Ore-forming fluid migration model constrained by fluid inclusions, infrared spectroscopy, and trace elements: a case study of the Banxi Sb deposit, South China

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The Banxi Sb deposit is a low-temperature hydrothermal deposit associated with the Xuefeng arcuate structure and regional fault systems. However, the migration pathways and flow directions of deep ore-forming fluids remain poorly constrained, thereby limiting the potential for deep exploration. This study integrates whole-rock trace-element geochemistry, fluid-inclusion analysis, and short-wave infrared (SWIR) spectroscopy with machine-learning algorithms, including a convolutional neural network (CNN) and orthogonal partial least-squares discriminant analysis (OPLS-DA), to develop a multi-parameter prospecting model. Key results demonstrate: Geochemical zoning defines three distinct element assemblages—Co-Cr-Fe-Ni–W-Sn-Bi (sub-ore halo), Ag-Cd-Cu-Pb-Zn (supra-ore halo), and Au-As-Sb (near-ore halo)—that exhibit systematic spatial correspondence with major faults and cleavage zones. The ore-forming fluids are characterized by low temperature (160–240 °C), low salinity (4–6 wt% NaCl eq.), and a reducing fluid composition (CO 2 -CH 4 -N 2 -H 2 S), with pressure of 600–800 bar and densities of 0.8–0.9 g/cm 3 . Machine-learning analyses confirm that the SWIR illite-crystallinity index (SWIR-IC = Dep2200/Dep1900) is a key mineralization indicator, with SWIR-IC anomalies spatially coinciding with major fault structures. Integration of elemental, spectral, fluid-inclusion, and alteration data suggests that the ore-forming fluids ascended from the deep segment of the fault through multiple subsidiary fracture systems. This integrated approach delineates high-potential targets at depths beneath known ore bodies and establishes a novel, reproducible framework for deep mineral exploration.