Data-driven hydrogeophysical and redox modelling

Abstract

Summary Detailed 3D structural information of the subsurface is fundamental for development of both the hydrological and the geochemical models that can be used for analysis of nitrate reduction processes in the subsurface and targeted nitrate regulation. In some areas data, coverage might be sparse or suffering from bad data quality, which results in information gaps. We suggest therefore a workflow that merges tTEM resistivity data and borehole lithologies, and uses these datasets to generate an ensemble of equally plausible 3D models of hydrogeological units and redox conditions. In an initial step the input datasets are merged via accumulated clay thickness modeling. This dataset is in a second step transformed into a training image, that is to be used in multipoint statistical simulations. The application of Direct Sampling within this workflow allows for simultaneous simulation of these variables. This approach allows for retaining the complex geostatistical spatial relationships that can exist between the different datasets in the resulting generated 3D models.