An efficient and automatic procedure for integrating resistivity and borehole information for large scale groundwater modelling

Abstract

We present an automatic method for parameterization of a 3D model of the subsurface, integrating lithological information from boreholes with resistivity models through an inverse optimization, with the objective of creating a direct input to groundwater models. The parameter of interest is the clay fraction, expressed as the relative length of clay-units in a depth interval. The clay fraction is obtained from lithological logs and the clay fraction from the resistivity is obtained by establishing a simple petrophysical relationship, a translator function, between resistivity and the clay fraction. Through inversion we use the lithological data and the resistivity data to determine the optimum spatially distributed translator function. Applying the translator function we get a 3D clay fraction model, which holds information from the resistivity dataset and the borehole dataset in one variable. Finally, we use k-means clustering to generate a 3D model of the subsurface structures, which we then use as direct input in a groundwater model. We apply the concept to the Norsminde survey in Denmark integrating approximately 700 boreholes and more than 100,000 resistivity models from an airborne survey in the parameterization of the 3D model covering 156 km2. The final five-cluster 3D model is input to a groundwater model and it performs equally well or slightly better than traditional groundwater models from the area.