1D laterally constrained inversion of towed-array capacitive resistivity imaging data

Towed-array Capacitive Resistivity Imaging has proved to be a viable, convenient and effective technique for acquiring multi-channel high-resolution Electrical Resistivity Tomography data with dense lateral coverage on engineered surfaces. As resistance data measured with capacitive coupling under quasi-static conditions are equivalent to conventional galvanic data, popular ERT interpretation schemes such as least-squares smoothness-constrained resistivity inversion are fully applicable to CRI data. However, for certain specialised applications, much simpler earth models (e.g. 1D with moderate lateral variations) may be sufficient to adequately reflect the subsurface structure under investigation and a significant amount of a-priori information may exist that can be used to constrain the inverse models. One way to exploit these simplifications is to employ piecewise 1D Laterally Constrained Inversion, which divides the subsurface into a series of 1D earth models connected laterally by model constraints that control the similarity between adjacent models and the propagation of subsurface information along a given interpretational profile. In this study we demonstrate the feasibility of applying 1D-LCI to towed-array CRI data and show the utility of this approach for the analysis of datasets acquired to assess road subgrade condition.