Roula Dambrink

This paper presents method and first results of a study to quantify and communicate geotechnical risk for highway construction on soft soil and large building pits associated with infrastructural works in the Netherlands. A set of easy-to-read maps will inform the end users, geotechnical consultants at the Dutch Ministry of Infrastructure and Environment, in the early stage of projects of the most important subsoil-related geotechnical risks and their spatial distribution. The method involves risk identification, risk assessment, identification of critical geological features contributing to this risk, and development of maps reflecting the magnitude of the geotechnical risk. Geological information is derived from the detailed 3D geological model GeoTOP. GeoTOP allows quick data assessment and creation of maps on a regional to nationwide scale. Close cooperation between geologists, geotechnical engineers and end users is the key success factor in application of the method. Geotechnical consultants will use the maps to identify risks, determine early risk mitigation measures and design site-investigation schemes.

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 geolo...

This paper presents method and  first  results of a  study  to quantify and  communicate geotechnical risk for highway construction on soft soil and large building pits associated with infrastructural works in the Netherlands. A set of easy-to-read maps will inform the end users, geotechnical consultants at the Dutch Ministry of Infrastructure and Environment, in the early stage of projects of the most important subsoil-related geotechnical risks and their spatial distribution. The method involves risk identification, risk assessment, identification of critical geological features contributing to this risk, and development of maps reflecting the magnitude of the geotechnical risk. Geological information  is derived from the detailed 3D geological model GeoTOP. GeoTOP allows quick data assessment and creation of maps on a regional to nationwide scale. Close cooperation between geologists, geotechnical engineers and end users is the key success factor in application of the method. Geotechnical consultants will use the maps to identify risks, determine early risk mitigation measures and design site-investigation schemes.

Amsterdam is situated on the coastal-deltaic plain of the western Netherlands. Its geographical position brought the city prosperity, but also created huge challenges associated with heterogeneous and often adverse ground conditions. This paper explores the geology of Amsterdam to a depth of c. 100 m, based on the output of the 3D geological subsurface models DGM and GeoTOP. The model results are used to create a geological map of the area, to determine the extent and depth of the foundation levels that are in use for buildings in the city centre and to detect the source of filling sand on which part of the more recent expansion of the city was founded. It is shown that subsurface conditions have had a profound effect on both landscape development and historical city growth. Geomodels like DGM and GeoTOP provide an easily accessible way to obtain a better understanding of the shallow subsurface.

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.

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.

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.

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.