Improvement of electrical resistivity tomography for leachate injection monitoring

Leachate recirculation is a key process in the scope of operating municipal waste landfills as bioreactors, which aims to increase the moisture content to optimize the biodegradation in landfills. Given that liquid flows exhibit a complex behaviour in very heterogeneous porous media, in situ monitoring methods are required. Surface time-lapse electrical resistivity tomography (ERT) is usually proposed. Using numerical modelling with typical 2D and 3D injection plume patterns and 2D and 3D inversion codes, we show that wrong changes of resistivity can be calculated at depth if standard parameters are used for time-lapse ERT inversion. Major artefacts typically exhibit significant increases of resistivity (more than +30%) which can be misinterpreted as gas migration within the waste. In order to eliminate these artefacts, we tested an advanced time-lapse ERT procedure that includes (i) two advanced inversion tools and (ii) two alternative array geometries. The first advanced tool uses invariant regions in the model. The second advanced tool uses an inversion with a "minimum length" constraint. The alternative arrays focus on (i) a pole-dipole array (2D case), and (ii) a star array (3D case). The results show that these two advanced inversion tools and the two alternative arrays remove almost completely the artefacts within +/-5% both for 2D and 3D situations. As a field application, time-lapse ERT is applied using the star array during a 3D leachate injection in a non-hazardous municipal waste landfill. To evaluate the robustness of the two advanced tools, a synthetic model including both true decrease and increase of resistivity is built. The advanced time-lapse ERT procedure eliminates unwanted artefacts, while keeping a satisfactory image of true resistivity variations. This study demonstrates that significant and robust improvements can be obtained for time-lapse ERT monitoring of leachate recirculation in waste landfills. (c) 2009 Elsevier Ltd. All rights reserved.