Quantitative integration of hydrogeophysical data: Conditional geostatistical simulation for characterizing heterogeneous alluvial aquifers

Abstract

High-resolution geophysical parameter information, as it can be provided, for example, by crosshole georadar and seismic tomography, has proven to provide useful spatial information to complement traditional hydrological methods such as core analyses, logging techniques, and tracer or pumping tests. Quantitative integration of these diverse database components is one of the major challenges in the field of high-resolution hydrogeophysics because of their different scales of measurement and the usually weak petrophysical relations among the measurements. In this study, we systematically explore the usefulness of a conditional stochastic simulation approach based on simulated annealing for this purpose. First, we generate a realistic model of an alluvial aquifer consisting of a 2D scale-invariant porosity field. On the basis of this model, we generate synthetic neutron porosity logs and crosshole georadar tomographic surveys. We then use the proposed geostatistical simulation approach to integrate this hydrogeophysical database. The effectiveness of this approach to characterize the detailed porosity distribution in heterogeneous alluvial aquifers is assessed by comparing the results for a variety of simulated porosity fields that differ fundamentally in terms of their conditioning information. Our results indicate this approach has the potential to allow for a realistic hydrogeophysical characterization in the submeter range of the porosity distribution in heterogeneous alluvial aquifers.