Image-guided Structure-constrained Inversion of Electrical Resistivity Data for Improving Contaminations Characterization

Abstract

Abstract Electrical resistivity tomography often has high uncertainty in contamination characterization due to the complex subsurface structure. Utilizing available prior information is crucial for enhancing geological plausibility. We propose an improved structure-constrained method that updates the smooth weights of all eight elements surrounding a boundary element using three different magnitudes. The methodology is tested on seven synthetic models and a field case covering four different types of structural boundaries. Structural constraints are vital to increasing boundary contrast. With the increase of data points from an optimized array, the influence of structural constraint is reduced. Correct structural constraints can tighten the abnormal contamination resistivity. However, misplaced structural constraints in the proximity of the contamination can lead to worse characterization. Without knowing exactly the boundary information, we propose a method to obtain local constraints from borehole logging, which is verified by both numerical and field data. This method reduces the interference of uncertain structural boundaries and enhances the robustness of the IIGSC method in contamination surveys. In the end, we conclude that correct boundary information even with limited constraints from borehole logging can increase the identification of the abnormal contamination resistivity.