Deep exploration evaluation method based on multi-parameter geology and thermal history simulation

Abstract

The invention relates to the technical field of geological exploration, and discloses a deep exploration evaluation method based on multi-parameter geology and thermal history simulation. Mineralized quartz and granite samples in a target area are collected, the samples are sent into a laboratory to be processed, including cleaning, cutting and grinding, the collected samples are analyzed, and the analysis result is obtained. The method specifically comprises the following steps: analyzing the metallogenic depth of an inclusion, analyzing the invasion depth of a rock mass, analyzing the invasion age of a sample, and obtaining the cooling age of the sample by combining fission tracks of zircon and apatite. The method is used for analyzing a collected sample, and specifically comprises the following steps: analyzing the metallogenic depth of an inclusion, analyzing the invasion depth of a rock mass, analyzing the invasion age of the sample, obtaining the cooling age of the sample by combining fission tracks of zircon and apatite, and carrying out comprehensive calculation based on the denudation thickness, the invasion depth and the formation depth of an ore body. Therefore, the storage condition of the ore body is finally obtained, deep mineralization favorable information is obtained, and deep mineral product prediction is realized.

Description

Technical Field

[0001] The present invention relates to the field of geological exploration technology, and in particular to a deep exploration evaluation method based on multi-parameter geological and thermal history simulation. Background Art

[0002] Mineral resources are an important material basis for human survival and development. The safe supply of mineral resources depends to a large extent on the development level of mineral exploration technology. With the continuous strengthening of mineral exploration and development, surface mines, shallow mines, and easily identifiable mines are decreasing. Mineral exploration work is shifting towards finding hidden mines, deep mines, and difficult-to-identify mines, and the difficulty of prospecting is increasing. With the increase in prospecting depth and the reduction in exploration projects, the available favorable information on deep mineralization is becoming less and less. How to use limited exploration data to carry out prediction and evaluation of deep minerals is a technical difficulty that we currently need to solve. Summary of the invention

[0003] 1. Technical issues to be resolved

[0004] In view of the deficiencies of the prior art, the present invention provides a deep exploration and evaluation method based on multi-parameter geological and thermal history simulation, which has the advantages of deep mineral prediction and solves the above-mentioned technical problems.

[0005] (II) Technical solution

[0006] To achieve the above object, the present invention provides the following technical solution: a deep exploration evaluation method based on multi-parameter geological and thermal history simulation, comprising the following steps:

[0007] S1: Collect mineralized quartz and granite samples from the target area and send them to the laboratory for processing, including cleaning, cutting and grinding;

[0008] S2: Analyze the collected samples, including: mineralization depth analysis of inclusions, emplacement depth analysis of rock mass, emplacement age analysis of samples, and obtaining cooling age of samples by combining fission tracks of zircon and apatite;

[0009] S3: Conduct thermal history simulation reconstruction, combine geothermal gradients at different periods, and calculate the ore body erosion thickness;

[0010] S4: Conduct deep ore body prediction, including combining emplacement depth and denudation thickness data to assess the preservation status of the ore body.

[0011] As a preferred technical solution of the present invention, the steps of processing in combination with the fission tracks of zircon and apatite in step S2 are as follows:

[0012] S2.1: The collected samples are crushed and preliminarily screened by magnetic separation and gravity separation;

[0013] S2.2: Select apatite and zircon single mineral grains for fission track analysis under a microscope;

[0014] S2.3: Apatite and zircon single mineral particles are made into targets using epoxy resin and polytetrafluoroethylene oxide resin respectively, and then flattened and polished to expose the inner surface of the mineral particles;

[0015] S2.4: The zircon sample was continuously etched in a NaOH-KOH mixed solution at a temperature of 220°C for 25 hours, and the apatite sample was continuously etched in a 5.0% HNO3 solution at a temperature of 25°C for 30 seconds, and the samples were irradiated in a thermal neutron nuclear reactor;

[0016] S2.5: After irradiation, the muscovite mica used as an external detector was placed in a 40% HF acid solution at a temperature of 25°C and etched continuously for 20 minutes to reveal the fission tracks induced in the muscovite. A 1000x microscope was used to measure the density of induced and spontaneous fission tracks and the density of induced tracks in the standard monitoring glass, as well as the length information of the fission tracks in the apatite sample.

[0017] As a preferred technical solution of the present invention, the specific expression of the inclusion mineralization depth analysis recorded in step S2 is as follows:

[0018]

[0019] Where D represents the mineralization depth, ρ represents the average density of the rock, and P final represents the pressure inferred from the homogenization temperature of the fluid inclusion, P initial represents the surface pressure, h0 represents the surface datum, and g represents the gravitational acceleration.

[0020] As a preferred technical solution of the present invention, the pressure P calculated from the homogenous temperature of the fluid inclusion is final The specific expression is as follows:

[0021] P final =A+B·T h +C.S

[0022] Among them, P final represents the pressure calculated from the homogenization temperature of the fluid inclusion. A, B, and C are all empirical coefficients. T h It represents the uniform temperature obtained through the hot and cold stage experiment, represents the phase change temperature of the fluid under high temperature state, and S represents the salinity calculated from the freezing point.

[0023] As a preferred technical solution of the present invention, the emplacement age analysis of the sample is performed using RadialPlotter software.

[0024] As a preferred technical solution of the present invention, the specific expression of the rock mass emplacement depth analysis in step S2 is as follows:

[0025]

[0026] Among them, D i Indicates the penetration depth, P inv It represents the equilibrium pressure after the rock mass is intruded, and P represents the average geopressure gradient.

[0027] As a preferred technical solution of the present invention, the simulation software used for the thermal history reconstruction is HeFTy.

[0028] As a preferred technical solution of the present invention, the calculation expression of the ore body erosion thickness in step S3 is as follows:

[0029]

[0030] Where E represents the ore body denudation thickness, represents the cooling rate in the jth stage, T j represents the geothermal gradient of the jth stage, t j Represents the duration of the jth stage.

[0031] As a preferred technical solution of the present invention, the specific expression of the preservation condition of the ore body is as follows:

[0032] S=DE

[0033] Among them, S represents the preservation condition of the ore body, D represents the formation depth of the ore body, and E represents the erosion thickness of the ore body.

[0034] As a preferred technical solution of the present invention, the step S4 also includes, after determining the preservation status of the ore body, conducting deep drilling to expose the deep ore body.

[0035] Compared with the prior art, the present invention provides a deep exploration evaluation method based on multi-parameter geological and thermal history simulation, which has the following beneficial effects:

[0036] The present invention collects mineralized quartz and granite samples in the target area, and sends the samples to the laboratory for processing, including cleaning, cutting and grinding, and analyzes the collected samples, specifically including: inclusion mineralization depth analysis, rock mass emplacement depth analysis, sample emplacement age analysis, and combining zircon and apatite fission track to obtain the sample cooling age, thereby finally obtaining the preservation status of the ore body, obtaining favorable information on deep mineralization, and realizing the prediction of deep mineral resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 It is a schematic diagram of the process of the present invention;

[0038] Figure 2 This is a schematic diagram of the zircon fission track radar diagram of the present invention;

[0039] Figure 3 This is a schematic diagram of the age decomposition of samples with zircon fission track age P(χ2) detection value <5% according to the present invention;

[0040] Figure 4 This is a schematic diagram of the apatite fission track radar of the present invention;

[0041] Figure 5 It is a schematic diagram of thermal history simulation based on apatite fission track data of the present invention;

[0042] Figure 6 Schematic diagram of the relationship between the sample depth and the apatite fission track record age of the present invention. DETAILED DESCRIPTION

[0043] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0044] See also Figure 1-5 , a deep exploration evaluation method based on multi-parameter geological and thermal history simulation includes the following steps:

[0045] S1: Collect mineralized quartz and granite samples from the target area and send them to the laboratory for processing, including cleaning, cutting and grinding;

[0046] S2: Analyze the collected samples, including: mineralization depth analysis of inclusions, emplacement depth analysis of rock mass, emplacement age analysis of samples, and obtaining cooling age of samples in combination with fission tracks of zircon and apatite. The steps of processing in combination with fission tracks of zircon and apatite in step S2 are as follows:

[0047] S2.1: The collected samples are crushed and preliminarily screened by magnetic separation and gravity separation;

[0048] S2.2: Select apatite and zircon single mineral grains for fission track analysis under a microscope;

[0049] S2.3: Apatite and zircon single mineral particles are made into targets using epoxy resin and polytetrafluoroethylene oxide resin respectively, and then flattened and polished to expose the inner surface of the mineral particles;

[0050] S2.4: The zircon sample was continuously etched in a NaOH-KOH mixed solution at a temperature of 220°C for 25 hours, and the apatite sample was continuously etched in a 5.0% HNO3 solution at a temperature of 25°C for 30 seconds, and the samples were irradiated in a thermal neutron nuclear reactor;

[0051] S2.5: After irradiation, the muscovite used as the external detector was placed in a 40% HF acid solution at a temperature of 25°C for continuous etching for 20 minutes to reveal the fission tracks induced in the muscovite. A 1000x microscope was used to measure the density of induced and spontaneous fission tracks and the density of induced tracks in the standard monitoring glass, as well as the length information of the fission tracks in the apatite sample. The specific expression of the inclusion mineralization depth analysis recorded in step S2 is as follows:

[0052]

[0053] Where D represents the mineralization depth, ρ represents the average density of the rock, and P final represents the pressure inferred from the homogenization temperature of the fluid inclusion, P initial represents the surface pressure, g represents the gravitational acceleration, and the pressure P is calculated from the homogenization temperature of the fluid inclusion. final The specific expression is as follows:

[0054] P final =A+B·T h +C.S

[0055] Among them, P final represents the pressure calculated from the homogenization temperature of the fluid inclusion. A, B, and C are all empirical coefficients. T h The homogenization temperature is obtained through the hot and cold stage experiment, which indicates the phase transition temperature of the fluid under high temperature. S indicates the salinity calculated from the freezing point. The emplacement age analysis of the sample is analyzed using RadialPlotter software. The specific expression of the rock emplacement depth analysis in step S2 is as follows:

[0056]

[0057] Among them, D i Indicates the penetration depth, P inv represents the equilibrium pressure after the rock mass is emplaced, and P represents the average geopressure gradient;

[0058] S3: thermal history reconstruction and erosion thickness calculation. The simulation software used for thermal history reconstruction is HeFTy, and the annealing model used is Ketchametal. The calculation expression of ore body erosion thickness in step S3 is as follows:

[0059]

[0060] Where E represents the ore body denudation thickness, represents the cooling rate in the jth stage, T j represents the geothermal gradient of the jth stage, t j represents the duration of the jth stage;

[0061] S4: Predict deep ore bodies, including evaluating the preservation status of the ore bodies by combining the emplacement depth and erosion thickness data. The specific expression of the preservation status of the ore bodies is as follows:

[0062] S=DE

[0063] Among them, S represents the preservation condition of the ore body, D represents the formation depth of the ore body, and E represents the erosion thickness of the ore body. Step S4 also includes establishing a three-dimensional post-section characteristic map after determining the preservation condition of the ore body, delineating the mineralization site, and drilling deep holes to expose the deep ore body.

[0064] This time, samples from four boreholes at different depths, namely ZK740, ZK744, ZK781 and ZK712, in the 320th exploration line of Shaling Gold Mine were selected as research objects. Six samples were selected for apatite sample fission track experiment, and three samples were selected for zircon sample fission track experiment (Table 1).

[0065] Table 1 Fission track experiment sample information

[0066]

[0067]

[0068] Note: ZFT is zircon fission track, AFT is apatite fission track.

[0069] The rock samples collected in the field were crushed to a size that was compatible with the particle size of apatite and zircon mineral particles in the rock. Then, they were roughly selected using conventional magnetic separation and gravity separation, and then single apatite and zircon mineral particles for fission track analysis were selected under a microscope. The fission track dating of the selected zircon and apatite was completed by Yuan Wanming's team at China University of Geosciences (Beijing), and the sample testing was completed at the Institute of High Energy Physics, Chinese Academy of Sciences using the external detector method. Single apatite and zircon mineral particles were made into targets using epoxy resin and polytetrafluoroethylene resin, respectively, and then flattened and polished to expose the inner surface of the mineral particles. Then, the zircon sample was continuously etched in a NaOH-KOH mixed solution at a temperature of 220°C for 25 hours, and the apatite sample was continuously etched in a 5.0% HNO3 solution at a temperature of 25°C for 30 seconds. The samples were then irradiated in the 492 thermal neutron nuclear reactor of the China Institute of Atomic Energy. The cadmium-gold ratio of the 492 thermal neutron nuclear reactor was greater than 100, indicating sufficient thermalization.

[0070] During the sample measurement, the neutron flux was calibrated by using CN2 (zircon) and CN5 (apatite) uranium standard glasses (Yuan et al., 2009). After irradiation, the muscovite used as the external detector was placed in a 40% HF acid solution at 25°C for 20 minutes of continuous etching to reveal the fission tracks induced in the muscovite. Finally, a 1000x microscope was used to measure the density of induced and spontaneous fission tracks and the density of induced tracks in the standard monitoring glass (i.e., standard track density), as well as the length information of the fission tracks in the apatite sample.

[0071] Usually more than 20 grains are selected for each sample to determine the age of the sample. The median age is calculated using the Zeta calibration method (Green, 1981). The Zeta values ​​of the CN2 and CN5 uranium standard glasses are 88.2±2.9 and 391±17.8, respectively. The 1σ error is obtained by using the RadialPlotter software (Vermeesch, 2009). The chi-square test value P (χ 2 ) is used to determine whether the single-grain fission track ages studied belong to the same group Galbraith (1981). Usually P(χ 2 ) greater than 5% of all single grain ages of the sample are considered to belong to the same group.

[0072] The zircon fission track age of the sample reflects the historical time when the sample temperature cooled through the temperature range closed by the zircon fission track (240±50℃). The consistency of the apatite fission track length and the practical feasibility of the measurement together with the apatite fission track age record the low-temperature thermal history information experienced by the sample and are often used for thermal history simulation. In order to ensure the quality of the simulation results, this study only used software to simulate the thermal history of apatite samples with a confining track number of not less than 90 obtained in the test. The thermal history simulation software used is HeFTy (Ketcham, 2012), and the annealing model used is Ketchametal. (2007);

[0073] The median ages of the three zircon fission track ages range from 144.2±6.3Ma to 124.4±5.5Ma (Table 2). 2 ) was 53.3%, and the P(χ 2 ) is less than 5%, low P(χ 2) detection value (<5%) is generally considered to contain at least two age components (O'Sullivan and Parrish, 1995; Brandon, 2002), or the zircon grains are damaged by radiation. There is no systematic relationship between the zircon single grain age value and the U content in this experiment. The U content of all zircons is low, ranging from 339ppm to 34ppm. In addition, the Linglong granite is relatively young (160Ma to 150Ma), and the zircon should be slightly damaged by radiation. Therefore, it can be ruled out that the radiation damage of zircon grains caused the low P (χ 2 ).

[0074] Binomfit software (Brandon, 1992, 1996) was used to decompose the ages. The zircon fission track age of ZK740-1 was divided into two groups of fitting ages: 152.9 (-15.6 / +17.3) Ma and 120.0 (-11.3 / +12.5) Ma. The zircon fission track age of ZK712-3 was divided into two groups of fitting ages: 157.8 (-9.3 / +9.8) Ma and 122.4 (-11.8 / +13.0) Ma. Figure 3 ). Since these two samples are both Linglong period potassic granites at the foot of the main fracture surface, and the lithology is relatively simple, the ages formed by the mixing of zircons of different lithologies can be excluded. After the Linglong granite was emplaced, it may have quickly reached equilibrium with the surrounding rock temperature near the contact zone, and dropped to the closed interval of zircon fission tracks at 157.8-152.9 Ma, and the age was recorded for the first time. After about 120 Ma (Zhang et al., 2020), the Linglong granite far away from the main fracture surface underwent weak potassic alteration. During this process, some zircons in the original rock were modified, thereby resetting the age of the zircon fission track. Later, due to the drop in temperature, it passed through the closed interval of zircon fission tracks again at 122.4-120.0 Ma, and the age was recorded for the second time. The mixing of the above two groups of ages led to the low P (χ 2 ) detection value.

[0075] ZK712-1 near the main fracture surface is a sericite granite, which is highly affected by the mineralization hydrothermal fluid. The age recorded by the zircon fission track has been completely reset, and its recorded age is basically consistent with the age of the second record of the above two samples. Previous studies on the homogenization temperature of fluid inclusions in the gold mineralization period in Jiaodong area showed that the gold mineralization temperature is generally 170-350℃ (Xu Jiuhua et al., 1997; Fan Hongrui et al., 2005; Zhang Zuqing et al., 2007; Wang et al., 2015), which is close to the closure temperature of zircon fission track (240±50℃; Zaun and Wager, 1985; Hurford, 1986; Bernet, 2009). Therefore, it can be considered that the zircon fission track represents the gold mineralization age in Jiaodong area to a certain extent.

[0076] Table 2 Zircon fission track analysis results

[0077]

[0078] like Figure 2-3 The position value of the intersection of the straight line through the origin and a certain grain point and the arc on the right is the zircon fission track age of the single grain; σ / t and t / σ on the left side of the horizontal axis represent the relative error and accuracy of the grain point respectively; the color of the single grain point corresponds to the value in the scale below represents the U content in the zircon grain.

[0079] The track ages obtained from the six apatite fission track dating experiments range from 16.2±1.0Ma to 28.1±2.6Ma (Table 3, except for the P(χ 2 ) is 0, and the P(χ 2 ) test results were all greater than 5%, ranging from 17.1% to 100%, and passed the P(χ 2 ) detection.

[0080] The length of apatite fission track of 6 samples ranges from 11.4±2.3μm to 12.4±2.0μm (Table 3), and the standard deviation ranges from 2.0μm to 2.6μm. The sample track lengths are mostly unimodal with a slightly negative skew feature, indicating that the samples pass through the partial annealing zone of apatite fission track monotonically and slowly. The position value of the intersection of the straight line through the origin and a certain particle point and the arc on the right is the apatite fission track age of the single particle; σ / t and t / σ on the left side of the horizontal axis represent the relative error and precision of the particle point respectively; the color of the single particle point corresponds to the value in the scale below represents the Dpar value in the apatite particle;

[0081] Table 3 Apatite fission track analysis results

[0082]

[0083]

[0084] The number of apatite fission track measurements for the six samples was 99 to 107, and the thermal history simulation results were highly reliable. According to the temperatures at different depths obtained from the 3000m borehole geophysical logging well in the northern section of Zhaoping, Jiaodong, the temperature range of apatite fission track was 125°C to 60°C for simulation. In the simulation, the standard for sufficiently good thermal history curves was set at 100, and the simulation process was automatically terminated until this standard was reached. Usually, while 100 sufficiently good thermal history inversion curves were generated, at least thousands of acceptable thermal history curves were generated, providing reliable support for the thermal history inversion simulation results.

[0085] The GOF values ​​of the simulated ages of the six samples are all greater than 94%, indicating that the age values ​​are reliable; however, the GOF values ​​of the fission track length are relatively poor. From the thermal history simulation results of the four samples with GOF values ​​of fission track length greater than 50% ( Figure 5 ) It can be seen that the simulation curves have gradually entered the partial annealing zone since 30Ma, which is consistent with the age of 27.5±2.0Ma to 15.9±1.5Ma recorded by apatite fission track. The pink and light green areas in the figure represent good and acceptable simulation results, respectively, and the black solid line is the best thermal history simulation curve.

[0086] The simulation curves of the four samples are quite similar. According to the thermal history simulation curves, the thermal history can be roughly divided into two stages: one is the relatively rapid cooling from 25 to 10 Ma, and the other is the rapid cooling from 10 to 10 Ma. The turning point of the cooling rate around 10 Ma may be caused by rapid uplift, but the more likely reason is the decrease in geothermal gradient since the late Miocene (from 44°C / km to 30°C / km) (Zhao et al., 2007; Yao Hefa et al., 2006). It is estimated that the overall cooling rate from 25 Ma to the present is about 2.5°C / Ma.

[0087] The relationship between low-temperature thermochronological age and elevation extracted from the profile has advantages in quantifying the exhumation age and erosion rate of orogenic belts and hydrothermal deposits. It can also be used to constrain the relative sliding distance of faults, thereby avoiding the influence of paleo-geothermal gradient on the calculation results (McInnes et al., 1999; Reiners and Brandon, 2006; Liu et al., 2017; Leng et al., 2018). However, the premise of this method is that the closure temperature isotherms of all samples in the vertical profile are at the same height (Peyton and Carrapa, 2013). All samples in this study were taken from boreholes with similar distances in the same profile, and the closure temperature isotherms of all samples can be considered to be similar. In addition, the topography in the region is not very different, so the influence of topography on the isotherms can also be ignored. Therefore, the relationship between age and altitude in this study is relatively objective. Among the six apatite fission track samples in this study, five were taken from the footwall of the main fracture surface (fault mud), and only ZK712-1 was taken from the upper wall of the main fracture surface. The four samples studied by Sun et al. (2017) in ZK4 (hole depth 1002.84m) in the Jiaojia gold field were also taken from the footwall of the main fracture surface. Liu Zhenjiang et al. (2010) conducted an AFT study on one sample of the Shangzhuang rock mass on the surface of the lower wall of the Jiaojia fault zone. Through comparative studies, it was found that there is a linear relationship between the apatite fission track age (AFT) and the depth of the sample. As the depth of the sample increases, the recorded age changes regularly in stages, and the exfoliation rate is divided into three stages by the slope ( Figure 6 The erosion rate from 100 to 60 Ma is about 27 m / Ma. Combined with the geothermal gradient (44℃ / Ma), the cooling rate is calculated to be 1.2℃ / Ma, and the erosion thickness is 1.10 km, which generally presents a relatively slow uplift and erosion process; the erosion rate from 60 to 25 Ma is about 14 m / Ma, the cooling rate is 0.6℃ / Ma, and the erosion thickness is 0.5 km, which generally presents a slow uplift and erosion process; the erosion rate from 25 to 0 Ma is about 53 m / Ma, the cooling rate is 2.3℃ / Ma, and the erosion thickness is 1.3 km, which generally presents a relatively fast uplift and erosion process. The cooling rate in this stage is similar to the cooling rate of the AFT thermal simulation.

[0088] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A deep exploration evaluation method based on multi-parameter geological and thermal history simulation, characterized by: The following steps are involved: S1: Collect mineralized quartz and granite samples from the target area and send them to the laboratory for processing, including cleaning, cutting and grinding; S2: Analyze the collected samples, including: mineralization depth analysis of inclusions, emplacement depth analysis of rock mass, emplacement age analysis of samples, and obtaining cooling age of samples by combining fission tracks of zircon and apatite; S3: Conduct thermal history simulation reconstruction, combine geothermal gradients at different periods, and calculate the ore body erosion thickness; S4: Conduct deep ore body prediction, including combining emplacement depth and denudation thickness data to assess the preservation status of the ore body.

2. The deep exploration evaluation method based on multi-parameter geological and thermal history simulation according to claim 1 is characterized in that: The steps of processing the fission tracks of zircon and apatite in step S2 are as follows: S2.1: The collected samples are crushed and preliminarily screened by magnetic separation and gravity separation; S2.2: Select apatite and zircon single mineral grains for fission track analysis under a microscope; S2.3: Apatite and zircon single mineral particles are made into targets using epoxy resin and polytetrafluoroethylene oxide resin respectively, and then flattened and polished to expose the inner surface of the mineral particles; S2.4: The zircon sample was continuously etched in a NaOH-KOH mixed solution at a temperature of 220°C for 25 hours, and the apatite sample was continuously etched in a 5.0% HNO3 solution at a temperature of 25°C for 30 seconds, and the samples were irradiated in a thermal neutron nuclear reactor; S2.5: After irradiation, the muscovite mica used as an external detector was placed in a 40% HF acid solution at a temperature of 25°C and etched continuously for 20 minutes to reveal the fission tracks induced in the muscovite. A 1000x microscope was used to measure the density of induced and spontaneous fission tracks and the density of induced tracks in the standard monitoring glass, as well as the length information of the fission tracks in the apatite sample.

3. The deep exploration evaluation method based on multi-parameter geological and thermal history simulation according to claim 1 is characterized in that: The specific expression of the inclusion mineralization depth analysis recorded in step S2 is as follows: Where D represents the mineralization depth, ρ represents the average density of the rock, and P final represents the pressure inferred from the homogenization temperature of the fluid inclusion, P initial represents the surface pressure and g represents the acceleration due to gravity.

4. The deep exploration evaluation method based on multi-parameter geological and thermal history simulation according to claim 3 is characterized in that: The pressure P calculated from the homogenization temperature of the fluid inclusion final The specific expression is as follows: P final =A+B·T h +C·S Among them, P final represents the pressure calculated from the homogenization temperature of the fluid inclusion. A, B, and C are all empirical coefficients. T h It represents the uniform temperature obtained through the hot and cold stage experiment, represents the phase change temperature of the fluid under high temperature state, and S represents the salinity calculated from the freezing point.

5. The deep exploration evaluation method based on multi-parameter geological and thermal history simulation according to claim 2 is characterized in that: The emplacement age analysis of the samples was performed using RadialPlotter software.

6. The deep exploration evaluation method based on multi-parameter geological and thermal history simulation according to claim 1 is characterized in that: The specific expression for the rock mass emplacement depth analysis in step S2 is as follows: Among them, D i Indicates the penetration depth, P inv It represents the equilibrium pressure after the rock mass is intruded, and P represents the average geopressure gradient.

7. The deep exploration evaluation method based on multi-parameter geological and thermal history simulation according to claim 1 is characterized in that: The simulation software used for the thermal history reconstruction is HeFTy.

8. The deep exploration evaluation method based on multi-parameter geological and thermal history simulation according to claim 1 is characterized in that: The calculation expression of the ore body erosion thickness in step S3 is as follows: Where E represents the ore body denudation thickness, represents the cooling rate in the jth stage, T j represents the geothermal gradient of the jth stage, t j Represents the duration of the jth stage.

9. The deep exploration evaluation method based on multi-parameter geological and thermal history simulation according to claim 8, characterized in that: The specific expression of the preservation status of the ore body is as follows: S=DE Among them, S represents the preservation condition of the ore body, D represents the formation depth of the ore body, and E represents the erosion thickness of the ore body.

10. The deep exploration evaluation method based on multi-parameter geological and thermal history simulation according to claim 1, characterized in that: The step S4 also includes, after determining the preservation status of the ore body, conducting deep drilling to expose the deep ore body.

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