Optimisation of electrode arrays used in 2D resistivity imaging surveys

Abstract

This paper describes four different methods to automatically select the optimal set of array configurations that give the maximum resolution of the subsurface with 2D electrical imaging surveys for a limited of measurements. The first method (CR method) directly calculates the improvement in the model resolution for each new array configuration added to the set of measurements. It gives the best results but is the slowest. The second (BGS) and third (ETH) methods use linear approximations (using the second and first power of the sensitivity values respectively) to estimate the change in the model resolution matrix. Both methods are about an order of magnitude faster than the first method. The BGS method produces array configurations with model resolution values that approaches the results obtained by the CR method, while the ETH method gives significantly poorer results. The fourth method uses a combination of the BGS and CR methods. It produces results that are almost identical to the CR method but is several times faster. The different methods were tested using data from synthetic models and field surveys. The results show that the optimised array configuration data sets significantly improve the subsurface resolution achieved by the survey compared to conventional arrays such as the Wenner, Schlumberger and dipole-dipole arrays.