TAILOR-MADE MAPS GENERATED FROM 3D GEOLOGICAL VOXEL MODELS

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.