International Society for Industrial Process Tomography

Subsurface Resistivity Imaging with Nonlinear Differential Approach using Electrical Resistance Tomography

A. K. Khambampati¹, S. K. Konki², Y. J. Han², K. Y. Kim^2*

¹BK 21+ Clean Energy Convergence and Integration Center for Human Resources Training and Education, Jeju National University, Jeju, South Korea 63243

² Department of Electronic Engineering, Jeju National University, Jeju, South Korea 63243

^*Email: kyungyk@jejunu.ac.kr

ABSTRACT

Subsurface resistivity profile is helpful in designing grounding grids, studying salt water intrusions, contaminant plumes and waste dumps etc. Electrical resistance tomography (ERT) tomograms characterize the soil subsurface resistivity distribution based on the measurements taken from the electrodes placed in the domain of interest. The relationship between the measured voltages and the change in resistivity distribution is nonlinear and the inverse problem is highly ill-posed. Thus, the solution is affected due to modeling errors. Conventional absolute imaging is very sensitive to modeling errors. Linear difference imaging can tackle the modeling errors to some extent. However, when the changes in the distribution are more compared to initial distribution then it can lead to undesirable reconstructed images. In this paper, three dimensional subsurface resistivity distribution is reconstructed using nonlinear difference imaging approach. The nonlinear resistivity distribution is parameterized as initial and change in resistivity. This parameterization helps in modeling the initial and change in resistivity independently. The nonlinear difference imaging is solved by considering the measurements from initial and change in distribution together while initial and change in resistivity are reconstructed at the same time from the combined data. Through extensive numerical and experimental results, it is found that ERT offers promising performance with non linear difference imaging in estimating the three-dimensional soil resistivity distribution.

Keywords Electrical resistance tomography, inverse problem, image reconstruction, region of interest, three dimensional imaging

Industrial Application General