Abstract
As a product of hydrothermal activity, seafloor polymetallic sulfide deposit has become the focus of marine mineral exploration due to its great prospects for mineralization potential. The mineral prospectivity mapping is a multiple process that involves weighting and integrating evidential layers to further explore the potential target areas, which can be categorized into data-driven and knowledge-driven methods. This paper describes the application of fuzzy logic and fuzzy analytic hierarchy process (AHP) models to process the data of the Southwest Indian Ocean Mid-Ridge seafloor sulfide deposit and delineate prospect areas. Nine spatial evidential layers representing the controlling factors for the formation and occurrence of polymetallic sulfide deposit were extracted to establish a prospecting prediction model. Fuzzy logic and fuzzy AHP models combine expert experience and fuzzy sets to assign weights to each layer and integrate the evidence layers to generate prospectivity map. Based on prediction-area (P-A) model, the optimal gamma operator (γ) values were determined to be 0.95 and 0.90 for fuzzy logic and fuzzy AHP to synthesize the evidence layers. The concentration-area (C-A) fractal method was used to classify different levels of metallogenic probability by determining corresponding thresholds. Finally, Receiver Operating Characteristic (ROC) curves were applied to measure the performance of the two prospectivity models. The results show that the areas under the ROC curve of the fuzzy logic and the fuzzy AHP model are 0.813 and 0.887, respectively, indicating that prediction based on knowledge-driven methods can effectively predict the metallogenic favorable area in the study area, opening the door for future exploration of seafloor polymetallic sulfide deposits.
Highlights
With the progress of deep-sea exploration technology and depletion of terrestrial mineral resources, the exploration for seafloor mineral resources has been paid considerable attention by various countries [1]
Seabed Authority (ISA) approved China’s application for a 10,000 km2 region of the seafloor along the Southwest Indian Ridge (SWIR), and China have granted to exclusive exploration rights and preferential commercial mining rights in the area [5]
The mantle detachment faultcolumn has exposed lower crust and mantle materials the seafloor inferred by materials on the seafloor by gravity, magnetic, borehole andthe seismic geophysical surveys, gravity, magnetic, boreholeinferred and seismic geophysical surveys, favoring formation of an oceanic core favoring of an oceanic core complex hydrothermal circulation system
Summary
With the progress of deep-sea exploration technology and depletion of terrestrial mineral resources, the exploration for seafloor mineral resources has been paid considerable attention by various countries [1]. As regulated by the contract, by 2021 China can only retain exploration and mining rights of 25% of its area In this regard, application of mineral prospectivity mapping (MPM) techniques to delineate potential areas that likely contain sulfide occurrences in this region of interest is urgent. Fuzzy analytic hierarchy process (AHP) [19,21] Comparing this approach to the data-driven method required a certain number of discovered mineral deposits; the knowledge-driven techniques are suitable for undeveloped areas where no or very few mineral deposits are known to occur. The objectives include the demonstration of two knowledge-driven methods for MPM in seafloor sulfides, generation of seafloor sulfide prospectivity map for further exploration, and comparison of the performance of the two methods
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