Abstract

AbstractThe Ailaoshan Orogen in the southeastern Tibet Plateau, 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 elements can conceal or reduce anomalies due to the mutual effect between different anomaly areas. Dividing the whole zone into subzones based on tectonic settings, ore cluster areas, or sample catchment basins (Scb), geochemical and structural anomalies associated with gold (Au) mineralization have been identified utilizing mean plus twice standard deviations (Mean + 2STD), factor analysis (FA), concentration‐area (C‐A) modeling of stream sediment geochemical data, and lineament density in both the Ailaoshan Orogen and the individual subzones. The FA in the divided 98 Scbs with 6 Scbs containing Au deposits can roughly ascertain unknown rock types, identify specific element associations of known rocks and discern the porphyry or skarn‐type Au mineralization. Compared with methods of Mean + 2STD and C‐A model of data in the whole 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 Au deposits because of 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 Au deposits. By analyzing the map of faults and Au anomalies, two potential prospecting targets, Scbs 1 and 63 with a sandstone as a potential host rock for Au, have been 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.

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