Practical aspects of applied optimized survey design for electrical resistivity tomography

The use of optimized resistivity tomography surveys to acquire field data imposes extra constraints on the design strategy beyond maximizing the quality of the resulting tomographic image. In this paper, methods are presented to (1) minimize electrode polarization effects (2) make efficient use of parallel measurement channels and (3) incorporate data noise estimates in the optimization process. (1) A simulated annealing algorithm is used to rearrange the optimized measurement sequences to minimize polarization errors. The method is developed using random survey designs and is demonstrated to be effective for use with single and multichannel optimized surveys. (2) An optimization algorithm is developed to design surveys by successive addition of multichannel groups of measurements rather than individual electrode configurations. The multichannel surveys are shown to produce results nearly as close to optimal as equivalent single channel surveys, while reducing data collection times by an order of magnitude. (3) Random errors in the data are accounted for by weighting the electrode configurations in the optimization process according to a simple error model incorporating background and voltage-dependent noise. The use of data weighting produces optimized surveys that are more robust in the presence of noise, while maintaining as much of the image resolution of the noise-free designs as possible. All the new methods described in this paper are demonstrated using both synthetic and real data, the latter having been measured on an active landslide using a permanently installed geoelectrical monitoring system.