Resolving Hydrogeological Parameters Through Joint Inversion of Seismic and Electric Data Considering Surface Conductivity

Abstract

Geophysical methods have proven to overcome the spatial limitations of direct investigations by providing spatio-temporal information about subsurface properties with an adequate resolution in a non-invasive manner. However, the resolved models remain qualitative unless subsequently transformed to the quantitative estimates of the parameters of interest based on a petrophysical model. Petrophysical joint inversion (PJI) approaches permit an improved quantitative estimation of hydrogeological parameters by simultaneously inverting complementary geophysical datasets, e.g., seismic and electric data, related through a common petrophysical parameter. Subsurface models resolved for data collected in fine-grained environments might still be biased if the petrophysical model underlying the PJI framework does not consider the conduction of electric current along the grain-fluid interface. In this study, we present a PJI framework that implicitly takes into account the surface conductivity based DC and instantaneous resistivity data. We apply this PJI approach to data collected in the Hydrological Open Air Laboratory (HOAL; Petzenkirchen, Austria) to solve for hydrogeological parameters relevant for the understanding of surface-groundwater interactions. We discuss the resolved subsurface models with respect to models obtained through a PJI approach neglecting the surface conductivity, demonstrate the good agreement with available direct information and provide an interpretation of the subsurface conditions.