Accurate modelling and inversion of electrical resistivity data in the presence of metallic infrastructure with known location and dimension

Electrical resistivity tomography (ERT) has been widely used in environmental applications to study processes associated with subsurface contaminants and contaminant remediation. Anthropogenic alterations in subsurface electrical conductivity associated with contamination often originate from highly industrialized areas with significant amounts of buried metallic infrastructure. The deleterious influence of such infrastructure on imaging results generally limits the utility of ERT where it might otherwise prove useful for subsurface investigation and monitoring. In this manuscript we present a method of accurately modelling the effects of buried conductive infrastructure within the forward modelling algorithm, thereby removing them from the inversion results. The method is implemented in parallel using immersed interface boundary conditions, whereby the global solution is reconstructed from a series of well-conditioned partial solutions. Forward modelling accuracy is demonstrated by comparison with analytic solutions. Synthetic imaging examples are used to investigate imaging capabilities within a subsurface containing electrically conductive buried tanks, transfer piping, and well casing, using both well casings and vertical electrode arrays as current sources and potential measurement electrodes. Results show that, although accurate infrastructure modelling removes the dominating influence of buried metallic features, the presence of metallic infrastructure degrades imaging resolution compared to ERT imaging in the absence of infrastructure. However, it is possible to rectify this degradation in resolution through appropriate placement of electrodes.