Screening method for ore-contained rock mass in tungsten-tin ore prospecting prospective area

Abstract

The invention discloses a method for screening ore-contained rock masses in a tungsten-tin ore prospecting prospective area, and a tungsten-tin ore metallogenic specificity distinguishing system and a screening method are constructed on the basis of fusing rock ore total rock geochemical data, a partial fusion numerical simulation experiment, a Rayleigh shunt numerical simulation experiment and a crystal porridge body model. According to the method, through quantitative analysis of essential differences of the ore-containing rock mass, the lean ore rock mass and the non-ore-containing rock mass in the magma differentiation degree, rapid and accurate screening of the hidden mineralized rock mass in the prospecting distant view area is achieved, and the ore-containing rock mass with the most mineralization potential can be rapidly screened out from the non-ore-containing rock mass or the lean ore rock mass.

Description

Technical Field

[0001] This invention belongs to the field of mineral resource exploration technology, specifically relating to the design of a screening method for ore-bearing rock masses in prospective areas for tungsten-tin ore exploration. Background Technology

[0002] Tungsten-tin (W-Sn) ore, a rare metal mineral resource, is a crucial strategic reserve metal in my country, making significant contributions to industries such as new energy, aerospace, military, alloy manufacturing, electronics, and information technology. Therefore, developing a simple and effective method for identifying the tungsten-tin mineralization potential of granite bodies is a core requirement for improving the accuracy of regional mineral exploration. Existing technologies mainly utilize the Nb / Ta, Zr / Hf, and TE ratios of the whole granite rock. 1,3 The evolution of magma is determined by parameters such as Rb / Sr, K / Rb, europium anomaly, light rare earth elements, heavy rare earth elements, and temperature (T) and oxygen fugacity in zircon from granites. Based on three indicators—magmatic oxygen fugacity, magmatic differentiation, and magmatic-hydrothermal conversion intensity—it is determined whether granites have tungsten-tin mineralization potential. However, this method has obvious limitations: although it meets the key characteristics of existing discrimination systems—such as low temperature, low oxygen fugacity, strong magmatic-hydrothermal conversion process, and high differentiation characteristics indicated by zircon Ti thermometers—it does not actually have W-Sn mineralization potential, resulting in insufficient applicability of existing methods in this region. Summary of the Invention

[0003] The purpose of this invention is to address the problems of strong interpretation ambiguity and weak mineral type specificity in existing mineralization prediction methods, and to propose a method for screening ore-bearing rock masses in prospective areas for tungsten-tin deposits.

[0004] The technical solution of this invention is: a method for screening ore-bearing rock masses in a prospective area for tungsten-tin ore exploration, comprising the following steps: S1. Select tungsten-tin ore deposits and collect samples.

[0005] S2. Perform whole-rock major and trace element analysis on the sample to obtain whole-rock major and trace element data, and calculate the relevant indicators of the whole rock of granite based on the whole-rock major and trace element data.

[0006] S3. Determine the impact of source region properties on the mineralization potential of tungsten-tin deposits based on whole-rock major and trace element data.

[0007] S4. In response to the contribution of the source region to the mineralization of tungsten-tin ore, a partial melting numerical simulation experiment was conducted.

[0008] S5. In response to the partial melting numerical simulation experiment showing that the tungsten and tin content in the magma melt is higher than the crustal average, Rayleigh fractionation numerical simulation experiments were conducted based on the crystal porridge model to classify the ore-forming potential of tungsten and tin ore-forming areas and complete the screening of ore-bearing rock masses.

[0009] Further, step S1 includes the following sub-steps: S11. Collect geological maps of the target area at a scale of 1:50,000 or 1:25,000, highlighting the Miocene Himalayan pale granite body, fault zones, and stratigraphic lithology, and preliminarily exclude areas without mineralization geological conditions.

[0010] S12. Conduct on-site surveys of the potential areas after preliminary screening to observe whether there are mineralized outcrops or mineralized rocks on the surface, further narrowing down the delineation area and determining the tungsten-tin ore-forming area.

[0011] S13. Collect 5 to 8 samples from each outcrop in the core and transitional areas of tungsten-tin ore-forming sites.

[0012] Furthermore, the samples collected in step S1 include rock mass samples and mineralization-related samples.

[0013] Furthermore, the relevant whole-rock indices of the granite in step S2 include Fe2O3 / FeO, Rb / Sr, K / Rb, Nb / Ta, Zr / Hf, and TE. 1,3 Differentiation coefficient.

[0014] Furthermore, TE 1,3 The formula for calculating the differentiation coefficient is: Subscript This represents the normalized value for chondrites.

[0015] Furthermore, step S3 includes the following sub-steps: S31. Determine the type of parent rock in the tungsten-tin ore-forming area.

[0016] S32. Calculate the average W and Sn contents of the parent rock magma based on whole-rock major and trace element data.

[0017] S33. Compare the average W and Sn content of the parent rock magma with the average W and Sn content of the Earth's crust. If the average W and Sn content of the parent rock magma is lower than that of the Earth's crust, the mineralization potential of the source area is low and the source area does not contribute to the mineralization of tungsten-tin ore. Otherwise, the source area has the possibility of enrichment and contributes to the mineralization of tungsten-tin ore.

[0018] Furthermore, step S4 includes the following sub-steps: S41. In response to the contribution of the source region to the mineralization of tungsten-tin ore, the mineral assemblage of the sample is classified.

[0019] S42. Calculate the partition coefficient between the melt and the equilibrium mineral phase based on the mineral assemblage of the sample.

[0020] S43. Based on the distribution coefficient between the melt and the equilibrium mineral phase, simulate the mineral consumption and remaining content of the mineral assemblage during partial melting to obtain the numerical simulation results of partial melting.

[0021] Furthermore, if the melting method in step S42 is batch partial melting, the formula for calculating the partition coefficient between the melt and the equilibrium mineral phase is: If the melting method is partial melting, the formula for calculating the partition coefficient between the melt and the equilibrium mineral phase is: in Represents the elements in the melt The content, elements in the original rock The content, Represents element The partition coefficient between the melt and the equilibrium mineral phase. Indicates the volume fraction of the melt. Represents element The contribution of the melt to the melt during the separation of the melt from the residual melt.

[0022] Furthermore, the formula for Rayleigh fractionation in step S5 is: in This indicates the elemental concentration in the original parent magma. This indicates the elemental concentration in the residual magma. Indicates the volume fraction of the melt. This represents the distribution coefficient of an element between the melt and the equilibrium mineral phase.

[0023] Furthermore, the formula for calculating the composition of the crystal porridge model in step S5 is as follows: in This indicates the proportion of melt that has been extracted from the crystal porridge system. Indicates the original rock composition. Indicates the composition of high-silica granite. This indicates the components of the solidified porridge.

[0024] The beneficial effects of this invention are: (1) This invention solves the problem of identifying false positives in the Himalayan region using existing methods: Existing technologies only use surface features such as low temperature, low oxygen fugacity, and high differentiation of magma to determine mineralization potential, which leads to misjudgments of Himalayan pale granite that "meet the features but have no W-Sn mineralization potential". This invention introduces a crystal porridge model and combines partial melting and Rayleigh fractionation dual digital simulation experiments to quantitatively analyze the essential differences between mineralized and non-mineralized rock bodies in the magma differentiation process, accurately eliminates false positive rock bodies that do not meet the mineralization conditions, and significantly improves the regional applicability.

[0025] (2) It enables rapid batch screening of new exploration areas and improves mineral exploration efficiency: Existing technologies rely on single analysis of whole-rock geochemistry and zircon parameters, which is difficult to meet the rapid assessment needs of a large number of rock samples in prospective mineral exploration areas. This invention can process three types of samples in batches—mineralized, low-mineralized, and non-mineralized—through a standardized index calculation-simulation experiment-classification and judgment process, without the need to carry out complex field verification one by one, significantly shortening the screening cycle and providing efficient technical support for target area delineation in new exploration areas.

[0026] (3) Comprehensive technical logic, covering key mineralization links: Existing technologies only focus on terminal indicators such as magma differentiation degree and oxygen fugacity, ignoring the fundamental influence of source area properties on mineralization. This invention adds source area property discrimination and two numerical simulation experimental steps. First, unsuitable rock masses in the source area are excluded through whole-rock geochemical indicators, and then subsequent simulation experiments are carried out to form a complete logical chain of source area-evolution-mineralization, avoiding ineffective experimental costs and further ensuring the reliability of discrimination results. Attached Figure Description

[0027] Figure 1 The diagram shown is a flowchart of a method for screening ore-bearing rock masses in a prospective area for tungsten-tin ore exploration, provided by an embodiment of the present invention.

[0028] Figure 2 The image shown is a W-Sn mineralization potential discrimination diagram of light-colored granite in the eastern Himalayas provided in an embodiment of the present invention. Detailed Implementation

[0029] Exemplary embodiments of the present invention will now be described in detail with reference to the accompanying drawings. It should be understood that the embodiments shown and described in the drawings are merely exemplary and are intended to illustrate the principles and spirit of the invention, and are not intended to limit the scope of the invention.

[0030] This invention provides a method for screening ore-bearing rock masses within a prospective area for tungsten-tin ore exploration, such as... Figure 1 As shown, the process includes the following steps S1 to S5: S1. Select tungsten-tin ore deposits and collect samples.

[0031] In mineral exploration, areas with significant potential and prospects are generally referred to as prospective areas after comprehensive analysis through geological exploration (geophysical, geochemical, remote sensing, etc.).

[0032] Step S1 includes the following sub-steps S11 to S13: S11. Collect geological maps of the target area at a scale of 1:50,000 or 1:25,000, highlighting the Miocene Himalayan pale granite body (tungsten-tin deposits are often associated with this period of rock bodies), fault zones (key to ore control), and stratigraphic lithology (such as carbonate rocks, clastic rocks, and other ore-bearing strata), and preliminarily exclude areas without mineralization geological conditions.

[0033] S12. Conduct on-site surveys of the potential areas after preliminary screening to observe whether there are mineralized outcrops (such as quartz veins, greisen alteration, etc.) or mineralized boulders on the surface, further narrowing down the delineation range and determining the tungsten-tin ore-forming areas.

[0034] S13. In the core and transitional areas of tungsten-tin ore deposits, collect 5 to 8 samples from each outcrop to ensure comprehensive data.

[0035] In this embodiment of the invention, the collected samples include rock mass samples and mineralization-related samples. Rock mass samples, such as granite outcrops and drill cores, reflect the mineral content of the rock mass itself. Mineralization-related samples, such as altered rocks and soil, reflect the enrichment of elements.

[0036] S2. Perform whole-rock major and trace element analysis on the sample to obtain whole-rock major and trace element data, and calculate the relevant indicators of the whole rock of granite based on the whole-rock major and trace element data.

[0037] In this embodiment of the invention, micro-area analysis of zircon minerals was performed to obtain trace element data of zircon; a Primus II X-ray fluorescence spectrometer (XRF) from Rigaku, Japan, and an Agilent 7700e inductively coupled plasma mass spectrometer (ICP-MS) from Agilent Technologies, USA, were used to complete the analysis of major and trace elements in the samples.

[0038] In this embodiment of the invention, based on whole-rock major and trace element data, relevant indices of the granite whole-rock are calculated using GEOKIT software, including Fe2O3 / FeO, Rb / Sr, K / Rb, Nb / Ta, Zr / Hf, and TE. 1,3 Differentiation coefficient.

[0039] TE 1,3 The formula for calculating the differentiation coefficient is: Subscript This represents the normalized value for chondrites. In-situ micro-area trace element analysis of single minerals was performed using laser ablation-inductively coupled plasma mass spectrometry (LA-ICP-MS). This analysis primarily involved rock-forming minerals such as mica. The instruments used in the experiment were an Agilent 7700e ICP-MS mass spectrometer and a 102-type 193nm ArF laser ablation system.

[0040] S3. Determine the impact of source region properties on the mineralization potential of tungsten-tin deposits based on whole-rock major and trace element data.

[0041] In this embodiment of the invention, the source region nature refers to the crustal source region where rare metals such as W and Sn originate, and the magma carries key elements of the ore source layer during partial melting.

[0042] Step S3 includes the following sub-steps S31 to S33: S31. Determine the type of parent rock in the tungsten-tin ore-forming area.

[0043] S32. Calculate the average W and Sn contents of the parent rock magma based on whole-rock major and trace element data.

[0044] S33. Compare the average W and Sn contents of the parent rock magma with the average W (1 ppm) and Sn (1.7 ppm) contents of the crust (W is an extremely incompatible element, with a crustal abundance approximately 250 times that of the mantle. Although it is enriched during partial melting and magma evolution, it exhibits a negative anomaly during high differentiation stages, and its content is more influenced by the source region or moderate differentiation; Sn enrichment source regions require less heat input, lower degree of partial melting, and magma evolution to form tin-rich magma). If the average W and Sn contents of the parent rock magma are lower than the average W and Sn contents of the crust, the source region has low mineralization potential and does not contribute to tungsten-tin mineralization; otherwise, the source region has the potential for enrichment and contributes to tungsten-tin mineralization.

[0045] S4. In response to the contribution of the source region to the mineralization of tungsten-tin ore, a partial melting numerical simulation experiment was conducted.

[0046] Metamorphic complex melting experiments cannot definitively determine the trace elements in the melt, making direct comparison between whole-rock trace element data and experimental melt trace composition impossible. Due to current analytical limitations, it is generally impossible to definitively determine the trace elements in the test melt during metamorphic complex melting experiments; therefore, direct comparison between whole-rock trace element data and the trace composition of the test melt in melting experiments is not possible. However, for large ion lithophile elements (Rb, Sr, Ba), they are mainly hosted in major rock-forming minerals such as feldspar and mica, which are also the main mineral phases in the metamorphic complex melting reaction. Therefore, the content of these large ion lithophile elements in the melt can be obtained through numerical simulation calculations.

[0047] Knowing the initial rare metal content of the molten lava, the distribution coefficients of elements between the melt and minerals, the equilibrium mineral assemblage of the melt, and the degree of partial melting, it is possible to simulate the content and changes of W-Sn in partial melting and explore the degree of enrichment.

[0048] Step S4 includes the following sub-steps S41 to S43: S41. In response to the contribution of the source region to the mineralization of tungsten-tin ore, the mineral assemblage of the sample is divided for mineral simulation calculations.

[0049] In this embodiment of the invention, if the parent magma cannot be determined, the average value of the integrated data of ancient metamorphic complex and sedimentary rocks in the study area is used as the initial melt, and the average content of W, Sn and Cs is taken.

[0050] S42. Calculate the partition coefficient between the melt and the equilibrium mineral phase based on the mineral assemblage of the sample.

[0051] In this embodiment of the invention, if the melting method is batch partial melting, the formula for calculating the distribution coefficient between the melt and the equilibrium mineral phase is: If the melting method is partial melting, the formula for calculating the partition coefficient between the melt and the equilibrium mineral phase is: in Represents the elements in the melt The content, elements in the original rock The content, Represents element The partition coefficient between the melt and the equilibrium mineral phase. Indicates the volume fraction of the melt. Represents element The contribution of the melt to the melt during the separation of the melt from the residual melt.

[0052] S43. Based on the distribution coefficient between the melt and the equilibrium mineral phase, simulate the mineral consumption and remaining content of the mineral assemblage during partial melting to obtain the numerical simulation results of partial melting.

[0053] S5. In response to the partial melting numerical simulation experiment showing that the tungsten and tin content in the magma melt is higher than the crustal average, Rayleigh fractionation numerical simulation experiments were conducted based on the crystal porridge model (MUSH model) to classify the ore-forming potential of tungsten and tin ore-forming areas and complete the screening of ore-bearing rock masses.

[0054] In this embodiment of the invention, the core basis of the Rayleigh fractionation numerical simulation experiment is that the increase in the content of incompatible elements in granite melt is mostly due to the separation crystallization process, and the enrichment of rare elements in leucogranite and pegmatite is related to this.

[0055] Rayleigh fractionation numerical simulation experiments used Rb, Sr, and Cs (which are found in mica and feldspar, making it easier to reflect the separation and crystallization process) for simulation.

[0056] The formula for Rayleigh fractionation is: in This indicates the elemental concentration in the original parent magma. This indicates the elemental concentration in the residual magma. Indicates the volume fraction of the melt. This represents the distribution coefficient of an element between the melt and the equilibrium mineral phase.

[0057] The Rayleigh fractionation numerical simulation experiment was divided into 5 groups based on the granite lithology distribution in the study area (the specific groups were adjusted according to the mineralization of the samples), arranged from high to low degree of evolution: Fine-grained rock (quartz 26%+, potassium feldspar 33%+, plagioclase 39%+, muscovite 3%) Granite pegmatite (quartz 36%+, potassium feldspar 13%+, plagioclase 42%+, muscovite 2%) Muscovite granite (quartz 32%+, potassium feldspar 22%+, plagioclase 40%+, muscovite 10%). Two-mica granite (quartz 30%+, potassium feldspar 24%+, plagioclase 39%+, biotite 8%+, muscovite 8%). Biotite granite (quartz 20%+, potassium feldspar 25%+, plagioclase 42%+, biotite 10%+, muscovite 2%).

[0058] Using the initial melt composition after partial melting in step S4 as the parent magma composition, the simulation showed two cases: samples on the curve and samples outside the curve. Since the simple separation crystallization mode cannot explain magma differentiation, the crystal porridge model was introduced.

[0059] The slurry model broadly explains how high-silica granites are formed in magma through the separation of melt and crystals. Specifically, when the proportion of crystalline solids in the magma chamber approaches 40%, they mix with the intercrystalline melt to form a slurry-like slurry. As crystallization intensifies, the melt located in the intercrystalline spaces gradually moves into the magma chamber. Alternatively, under differentiation processes such as compaction and gravitational settling, the crystals separate from the melt, resulting in compositional changes. The melt extracted during this process eventually transforms into silica-rich granite types.

[0060] When the crystalline solids account for nearly 40% of the magma chamber, a slurry-like crystal porridge is formed. During crystallization enhancement, the melt moves between the crystals or differentiates through compaction / gravity settling, causing the crystals to separate from the melt. The extracted melt is transformed into silica-rich granite.

[0061] The silica-rich magma system is divided into detached highly differentiated melts and residual crystal porridges (intercrystalline melts + crystals). The former is rich in incompatible elements, while the latter is poor in incompatible elements.

[0062] The formula for calculating the composition of the crystal porridge model is as follows: in This indicates the proportion of melt that has been extracted from the crystal porridge system. This indicates the composition of the protolith, that is, the elemental concentration in the original parent magma. Indicates the composition of high-silica granite. This indicates the components of the solidified porridge.

[0063] In this embodiment of the invention, the crystal porridge system refers to the entire magma chamber as a dynamic system composed of crystals, melts and fluids, in which a series of physical and chemical processes are taking place.

[0064] Based on the distribution of samples on the separation crystallization curve in the crystallization model, the mineralization potential is classified according to the degree of differentiation (W-Sn mineralization potential is greater in granites with a high degree of differentiation than in insolids with a low degree of differentiation): Low degree of differentiation: 0~30%; Low to moderate differentiation: 30-60%; Moderate differentiation: 60-90%; High degree of differentiation: ≥90%.

[0065] The specific range of mineralization potential calculated in this embodiment of the invention is as follows: W ore: Only rock masses with moderate differentiation (60~90%) have mineralization potential, while those with 0~60% (low / low-middle differentiation) and ≥90% (high differentiation) have no mineralization potential.

[0066] Sn ore: The mineralization potential is optimal when the differentiation is ≥70%.

[0067] The following specific experimental example further illustrates the method for screening ore-bearing rock masses within a prospective area for tungsten-tin ore exploration provided by this invention: (1) Current status of regional mineralization.

[0068] In the eastern Himalayas: the Cuona Cave Be-Sn-W polymetallic deposit, the Kuju Township Li-Be-Nb-Ta mineralization, the Lalong Be-Nb-Ta deposit, the Luozha Li-Be-Nb-Ta deposit, and the Gabo Li deposit have been discovered. The beryl-bearing pegmatite on the north side of the Yala Xiangbo Dome has Be mineralization (similar to the characteristics of typical pegmatite Be-Ta-Nb mineralization zones). In the central Himalayas: the Xiaru Dome Nb-Ta-W deposit, the Jilong Li-Be-Sn-Cs-Nb-Ta deposit, the Pushila / Requ Li-Be-Sn-Nb-Ta deposit, the Qianjingou / Qiongjiagang Li deposit, and the Gaowu Sn-Cs-Tl mineralization have been discovered.

[0069] (2) Existing research.

[0070] Wang Rucheng, Wu Fuyuan, et al. (2017) investigated 15 leucogranite bodies in the Himalayas and found rare metal mineralization in 12 of them, confirming their good mineralization potential. The mineralization characteristics of the leucogranite in this region are similar to those of rare metal mineralization in South China, western Sichuan, the Greater Khingan Mountains, and the Hercynian Beauvoir granite in France and Cínovec granite in the Czech Republic worldwide.

[0071] (3) Geochemical analysis and mineralization matching: The method of this invention was used to perform geochemical mapping on more than 2,000 Cenozoic magmatic rock samples in the region, such as... Figure 2 As shown, where Figure 2 (a) shows the Rayleigh fractionation simulation results of the W mineralization potential model in the Cenozoic magmatic rocks of the Himalayas after the introduction of magma into the crystal porphyry model. Figure 2 (b) shows the Rayleigh fractionation simulation results of the Sn mineralization potential model in the Cenozoic magmatic rocks of the Himalayas after the introduction of magma into the crystal body model. The results show that the discovered W-Sn mineralized / mineralized rock bodies all conform to the mineralization characteristics of "60-90% differentiation of W ore and ≥70% differentiation of Sn ore" in this experimental example; at the same time, it was found that a large number of unmineralized rock bodies also have the above differentiation characteristics, indicating that the W-Sn mineralization potential in the Himalayas has great development prospects.

[0072] In summary, the embodiments of the present invention, by introducing the crystal porridge theory to correct the traditional Rayleigh fractionation simulation, can accurately capture the enrichment threshold of tungsten and tin elements in the magma-hydrothermal transition stage (e.g., a differentiation degree of 60%~90% is the ore-forming potential value of W, and greater than 70% is the ore-forming potential value of Sn), thus solving the false positive discrimination problem of Himalayan leucogranite and being the key to ensuring the accuracy of ore-forming potential discrimination.

[0073] This invention integrates three major technical modules: whole-rock major and trace element (differentiation coefficients such as Zr / Hf, Nb / Ta, Rb / Sr, etc.) calculation, partial melting simulation, and Rayleigh fractionation simulation. This forms a synergistic mechanism of qualitative prediction and quantitative verification: rapid initial screening of rock masses using whole-rock indicators, and quantification of differentiation degree through dual simulation experiments. The combination of these two approaches achieves a breakthrough from qualitative description to quantitative judgment, which is the core technical support for efficient screening.

[0074] Based on the existing technology that does not consider the influence of the source region, this invention adds source region property identification and two numerical simulation experimental steps. By analyzing the material composition and evolution background of the magma source region through whole-rock geochemical parameters, rock masses with unsuitable source regions (such as those lacking initial W-Sn enrichment conditions) are preferentially excluded, reducing the workload of subsequent simulation experiments. This is an important supplement to improve screening efficiency.

[0075] Those skilled in the art will recognize that the embodiments described herein are intended to help the reader understand the principles of the invention, and should be understood that the scope of protection of the invention is not limited to such specific statements and embodiments. Those skilled in the art can make various other specific modifications and combinations based on the technical teachings disclosed in this invention without departing from the spirit of the invention, and these modifications and combinations are still within the scope of protection of this invention.

Claims

1. A method for screening ore-bearing rock masses within a prospective area for tungsten-tin ore exploration, characterized in that, Includes the following steps: S1. Select tungsten-tin ore-forming areas and collect samples; S2. Perform whole-rock major and trace element analysis on the sample to obtain whole-rock major and trace element data, and calculate relevant indicators of the whole rock of granite based on the whole-rock major and trace element data; S3. Determine the impact of source region properties on the mineralization potential of tungsten-tin deposits based on whole-rock major and trace element data; S4. In response to the contribution of the source region to the mineralization of tungsten-tin ore, a partial melting numerical simulation experiment was conducted. S5. In response to the partial melting numerical simulation experiment showing that the tungsten and tin content in the magma melt is higher than the crustal average, Rayleigh fractionation numerical simulation experiments were conducted based on the crystal porridge model to classify the ore-forming potential of tungsten and tin ore-forming areas and complete the screening of ore-bearing rock masses.

2. The method for screening ore-bearing rock masses within a prospective tungsten-tin deposit area according to claim 1, characterized in that, Step S1 includes the following sub-steps: S11. Collect geological maps of the target area at a scale of 1:50,000 or 1:25,000, highlighting the Miocene Himalayan pale granite body, fault zones, and stratigraphic lithology, and preliminarily excluding areas without mineralization geological conditions. S12. Conduct on-site surveys of potential areas after preliminary screening, observe whether there are mineralized outcrops or mineralized boulders on the surface, further narrow down the delineation area, and determine the tungsten-tin ore-forming area. S13. Collect 5 to 8 samples from each outcrop in the core and transitional areas of tungsten-tin ore-forming sites.

3. The method for screening ore-bearing rock masses within a prospective tungsten-tin deposit area according to claim 1, characterized in that, The samples collected in step S1 include rock samples and mineralization-related samples.

4. The method for screening ore-bearing rock masses within a prospective tungsten-tin deposit area according to claim 1, characterized in that, The relevant whole-rock indices of the granite in step S2 include Fe2O3 / FeO, Rb / Sr, K / Rb, Nb / Ta, Zr / Hf, and TE. 1,3 Differentiation coefficient.

5. The method for screening ore-bearing rock masses within a prospective tungsten-tin deposit area according to claim 4, characterized in that, The TE 1,3 The formula for calculating the differentiation coefficient is: Subscript This represents the normalized value for chondrites.

6. The method for screening ore-bearing rock masses within a prospective tungsten-tin deposit area according to claim 1, characterized in that, Step S3 includes the following sub-steps: S31. Determine the type of parent rock in the tungsten-tin ore-forming area; S32. Calculate the average W and Sn contents of the parent rock magma based on whole-rock major and trace element data; S33. Compare the average W and Sn content of the parent rock magma with the average W and Sn content of the Earth's crust. If the average W and Sn content of the parent rock magma is lower than that of the Earth's crust, the mineralization potential of the source area is low and the source area does not contribute to the mineralization of tungsten-tin ore. Otherwise, the source area has the possibility of enrichment and contributes to the mineralization of tungsten-tin ore.

7. The method for screening ore-bearing rock masses within a prospective tungsten-tin deposit area according to claim 1, characterized in that, Step S4 includes the following sub-steps: S41. In response to the contribution of the source region to the mineralization of tungsten-tin ore, the mineral assemblage of the samples is classified. S42. Calculate the partition coefficient between the melt and the equilibrium mineral phase based on the mineral assemblage of the sample; S43. Based on the distribution coefficient between the melt and the equilibrium mineral phase, simulate the mineral consumption and remaining content of the mineral assemblage during partial melting to obtain the numerical simulation results of partial melting.

8. The method for screening ore-bearing rock masses within a prospective tungsten-tin deposit area according to claim 7, characterized in that, If the melting method in step S42 is batch partial melting, then the formula for calculating the distribution coefficient between the melt and the equilibrium mineral phase is: If the melting method is partial melting, the formula for calculating the partition coefficient between the melt and the equilibrium mineral phase is: in Represents the elements in the melt The content, Indicates elements in the original rock The content, Represents element The partition coefficient between the melt and the equilibrium mineral phase. Indicates the volume fraction of the melt. Represents element The contribution of the melt to the melt during the separation of the melt from the residual melt.

9. The method for screening ore-bearing rock masses within a prospective tungsten-tin deposit area according to claim 1, characterized in that, The formula for Rayleigh fractionation in step S5 is: in This indicates the elemental concentration in the original parent magma. This indicates the elemental concentration in the residual magma. Indicates the volume fraction of the melt. This represents the distribution coefficient of an element between the melt and the equilibrium mineral phase.

10. The method for screening ore-bearing rock masses within a prospective tungsten-tin deposit area according to claim 1, characterized in that, The formula for calculating the composition of the crystal porridge model in step S5 is as follows: in This indicates the proportion of melt that has been extracted from the crystal porridge system. Indicates the original rock composition. Indicates the composition of high-silica granite. This indicates the components of the solidified porridge.

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