Coupling of hydrogeological models with hydrogeophysical data to characterize seawater intrusion and shallow geothermal systems

While coastal aquifers are being stressed due to climate changes and excessive groundwater withdrawals require characterizing efficiently seawater intrusion (SWI) dynamics, production of geothermal energy is increasingly being used to hinder global warming. To study these issues, we need both robust measuring technologies and reliable predictions based on numerical models. SWI models are currently calibrated using borehole observations. Similarly, geothermal models depend mainly on the temperature field at few locations. Electrical resistivity tomography (ERT) can be used to improve these models given its high sensitivity to TDS and temperature and its relatively high lateral resolution. Inherent geophysical limitations, such as the resolution loss, can affect the overall quality of the ERT images and also prevent the correct recovery of the desired hydrochemical property. We present an uncoupled and coupled hydrogeophysical inversion to calibrate SWI and thermohydrogeologic models using ERT.

In the SWI models, we demonstrate with two synthetic benchmarks (homogeneous and heterogeneous coastal aquifers) the ability of cumulative sensitivity-filtered ERT images using surface-only data to recover the hydraulic conductivity. Filtering of ERT-derived data at depth, where resolution is poorer, and the model errors make the dispersivity more difficult to estimate. In the coupled approach, we showed that parameter estimation is significantly improved because regularization bias is replaced by forward modeling only. Our efforts are currently focusing on applying the uncoupled/coupled approaches on a real life case study using field data from the site of Almeria, SE Spain.

In the thermohydrogeologic models, the most sensitive hydrologic parameters responsible for heat transport are estimated from surface ERT-derived temperatures and ERT resistance data. A real life geothermal experiment that took place on the Campus De Sterre of Ghent University, Belgium and a synthetic case are tested. They consist in a thermal injection and storage of water in a shallow sandy aquifer. The use of a physically-based constraint accounting for the difference in conductivity between the formation and the tap injected water and based on the hydrogeological model calibrated first on temperatures is necessary to improve the parameter estimation. Results suggest that time-lapse ERT data may be limited but useful information for estimating groundwater flow and transport parameters for both the convection and conduction phases.