The PSO inversion scheme was applied to the grounded wire TDEM method to infer subsurface resistivity models. The forward modeling part was expressed in the Laplace domain, while the transformation into the time-domain was conducted using the Gaver-Stehvest method. The inversion scheme was tested on noise-free and noisy synthetic data to evaluate the accuracy of the scheme and was then applied to field data recorded at two stations in a volcanic-geothermal region. The inversion scheme gave an excellent fit between the observed data and the calculated data.
A nonlinear stochastic inversion scheme, called very fast simulated annealing (VFSA), was applied to the time-domain electromagnetic data generated from a horizontal electric dipole. The forward formulation of the vertical magnetic field was expressed in the Laplace domain by applying the Hankel integral transform. Time-domain transformation was performed by applying the inverse Laplace transform using the Gaver–Stehfest algorithm. In this study, for noise-free synthetic data, the VFSA scheme yielded the smallest misfit and an inverted resistivity model that resembled the test model. The addition of 5% random noise to the synthetic data produced the same level of misfit and a model that still mimicked the test model. However, the addition of 10% noise to the synthetic data resulted in a misfit value that was three times that of the first two values and a resistivity model with a large discrepancy with the test model, particularly at large depths. These results indicate the efficacy of the VFSA inversion scheme for inferring the subsurface resistivity structure from the electromagnetic data. This inversion scheme was applied to field data measured in a volcanic environment. The general pattern of the resistivity structure inferred by the VFSA inversion is consistent with the structure obtained previously by using a deterministic inversion scheme.
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