Strategies to overcome near surface disturbances while inverting time-lapse surface ERT data

An important basis for a reliable groundwater management is the detailed knowledge of the aquifer. We attempt here to determine groundwater flow velocity and direction of an hard rock aquifer in a groundwater protection area (Hastenrather Graben, Germany). In a common experimental set-up, we injected low salinity water in the aquifer and monitored the resistivity changes in the aquifer using time-lapse Electrical Resistivity Tomography (ERT). However, we witnessed strong influences from near surface resistivity fluctuations which were in the range of expected changes within the aquifer. We investigated these disturbances in more detail and determined two main sources of disturbance: a surface ditch, used for drainage with varying water fillings and, therefore, varying resistivities over time; secondly, changes of soil-atmosphere interactions, i.e., water accumulation in slight surface depressions after rain events. In addition to these main sources, the measured data is furthermore affected by random noise. In this paper, we compare three approaches to reduce the influence of these effects. After identifying disturbed areas, we exclude data near disturbed areas from the inversion as first approach; secondly, we refined the mesh at disturbed areas; and thirdly, we apply a region-based regularization to the time-lapse inversion. In a synthetic case study, all three approaches improve the inversion result. However, the region-based regularization recovers the input features best. The geometry of changes at depth are here less masked and the simulated injection body is better resolved. Nevertheless, the values are less accurately fitted than with a global regularization factor. Therefore, applying the approach on field data requires careful adjustment of the individual regularization factors to improve the time-lapse inversion results. We apply the combined first and third approach on our field data. As expected from the synthetic study, we see less masking and compensatory effects. The injection plume is visible in the resistivity distribution. The groundwater flow seems to be negligibly small, which is in accordance with an existing groundwater flow model of the aquifer. Our results confirm the fact that it is important to consider potential near-surface influences when analysing time-lapse ERT data. Based on a detailed synthetic case and an application to a aquifer injection study, we suggest to exclude data near heavily disturbed areas, in addition to applying a region-based regularization scheme. © 2021