Numerical modeling of the mineralizing processes within the Shaxi porphyry-type Cu-Au deposit, Eastern China: Influence and restriction from physical and chemical characteristics of host rocks

The Shaxi porphyry-type Cu-Au deposit is located in the northwestern outer margin of the Luzong volcanic basin, which is situated in the Middle-Lower Yangtze River Metallogenic Belt (MLYRMB), Eastern China. It is a large porphyry-type Cu-Au deposit with confirmed copper resources exceeding 1 Mt and gold resources exceeding 40 tons. Previous studies have extensively investigated the genesis, controlling structures, geochemical characteristics, fluid evolution, alteration zone, and ages of mineralization and host rocks in this deposit. However, research on the influence of the physical and chemical properties of the host rocks on the mineralizing processes has not been explored in detail. This study employs the finite element method to apply numerical modeling of multiple physical and chemical fields, interlinking heat transfer, fluid flow, material migration, mineralization reaction, and their coupling with porosity and permeability of rock, to investigation of the influence of different porosities, permeabilities, and chemical properties of the host rocks on the mineralizing processes in the Shaxi deposit. The results show that the porosity and permeability of the host rocks play a significant role in the mineralization of porphyry-type systems. The different porosity and permeability of the intrusions and strata control the depth, the mineralization intensity, the morphology of the ore bodies, and the spatial location of the mineralization center. The chemical properties of the strata significantly restrict the mineralization intensity and horizontal spatial rather than affecting the depth of mineralization. Furthermore, the formation of skarn-type deposits may require a longer period of time than that of porphyry-type deposits under the same mineralization conditions and ore grade. This paper also indicates that the numerical modeling method employed in this study can be used to predict the mineralization depth and spatial location of deep concealed porphyry-type deposits, aiding research in deep-seated mineral exploration.