Introduction

The Sichuan-Yunnan-Guizhou metallogenic province (SYGMP) in southwestern China contains over 400 Pb-Zn deposits, accounting for 27% of the total Zn–Pb reserves of China1,2,3 (Fig. 1), and the Sichuan–Yunnan–Guizhou (SYG) metallogenic province in China is a significant source of Pb–Zn, Ag, and trace elements (e.g., Ga, Ge, Cd), have been the subject of research interest for the past decade4,5,6,7,8,9,10,11,12,13,14,15. The Pb–Zn deposits in the SYG province contain > 20 Mt of Pb and Zn metals at grades of > 10 wt% (Pb + Zn) found in carbonate host rocks from the late Sinian, Devonian, Carboniferous, and lower Permian periods6. Zhugongtang lead-zinc deposit is the largest lead-zinc deposit discovered in the southeastern area of the SYG province in recent years16. It contains > 3.0 Mt of Pb and Zn ore resources with an average grade > 12 wt%. The ore deposits in this region are noted for their high grade, significant thickness, and extensive distribution. In recent years, significant studies have been carried out on the Zhugongtang Pb-Zn deposits, which mainly centered on geological characteristics and Geochemical characteristics of trace elements17,18,19,20,21,22, ore deposit genesis and material sources1,13,16,23,24,25, Integrated geophysical exploration applications26,27,28,29.

Previous research on the Zhugongtang lead-zinc deposit mainly focused on the ore-forming theory, ore-controlling structures and qualitative analysis of the impact of hydrothermal migration on the ore-forming process30,31,32,33,34. However, there is a lack of research on the multi-physical field coupling process within the fault-fold structure. Compared with geological models based on field observations, numerical models have the advantages of low risk, low cost, and the ability to break through time and space limitations for multi-parameter quantitative analysis. In contrast to prospectivity models that focus on future mineral exploration35, numerical simulations offer valuable insights into the processes of mineralization, thereby deepening our comprehension of these processes36,37. Previous studies have demonstrated that numerical simulation is effective in solving ore deposit related problem, as seen in the Century deposit38, Fushan Iron deposit39, Hutouya Pb-Zn deposit40, Chating Cu-Ag deposit41, McArthur River deposit42, Gejiu ore deposit43, Maoping Pb-Zn deposit44, skarn-type Pb-Zn deposits45, Qiaomaishan skarn Cu deposit46, Shaxi porphyry-type Cu-Au deposit47, Huize deposit48. Unlike previous simulation methods (e.g., Fan et al., 2021, for Gejiu deposit simulations43; Zhao et al., 2024, for the Huize deposit simulation48, this study utilized COMSOL Multiphysics software to numerically simulate the Zhugongtang lead-zinc deposit. This study, incorporating fault-fold coupling into the analysis of the interlimb angle effect, revealed the influence of the interlimb angle on Zn2+ distribution and explored its mineralization process. By utilizing the finite element method, the study integrates various physical fields, including fluid migration, heat transfer, and pressure, to gather crucial data on temperature, stress distribution, and concentration. This analysis uncovers the genetic processes and controlling elements that determine the spatial distribution of the Zhugongtang lead-zinc deposit. The findings offer fresh perspectives for exploring the Zhugongtang lead-zinc deposit and serve as scientific guidance for future exploration efforts. This study explores two core questions: (1) How does multi-field coupling (temperature, pressure, fluid) of fault folds control thermal Zn²⁺ distribution? (2) How does the interlimb angle between faults affect the location of mineralization?

Fig. 1
figure 1

Regional geological map. (a) South China; (b) Southwest margin of Yangtze Block49; (c) Geological map of the Pb-Zn deposits in Northwestern Guizhou50; (d) Geological map of the Zhugongtang Pb-Zn deposit51.

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Geological setting

Regional geology

The SYG metallogenic province is a basement-sedimentary cover triangle located on the western edge of the Yangtze Block. It is bordered by the Xiaojiang Fault, the Kangding-Shuicheng Fault Zone, and the Mile-Shizong-Shuicheng Fault Zone, and is influenced by the Paleo-Tethys tectonic domain as well as the Circum-Pacific tectonic domains52,53,54 (Fig. 1a,b). The basement is folded and includes Archaean igneous rocks (~ 2.8 Ga), as evidenced by xenocrystic zircons, along with ~ 1.7 Ga Dongchuan and ~ 1.0 Ga Kunyang groups55. The cover sequence includes shallow marine sedimentary rocks from the Paleozoic and lower Mesozoic eras, as well as continental sedimentary rocks dating from the Jurassic to the Cenozoic periods56,57,58,59. The platform carbonate sequence is a significant component of the marine layers dating from the Late Ediacaran to the Triassic, characterized by abundant rock salt, gypsum, and organic material7,60,61.

The northwestern Guizhou metallogenic region is a significant component of the SYG metallogenic province. The NW-striking Yadu–Mangdong structure and the Weining–Shuicheng structure, and the NE-striking Yinchangpo–Yunluhe structure are the key lead-zinc ore-controlling structures in the area. The Pb–Zn deposits in NW Guizhou province can be categorized into distinct two types: the first type is influenced by the Carboniferous Baizuo and Shangsi formations, exemplified by the Tianqiao Pb–Zn deposit; the second type is governed by the Yadu–Mangdong fault, represented by the Zhugongtang Pb–Zn deposit62. The Pb–Zn deposits are typically associated with NW-trending thrust faults and folds63 (Fig. 1c). The Zhugongtang deposit is also structurally controlled by NW–SE faults (Fig. 1b,c).

Geology of the deposit

The lead-zinc deposits in northwestern Guizhou are primarily distributed along three structural belts: the NW-trending Yadu–Mangdong structural belt, the Weining–Shuicheng structural belt, and the NE-trending Yinchangpo–Yunluhe structural belt. The Zhugongtang lead-zinc deposit can be found to the northwest of the Yadu–Mangdong fault (Fig. 1c), approximately 15 km southwest of Hezhang County. The main ore-bearing strata of the Zhugongtang deposit are the Qixia formation and the Maokou formation16. The primary ore minerals consist of pyrite, sphalerite, and galena. The gangue minerals primarily consist of calcite, dolomite and rare quartz. The ore structures are characterized by massive, disseminated, veined, and banded structures. The principal ore textures are euhedral–partial euhedral granular, xenomorphic granular, metasomatic relict13. The Zhugongtang deposit, hosted by Devonian to Permian carbonate rocks, consists of significant ore bodies that can be divided into three types: layered, steeply dipping veins and lenticular16. The steeply dipping vein-like ore bodies develop along faults, the nearly bedded ore bodies are found in interlayer fracture zones, and the lenticular ore bodies are located in dissolution pores64. The Zhugongtang ores also contains trace amounts of metals, such as Ge, Se, Cd, Cu, and Ag, which are likely hosted by sphalerite and galena51. Gold paragenesis is clearly observable in certain ore bodies. In the Zhugongtang deposit, there are distinct boundaries between the ore bodies and the surrounding rock. The alteration of the host rock is relatively weak, and mainly of dolomitization, followed by discoloration (ferritization), calcification, pyritization, silicification and limonitization. The dolomitization that occurred during the sedimentary diagenetic phase resulted in the creation of numerous fractures, which allowed for mineralization to take place. The main indicator is that ore-bearing fluids migrate vertically along faults from deep to shallow levels and then horizontally from faults into fold zones (Fig. 2).

Fig. 2
figure 2

Structural ore-controlling model of lead-zinc deposits in the northwest Guizhou ore concentration area65. (1) Carboniferous system; (2) fault; (3) ore body; (4) deposit; (5) Feixianguan Formation; (6) Qixiamaokou Formation; (7) the Maximum tensile stress; (8) Emeishan basalt Formation; (9) Liangshan Formation; (10) deep fluid;11-basin fluid; (①) Yadu Shaojiwan deposit; (②) Zhugongtang deposit; (③) Tianqiao deposit; (④) Liangyan deposit; (⑤) Caoziping deposit; (⑥) Maomaochang deposit; (⑦) Changpingzi deposit; (⑧) Shanshulin deposit; (⑨) Qinshan deposit.

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Set up model

Mathematical model

Combines heat transfer, pressure, fluid-flow and material migration to describe the mineralization process of the Zhugongtang deposit. These factors influence each other and combine in various ways throughout the mineralization process. The governing equations that determine their behavior are given below, accompanied by detailed explanations of the variables.

The workflow of numerical modeling of the mineralization for the Zhugongtang lead-zinc deposit used in this study is shown in Fig. 3.

Fig. 3
figure 3

Workflow used in the numerical modeling of the mineralization for the Zhugongtang lead-zinc deposit.

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Geothermal/lithostatic gradient

The equations below are used to calculate geothermal and lithostatic pressure gradients41:

$$\:\begin{array}{c}T={T}_{0}-y{G}_{T}\end{array}$$
(1)
$$\:\begin{array}{c}P={P}_{0}-y{G}_{P}\end{array}$$
(2)

The model temperature’s initial value is denoted as \(\:T\) in °C, while \(\:{T}_{0}\) refers to the ambient temperature (typically 20 °C, 1 atmosphere, \(\:0.1013\:MPa\)). The depth is represented by \(\:y\) in meters, and \(\:{G}_{T}\) denotes the temperature gradient within the geological unit in the model66,67, which is set at 25 °C/km. The pressure is denoted as \(\:P\) in \(\:MPa\), and \(\:{P}_{0}\) corresponds to the atmospheric pressure. \(\:{G}_{P}\) represents the pressure gradient within the geological units in the model, which reflects the average density of these units and is set at \(\:6.5\:MPa/km\)68,69.

Heat transfer in porous media

CFD packages define a set of default equations to describe heat exchange and energy conservation. The equations used in our model are as follows70:

$$\:\begin{array}{c}{d}_{z}{\left(\rho\:{C}_{p}\right)}_{eff}\frac{\partial\:T}{\partial\:t}+{d}_{z}\rho\:{C}_{p}u\cdot\:\nabla\:T+\nabla\:\cdot\:q={d}_{z}Q+{q}_{0}+{d}_{z}{Q}_{vd}\end{array}$$
(3)
$$\:\begin{array}{c}q=-{d}_{z}{k}_{eff}\nabla\:T\end{array}$$
(4)
$$\:\begin{array}{c}{\left(\rho\:{C}_{p}\right)}_{eff}={{\uptheta\:}}_{p}{\rho\:}_{p}{C}_{p.\text{p}}+\left(1-{{\uptheta\:}}_{p}\right)\rho\:{C}_{p}\end{array}$$
(5)
$$\:\begin{array}{c}{k}_{eff}={\theta\:}_{p}{C}_{pr}+\left(1-{\theta\:}_{p}\right){C}_{m}+{k}_{disp}\end{array}$$
(6)
$$\:\begin{array}{c}{\theta\:}_{p}=1-\theta\:\end{array}$$
(7)

\(\:{d}_{z}\), which is the section thickness set at 1000 m; \(\:\rho\:\), the fluid density; \(\:{C}_{p}\), the heat capacity of the fluid and chemical reactant mixture; \(\:T\), the temperature; \(\:t\), the time; \(\:\varvec{u}\), the fluid flow velocity; \(\:\varvec{q}\), the heat dissipation; \(\:{q}_{0}\), the generalized inward heat flux; \(\:Q\), the heat of reaction; \(\:{Q}_{vd}\), the heat transferred from the surrounding environment; \(\:\rho\:\), the density of porous rock; \(\:{\theta\:}_{p}\), the volume fraction of porous rock; \(\:{C}_{p.\text{p}}\), the specific heat capacity; \(\:{k}_{eff}\), the effective thermal conductivity; \(\:{C}_{pr}\), the thermal conductivity of the porous rock; \(\:{C}_{m}\), the thermal conductivity of the fluid and chemical reactant mixture; \(\:{k}_{disp}\), the coefficient of initial heat dissipation to the surrounding environment; and \(\:\theta\:\), the porosity.

Fluid flow driven by rock-static pressure gradient

In this model, the movement of fluid is regulated by Darcy’s law44,71,72, and the equations for transient analyses are as follows:

$$\:\begin{array}{c}u=-\frac{k}{\mu\:}\nabla\:p+g\rho\:\end{array}$$
(8)
$$\:\begin{array}{c}\frac{\partial\:}{\partial\:t}\left(\epsilon\:\rho\:\right)+\nabla\:\left(\rho\:\varvec{u}\right)={Q}_{m}\:\end{array}$$
(9)

The equation defines the vector velocity of the fluid flow as \(\:\varvec{u}\), with permeability \(\:k\) and dynamic viscosity \(\:\mu\:\), in a porous medium with porosity \(\:\varepsilon\:\). The fluid source term is denoted as \(\:{Q}_{m}\) and represents the total flow of fluids into or through the model71. Time is represented as \(\:t\), while the pressure gradient is \(\:\nabla\:p\) and the body force is the combination of gravity and the density of the fluid in the porous rock, represented as \(\:\mathbf{g}\rho\:\), where \(\:\mathbf{g}\) is the gravity vector and \(\:\rho\:\) is the density of the liquid in question.

Diffusion of Zn2+ in porous media

In the context of mass transport involving dissolved species (solute species), diffusion occurs due to concentration gradients44. This relationship is represented in the fluid flow equation for porous rock as follows:

$$\:\begin{array}{c}{\varvec{N}}_{\varvec{i}}=-{D}_{i}\nabla\:{c}_{i}+u\cdot \:{c}_{i}\end{array}$$
(10)

The concentration of species \(\:i\) in the liquid, denoted as \(\:{c}_{i}\) (SI unit: mol/m3), is influenced by the diffusion coefficient of element \(\:i\) in the fluid, represented as \(\:{D}_{i}\). At 25 °C, the diffusion coefficient of zinc ions in dilute solution is approximately 1.2 × 10− 7cm2/s73 is directly related to the fluid flow velocity, \(\:\varvec{u}\), and the quantity of element \(\:i\:\)involved in the diffusion process, \(\:{\varvec{N}}_{\varvec{i}}\)74. In this context, element \(\:i\) pertains specifically to Zn2+.

Simplified modeling and software used

Simplified modeling

According to the geological concepts and models for the Zhugongtang regions (Fig. 4), a two-dimensional geometric model was constructed. The Zhugongtang model measures 3200 m in length and 2200 m in width and set two points on the anticline to monitor the variation of Zn2+ concentration (Fig. 5). Due to the complexity of the entire ore-forming process, we decided to simplify the calculations. In order to follow the principles of numerical simulation and simplify the calculation, we ignored non-critical morphological features and changes when building the model (The petrophysical property parameters are in Table 1). In order to gain a deeper understanding of the mineralization mechanism, the model system was further expanded. While keeping the faults unchanged, two groups of models, steep folds and gentle folds, were added to analyze the impact of different structural types on the migration of ore-bearing fluids and reveal the intrinsic connection between different interlimb angle structure and mineralization.

Fig. 4
figure 4

Diagrams showing the brief characteristics and the location of orebodies of Zhugongtang lead-zinc deposit65.

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Fig. 5
figure 5

(a) Simplified model and (b) CFD mesh model of the Zhugongtang deposit.

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Table 1 Material parameters used in our simulation model, adapted from Guizhou provincial bureau of geology and mineral resources 113th geological brigade (2018)75.
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According to the geological information from the Zhugongtang lead-zinc deposit, we constructed a comprehensive simulation model. Firstly, previous studies on the temperature measurement of inclusions in the Zhugongtang lead-zinc deposit have indicated a mineralization temperature range of 105∼210 °C16. Therefore, within the mine-fault, we set the fluid temperature at 250 °C, slightly higher than 210 °C, to simulate the hydrothermal migration process. We set the Zn2+ injection concentration at 0.1 mol/m3, while in other geological units, the Zn2+ concentration was set at 0 mol/m3 to monitor the migration of Zn2+.

Previous studies have shown that the formation of sphalerite and galena lasted for about 10,000 years40,44. Therefore, we chose a calculation time of 10,000 years and set a time step of 30 years to obtain transient results. This comprehensive model aids in better understanding the mineralization processes and hydrothermal migration characteristics of the Zhugongtang lead-zinc deposits.

Software

Magmatic hydrothermal mineralization is a complex process, which is usually described by a multi-physical coupled model71,76. The actual geological model is relatively complex. In order to meet the calculation requirements of the complex geological model, we choose the finite element method (FEM) to meet the required complex calculations. FEM can use different complex elements to model geometrically complex solution domains77. It can be said that FEM is one of the numerical simulation methods widely used in the engineering field78. COMSOL Multiphysics stands out as a comprehensive and advanced numerical simulation software based on the finite element method79. Its main advantage is that it can flexibly couple multiple physical fields, using advanced numerical solution algorithms and parallel computing capabilities to ensure the accuracy and efficiency of multi-field coupling analysis capabilities and high-performance numerical simulation calculations80. The COMSOL Multiphysics software has been widely application in previous studies. Kalavagunta and Weller81 Calculate the geometry factor for laboratory-scale sensitivity experiments. Braun et al.82 Model the propagation of electromagnetic waves in conductive media. Park et al.83 Model controlled source electromagnetics. Zhao et al.72 provided an overview of coupled modeling of mineralization and geochemical systems. Fan et al.43 conducted ore-forming factors of the Gejiu ore deposit was simulated. In conclusion, the COMSOL simulation results are accurate and effective.

Results

Temperature distribution

Temperature is one of the key controlling factors for mineralization distribution in hydrothermal systems44,84,85, which means the distribution of temperature can reflect the distributions of mineralization in a mineral deposit86. The temperature distribution within the fault-fold zone of the Zhugongtang deposit ranges from 110 °C to 220 °C, which aligns closely with previous fluid inclusion thermometry results16. Upper and lower fracture surfaces near the fault zone, Due to the rapid heat dissipation, resulting in lower temperatures. Conversely, the temperature of the fault zone itself is higher. Thermal dissipation across layers occurs more swiftly, resulting in lower temperatures (Fig. 6).

Fig. 6
figure 6

The graph showing the temperature distribution over time focuses on the temperature range of 110 °C to 220 °C, reflecting the formation temperature of Zn2+ mineralization in the Zhugongtang deposit.

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Pressure distribution, pressure anomaly, Darcy velocity field

In the core region of the Zhugongtang fold-thrust belt and the flank of the anticline close to the fault, the pressure is relatively higher compared to other region at the same elevation. This negative pressure anomaly may induce rock fracturing, thereby providing secondary fracture-type reservoir space for the mineralization process lead–zinc deposit’s (Fig. 7).

Fig. 7
figure 7

Diagrams showing (a) variations in the distribution of pressure p and (b) pressure anomaly p’ (p’ = p − PG).

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Fluid velocity and distribution

In the Zhugongtang fold-thrust belt, fluids in the deep base of the fault zones migrate rapidly along the fault zones (Fig. 8). Upon reaching the interlayer fault zones, its velocity decreases. When encountering formation fluids, they experience resistance and subsequently migrate toward in the opposite direction, fluid from two opposite directions mix on the SE flank of the anticline. The site where fluid intersect and mixing occurs represents a favorable location for ore mineralization.

Fig. 8
figure 8

Diagrams showing variations in the distribution of fluid velocity and the directions of fluids.

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Zn2+ concentration changes with time

Fluid migration is an ideal force and carrier for transporting metals. Over a 330-year period, Zn2+ exhibited upward migration along the fault, eventually reaching the northwest flank of the Zhugongtang anticline. However, beyond the 500-year timeframe, Zn2+, controlled by the fluid flow, ceased its movement towards the northwest flank (Figs. 9 and 10). In the initial stage, Zn2+ primarily enriched within the fault zone. With the continuous injection of fluids, Zn2+ concentration diffuses into the interlayer fractured zones within the fold-thrust. Along the fault or interlayer zones, the concentration is relatively high, while across the layers they tend to be lower.

Fig. 9
figure 9

Diagrams showing variations in the distribution of the concentration of Zn2+ over time.

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Fig. 10
figure 10

Changes of concentrations of Zn2+ in P1 against time.

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For comparison, we used the control variable method to set up the styles of steep and gentle anticlines while keeping the fault unchanged. The differences in Zn2+ distribution changes were analyzed under the same parameters. It can be seen that there is no difference in concentration within the fault zone. In the gentle anticline, the concentration migrates more and the concentration diffuses faster (Fig. 11). This is because the rock layer is relatively flat, providing a longer and long-distance migration channel for fluid flow, allowing the fluid to migrate over a long distance. In the steep anticline, the concentration migrates less and the concentration diffuses more slowly (Fig. 12). This is because the anticline is steeper, and the fluid flow needs to overcome greater gravity resistance, which greatly limits the range of flow migration and makes the fluid migration path shorter. It is consistent with expectations.

Fig. 11
figure 11

Diagrams showing variations in the distribution of the concentration of Zn2+ over time (gentle anticline).

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Fig. 12
figure 12

Diagrams showing variations in the distribution of the concentration of Zn2+ over time (steep anticline).

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Discussion

Implications for exploration

Our simulation results provide valuable insights into the mineralization mechanisms of the Zhugongtang area, particularly regarding mineralization temperature, stress anomalies, and fluid dynamics. The distribution of ore bodies in the Zhugongtang lead-zinc deposit is controlled by heat conduction, fluid flow, and lithostatic pressure. These factors interact to govern ore deposition at the intersection of fault folds. The temperature range determined by the simulation is 110 and 220 °C, similar to previous research87. Temperature variations are evident near the upper and lower fault planes of the fault zone, where rapid heat dissipation results in lower temperatures, while temperatures are higher within the fault zone. When fluids enter the fold slip space, the temperature increases along the bedding, while heat dissipation is more rapid as they pass through the bedding. Higher temperatures enhance the migration of ore-bearing fluids, promote material exchange, and facilitate mineral deposition, while lower temperatures hinder ore body formation. The simulation also reveals stress anomalies in the Zhugongtang area. These stress anomalies are often associated with interlayer fractures88. Negative stress anomalies in the core and southeast flank of the fold-thrust belt fracture the rock, creating low-stress zones favorable for mineralization and, consequently, reservoirs conducive to lead-zinc mineralization89,90. The simulation of the Darcy velocity field further reveals how different fluid dynamic conditions influence the migration and deposition of ore-bearing fluids. Fluid migration and distribution play a crucial role in the migration, deposition, and accumulation of ore-forming elements. In the Zhugongtang fold-thrust belt, fluids at the deep bottom of the fault zone migrate rapidly along the fault zone, and the flow rate slows down after reaching the interlayer fault zone or expansion space. Locations where fluids meet and mixing occur represent favorable locations for mineralization of deposits91.

By analyzing the two models of steep anticline and gentle anticline, it was found that the migration of fluids in the fault zone is mainly controlled by the properties of the fault. In the gentle anticline (larger interlimb angle), relatively flat rock formations provide long, continuous migration pathways. The larger interlimb angle results in a smaller dip, which reduces horizontal flow resistance and facilitates fluid diffusion into the strata. This allows the fluid to diffuse more widely and interact with the parent rock, forming stratum-bound mineralization. This allows the ore-bearing fluid to diffuse further along stratum interfaces or fault zones. In the transition zone from gentle to steep anticlines, fluid migration distances are moderate. These areas lack the long-distance migration pathways of gentle anticlines, nor the strong gravity constraints of steep anticlines. On the contrary, in the steep anticline area (smaller interlimb angle), a smaller interlimb angle will lead to a larger wing inclination angle. Since the effective permeability perpendicular to the bedding is reduced, the tortuosity and hydraulic resistance of the folded strata are increased, which forces the ore-bearing fluid to migrate vertically along the high-permeability faults, greatly restricting the migration of the fluid, resulting in a shorter diffusion distance and slower migration speed. Therefore, the anticline contains ore bodies but fewer ore bodies92. This finding is consistent with the field observations of the Maomaochang deposit and Liangyan lead-zinc deposit in northwestern Guizhou65,93, we deduced that during the ore prospecting process in northwest Guizhou, the degree of opening of the derived folds in the hanging wall of the ore-controlling fault may have certain indicative significance for ore prospecting.

Limitations

Although our study has made important progress in understanding the mineralization mechanisms of the Zhugongtang area, several limitations remain. The finite element method simplifies geological models, omitting unmeasurable characteristics such as multiphase fluid dynamics and the detailed deformation effects during mineralization, leading to certain discrepancies between simulation results and geological conditions. Additionally, pre-mineralization phenomena can only be reconstructed through speculation, introducing uncertainties in boundary conditions. The quasi-three-dimensional (two-dimensional profile) model used in this study simplifies the migration processes of matter and heat in the three-dimensional geological environment to some extent, but still reflects its main characteristics relatively well. Since the model profile cannot fully represent the lateral dissipation of pressure, the two-dimensional approximation may slightly enhance the pressure gradient in localized areas. Compared to a real three-dimensional system, this may lead to relatively stronger positive and negative pressure anomalies at fault-fold intersections, because under three-dimensional conditions, some stress can be released along the third dimension. Similarly, due to the lack of out-of-plane flow, the lateral diffusion of temperature and solute concentration is somewhat limited, making the mixing front appear more localized. To ensure modeling stability, we also ignored deformation during the apparent evolution stage of the Zhugongtang lead-zinc deposit, which limits our understanding of its role in mineralization. Furthermore, this study focuses on the migration path and spatiotemporal distribution of ore-bearing fluids without considering chemical reactions involved in mineral precipitation. Addressing these limitations in future research—through improved simulation models, consideration of multiphase fluids, and integration of three-dimensional effects—will enhance the practical significance of numerical simulations in geological research. Despite these challenges, our study provides valuable insights into the mineralization mechanisms of the Zhugongtang area, particularly in terms of temperature, stress, and fluid dynamics, offering important guidance for future exploration efforts and advancing the use of numerical simulations in geological studies.

Conclusions

There is an obvious negative stress anomaly at the intersection of fault folds, which may induce rock mass fragmentation and form secondary interlayer sliding faults and tension spaces in the fold core, which is conducive to the accumulation and precipitation of ore-bearing fluids.

(1) Significant negative stress anomalies exist at the intersection of fault folds. This anomaly may have induced rock mass fragmentation, forming secondary interlaminar slip faults and tensional spaces within the fold core, favoring the accumulation and precipitation of ore-bearing fluids.

(2) Simulations indicate that smaller interlimb angles favor fault-hosted Zn2+ mineralization, while larger interlimb angles favor strata-bound ore bodies. This pattern is also observed in deposits such as the Maomaochang and Liangyan deposits in northwestern Guizhou.

These insights help analyze the mineralization positioning of ore deposits in northwestern Guizhou, which is controlled by fault structures, and offering valuable knowledge for future studies in economic geology and mineral exploration.