An automatic inversion approach for magnetic data applying the global bat optimization algorithm (GBOA): application to ore deposits and basement rock intrusion

Abstract

Abstract Recently, metaheuristic approaches are frequently used to the potential data inversion (i.e., magnetic data) as a global optimizing approach. In the present study, we proposed a global optimizing bat algorithm (GOBA) that based on bat echolocation behavior to obtain globally optimal solutions (best parameters) of magnetic anomalies. The best determined source parameters were picked at the suggested minimum objective function. The proposed GOBA approach does not require prior information and represents an effective technique of surveying the entire domain of the raw data to evaluate sources optimal parameters. The GOBA approach is employed to magnetic data profiles to determine the characteristic source attributes (i.e. the vertical depths to the center of the anomalous structures, the magnitude of amplitude coefficients, the sources origin, the approximated geometric form factors, and the effective angles of magnetization). The GOBA approach can be applied to single and multiple anomaly structures in the restricted categories of basic geometric shapes (spheres, cylinders, sheets, and dikes). The stability, constancy, and performance of the given GOBA approach are achieved on different purely and contaminated examples for individual and double sources. Besides, the introduced GOBA approach has been fruitfully utilized to three field datasets from Turkey, Canada, and Senegal for ore deposit and basement rock intrusion investigations. Overall, the recovered inversion results from the GOBA approach are in high correlation with the available drill-holes, geologic data, and scholarly articles outcomes. Finally, the provided metaheuristic GOBA approach is a simple, accurate, and powerful technique for magnetic data interpretation. Article highlights An automatic approach for magnetic data interpretation to investigate the ore deposits and sustainable resources such as volcanic and basement rock intrusions based on bat echolocation behavior to obtain the global optimal solutions. In this study we built 2D models aims to image of the interior of the subsurface to investigate their natural resources, for example minerals & ore deposits and rock intrusions, helping in understand their concentration and the distribution location, including the depth to their sources. We came to the conclusion that the suggested approach is useful in ore & mineral research, the reconnaissance geological studies and can be extend to the volcanic activity & geothermal exploration studies in the future.