Experimental design: Electrical resistivity data sets that provide optimum subsurface information

Abstract Although multielectrode electrical-resistivity systems have been commercially available for more than a decade, resistivity imaging of the subsurface continues to be based on data sets recorded using one or more of the standard electrode arrays (e.g., the Wenner or conventional dipole-dipole array). To exploit better the full capabilities of multielectrode acquisition systems, we have developed an experimental design procedure to identify suites of electrode configurations that provide subsurface information according to predefined optimization criteria. The experimental design algorithm includes a goodness function that ranks the sensitivity of every possible electrode configuration to changes in the subsurface parameters. To examine the potential and limitations of the new algorithm, comprehensive data sets that included data from all standard and nonstandard electrode configurations were (a) generated for a complex 2D resistivity model and (b) recorded across a well-studied test site in Switzerland. Images determined from the resultant comprehensive data sets were used as benchmarks against which the images derived from the optimized data sets were assessed. Images from relatively small optimized data sets, containing 265–282 data points, provided more information than did those from standard data sets of equal size. By far the best images, comparable to those determined from the much larger comprehensive data sets, were obtained from optimized data sets with 1000–6000 data points. These images supplied reliable information over depth ranges that were three times greater than the depth ranges resolved by the standard images. The first ∼600 electrode configurations selected by the experimental design procedure were nonstandard dipole-dipole-type arrays, whereas the following ∼4800 electrode configurations were an approximately equal mix of nonstandard dipole-dipole-type arrays and nested configurations (i.e., mostly gradient and other nonstandard arrays).