Prospectivity mapping for “Zhuxi-type” copper-tungsten polymetallic deposits in the Jingdezhen region of Jiangxi Province, South China

Abstract The Zhuxi deposit is the largest copper-tungsten polymetallic deposit in the world and is in Jiangxi Province in South China. The ore body is characterized by hydrothermal-vein deposits of copper, lead, and zinc minerals at shallow levels, skarn deposits of tungsten and copper minerals at middle levels, and altered-granite-hosted copper and tungsten minerals at depth. Such metallogenic systems are typically intrusion-related. The intrusive granites related to the Zhuxi polymetallic deposit have been dated at 152.9 Ma to 146.9 Ma. The intrusions provided the thermal energy and the source material for the ore mineralization. Skarns mineralization, the main type of ore mineralization, developed in the contact zone of Carboniferous-Permian formations with the granites. Nappe structures changed the dip of the ore bodies from steep in the top part to gentle in the bottom. NE-trending faults provided the fluid pathways and controlled the geological framework and distribution of ore deposits on a regional scale. In this study, recognition exploration criteria were analyzed based on a mineral deposit model and the geological setting. Extraction of favorable geological information and GIS-based data-integration methods were used for mineral-prospectivity mapping of Zhuxi-type polymetallic deposits. Buffering analysis was employed to extract structural information (e.g. faults) and lithologic or stratigraphic information (e.g. granites or geologic units). The singularity method and spatially weighted principal component analysis were used to enhance and delineate geochemical anomalies. The derivative norm was utilized to extract magnetic-gradient anomalies associated with intrusive granites. Student t -test of weights-of-evidence (WofE) proved to be an effective way to optimize threshold values for binarization of variables as evidence layers by evaluating the spatial correlation between known deposits and geological variables. The posterior probabilities of WofE gave a relative estimation of mineralization potential. Areas delineated by high posterior probability had much higher potentiality for the discovery of new deposits where had none had been found yet.