Automated optimization of electrode locations for electrical resistivity tomography

Abstract

This work describes the automated search for optimal electrode locations that will improve reconstructions of a 2D electrical resistivity tomography problem within a meta inverse framework. The meta inverse framework was incorporated into a finite integration forward solver developed for simulating the measurement data, and into an inverse solver developed for reconstructing the resistivity distribution within the subsurface. The meta inverse framework solver then searched to find optimal electrode locations at which best reconstructions of the resistivity distribution within the subsurface could be obtained. The numerical results obtained from applying the forward, inverse and meta inverse solvers to search for resistance anomalies in an electrical resistivity tomography problem are presented. The results show that these solvers are successful for simulations, reconstructions, and for determining the optimal electrode locations at which the best reconstruction of the resistivity distribution can be obtained.