A prosperous and thorough analysis of gravity profiles for resources exploration utilizing the metaheuristic Bat Algorithm

作     者：Essa, Khalid S. Gomaa, Omar A. Elhussein, Mahmoud Geraud, Yves Diraison, Marc Diab, Zein E. 

作者机构：Cairo Univ Fac Sci Geophys Dept Giza 12613 Egypt Univ Lorraine GeoRessources Lab F-54500 Nancy France 

出 版 物：《SCIENTIFIC REPORTS》 (Sci. Rep.)

年 卷 期：2025年第15卷第1期

页      面：1-31页

核心收录：

主　　题：MBA Gravity data analysis SHG Source parameters estimation Volcanic and mining studies 

摘      要：Here, we present a remarkable methodology for unveiling subsurface structures with the potential to transform the exploration of mineral and ores resources, as well as the study of volcanic activity. By incorporating the Metaheuristic Bat algorithm (MBA) with the second horizontal gravity gradient (SHG) and employing variable window lengths, we aim to eliminate the regional effect in gravity data, thereby improving the precision of subsurface structure parameter estimation. Through rigorous evaluation on synthetic cases, we have demonstrated the robustness of our approach and its ability to handle diverse geological complexities and noise levels. Furthermore, our method has been applied to actual gravity data from three distinct locations: Canada, India, and Cuba, yielding excellent results that confirm the reliability and applicability of our methodology to real-world geological settings. We are confident that the use of variable window lengths in the SHG computation, coupled with the optimization of the global optimal solution via the Metaheuristic Bat Algorithm, can significantly contribute to the enhanced precision of subsurface structural parameter estimation. We hope our research will inspire others to explore this groundbreaking methodology and continue advancing the field of subsurface structure optimization.