Leakage detection of water reservoirs using a Mise-à-la-Masse approach

Abstract

Localizing leaks of water and fluids from storage tanks and water reservoirs with geomembranes is an important task for a variety of environmental applications and water resources applications. The minimally intrusive mise-à-la-masse method is used to detect leaks with the current injected inside the reservoir and a return current electrode located remotely. We test a new approach for the inversion of the voltage data using sandbox experiments and numerical modeling. A method similar to the self-potential inversion method is proposed to inverse the voltages recorded around the tank or reservoir. A global objective function with a data misfit term and regularization term is minimized to invert the voltages. In the inversion process, a depth-weighting matrix is used to strengthen the depth resolution of the current source, and the minimum support method is used to avoid oversmoothed results in terms of leak detection. The distributions of electrical current density on the walls of reservoir indicate the position of leaks. The results show that the inversion method with source compaction accurately identifies the location of single leaks. For two separated leaks, there is an obvious bias for the deeper hole and the bias increases with its depth. For three holes, the source compaction method generally identifies the location of the three leaks when their depth ranges are similar. When one of the leaks becomes deeper, localization of the deeper one becomes more difficult. The influence of the size of the leak on the inversion results is also investigated. The inversion algorithm overestimates the depth of small leaks while it slightly underestimates the depth of large leaks. For a leak having the form of a crack, the inversion results using the source compaction method agree with the position of the leak and its shape.