Abstract

Skarn deposits are high grade hydrothermal deposits distributed throughout the world, containing multiple mineral resources. However, the formation of skarn deposits is extremely complex, hindering our in-depth understanding of these deposits with high economic value. The Qiaomaishan Cu deposit is a typical skarn deposit located in the Liqiao-Tongshan orefield, Middle-Lower Yangtze River Metallogenic Belt (MLYRMB). This study applied numerical simulation approach to quantitatively describe the formation of copper mineralization within the Qiaomaishan skarn deposit, and explored the correlation between the surface morphology of intrusion and the formation of mineralization. This numerical model links five main processes related to ore formation within hydrothermal ore-forming system and their complex coupled relationship, namely chemical reactions, heat conduction, rock deformation, fluid migration, and materials diffusion. Results show that rough surface morphology of the intrusions is an ore controlling factor within the Qiaomaishan skarn deposit. The uneven surface of the intrusions greatly affects the time spent in cooling, thereby affecting the generation and spatial distribution of chalcopyrite. The concave part of the surface of the intrusions lives a longer cooling period (1000–2500 years) than the convex part (110–160 years) from 310 to 260 °C, which directly causes the difference in the temporal-spatial distribution of chalcopyrite. Results also show that the factors involved in prospectivity modeling must undergo strict conditional independence analysis, and numerical simulation method can be used to effectively achieve this goal. However, there are also some problems unsolved, such as difficulties caused by lack of data and oversimplified ore-forming chemical reactions. Future development of both geological research and modification of the law of mass action will undoubtedly improve the accuracy and practicability of numerical simulation and our understanding of the Qiaomaishan as well as other skarn deposit, providing information for mineral deposit research from the perspective of computational geoscience.

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