A hybrid optimization scheme for self-potential measurements due to multiple sheet-like bodies in arbitrary 2D resistivity distributions
I Giannakis, P. Tsourlos, C. Papazachos, G. Vargemezis, A. Giannopoulos, N. Papadopoulos, F. Tosti and A. Alani
Journal name: Geophysical Prospecting
Issue: Vol 67, No 7, September 2019 pp. 1948 - 1964
Info: Article, PDF ( 4.21Mb )
Self-potential is a passive geophysical method that can be applied in a straightfor-ward manner with minimum requirements in the field. Nonetheless, interpretation of self-potential data is particularly challenging due to the inherited non-uniqueness present in all potential methods. Incorporating information regarding the target of interest can facilitate interpretation and increase the reliability of the final output. In the current paper, a novel method for detecting multiple sheet-like targets is pre-sented. A numerical framework is initially described that simulates sheet-like bodies in an arbitrary 2D resistivity distribution. A scattered field formulation based on finite differences is employed that allows the edges of the sheet to be independent of the grid geometry. A novel analytical solution for two-layered models is derived and sub-sequently used to validate the accuracy of the proposed numerical scheme. Lastly, a hybrid optimization is proposed that couples linear least-squares with particle-swarm optimization in order to effectively locate the edges of multiple sheet-like bodies. Through numerical and real data, it is proven that the hybrid optimization over-comes local minimal that occurs in complex resistivity distributions and converges substantially faster compared to traditional particle-swarm optimization.