effects on the subsurface, and those of global change.
Following the needs of our users, traditional geologic surveying and mapping evolved into our current systematic mapping programme. The information we supply has become more quantitative and application-oriented. Progress has also been made in the extent to which geological knowledge is incorporated in geomodels. We will discuss the state-of-the-art in geomodelling, and provide a Dutch perspective on the future of information delivery by geological surveys. Following the evolution from 2D to 3D information products, our next important step will be towards building 4D models, which represent not only geological conditions, but also processes such as subsidence, anthropogenic effects on the subsurface, and those of global change.
INLEIDING De ondergrond van Nederland is van groot maatschappelijk belang. Ze levert de samenleving een schat aan delfstoffen, schoon drinkwater, ruimte voor infrastructuur en voedingsstoffen voor gewassen en natuurlijke vegetaties. De... more
INLEIDING
De ondergrond van Nederland is van groot maatschappelijk belang. Ze levert de samenleving een schat aan delfstoffen, schoon drinkwater, ruimte voor infrastructuur en voedingsstoffen voor gewassen en natuurlijke vegetaties. De Nederlandse ondergrond bestaat vooral uit zand, grind, klei en veen. De afwisseling in deze grondsoorten en de daarmee samenhangende eigenschappen bepaalt mede het voorkomen, de kwaliteit en de stroming van het grondwater.
Voor een duurzaam gebruik en beheer van de ondergrond is informatie over de opbouw en eigenschappen van de ondergrond essentieel. De Geologische Dienst Nederland van TNO levert deze informatie in de vorm van computermodellen van de Nederlandse ondergrond. Voor een diepte tot ca. 500 meter zijn dit de modellen DGM, REGIS-II, GeoTOP en NL3D.
GeoTOP
Het model GeoTOP geeft een gedetailleerd (100 bij 100 bij 0.5m resolutie) driedimensionaal beeld van de opbouw en eigenschappen van de Nederlandse ondergrond tot een diepte van 30 meter onder maaiveld. Het model bestrijkt hiermee het deel van de bodem dat in Nederland het meest intensief wordt gebruikt. GeoTOP vormt de basis voor het beantwoorden van vragen op het gebied van de ruimtelijke ordening van de ondergrond, de ondiepe delfstoffenwinning en het grondwater.
TOEPASSING
Waternet werkt in opdracht van Waterschap Amstel, Gooi en Vecht aan het schoonmaken van de Vecht. De komende 4 jaar schept Waternet van Muiden tot Utrecht vervuilde bagger van de bodem, in totaal 2,5 miljoen kuub. Hierdoor gaat de kwaliteit van het water vooruit, neemt de diversiteit aan planten en dieren toe en verbetert de doorvaart. Het is echter wel van belang dat deze baggerwerkzaamheden geen invloed hebben op de lokale en regionale grondwaterstanden.
GeoTOP is door Waternet gebruikt om inzichtelijk te krijgen welke afzettingen op welke plaats en diepte voorkomen in de stroomgordel van de Vecht. Wanneer er een erg zandige afzetting verwacht wordt, is het van belang om na te gaan of op deze plaats geen kortsluiting kan optreden met de onderliggende watervoerende pakketten. Dit wordt nagegaan door als eerste de verbreidingsgrenzen van de verschillende afzettingen te visualiseren, en dit vervolgens te koppelen aan het te ontgraven model.
Deze laatste bewerking wordt uitgevoerd in de GIS omgeving van GeoTOP, waarbij het digitale terrein model van het saneringsprofiel is gekruisd met het voorkomen van de top van de verschillende afzettingen. Middels controleboringen wordt op locaties die als risicovol worden beschouwd, de precieze diepte en samenstelling van de verschillende afzettingen vastgesteld.
GeoTOP is over het tracé Nigtevecht – Utrecht gebruikt om op een juiste wijze te kunnen voorspellen waar eventuele risicovolle afzettingen gelegen kunnen zijn. Hierdoor kan verder grondonderzoek afgestemd worden op specifieke stukken van bovenstaand tracé. Dit levert een voordeel in tijd, geld en inzet van materiaal op. Bovendien wordt inzichtelijk gemaakt hoe de Vecht zich heeft ontwikkeld in het gebied, omdat er een totaal beeld van de ondergrond wordt geleverd. Voor Waternet is juist deze informatie van groot belang, omdat hiermee de keuzes voor specifiek grondonderzoek kan worden gewaarborgd. Bovendien is de visualisatie van GeoTOP uitermate goed geschikt om duidelijk te maken aan de uitvoerende partij met welke soort grondopbouw zij te maken hebben, en waardoor sommige gebieden (waar diep gebaggerd wordt) een mogelijk riscio vormen, en waar dus extra monitoring wordt gevraagd.
Momenteel is Waternet bezig met het bekijken van de mogelijkheid om een hydrologisch model te koppelen aan de data van GeoTOP, zodat er een volledig beeld geschetst kan worden van mogelijke effecten op de ondergrond.
De ondergrond van Nederland is van groot maatschappelijk belang. Ze levert de samenleving een schat aan delfstoffen, schoon drinkwater, ruimte voor infrastructuur en voedingsstoffen voor gewassen en natuurlijke vegetaties. De Nederlandse ondergrond bestaat vooral uit zand, grind, klei en veen. De afwisseling in deze grondsoorten en de daarmee samenhangende eigenschappen bepaalt mede het voorkomen, de kwaliteit en de stroming van het grondwater.
Voor een duurzaam gebruik en beheer van de ondergrond is informatie over de opbouw en eigenschappen van de ondergrond essentieel. De Geologische Dienst Nederland van TNO levert deze informatie in de vorm van computermodellen van de Nederlandse ondergrond. Voor een diepte tot ca. 500 meter zijn dit de modellen DGM, REGIS-II, GeoTOP en NL3D.
GeoTOP
Het model GeoTOP geeft een gedetailleerd (100 bij 100 bij 0.5m resolutie) driedimensionaal beeld van de opbouw en eigenschappen van de Nederlandse ondergrond tot een diepte van 30 meter onder maaiveld. Het model bestrijkt hiermee het deel van de bodem dat in Nederland het meest intensief wordt gebruikt. GeoTOP vormt de basis voor het beantwoorden van vragen op het gebied van de ruimtelijke ordening van de ondergrond, de ondiepe delfstoffenwinning en het grondwater.
TOEPASSING
Waternet werkt in opdracht van Waterschap Amstel, Gooi en Vecht aan het schoonmaken van de Vecht. De komende 4 jaar schept Waternet van Muiden tot Utrecht vervuilde bagger van de bodem, in totaal 2,5 miljoen kuub. Hierdoor gaat de kwaliteit van het water vooruit, neemt de diversiteit aan planten en dieren toe en verbetert de doorvaart. Het is echter wel van belang dat deze baggerwerkzaamheden geen invloed hebben op de lokale en regionale grondwaterstanden.
GeoTOP is door Waternet gebruikt om inzichtelijk te krijgen welke afzettingen op welke plaats en diepte voorkomen in de stroomgordel van de Vecht. Wanneer er een erg zandige afzetting verwacht wordt, is het van belang om na te gaan of op deze plaats geen kortsluiting kan optreden met de onderliggende watervoerende pakketten. Dit wordt nagegaan door als eerste de verbreidingsgrenzen van de verschillende afzettingen te visualiseren, en dit vervolgens te koppelen aan het te ontgraven model.
Deze laatste bewerking wordt uitgevoerd in de GIS omgeving van GeoTOP, waarbij het digitale terrein model van het saneringsprofiel is gekruisd met het voorkomen van de top van de verschillende afzettingen. Middels controleboringen wordt op locaties die als risicovol worden beschouwd, de precieze diepte en samenstelling van de verschillende afzettingen vastgesteld.
GeoTOP is over het tracé Nigtevecht – Utrecht gebruikt om op een juiste wijze te kunnen voorspellen waar eventuele risicovolle afzettingen gelegen kunnen zijn. Hierdoor kan verder grondonderzoek afgestemd worden op specifieke stukken van bovenstaand tracé. Dit levert een voordeel in tijd, geld en inzet van materiaal op. Bovendien wordt inzichtelijk gemaakt hoe de Vecht zich heeft ontwikkeld in het gebied, omdat er een totaal beeld van de ondergrond wordt geleverd. Voor Waternet is juist deze informatie van groot belang, omdat hiermee de keuzes voor specifiek grondonderzoek kan worden gewaarborgd. Bovendien is de visualisatie van GeoTOP uitermate goed geschikt om duidelijk te maken aan de uitvoerende partij met welke soort grondopbouw zij te maken hebben, en waardoor sommige gebieden (waar diep gebaggerd wordt) een mogelijk riscio vormen, en waar dus extra monitoring wordt gevraagd.
Momenteel is Waternet bezig met het bekijken van de mogelijkheid om een hydrologisch model te koppelen aan de data van GeoTOP, zodat er een volledig beeld geschetst kan worden van mogelijke effecten op de ondergrond.
"The Geological Survey of the Netherlands delivers a suite of geological models. They are predictions of geometry and properties of the subsurface, for sustainable management of earth resources, safe living in subsiding lowlands, and the... more
"The Geological Survey of the Netherlands delivers a suite of geological models. They are predictions of geometry and properties of the subsurface, for sustainable management of earth resources, safe living in subsiding lowlands, and the reduction of costs related to ground conditions.
Following the needs of our users, traditional geologic surveying and mapping evolved into our current systematic modelling programme. The information we supply has become more quantitative and application-oriented. Progress has also been made in the extent to which geological knowledge is incorporated in geomodels. We will discuss the state-of-the-art in geomodelling, and provide a Dutch perspective on the future of information delivery by geological surveys. Following the evolution from 2D to 3D information products, our next important step will be towards building 4D models, which represent not only geological conditions, but also processes such as subsidence, anthropogenic effects on the subsurface, and those of global change."
Following the needs of our users, traditional geologic surveying and mapping evolved into our current systematic modelling programme. The information we supply has become more quantitative and application-oriented. Progress has also been made in the extent to which geological knowledge is incorporated in geomodels. We will discuss the state-of-the-art in geomodelling, and provide a Dutch perspective on the future of information delivery by geological surveys. Following the evolution from 2D to 3D information products, our next important step will be towards building 4D models, which represent not only geological conditions, but also processes such as subsidence, anthropogenic effects on the subsurface, and those of global change."
"TNO - Geological Survey of the Netherlands produces nation wide 3D voxel models up to a depth of 50m below the land surface. The models are integrations of several hundred thousands of database stored borehole descriptions with existing... more
"TNO - Geological Survey of the Netherlands produces nation wide 3D voxel models up to a depth of 50m below the land surface. The models are integrations of several hundred thousands of database stored borehole descriptions with existing geological mapping and geological expertise. They contain estimates of stratigraphy, lithology (clay, sand, peat) and, where applicable, sand-grain size class data at voxel-resolutions up-to 100*100*0.5m.
Besides serving as a source of subsurface information for the applied geosciences, the models also give new insights in the geological development of the Netherlands throughout the Quaternary. The combination of large amounts of borehole data and the use of powerful new visualisation software (INSIGHT GmbH Subsurface Viewer) reveals new geological patterns that were not known from (classic) geological studies. An example of this is the distribution of peats below the Saalian (Illinoian) glacial till in the northern Netherlands. Borehole data and transects from earlier geological studies already indicated the presence of peat below the till. The 3D distribution of peat in our NL3D voxel model however revealed that the peat occurs in a narrow SE-NW oriented zone. This remarkable spatial distribution suggests that the peats represent the infill of a large incised palaeovalley of the Rhine River that flowed in the area just before progradation of the Saalian ice-sheet into the Netherlands.
It is important to note that these findings ‘emerged’ from the models without direct geological steering. This shows that 3D voxel models like those produced at TNO - Geological Survey of the Netherlands, are valuable sources for obtaining new geological insights in the future."
Besides serving as a source of subsurface information for the applied geosciences, the models also give new insights in the geological development of the Netherlands throughout the Quaternary. The combination of large amounts of borehole data and the use of powerful new visualisation software (INSIGHT GmbH Subsurface Viewer) reveals new geological patterns that were not known from (classic) geological studies. An example of this is the distribution of peats below the Saalian (Illinoian) glacial till in the northern Netherlands. Borehole data and transects from earlier geological studies already indicated the presence of peat below the till. The 3D distribution of peat in our NL3D voxel model however revealed that the peat occurs in a narrow SE-NW oriented zone. This remarkable spatial distribution suggests that the peats represent the infill of a large incised palaeovalley of the Rhine River that flowed in the area just before progradation of the Saalian ice-sheet into the Netherlands.
It is important to note that these findings ‘emerged’ from the models without direct geological steering. This shows that 3D voxel models like those produced at TNO - Geological Survey of the Netherlands, are valuable sources for obtaining new geological insights in the future."
In 2002, I joined the UNIGIS postgraduate diploma course Geographic Information Science at VU University Amsterdam (www.unigis.nl). The aim of this course is to give students an understanding of the technical, geographical and... more
In 2002, I joined the UNIGIS postgraduate diploma course Geographic Information Science at VU University Amsterdam (www.unigis.nl). The aim of this course is to give students an understanding of the technical, geographical and organizational aspects of GIS. The program consists of eight modules and three workshops. Each module is concluded by writing two essays on the subject of the modules. The 16 essays are incorporated in my Academia UNIGIS Essay section.
Research Interests:
In 2002, I joined the UNIGIS postgraduate diploma course Geographic Information Science at VU University Amsterdam (www.unigis.nl). The aim of this course is to give students an understanding of the technical, geographical and... more
In 2002, I joined the UNIGIS postgraduate diploma course Geographic Information Science at VU University Amsterdam (www.unigis.nl). The aim of this course is to give students an understanding of the technical, geographical and organizational aspects of GIS. The program consists of eight modules and three workshops. Each module is concluded by writing two essays on the subject of the modules. The 16 essays are incorporated in my Academia UNIGIS Essay section.
Research Interests:
In 2002, I joined the UNIGIS postgraduate diploma course Geographic Information Science at VU University Amsterdam (www.unigis.nl). The aim of this course is to give students an understanding of the technical, geographical and... more
In 2002, I joined the UNIGIS postgraduate diploma course Geographic Information Science at VU University Amsterdam (www.unigis.nl). The aim of this course is to give students an understanding of the technical, geographical and organizational aspects of GIS. The program consists of eight modules and three workshops. Each module is concluded by writing two essays on the subject of the modules. The 16 essays are incorporated in my Academia UNIGIS Essay section.
Research Interests:
In 2002, I joined the UNIGIS postgraduate diploma course Geographic Information Science at VU University Amsterdam (www.unigis.nl). The aim of this course is to give students an understanding of the technical, geographical and... more
In 2002, I joined the UNIGIS postgraduate diploma course Geographic Information Science at VU University Amsterdam (www.unigis.nl). The aim of this course is to give students an understanding of the technical, geographical and organizational aspects of GIS. The program consists of eight modules and three workshops. Each module is concluded by writing two essays on the subject of the modules. The 16 essays are incorporated in my Academia UNIGIS Essay section.
Research Interests:
In 2002, I joined the UNIGIS postgraduate diploma course Geographic Information Science at VU University Amsterdam (www.unigis.nl). The aim of this course is to give students an understanding of the technical, geographical and... more
In 2002, I joined the UNIGIS postgraduate diploma course Geographic Information Science at VU University Amsterdam (www.unigis.nl). The aim of this course is to give students an understanding of the technical, geographical and organizational aspects of GIS. The program consists of eight modules and three workshops. Each module is concluded by writing two essays on the subject of the modules. The 16 essays are incorporated in my Academia UNIGIS Essay section.
Research Interests:
In 2002, I joined the UNIGIS postgraduate diploma course Geographic Information Science at VU University Amsterdam (www.unigis.nl). The aim of this course is to give students an understanding of the technical, geographical and... more
In 2002, I joined the UNIGIS postgraduate diploma course Geographic Information Science at VU University Amsterdam (www.unigis.nl). The aim of this course is to give students an understanding of the technical, geographical and organizational aspects of GIS. The program consists of eight modules and three workshops. Each module is concluded by writing two essays on the subject of the modules. The 16 essays are incorporated in my Academia UNIGIS Essay section.
Research Interests:
In 2002, I joined the UNIGIS postgraduate diploma course Geographic Information Science at VU University Amsterdam (www.unigis.nl). The aim of this course is to give students an understanding of the technical, geographical and... more
In 2002, I joined the UNIGIS postgraduate diploma course Geographic Information Science at VU University Amsterdam (www.unigis.nl). The aim of this course is to give students an understanding of the technical, geographical and organizational aspects of GIS. The program consists of eight modules and three workshops. Each module is concluded by writing two essays on the subject of the modules. The 16 essays are incorporated in my Academia UNIGIS Essay section.
Research Interests:
In 2002, I joined the UNIGIS postgraduate diploma course Geographic Information Science at VU University Amsterdam (www.unigis.nl). The aim of this course is to give students an understanding of the technical, geographical and... more
In 2002, I joined the UNIGIS postgraduate diploma course Geographic Information Science at VU University Amsterdam (www.unigis.nl). The aim of this course is to give students an understanding of the technical, geographical and organizational aspects of GIS. The program consists of eight modules and three workshops. Each module is concluded by writing two essays on the subject of the modules. The 16 essays are incorporated in my Academia UNIGIS Essay section.
Research Interests:
In 2002, I joined the UNIGIS postgraduate diploma course Geographic Information Science at VU University Amsterdam (www.unigis.nl). The aim of this course is to give students an understanding of the technical, geographical and... more
In 2002, I joined the UNIGIS postgraduate diploma course Geographic Information Science at VU University Amsterdam (www.unigis.nl). The aim of this course is to give students an understanding of the technical, geographical and organizational aspects of GIS. The program consists of eight modules and three workshops. Each module is concluded by writing two essays on the subject of the modules. The 16 essays are incorporated in my Academia UNIGIS Essay section.
Research Interests:
In 2002, I joined the UNIGIS postgraduate diploma course Geographic Information Science at VU University Amsterdam (www.unigis.nl). The aim of this course is to give students an understanding of the technical, geographical and... more
In 2002, I joined the UNIGIS postgraduate diploma course Geographic Information Science at VU University Amsterdam (www.unigis.nl). The aim of this course is to give students an understanding of the technical, geographical and organizational aspects of GIS. The program consists of eight modules and three workshops. Each module is concluded by writing two essays on the subject of the modules. The 16 essays are incorporated in my Academia UNIGIS Essay section.
Research Interests:
In 2002, I joined the UNIGIS postgraduate diploma course Geographic Information Science at VU University Amsterdam (www.unigis.nl). The aim of this course is to give students an understanding of the technical, geographical and... more
In 2002, I joined the UNIGIS postgraduate diploma course Geographic Information Science at VU University Amsterdam (www.unigis.nl). The aim of this course is to give students an understanding of the technical, geographical and organizational aspects of GIS. The program consists of eight modules and three workshops. Each module is concluded by writing two essays on the subject of the modules. The 16 essays are incorporated in my Academia UNIGIS Essay section.
Research Interests:
In 2002, I joined the UNIGIS postgraduate diploma course Geographic Information Science at VU University Amsterdam (www.unigis.nl). The aim of this course is to give students an understanding of the technical, geographical and... more
In 2002, I joined the UNIGIS postgraduate diploma course Geographic Information Science at VU University Amsterdam (www.unigis.nl). The aim of this course is to give students an understanding of the technical, geographical and organizational aspects of GIS. The program consists of eight modules and three workshops. Each module is concluded by writing two essays on the subject of the modules. The 16 essays are incorporated in my Academia UNIGIS Essay section.
Research Interests:
In 2002, I joined the UNIGIS postgraduate diploma course Geographic Information Science at VU University Amsterdam (www.unigis.nl). The aim of this course is to give students an understanding of the technical, geographical and... more
In 2002, I joined the UNIGIS postgraduate diploma course Geographic Information Science at VU University Amsterdam (www.unigis.nl). The aim of this course is to give students an understanding of the technical, geographical and organizational aspects of GIS. The program consists of eight modules and three workshops. Each module is concluded by writing two essays on the subject of the modules. The 16 essays are incorporated in my Academia UNIGIS Essay section.
Research Interests:
In 2002, I joined the UNIGIS postgraduate diploma course Geographic Information Science at VU University Amsterdam (www.unigis.nl). The aim of this course is to give students an understanding of the technical, geographical and... more
In 2002, I joined the UNIGIS postgraduate diploma course Geographic Information Science at VU University Amsterdam (www.unigis.nl). The aim of this course is to give students an understanding of the technical, geographical and organizational aspects of GIS. The program consists of eight modules and three workshops. Each module is concluded by writing two essays on the subject of the modules. The 16 essays are incorporated in my Academia UNIGIS Essay section.
Research Interests:
In 2002, I joined the UNIGIS postgraduate diploma course Geographic Information Science at VU University Amsterdam (www.unigis.nl). The aim of this course is to give students an understanding of the technical, geographical and... more
In 2002, I joined the UNIGIS postgraduate diploma course Geographic Information Science at VU University Amsterdam (www.unigis.nl). The aim of this course is to give students an understanding of the technical, geographical and organizational aspects of GIS. The program consists of eight modules and three workshops. Each module is concluded by writing two essays on the subject of the modules. The 16 essays are incorporated in my Academia UNIGIS Essay section.
Research Interests:
In 2002, I joined the UNIGIS postgraduate diploma course Geographic Information Science at VU University Amsterdam (www.unigis.nl). The aim of this course is to give students an understanding of the technical, geographical and... more
In 2002, I joined the UNIGIS postgraduate diploma course Geographic Information Science at VU University Amsterdam (www.unigis.nl). The aim of this course is to give students an understanding of the technical, geographical and organizational aspects of GIS. The program consists of eight modules and three workshops. Each module is concluded by writing two essays on the subject of the modules. The 16 essays are incorporated in my Academia UNIGIS Essay section.
Research Interests:
The accelerations experienced at the surface as a result of earthquakes induced by the production of gas from the Groningen gasfield depend on the local shallow geological and soil conditions. This is called the 'site response effect'. In... more
The accelerations experienced at the surface as a result of earthquakes induced by the production of gas from the Groningen gasfield depend on the local shallow geological and soil conditions. This is called the 'site response effect'. In order to improve our knowledge of this effect, the NAM invited Deltares to build a detailed model of the shallow subsurface below Groningen. This report prepared by Deltares describes the quaternary geology of the Groningen area.