Inversion of self-potential anomalies from regular geometric objects by using whale optimization algorithm

The whale optimization algorithm (WOA) is one of the meta-heuristic algorithms that achieve parameters optimization by simulating the feeding behavior of humpback whales. The WOA can be applied to self-potential (SP) data inversion for regular polarized geometric objects (i.e., sphere, horizontal cylinder, and vertical cylinder), which can assist in exploring subsurface geological objects. The WOA was first applied to perform parameter inversion on three models: the sphere, the vertical cylinder, and the combination of both models. The optimization process of the vertical cylinder model parameters was analyzed, and the convergence behavior of the WOA was discussed. Secondly, laboratory-measured data from three sets of physical models were used for parameters inversion, and a comparison was made with two other optimization algorithms to demonstrate the advantages of the WOA. Finally, the WOA was applied to process a set of field data. The WOA algorithm was employed for the inversion of SP data inversion from numerical experiments, physical experiments, and field examples. The inversion results demonstrate that the proposed WOA inversion has good stability and effectiveness in solving the self-potential inversion problem.