VEMI. A flexible interface for 3D tomographic inversion of time-and frequency-domain electrical data in EIDORS

The aim of this work is to present a Matlab interface called VEMI (Versatile interface for Electrical data Modelling and Inversion) included in the EIDORS software. The interface is able to invert 2D and 3D electrical data acquired in the time- or in the frequency-domain, both for cylindrical and prismatic geometries. Therefore, it can be a flexible tool for inversion of both real and complex-valued resistivity tomography data acquired in the laboratory and in field. The forward solver has proven to be stable and accurate through a comparison with an analytical solution, while the inverse solution, achieved through a Gauss-Newton routine with an optimised damping inner loop, can be performed with the help of useful tools to incorporate a priori information in the inversion process. The reliability of VEMI has been tested through a 3D laboratory example, where both time- and frequency-domain data were acquired and two 3D field example with time-domain data. The 3D laboratory example, simulating a shallow aquifer contaminated by a chlorinated solvent (HFE), demonstrated the reliability of VEMI to detect the contaminant pathway within the physical model. The HFE is clearly visible on phase and chargeability models, where the highest phase values are located underneath the spilling point, even though it remains undistinguishable in the resistivity and amplitude ones. Through the combined analysis of the inverted chargeability and phase models we can reduce the degree of uncertainty in interpretation of geophysical models. These results were also validated through the comparison with the respective synthetic models simulated in a previous paper by the same authors. Real world tests have been performed on a closed landfill where few a priori information are available about the original design and on an industrial site which is contaminated by chlorinated solvents. In the former case, we reconstruct a three-layer configuration (covering, waste and bottom liner), where the effective layering inferred from the resistivity model is confirmed by the chargeability one. In the latter case we detect the chlorinated solvents within the deeper aquifer through the combined analysis of the resistivity and chargeability models, where the highest resistivity values are associated with high chargeability.