Marine geophysical exploration for seafloor massive sulfides using unmanned underwater vehicles

Abstract Seafloor massive sulfide (SMS) deposits contain strategic metals essential for modern technologies, but traditional exploration methods using water column surveys and direct observation provide limited insight into subsurface extent and structure. This study evaluated three geophysical methods for SMS exploration using unmanned underwater vehicles: self-potential (SP), magnetic, and controlled-source electromagnetic (CSEM) techniques. Through 3D numerical modeling and inversion studies based on the Trans-Atlantic Geotraverse field, we demonstrated that SP and magnetic methods offer cost-effective, passive reconnaissance capabilities with limited depth resolution, while CSEM provides superior high-resolution 3D imaging but requires more sophisticated instrumentation. Autonomous underwater vehicles excel in large-scale surveys, whereas remotely operated vehicles enhance signal detection through closer seafloor proximity. Integration of multiple geophysical data sets significantly improved detection accuracy and reduced interpretive uncertainties. As marine sensors and numerical algorithms advance, these integrated geophysical approaches will play increasingly crucial roles in efficient SMS exploration, with benefits far outweighing survey costs.