Comparison between hydraulic conductivity anisotropy and electrical resistivity anisotropy from tomography inverse modeling

Abstract

Hydrogeophysics is increasingly used to understand groundwater flow and contaminant transport, essential basis for groundwater resources forecast, management, and remediation. It has proven its ability to improve the characterization of the hydraulic conductivity (K) when used along with hydrogeological knowledge. Geophysical tools and methods provide high density information of the spatial distribution of physical properties in the ground at relatively low costs and in a non-destructive manner. Amongst them, the Electrical Resistivity Tomography (ERT) has been widely used for its high spatial coverage and for the strong theoretical links between electrical resistivity (ρ) and key hydrogeological parameters, such as K. Historically, ERT data processing was based on isotropic hypothesis. However, the unconsolidated aquifers in Canada reveal in most cases a strong anisotropic behavior for K both with in situ or laboratory measurements. Recently, electrical anisotropy has been considered model-wise, but it is seldom considered as an interpretation tool or in the characterization process of the anisotropy of K. In order to evaluate the potential of ERT to assess the anisotropy of electrical resistivity, we developed a forward and inverse modeling code. These codes have been validated and tested on a realistic synthetic case reproducing the behavior of a real aquifer extensively characterized, the site of Saint-Lambert-de-Lauzon in Quebec (Canada). On this site, innovative in situ hydraulic tomography has revealed a strong anisotropy, with up to three orders of magnitude between horizontal and vertical K components. In order to confirm the link between in situ K- and ρ-anisotropies, an ERT survey has been performed, using the same wells as for the hydraulic tomography. The inversion confirms a strong link between K- and ρ-anisotropies. It demonstrates the suitability of the anisotropic ERT approach coupled with well measurements to provide better estimates of K and its anisotropy at the scale of a site.