For large parts of the Netherlands, sufficient subsurface data are available to reliably determine geothermal potential. Areas with limited subsurface data are described in the 2017 report 'Framework for exploration work programme geothermal in areas with low data density' by EBN and TNO (in Dutch). In some cases, the scarce information in these areas might still be sufficient to determine the geothermal potential of an aquifer. For example, the Rotliegend in the West Netherlands basin is very thin and deeply buried. Irrespective of the low data density, it can be stated with a high degree of certainty that the geothermal potential of the Rotliegend is low in that area. A different example is the province of Utrecht, where the potential of the Rotliegend is very uncertain due to the unknown maximum burial depth, despite its favourable depth (about 2000 meters) and thickness (locally more than 100 meters).
Data availability maps are generated for each aquifer to show the spatial distribution of uncertainty. Areas with low data density may still be interesting for geothermal energy exploration, despite a low predicted geothermal potential. Based on the different data types available, classes are defined reflecting the level of uncertainty on subsurface parameters. A low value represents a high level of uncertainty.
- Class 5: 3D seismic
- Class 4: digital 2D seismic > 1980 (reliable)
- Class 2: digital 2D seismic <= 1980 (moderately reliable)
- Class 4: within a radius of 4 kilometer of wells where the aquifer was drilled
The class of the 3D seismic applies for areas covered by both 3D and 2D seismic. The classes of seismic (class 5, 4 or 2) and wells (class 4) were summed to create the categorical map. The possible combinations are:
- 9: 3D seismic (class 5) + well (class 4)
- 8: 2D seismic > 1980 (class 4) + well (class 4)
- 6: 2D digital seismic <= 1980 (class 2) + well (class 4)
- 5: 3D seismic (class 5)
- 4: 2D digital seismic > 1980 (class 4) or well (class 4)
- 2: 2D digital seismic <= 1980 (class 2)
- 0: no data