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The Bat optimizing algorithm (BOA) is one of the metaheuristic algorithms and applied here to interpret self-potential (SP) data. The BOA is depending upon a bat echolocation behavior for global optimization, which the global optimum solution reached at the suggested minimum value of the objective function. The best interpretive source parameters for the subsurface structures occurred at the minimal the objective function value (global best solution). The BOA is applied to 2D SP anomaly data to estimate the characteristic source parameters (i.e., the depth to center, amplitude coefficient, origin location, geometric shape factor, and polarization and inclination angle of the causative buried structure). The BOA can be applied to single and multiple source structures in the restricted class of simple geometric shapes, which these bodies help in the validation of the subsurface ore and mineral targets. The stability and efficiency of the proposed BOA have been examined by several synthetic examples. In addition, three different real field examples from Germany and Indonesia have been successfully applied to ore and mineral investigation and geological structure studies. In general, the achieved results are in good agreement with the available borehole data and results mentioned in the literature. [ABSTRACT FROM AUTHOR]

Geophysical methods, especially the gravity method, are very helpful in ore and mineral explorations. Here, gravity modeling and interpretation for the subsurface geologic structures generally assumes either homogenous or spatially varying densities within target source rocks and surrounding structures. Therefore, the use of simple-geometric bodies helps in the validation of the subsurface ore and mineral targets. A Bat optimization algorithm is a recently developed metaheuristic algorithm that is used in various geophysical applications to explore and explain the parameters of buried ore and mineral targets. Using the Bat optimization algorithm, we were elucidating gravity anomaly profiles for ore and mineral cases. To perform global optimization, the Bat optimization algorithm is based on the echolocation behavior of bats. The global optimum solution in the Bat optimization algorithm reached the suggested minimum value of the objective function. The Bat optimization algorithm is applied to gravity data to estimate the target parameters (e.g., amplitude coefficient, depth, origin location, and geometric shape). The stability and efficiency of the introduced optimizing algorithm have been checked on two synthetic models represented in a spherical model and an infinitely horizontal cylinder model using two different kinds of noise. Furthermore, successful applications of the proposed algorithm for discovering the ore and minerals in Canada, Cuba, and India were presented. The results match well with the available geological and borehole information and other results from the published literature. [ABSTRACT FROM AUTHOR]