Model parameter estimation and its uncertainty for 2-D inclined sheet structure in self-potential data using crow search algorithm

Fracture or fault can control several geological or geophysical events and exploration, where the fault associated with mineralization or fluid flow can be used as a source for Self-Potential (SP) anomaly. The 2-D inclined sheet can be used for modeling for fault interpretation using SP data. In this paper, the improved crow search algorithm (ICSA) using Levy flight is proposed for SP data inversion in determining SP model parameters. In order to evaluate ICSA, the ICSA is compared with standard crow search algorithm (CSA) for determining synthetic SP data that contains multiple anomalies with inclined sheet type structures. It was found that CSA is more explorative than ICSA, and both algorithms can estimate the posterior distribution model (PDM) of SP data. Using uncertainty analysis within the applied threshold in the objective function, both algorithms are reliable to determine PDM. Furthermore, ICSA is tested and implemented to both synthetic and field of SP anomalies for providing the posterior distribution model of SP parameters. The experimental results demonstrate that the ICSA is feasible and effective for determining model parameters and its uncertainty of mono- and multi-SP anomalies. Furthermore, estimating both model parameter and its uncertainty are sufficient for validation with previous researchers. Finally, the interpretation of multiple anomalies in SP anomaly crossing the Grindulu Fault in Pacitan, East Java, Indonesia, is analyzed.