3D Joint hydrogeophysical inversion using similarity measures

Abstract

Parameter and state estimation for groundwater models within a coupled hydrogeophysical framework has become common in the last few years. It has been shown that such estimates are usually better than those from a single data inversion and different approaches have been suggested in literature to combine the essentially two different modalities in order to obtain a single estimate for the property of interest. However, most of the coupled hydrogeophysical frameworks rely on implementing some petrophysical relationships to couple the groundwater and geophysical variable. Such relationships are usually uncertain and hard to parametrize for a large region and can produce mass errors in the final estimates. Replacing the fixed petrophysical relationship by a more loose similarity constraint is therefore an appealing alternative for coupling the two different models.In this work we further explore the potential of structure similarity measures for coupled inversion in 3D, specifically a version of cross-gradient field product. Furthermore, we propose an efficient computational approach for minimization of coupled objective function with multiple data misfits, which is applicable to large scale inverse problems. To test the applicability of the structure-coupled inversion we analyzed three different synthetic scenarios for solute tracer tests, estimating initial conditions or hydraulic conductivity.