Assessing the reliability and performance of optimized and conventional resistivity arrays for shallow subsurface investigations

Abstract The optimized ‘Compare R’ (CR) method is considered one of the best algorithms to automatically generate a set of electrode arrays that maximizes the model resolution for electrical resistivity imaging. In its original version, the calculation time to generate a set of arrays, even for a short resistivity line, required several hours. Recently, researchers spent considerable effort to reduce execution time. In addition, other modifications have been made to improve the practical aspects, such as minimizing the electrode polarization effects and incorporating errors in the data. In line with this approach, the effectiveness of the optimized arrays that are generated based on a modified version of ‘Compare-R' optimization algorithm is demonstrated through a comprehensive and quantitative comparison with the conventional Dipole-Dipole (DD) and Wenner-Schlumberger (WS) arrays. Four different synthetic models were generated and noisy data cases were considered. The results show that the optimized array has significantly better resolution and target detail than conventional arrays. This is clear in enhancing the detectability accuracy in the deepest part of the inversion models. Of the conventional arrays, the DD array provides inversion images mostly closely related to the performance of the optimized array models.