Abstract

Abstract Electromagnetic (EM) data sets were acquired using ground-based small-loop electromagnetic (EM) sensors over an artificially constructed sandy ground in Tsukuba, Japan, for three conditions of water saturation. The research aim was to evaluate the imaging capability of the geophysical method for detecting a water leak. Because the sensitivity analysis showed a considerable three-dimensional (3D) distribution of sensitivity around the source–receiver location, 3D inversion was applied to the field data sets. We used an accurate 3D controlled-source electromagnetic (CSEM) inversion algorithm, which adopted an edge-based finite element method as a forward scheme. To obtain the best inversion strategy for our field data and for the selection of the optimal regularization method, 3D inversion was applied to synthetic data sets prior to the inversion of the field data; the synthetic data sets were based on synthetic resistivity models used to simulate the three water-saturation phases of the real test site. Based on the results of sensitivity analysis, different regularization methods were systematically tested and the inversion results were qualitatively analyzed. For our monitoring scenario, the best performance was achieved by combining spatially varying regularization parameters, structural constraints, and the reference model method. The reference model parameters were derived from the less ill-posed model, instead of the main target model, which allowed for more accurate imaging of the main region of interest. This optimal inversion strategy was applied to the test-site field data. The water leak was successfully visualized by small-loop EM data, with systematic application of a priori information as constraints.

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