Difference Inversion of ERT Data: a Fast Inversion Method for 3-D In Situ Monitoring

Abstract

A three-dimensional (3-D) Occam’s inversion algorithm for electrical resistivity tomography is modified to allow for inversion on the differences between the background and subsequent data sets. The algorithm is optimized for in situ monitoring applications. The resistivity obtained by the inversion of background data serves as the a priori model in the difference inversion. There are several advantages to this method. First, convergence is fast since the inverse routine needs only to find small perturbations about a good initial guess. Second, systematic errors such as those due to errors in field configuration and discretization errors in the forward modeling algorithm tend to cancel. The result is that we can fit the difference data far more closely than the individual potentials. Better data fits often equate to better resolution with fewer inversion artifacts. The difference inversion technique was applied to monitoring in-situ steam remediation in Portsmouth, Ohio and monitoring of flow in fluid fractures at the Box Canyon site near the Idaho National Engineering Laboratory. Small changes of conductivity were better resolved using the difference inversion method. Difference inversion produced high-quality images with fewer artifacts, and only took 25% to 50% run time of standard Occam’s inversion in the Box Canyon case.