4D ERT Inversion with a Weighted Time Constraint

Resistivity monitoring has been applied to wide range of engineering and environmental problems with the help of automatic/rapid data acquisition, data communication and effective interpretation software. At initial stage, the interpretation of collected resistivity monitoring data has been focused on inverting a time-lapse data set by using the reference model at a particular time step. However, the inverted images are strongly dependent on the reference model and frequently contaminated by the inversion artefacts. Recently 4D inversion was proposed, where the entire monitoring data sets at different times are simultaneously inverted. Moreover, the regularization is introduced to reduce the inversion artefacts In this study, we developed a new 4D inversion algorithm that automatically determines the time-domain regularization parameters based on model parameters and perturbations at the current iteration. The performance of the developed 4D inversion is examined with synthetic data sets for a given time-lapse model. Finally, we applied the proposed inversion algorithm to the inversion of resistivity monitoring data collected at an embankment dam for the detection of leakage.