Evaluating the utility of electrical resistivity tomography in the presence of metallic infrastructure

Legacy waste sites can pose a significant risk to human health and the environment. Interpolation of point-scale sampling data from wells is often used to characterize contaminant distributions, but this approach does not always provide a complete or representative picture to support site remedial decisions. Electrical resistivity tomography (ERT) provides a way to enhance the information obtained from point-scale well measurements. ERT is sensitive to moisture content, pore fluid ionic constituents and lithology and the data acquisition is cost-effective and non-invasive. However, many legacy waste sites have a considerable amount of conductive metallic infrastructure which has a strong influence on the ERT measurement, masking the locations of conductive targets. Previous research has demonstrated that incorporation of metallic infrastructure, through data correction or the ERT forward modeling algorithm, could increase the utility of ERT at legacy waste sites. However, the location and size of the infrastructure was known and could be properly emplaced in the numerical model. In some cases, the exact location of metallic infrastructure may not be known. The objective of this work is to investigate the efficacy of ERT in field scenarios where the exact location of metallic infrastructure is not known. ERT data was collected at two sites with a network of metallic infrastructure. We use synthetic models for a better understanding of including metallic infrastructure in the ERT modeling and evaluate the impact of including infrastructure on the surrounding bulk electrical conductivity structure. This study provides a framework to use ERT in environments not typically suited for this method, thereby increasing the applicability.