Ren Mengyi Metallogenic information extraction and quantitative prediction process of seafloor polymetallic sulfide resources in the Southwest Indian Ocean

Seafloor polymetallic sulfide resources exhibit significant development potential. In 2011, the China Ocean Mineral Resources Research and Development Association (COMRA) and International Seabed Authority (ISA) signed a contract for the exploration of 10,000 km2 of a hydrothermal sulfide area located on the Southwest Indian Ridge (SWIR). According to the Regulations, China will have to relinquish, respectively, 50 % and 75 % of the contract area within 8 and 10 years. However, an exploration of the seafloor hydrothermal sulfide deposits in China remains in the initial stage. According to the quantitative prediction theory and the exploration status of seafloor sulfides, this paper collects the ore-forming factors from topography, geology, geophysics, and several other related aspects in the SWIR and extracts the favorable metallogenic information to establish an ore deposit prediction model of the sulfide deposit. By employing the weights-of-evidence method, we obtain the weight of each metallogenic prediction factor and thereby obtain the posterior probability map of polymetallic sulfide deposits in the SWIR. The prediction result suggests that the central region of the SWIR has the highest posterior probability, which means that it has the best mineralization prospect. Known hydrothermal areas such as Mt. Jourdanne, area A and 10°E-16°E are all located in or near areas with high posterior probability value. The Chinese contract area of 48°–52°E has the highest posterior probability value and can thus be selected as the reserved region for additional exploration. By narrowing the exploration area and improving the exploration accuracy, the prediction will provide a basis for the further exploration of seafloor hydrothermal sulfide resources.