Informed experimental design for electrical resistivity imaging

Electrical resistivity imaging has been successfully used to monitor near-surface hydrologic processes but use of standard measurement arrays may not provide the greatest data sensitivity to the imaged region. We present a method of experimental design based on the concept of informed imaging for creating an electrical resistivity imaging experiment to monitor flow beneath a recharge pond. Informed imaging is the integration of all available data about a site into the acquisition, inversion and interpretation of electrical resistivity data. Informed experimental design uses all available information to develop an a priori model of the subsurface conductivity structure that guides the selection of measurement arrays for an electrical resistivity imaging experiment given spatial and temporal constraints on the acquisition. Selection of arrays focuses on maximizing the amount of unique information acquired with each source pair. We apply the method to the selection of arrays for imaging the top 5 m of the subsurface beneath a recharge pond in Northern California, which is part of an aquifer storage and recovery project. Decreasing infiltration rates over time reduce the effectiveness of the recharge pond. We seek to monitor infiltration processes at the contact between a fines-rich sand layer and coarser sand layer in an effort to understand the hydrologic controls on infiltration. The performance of the arrays selected using informed experimental design relative to two standard arrays (Wenner and dipole-dipole) is validated on two synthetic subsurface conductivity models, which are representative of conductivity structures that may arise during an infiltration event. Performance is evaluated in terms of a singular value decomposition of the sensitivity matrix produced by the three types of arrays, as well as a measure of the region of investigation. Results demonstrate that arrays selected using informed experimental design provide independent information about the imaged region and are robust in the presence of noise, improving the ability to image changes in a conductivity structure that result from infiltration processes.