A Stochastic Framework for Geochemical Parameter Estimation using Geophysical Methods: Development and Application

Quantitative estimation of geochemical parameters is important for guiding and for monitoring field-scale remedial activities at contaminated sites. Previous laboratory scale studies have demonstrated the close correlation between microbially mediated sulfide precipitation and complex resistivity and seismic attenuation responses. To advance the use of geophysical methods for estimating geochemical processes, a framework is needed that can integrate various time-lapse geochemical and geophysical data, track system changes as a function of spatial heterogeneity and time, and provide information about uncertainty. In this study, we develop a stochastic framework for geochemical parameter estimation, and test this approach using the previously collected laboratory-scale complex resistivity and seismic attenuation data. For the complex resistivity, we use a modified Cole-Cole model to link between electrical parameters with the volume of precipitates that are developed. For seismic waveform data, we use a double-porosity, or patchy saturation model, to relate the seismic attributes to precipitate formation. Although the framework is tested on specific geophysical datasets to estimate a particular geochemical process, the framework is general and can be applied to various time- lapse geophysical datasets for geochemical process monitoring, such as the complex resistivity, seismic, and geochemical data that are being collected at the DOE Rifle Site in Colorado.