Affiliation:
1. State Key Laboratory of Geological Processes and Mineral Resources China University of Geosciences Beijing 100083 China
2. Frontiers Science Center for Deep‐time Digital Earth China University of Geosciences (Beijing) Beijing 100083 China
3. Xi'an Center of Mineral Resources Survey China Geological Survey Xi'an 710010 China
4. Yunnan Gold Mining Industry Group Kunming 650299 China
5. State Key Laboratory of Nuclear Resources and Environment East China University of Technology Nanchang 330013 China
Abstract
AbstractThe Ailaoshan Orogen, situated between the Yangtze and Simao Blocks, underwent a complex structural, magmatic, and metamorphic evolution resulting in different tectonic subzones with varying structural lineaments and elemental concentrations. These can conceal or reduce anomalies due to the mutual effect between different anomaly areas. This study divided the whole zone into subzones based on tectonic settings, ore‐cluster areas, or sample catchment basins (SCB). To identify geochemical and structural anomalies associated with gold mineralization, the mean plus twice standard deviations (Mean+2STD), factor analysis (FA), concentration–area (C‐A) modeling of stream sediment geochemical data, and lineament density were utilized in both the Ailaoshan Orogen and the individual subzones. The FA in the divided 98 SCBs with 6 SCBs containing gold deposits can roughly ascertain unknown rock types, identify specific element associations of known rocks and discern the porphyry or skarn‐type gold mineralization. Compared with methods of Mean + 2STD and C–A model of data in the whole Ailaoshan Orogen, which mistake the anomalies as background or act the background as anomalies, the combined methods of FA and C‐A in the separate subzones or SCBs works well in regional metallogenic potential analysis. Mapping of lineament densities with a 10 km circle diameter is not suitable to locate gold deposits due to the delineated large areas of medium‐high lineament density. In contrast, the use of circle diameters of 1.3 km or 1.7 km in the ore‐cluster scale delineates areas with a higher concentration of lineament density, consistent with the locations of known gold deposits. By analyzing the map of faults and gold anomalies, two potential prospecting targets, SCBs 1 and 63 with a sandstone as a potential host rock for Au, were identified in the Ailaoshan Orogen. The use of combined methods in the divided subzones proved to be more effective in improving geological understanding and identifying mineralization anomalies associated with Au, rather than analyzing the entire large area.