A method, system, equipment and medium for predicting rare metal mineralization potential

Abstract

The present application relates to a method, system, equipment and medium for predicting the mineralization potential of rare metals. The prediction method comprises: obtaining tourmaline distribution data of a target area; performing microscopic petrographic analysis on tourmaline samples based on the tourmaline distribution data to identify the genetic type and ring-zone structure characteristics of the tourmaline samples; performing major element and trace element detection on the tourmaline samples according to the genetic type and ring-zone structure characteristics of the tourmaline samples to obtain major element data and trace element data; and determining the FeO2 content in the major element data based on the FeO2 content in the tourmaline samples. T The MgO ratio and the Nb and Sn contents in the trace element data, combined with the B isotope δ 11 B value, establish a magma-hydrothermal evolution model; based on the magma-hydrothermal evolution model, determine the characteristic element thresholds for rare metal mineralization potential; based on tourmaline distribution data and characteristic element thresholds, identify favorable prospecting areas in the target area. This application can effectively predict favorable areas for rare metal prospecting.

Description

Technical Field

[0001] The present application relates to the technical field of rare metal ore deposit exploration, and in particular to a method, system, equipment and medium for predicting rare metal mineralization potential. Background Art

[0002] With the growing global demand for rare metals, finding new economically viable mineral deposits has become a key task in geological prospecting. This is especially true in modern high-tech industries, where the demand for rare metals such as niobium, tantalum, and rare earth elements is becoming increasingly urgent. However, existing rare metal deposit exploration technologies still face numerous challenges, relying primarily on traditional geophysical exploration methods such as electrical, gravity, and magnetic methods. These methods are less effective in areas with complex terrain or strong interference from surrounding rocks, and their resolution is significantly insufficient when searching for concealed deposits. Furthermore, traditional rock geochemical analysis methods are typically based solely on whole-rock chemical composition, ignoring the role of key minerals in mineralogical analysis, such as tourmaline.

[0003] Tourmaline is a common boron-containing mineral that exhibits distinct chemical compositions and isotopic signatures in different geological environments. Previous studies have shown that tourmaline's composition can reflect magmatic-hydrothermal evolution and is closely related to the enrichment of rare metals. However, existing research has primarily focused on the genetic analysis of tourmaline, and its chemical composition and isotopic signatures have yet to be systematically applied to the prospecting of rare metal deposits. Despite the widespread presence of tourmaline in rare metal deposits, quantitative prospecting models based on tourmaline composition are still lacking. In particular, the prediction of mineralization potential remains a challenge, and in-depth research and practical application remain lacking.

[0004] Therefore, how to effectively utilize the chemical composition and isotopic characteristics of tourmaline to provide a more scientific and efficient prospecting method for rare metal deposits is still a technical problem that needs to be solved urgently. Summary of the Invention

[0005] In order to achieve effective prediction of favorable areas for rare metal prospecting, the present application provides a rare metal mineralization potential prediction method, system, equipment and medium.

[0006] In the first aspect, the present application provides a method for predicting rare metal mineralization potential, which adopts the following technical solution:

[0007] A method for predicting rare metal mineralization potential, comprising:

[0008] Acquire tourmaline distribution data in the target area; wherein the tourmaline distribution data includes the occurrence type and spatial distribution information of tourmaline samples in granite, the contact zone between rock mass and surrounding rock, and the surrounding rock;

[0009] Based on the tourmaline distribution data, performing microlithographic analysis on the tourmaline sample to identify the genetic type and zoning structure characteristics of the tourmaline sample;

[0010] According to the genesis type and ring-band structure characteristics of the tourmaline sample, the major element and trace element data of the tourmaline sample are detected to obtain the major element data and the trace element data;

[0011] Based on the FeO in the main element data T The ratio of MgO and the contents of Nb and Sn in the trace element data, combined with the B isotope δ 11 B value, to establish a magma-hydrothermal evolution model;

[0012] Determine the characteristic element thresholds of rare metal mineralization potential based on the magma-hydrothermal evolution model;

[0013] Based on the tourmaline distribution data and characteristic element thresholds, favorable prospecting areas in the target area are determined.

[0014] By adopting the above technical solutions, the mineralogy, geochemistry and isotope analysis of tourmaline were systematically integrated, and the multi-stage growth structure characteristics were identified by microlithography. T The method uses the Mg / MgO ratio, Nb and Sn enrichment trends, and the magma-hydrothermal evolution path of the Rayleigh fractionation model of the B isotope, and sets characteristic element thresholds as quantitative indicators of mineralization potential, effectively predicting favorable areas for rare metal prospecting. Compared with traditional exploration methods, this method uses tourmaline as a direct prospecting marker mineral, combining geological surveys, geochemical analysis, and quantitative model simulation to effectively locate rare metal ore bodies.

[0015] Optionally, the genetic type and ring-zone structure characteristics of the tourmaline sample are obtained by observing the tourmaline color, crystal form and mineral symbiosis through a polarizing microscope, combined with backscattered electron imaging technology.

[0016] Optionally, the main element data includes SiO2, TiO2, Al2O3, FeO T , MnO, MgO, CaO, Na2O, K2O, F and Cl, the major element data are obtained by electron probe detection; the trace element data include Li, Zn, Ga, Sr, Nb, Sn, La, Ce, the trace element data and the B isotope δ 11 The B value was obtained by laser ablation inductively coupled plasma mass spectrometry.

[0017] Optionally, the step of establishing the magma-hydrothermal evolution model includes:

[0018] Based on the FeO in the main element data T The magmatic-hydrothermal evolution stages of the tourmaline samples were divided according to the MgO ratio to generate stage classification results;

[0019] According to the stage classification results and the B isotope δ 11 B value, to determine the B isotope fractionation coefficient α and the melt / fluid residual ratio f;

[0020] Based on the FeO T / MgO ratio, Nb and Sn contents in the trace element data, and the fractionation coefficient α and residual ratio f, to construct a three-dimensional model of the magma-hydrothermal evolution path;

[0021] The three-dimensional model is compared and verified with field geological exploration data, the fractionation coefficient α and the Nb / Sn threshold are adjusted, and the calibrated magma-hydrothermal evolution model is output.

[0022] By adopting the above implementation method, a magma-hydrothermal evolution model of tourmaline is established, which provides an innovative tool for the effective exploration of rare metal deposits. T Comprehensive analysis of data such as the Mg / MgO ratio, B isotopes, and trace elements, along with the construction of a three-dimensional model, effectively predicts potential mineralization areas in both the magmatic and hydrothermal phases. Finally, comparison and verification with field geological exploration data ensured the accuracy and reliability of the model. This technical solution not only improves the accuracy of mineral deposit exploration but also provides a viable scientific basis and technical support for exploration in related fields.

[0023] Optionally, the formula for determining the melt / fluid residual ratio f is:

[0024] δ 11 B melt(fluid) =δ 11 B initialmelt（fluid） +(α−1)ln(f);

[0025] In the above formula, δ 11 B melt(fluid) represents the δ in the melt / fluid at different stages of crystallization evolution 11 B value, δ 11 B initialmelt（fluid） represents the δ in the initial melt / fluid 11 B value.

[0026] Optionally, the characteristic element thresholds are: Nb content>10 ppm, Sn content>100 ppm;

[0027] The determination of the favorable prospecting area is based on the following conditions: the tourmaline occurrence type is vein-like or cystic and meets the characteristic element threshold.

[0028] In a second aspect, the present application provides a rare metal mineralization potential prediction system, which adopts the following technical solutions:

[0029] A rare metal mineralization potential prediction system, comprising:

[0030] A data acquisition module is used to acquire tourmaline distribution data in a target area; wherein the tourmaline distribution data includes the occurrence type and spatial distribution information of tourmaline samples in granite, the contact zone between rock mass and surrounding rock, and the surrounding rock;

[0031] an identification module for performing microlithographic analysis on the tourmaline sample based on the tourmaline distribution data to identify the genetic type and zoning structural characteristics of the tourmaline sample;

[0032] An element detection module, configured to detect major elements and trace elements of the tourmaline sample according to the ring-shaped structural characteristics, and obtain major element data and trace element data;

[0033] Evolution model building module, used for FeO based on the main element data T The ratio of MgO and the contents of Nb and Sn in the trace element data, combined with the B isotope δ 11 B value, to establish a magma-hydrothermal evolution model;

[0034] A characteristic element threshold determination module is used to determine the characteristic element threshold of rare metal mineralization potential based on the magma-hydrothermal evolution model;

[0035] The module for determining favorable prospecting areas is used to determine favorable prospecting areas in the target area based on the tourmaline distribution data and characteristic element thresholds.

[0036] Optionally, the evolution model building module includes:

[0037] The stage division unit is used for FeO based on the main element data. T The magmatic-hydrothermal evolution stages of the tourmaline samples were divided according to the MgO ratio to generate stage classification results;

[0038] A parameter determination unit is used to determine the parameters of the phase classification result and the B isotope δ 11 B value, to determine the B isotope fractionation coefficient α and the melt / fluid residual ratio f;

[0039] Three-dimensional model building unit for the FeO T / MgO ratio, Nb and Sn contents in the trace element data, and the fractionation coefficient α and residual ratio f, to construct a three-dimensional model of the magma-hydrothermal evolution path;

[0040] The model calibration unit is used to compare and verify the three-dimensional model with field geological exploration data, adjust the fractionation coefficient α and the Nb / Sn threshold, and output the calibrated magma-hydrothermal evolution model.

[0041] In a third aspect, the present application provides a computer device that adopts the following technical solution:

[0042] A computer device comprises a memory, a processor and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the method according to the first aspect.

[0043] In a fourth aspect, the present application provides a computer-readable storage medium, which adopts the following technical solution:

[0044] A computer-readable storage medium stores a computer program capable of being loaded by a processor and executing any one of the methods in the first aspect.

[0045] In summary, the present application includes at least one of the following beneficial technical effects: by combining the chemical composition and B isotope characteristics of tourmaline, it can effectively identify the key geochemical characteristics in the magma-hydrothermal evolution process, and through geological, microlithographic and isotope simulation analysis, accurately evaluate the mineralization potential of the geological body, and then effectively identify favorable prospecting areas with further exploration value, thereby significantly improving the efficiency and accuracy of mineral exploration. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 This is a first flow chart of a method for predicting rare metal mineralization potential in one of the embodiments of the present application.

[0047] Figure 2 This is a second flow chart of a method for predicting rare metal mineralization potential in one of the embodiments of the present application.

[0048] Figure 3 These are the hand specimens, microscope photos, and BSE imaging characteristics of disseminated tourmaline in granite in one of the embodiments of the present application.

[0049] Figure 4 These are hand specimens, microscope photos, and BSE imaging features of tourmaline-quartz vesicles on the top and edge of granite in one of the embodiments of the present application.

[0050] Figure 5 These are the hand specimens, microscope photos and BSE imaging features of the tourmaline-quartz vein at the edge of the rock mass in one of the embodiments of the present application.

[0051] Figure 6This is a simulation diagram of the Rayleigh fractionation of B isotopes of different types of tourmaline in one of the embodiments of the present application, which aims to show the B isotope evolution characteristics of different tourmaline types during the magma-hydrothermal evolution process.

[0052] Figure 7 This is a box plot of major and trace elements in different types of tourmaline according to one embodiment of the present application, which aims to show the differences and trends in element content of each type of tourmaline. DETAILED DESCRIPTION

[0053] In order to make the purpose, technical solutions and advantages of this application more clear, the following Figure 1-7 It should be understood that the specific embodiments described herein are only used to explain the present application and are not intended to limit the present application.

[0054] The embodiments of the present application disclose a method for predicting rare metal mineralization potential.

[0055] Reference Figure 1 , a method for predicting rare metal mineralization potential, the prediction method includes:

[0056] Step S101, obtaining tourmaline distribution data of a target area;

[0057] Among them, the tourmaline distribution data include the occurrence type and spatial distribution information of tourmaline samples in granite, the contact zone between rock mass and surrounding rock, and the surrounding rock;

[0058] Specifically, obtaining distribution data for tourmaline samples in the target area is fundamental to the entire prediction method. Tourmaline is an indicator mineral for granite pegmatite-type rare metal deposits, and its distribution data can reveal the mineralization potential of the area. By investigating the occurrence type and spatial distribution of tourmaline samples in granite, the contact zone between the rock mass and the surrounding rock, and the surrounding rock, researchers can gain a preliminary understanding of the distribution characteristics of tourmaline in the area and determine which areas have high mineralization potential.

[0059] For example, if a large amount of tourmaline minerals are discovered in a certain area, concentrated near the contact zone between granite and surrounding rock, and the tourmaline types are diverse, this provides effective data support for subsequent microlithographic analysis and mineralization potential prediction. By obtaining tourmaline distribution data, areas with rare metal mineralization potential can be effectively delineated, providing guidance for subsequent detailed analysis and enhancing the efficiency and specificity of prospecting.

[0060] Step S102: Based on the tourmaline distribution data, microlithographic analysis is performed on the tourmaline sample to identify the genetic type and zoning structure characteristics of the tourmaline sample;

[0061] Microlithographic analysis can help identify the different compositions and formation processes of tourmaline minerals. By observing the zoning structure of tourmaline, the different stages of its formation can be determined. Zoning characteristics include oscillatory zoning, compositional abrupt zoning, and dissolution structures, which can reveal the different evolutionary processes that tourmaline has undergone during its magmatic and hydrothermal evolution.

[0062] For example, microscopic observation of tourmaline samples revealed a typical core-edge structure in some samples, indicating a two-stage growth process. Some samples also exhibited dissolution structures at their edges, likely related to fluid interaction. Microlithographic analysis can effectively identify the genesis and evolution of tourmaline, providing crucial insights for subsequent geochemical analysis and prediction of mineralization potential.

[0063] Step S103, performing major element and trace element testing on the tourmaline sample according to the genetic type and ring-band structure characteristics of the tourmaline sample to obtain major element data and trace element data;

[0064] Among them, the main element data include but are not limited to SiO2, TiO2, Al2O3, FeO T , MnO, MgO, CaO, Na2O, K2O, F and Cl, etc., and trace element data include but are not limited to Li, Zn, Ga, Sr, Nb, Sn, La, Ce, etc.

[0065] Specifically, the content of major elements and trace elements is the core indicator of tourmaline chemical characteristics, which can reflect the element migration and enrichment in the magma-hydrothermal process. The tourmaline samples were tested by electron probe (EPMA) and laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) to obtain SiO2, TiO2, Al2O3, FeO T , MnO, MgO, CaO, Na2O, K2O, F and Cl and trace elements such as Li, Zn, Ga, Sr, Nb, Sn, La and Ce.

[0066] For example, in some tourmaline samples, FeO T A high O / MgO ratio, along with Nb and Sn concentrations exceeding specific thresholds, suggests the region may have high rare metal mineralization potential. Obtaining major and trace element data for tourmaline samples further characterizes the chemical composition of tourmaline and closely links it to the formation of rare metal deposits, enhancing the accuracy of predictions of its mineralization potential.

[0067] Step S104: Based on the FeO in the main element data T The MgO ratio and the Nb and Sn contents in the trace element data, combined with the B isotope δ11 B value, to establish a magma-hydrothermal evolution model;

[0068] Among them, the chemical composition and isotopic characteristics of tourmaline are important records of the magma-hydrothermal evolution process. By combining the major element and trace element data of tourmaline samples and the B isotope δ 11 B value, and the establishment of a magma-hydrothermal evolution model can effectively simulate the evolution of tourmaline from the magma stage to the hydrothermal stage and further reveal the mineralization process.

[0069] For example, during the simulation, it was found that different types of tourmaline δ 11 The B value is consistent with the evolution of the simulated curve, indicating that its degree of crystallization evolution is increasing. By establishing a magma-hydrothermal evolution model, it can help clarify the evolutionary path of tourmaline mineralization, and then predict the distribution characteristics of rare metal deposits, improving the accuracy and reliability of the prediction.

[0070] Step S105, determining the characteristic element threshold of rare metal mineralization potential based on the magma-hydrothermal evolution model;

[0071] Based on a magma-hydrothermal evolution model, the concentrations of major and trace elements in different types of tourmaline were analyzed. Combined with the changing trends of these elements and the δ¹¹B values ​​of the B isotope, statistical and empirical data were used to determine characteristic element thresholds that are closely related to the mineralization potential of rare metals. These thresholds are typically minimum values ​​of the element content and are used to identify areas with high potential for mineralization.

[0072] Step S106: Determine the favorable prospecting area in the target area based on the tourmaline distribution data and the characteristic element threshold.

[0073] Among them, combining the tourmaline distribution data of the target area, microlithographic analysis results, element thresholds and magma-hydrothermal evolution model can effectively delineate potential favorable areas for mineral exploration.

[0074] For example, based on tourmaline composition analysis and characteristic element thresholds, combined with magma-hydrothermal model predictions, a favorable prospecting zone with a diameter of 200 meters was identified, within which two vein-like ore bodies were discovered. This method can accurately locate rare metal ore bodies, reduce the cost of blind exploration, and ensure efficient resource utilization and exploration efficiency.

[0075] In the examples of this application, the characteristic element thresholds are determined by actual research data: Nb content>10 ppm, Sn content>100 ppm, and δ 11 The B value is higher than −10.0‰; the determination of the favorable prospecting area is based on the following conditions: the occurrence type of tourmaline is vein-like or cystic, and it meets the above characteristic element thresholds and δ 11 B value range.

[0076] Specifically, Nb and Sn are characteristic elements of rare metals, and when their contents are enriched in ore deposits, they are usually related to hydrothermal activities and the formation of rare metal deposits. 11 The B value is an important indicator in the formation process of tourmaline. In the embodiment of the present application, the δ 11 The B value indicates that tourmaline has hydrothermal stage characteristics.

[0077] In addition, the occurrence type of tourmaline (such as vein or cyst) is usually related to the magma-hydrothermal evolution stage. Vein tourmaline usually represents the product of the hydrothermal stage, while cyst is the product of the magma-hydrothermal transition stage. According to the occurrence type of tourmaline, combined with the characteristic element threshold (Nb, Sn content and δ 11 B value range), can determine the prospecting favorable areas with further exploration value.

[0078] For example, if the tourmaline occurrence in a certain area is vein-like, and the Nb content is 20 ppm, the Sn content is 120 ppm, and the δ 11 If the B value is -9‰, the area meets the conditions of a favorable prospecting area, indicating that the area has a high mineralization potential.

[0079] In the above embodiment, the system integrates the mineralogy, geochemistry and isotope analysis of tourmaline, combines microlithography to identify the multi-stage growth structure characteristics, and constructs a FeO-based T The method uses the Mg / MgO ratio, Nb and Sn enrichment trends, and the magma-hydrothermal evolution path of the Rayleigh fractionation model of the B isotope. Characteristic element thresholds are set as quantitative indicators of mineralization potential, effectively predicting favorable areas for rare metal prospecting. Compared with traditional exploration methods, this method uses tourmaline as a direct prospecting marker mineral, combining geological surveys, geochemical analysis, and quantitative modeling to improve exploration efficiency.

[0080] As an implementation method of step S102, the genesis type and ring-zone structure characteristics of the tourmaline sample are obtained by observing the tourmaline color, crystal form and mineral symbiosis through a polarizing microscope, combined with backscattered electron imaging technology.

[0081] Among them, the zoning structural characteristics include oscillatory zoning, compositional mutation zoning and dissolution structure; oscillatory zoning refers to the periodically changing structure inside the mineral crystal due to the influence of changes in the external environment (such as temperature, pressure, chemical composition, etc.) during the crystallization process of the mineral; compositional mutation zoning refers to the sudden change in the internal composition of the mineral, which is usually caused by drastic changes in the external environment (such as temperature, chemical environment, etc.); dissolution structure refers to the damage to the mineral structure caused by the interaction between the mineral surface or the crystal interior and the fluid. This damage is usually caused by hydrothermal erosion, chemical dissolution, etc., and may manifest as irregular shapes, holes or cracks on the mineral surface.

[0082] Specifically, polarizing microscopy is a tool used to observe the color, crystal form, and mineral symbiosis in mineral samples. By illuminating the sample with a polarized light source, it reveals its microstructure and material properties. Combined with backscattered electron imaging (BSE), the crystal morphology and compositional distribution of the mineral can be further analyzed. This method was used to characterize the zoning structure of tourmaline, helping to determine its origin and evolution.

[0083] For example, under a polarizing microscope, a tourmaline sample exhibits a distinct zoning structure, with its color gradually changing from brown to blue-green, suggesting the possibility of multi-stage growth. Combined with BSE images, the chemical composition of the zoning can be determined, such as Nb- and Sn-rich regions located at the zoning edges.

[0084] As an implementation method of step S103, the major element data is obtained by electron probe detection, and the trace element data and the B isotope δ 11 The B value was obtained by laser ablation inductively coupled plasma mass spectrometry.

[0085] Among them, Electron Probe Micro-Analyzer (EPMA) is a technology widely used in mineral and rock analysis. It uses electron beams to excite the sample surface to generate X-rays, and then analyzes the energy spectrum of these X-rays to obtain the quantitative composition of each element in the sample. The electron probe can detect the main elements in the sample with high precision, such as SiO2, TiO2, Al2O3, FeO T , MnO, MgO, CaO, Na2O, K2O, F and Cl, etc. For example, it is assumed that FeO in a tourmaline sample is detected by an electron probe. T The content is 20% and the MgO content is 10%. These data can be used to further calculate the FeO T The Mg / MgO ratio helps determine the magmatic or hydrothermal evolutionary stage of the sample. High-precision electron probe detection ensures the accuracy and reliability of major element data, providing basic support for the division of magmatic-hydrothermal evolutionary stages.

[0086] In addition, laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) is a technique commonly used for trace element and isotope analysis of minerals. A laser beam is used to ablate a small amount of material from the sample surface, which is then excited into ions by a plasma source and analyzed by a mass spectrometer. This method can effectively determine trace elements (such as Li, Nb, Sn, etc.) and B isotopes (such as δ 11 B value). Assuming that the Nb concentration of the tourmaline sample is 30 ppm and the Sn concentration is 110 ppm using LA-ICP-MS technology, δ 11 The B value is -12.6‰. These data can be used to establish subsequent evolution models. By obtaining trace element and isotope data from tourmaline samples, they provide reliable data support for subsequent evolution path calculations and predictions of favorable prospecting areas.

[0087] Reference Figure 2 As an implementation method of step S104, the step of establishing a magma-hydrothermal evolution model includes:

[0088] Step S201, based on the FeO in the main element data T The magmatic-hydrothermal evolution stages of the tourmaline samples were divided according to the MgO ratio to generate stage classification results;

[0089] Among them, it is necessary to first obtain the main element data of the tourmaline sample, especially FeO T (iron oxide) and MgO (magnesium oxide). By calculating the ratio of the two (FeO T / MgO), can determine the magma-hydrothermal evolution stage of the sample and provide important initial information for subsequent evolution models.

[0090] Step S202: Based on the stage classification results and the B isotope δ 11 B value, to determine the B isotope fractionation coefficient α and the melt / fluid residual ratio f;

[0091] Among them, the B isotope (δ 11 B value) is used to further infer the evolutionary characteristics of tourmaline samples. According to different evolutionary stages (magmatic stage or hydrothermal stage), the B isotope fractionation coefficient α between magma melt and tourmaline and between hydrothermal fluid and tourmaline is different and is affected by temperature.

[0092] For example, assuming that a tourmaline sample is in the magma stage, its δ 11The B value is -12.6‰, and based on the fractionation coefficient α = 0.98 and f ≈ 0.8, the evolutionary path of the sample can be further inferred. The B isotope analysis provides more accurate fractionation and residual ratio data for the evolution of the tourmaline sample, helping to distinguish the degree of crystallization evolution of the mineral at different stages.

[0093] In the embodiment of the present application, the formula for determining the melt / fluid residual ratio f is:

[0094] δ 11 B melt(fluid) =δ 11 B initialmelt（fluid） +(α−1)ln(f);

[0095] In the above formula, δ 11 B melt(fluid) represents the δ in the melt / fluid at different stages of crystallization evolution 11 B value, δ 11 B initialmelt（fluid） represents the δ in the initial melt / fluid 11 B value.

[0096] The formula is used to calculate the B isotope in the melt or fluid stage based on the fractionation coefficient α, the initial B isotope value, and the melt / fluid residual ratio f. This formula indicates that as the melt or fluid evolves, the B isotope δ 11 The B value changes with the fractionation coefficient α. (α−1)ln(f) reflects the degree of B isotope variation in the melt or fluid phase, and the ln(f) term represents the contribution of the melt / fluid residual ratio to the B isotope variation.

[0097] Through this formula, when the initial B isotope value and fractionation coefficient are known, the B isotope changes of tourmaline at different evolutionary stages can be calculated, and detailed information of the magma-hydrothermal evolution process can be inferred.

[0098] Step S203, based on FeO T / MgO ratio, Nb and Sn contents in trace element data, as well as fractionation coefficient α and residual ratio f, to construct a three-dimensional model of the magma-hydrothermal evolution path;

[0099] Among them, FeO T The MgO / MgO ratio (representing the degree of magma-hydrothermal evolution), the Nb and Sn contents (reflecting the degree of rare metal enrichment), the fractionation coefficient α and the residual ratio f are combined to construct a three-dimensional model of magma-hydrothermal evolution. T / MgO ratio, depicting the evolution trend from magma to hydrothermal fluid; the Y axis represents δ 11 The B value reflects the fractionation process; the Z axis represents the Nb / Sn concentration, indicating the level of mineralization potential.

[0100] For example, assuming that in the magma stage, FeO T / MgO ratio is 5, δ 11 The B value is -12.6‰, Nb is 5 ppm, and Sn is 10 ppm. In the hydrothermal stage, FeO T / MgO ratio increased to 20, δ 11 The B value is -8‰, Nb is 35 ppm, and Sn is 80 ppm. By mapping this data into three-dimensional space, the evolutionary path from the magmatic stage to the hydrothermal stage can be clearly demonstrated, providing a spatialized view for subsequent mineralization potential prediction and improving prediction accuracy.

[0101] Step S204 : Compare and verify the three-dimensional model with field geological exploration data, adjust the fractionation coefficient α and the Nb / Sn threshold, and output a calibrated magma-hydrothermal evolution model.

[0102] Among them, the field geological exploration data includes the spatial location and element enrichment characteristics of known rocks / ore bodies. The obtained three-dimensional model is compared with the field geological exploration data to verify the accuracy of the model. For example, whether the actual ore body location overlaps with the predicted high potential area, if the prediction deviation exceeds a certain range (such as 20%), the fractionation coefficient α, initial δ 11 The B value and Nb / Sn threshold are calibrated to optimize the model prediction results.

[0103] For example, suppose that in actual exploration, the FeO T / MgO ratio is 15, Nb concentration is 70 ppm, δ 11 The B value is -9‰, which is consistent with the high hydrothermal potential area predicted by the model. By comparing with the actual data, if there is any deviation, the model parameters such as α value and Sn threshold are adjusted to optimize the final model.

[0104] In the above embodiment, the magma-hydrothermal evolution model of tourmaline is established, which provides an innovative tool for the effective exploration of rare metal deposits. T Comprehensive analysis of data such as the Mg / MgO ratio, B isotopes, and trace elements, along with the construction of a three-dimensional model, effectively predicts potential mineralization areas in both the magmatic and hydrothermal phases. Finally, comparison and verification with field geological exploration data ensured the accuracy and reliability of the model. This technical solution not only improves the accuracy of mineral deposit exploration but also provides a viable scientific basis and technical support for exploration in related fields.

[0105] This application provides a method for predicting the mineralization potential of rare metals based on the chemical composition and B isotope of tourmaline, which combines field geological surveys and indoor tourmaline geochemical research to achieve effective positioning of favorable areas for prospecting. First, through systematic field geological surveys of the target area, the occurrence differences of tourmaline in granite, contact zone and surrounding rock are accurately divided, and the distribution characteristics of different types of tourmaline are identified. Secondly, combined with microlithographic analysis, the multi-stage ring-shaped structure of tourmaline is identified, and the FeO T The quantitative correlation between the Mg / MgO ratio and hydrothermal evolution provides a geological context for the mineralization process. Using EPMA coupled with LA-ICP-MS, systematic and simultaneous major and trace element and B isotope data for tourmaline were obtained, revealing key geochemical characteristics of the magmatic-hydrothermal transition phase, particularly the variations in the contents of elements such as Nb and Sn and their B isotope values ​​in tourmaline. Based on B isotope simulations, a regional magmatic-hydrothermal evolution model was constructed, revealing the relationship between magmatic and hydrothermal evolution during tourmaline crystallization and providing theoretical support for subsequent prospecting. Finally, a correlation between the degree of magmatic-hydrothermal evolution and favorable prospecting areas was established. Combined with characteristic element thresholds (e.g., Nb > 10 ppm and Sn > 100 ppm), mineralization potential was assessed, ultimately identifying favorable prospecting areas with high potential.

[0106] The following are specific examples of the rare metal mineralization potential prediction method of this application in actual research process:

[0107] The Huoshbulak rare metal granite in Xinjiang is a newly discovered Nb-REE mineralized rock mass in recent geological surveys. Previous work has shown that the whole-rock niobium content of this rock mass mostly exceeds the cut-off grade, and multiple Nb and REE ore bodies have developed around the edges of the rock mass. The main economic minerals include columbite-tantalite, fluorocerium lanthanum ore, and fluorocarbon calcium cerium ore, indicating great mineralization potential. Therefore, for this favorable prospecting area, the rare metal mineralization potential prediction method proposed in this application is adopted. The detailed technical solution is as follows:

[0108] 1. Obtain the field geological characteristics of the target area: Conduct a geological survey of the route of the mineralized rock mass and find that tourmaline is widely developed in the rock mass. Figure 3 Further 1:500 large-scale profile measurements were conducted at the boundary of the rock mass, revealing that the tourmaline in the rock mass is mainly disseminated. Among them, a, b, and c are subhedral-allomorphic disseminated tourmaline in the granite of the Hoshbulak rock mass; d and e are micrographs of disseminated tourmaline (single polarization), with the core showing brown-yellow pleochroism (Tur-DB) and the edge showing blue-green pleochroism (Tur-DG); f is a backscattered image of disseminated tourmaline, with orange circles and blue circles with numbers representing the boron isotope analysis positions and corresponding δ 11B value, Tur = tourmaline, Qtz = quartz, Kf = potassium feldspar, Zr = zircon.

[0109] Reference Figure 4 A large number of tourmaline-quartz cysts appear at the top and edge of the rock mass. a, b, and c are field photos of tourmaline-quartz cysts in the Hoshbulak rock mass, showing a typical core-mantle-edge structure; d and e are sieve-like structures formed by the intergrowth of tourmaline and quartz, with a yellow-brown core (Tur-OB) and a blue-green edge (Tur-OG). The orange circles and the blue circles with numbers represent the boron isotope analysis positions and the corresponding δ 11 B value; f is the two-stage growth structure of tourmaline in the backscattered image, Tur=tourmaline, Qtz=quartz.

[0110] Reference Figure 5 A large number of tourmaline-quartz veins appeared in the contact zone between the edge of the rock mass and the surrounding rock. a, b, and c are field photos of tourmaline-quartz veins in the Hoshbulak rock mass; d and e are the ring zoning characteristics of tourmaline in the veins under single polarization. The orange and blue circles with numbers represent the boron isotope analysis positions and the corresponding δ 11 B value; f is the tourmaline ring in the backscattered image, Tur = tourmaline, Qtz = quartz.

[0111] A typical cyst consists of a columnar tourmaline core, a tourmaline-quartz mantle, and a light-colored rim. The core is primarily composed of euhedral columnar tourmaline clusters and minor quartz, while the mantle is composed of intergrown tourmaline and quartz. The rim is a fine-grained granite structure devoid of dark minerals. Tourmaline-quartz veins typically range in width from a few millimeters to tens of centimeters and in length from a few meters to several hundred meters. The primary minerals are tourmaline, quartz, and minor mica and fluorite. Hand specimens were observed for each type of tourmaline, and their mineralogical characteristics and occurrence patterns were carefully documented. A systematic collection of different sample types was conducted.

[0112] 2. Micropetrographic identification of tourmaline multi-stage growth information: Polarized light microscopy and BSE imaging observations were conducted on three types of samples collected in the field, and five types of tourmaline were identified, namely:

[0113] (1) Disseminated tourmaline that coexists with feldspar and quartz in the granite matrix. This type of tourmaline has a brown to yellowish brown core (HS-DB) and a blue-green rim (HS-DG) under single polarized light.

[0114] (2) Tourmaline in quartz cysts, with a brown to yellowish-brown core (HS-OB) and a bluish-green rim (HS-OG) under single polarized light;

[0115] (3) Tourmaline in tourmaline-quartz veins (HS-V).

[0116] 3. Obtain the main and trace components and B isotope characteristics of tourmaline: Use EPMA to analyze the main element composition (SiO2, TiO2, Al2O3, FeO T , MnO, MgO, CaO, Na2O, KO, F, and Cl) were analyzed. The trace element (Li, Zn, Ga, Sr, Nb, Sn, La, Ce, etc.) and B isotope composition of the tourmaline were analyzed using LA-ICP-MS. Based on the petrographic and geochemical characteristics of the tourmaline, the brown core of the disseminated tourmaline is determined to be magmatic tourmaline crystallized from residual melt in the late magmatic stage. The brown tourmaline in the cystic bodies is determined to be magmatic tourmaline crystallized from exsolved boron-rich melt. The blue-green accretionary rims of the disseminated and cystic tourmaline are hydrothermal accretionary rims formed by exsolved fluids, while the vein-like tourmaline formed during another boron-rich melt / fluid pulse.

[0117] 4. Construction of a geological model of magma-hydrothermal evolution: δ 11 B ranges from -12.6‰ to -5.2‰. Among them, brown-yellow tourmaline has a more negative δ 11 B range (-12.6‰ to -10.0‰), while the blue-green tourmaline overgrowth edge has a significantly more positive δ 11 B range (-10.2‰ to -4.9‰).

[0118] Reference Figure 6 , combined with the distribution coefficients between tourmaline and melt and between tourmaline and fluid, the Rayleigh fractionation simulation of tourmaline B isotope is carried out. Among them, the Rayleigh fractionation simulation of B isotope between (a) melt and magmatic tourmaline and (b) fluid and hydrothermal tourmaline is carried out. The initial δ 11 The B values ​​are set to -12.34‰ and -8.29‰ respectively, and the violin plots show the B isotope composition ranges of different types of tourmaline. The results show that as the δ 11 The B value gradually increases, and the rock body → tourmaline-quartz vesicles → vein body presents a continuous evolution process from magma stage to magma-hydrothermal transition stage and then to hydrothermal stage.

[0119] 5. Prediction of rare metal mineralization potential: Based on the above results, refer to Figure 7The box plots for some major elements (apfu, a-d) and trace elements (ppm, e-k) in the tourmaline of the Hoshbulak pluton are shown. The results show that in terms of major elements, the Fe and Ti contents decrease, while the Al and X-vac contents increase, from HS-DB to HS-OB to HS-DG to HS-OG to HS-V. In terms of trace elements, vein tourmaline (HS-V) and early brown tourmaline (HS-DB and HS-OB) have higher concentrations of Sc, Ga, Sr, Sn, and Nb, and lower concentrations of Li, than late blue-green tourmaline (HS-DG and HS-OG). In terms of B isotopes, tourmaline of HS-OB, HS-DB, and HS-V types shows a relatively narrow δ 11 B range, respectively, are -11.8‰ to -10.2‰, -12.6‰ to -10.0‰, and -11.7‰ to -10.1‰. In contrast, the δ 11 The B value range is higher, ranging from -9.8‰ to -7.4‰ (average -8.7‰, n=32) and -10.2‰ to -5.2‰ (average -8.2‰, n=29). T / MgO ratio, trace elements Nb>10 ppm, Sn>100 ppm, and high δ 11 The three B-value indicators identified a favorable prospecting zone for Nb and REE within 200 meters of the HS-V. Verification revealed two vein-like ore bodies within this favorable prospecting zone.

[0120] The embodiments of the present application also disclose a rare metal mineralization potential prediction system.

[0121] A rare metal mineralization potential prediction system, the prediction system comprising:

[0122] A data acquisition module is used to obtain tourmaline distribution data in the target area; wherein the tourmaline distribution data includes the occurrence type and spatial distribution information of tourmaline samples in granite, the contact zone between rock mass and surrounding rock, and the surrounding rock;

[0123] Identification module, used to perform microlithographic analysis on tourmaline samples based on tourmaline distribution data, and identify different genetic types and zoning structural characteristics of tourmaline samples;

[0124] An element detection module is used to detect major and trace elements in tourmaline samples based on the ring-band structure characteristics and obtain major and trace element data;

[0125] Evolution model building module for FeO based on major element data TThe MgO ratio and the Nb and Sn contents in the trace element data, combined with the B isotope δ 11 B value, to establish a magma-hydrothermal evolution model;

[0126] Characteristic element threshold determination module, used to determine the characteristic element threshold of rare metal mineralization potential based on the magma-hydrothermal evolution model;

[0127] The module for determining favorable prospecting areas is used to determine favorable prospecting areas in the target area based on tourmaline distribution data and characteristic element thresholds.

[0128] An implementation of the evolution model building module includes:

[0129] Phase division unit for FeO based on major element data T The magmatic-hydrothermal evolution stages of the tourmaline samples were divided according to the MgO ratio to generate stage classification results;

[0130] Parameter determination unit, used to determine the phase classification results and B isotope δ 11 B value, to determine the B isotope fractionation coefficient α and the melt / fluid residual ratio f;

[0131] 3D model building unit for FeO-based T / MgO ratio, Nb and Sn contents in trace element data, as well as fractionation coefficient α and residual ratio f, to construct a three-dimensional model of the magma-hydrothermal evolution path;

[0132] The model calibration unit is used to compare and verify the three-dimensional model with field geological exploration data, adjust the fractionation coefficient α and Nb / Sn threshold, and output the calibrated magma-hydrothermal evolution model.

[0133] A rare metal mineralization potential prediction system of an embodiment of the present application can implement any of the above-mentioned prediction methods, and the specific working processes of each module in the prediction system can refer to the corresponding processes in the above-mentioned method embodiments.

[0134] In the several embodiments provided in this application, it should be understood that the provided methods and systems can be implemented in other ways. For example, the system embodiments described above are merely illustrative; for example, the division of a module is merely a logical functional division, and in actual implementation, other division methods may be used, such as combining or integrating multiple modules into another system, or ignoring or not implementing certain features.

[0135] The embodiment of the present application also discloses a computer device.

[0136] A computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, a method for predicting the mineralization potential of rare metals as described above is implemented.

[0137] The embodiment of the present application also discloses a computer-readable storage medium.

[0138] A computer-readable storage medium stores a computer program that can be loaded by a processor and executed by any one of the above-mentioned methods for predicting rare metal mineralization potential.

[0139] Among them, computer-readable storage media can be any tangible medium that contains or stores a program that can be used by or in combination with an instruction execution system, apparatus or device; the program code contained on the computer-readable medium can be transmitted using any appropriate medium, including but not limited to wireless, wire, optical cable, RF, etc., or any suitable combination of the above.

[0140] It should be noted that, in the above embodiments, the description of each embodiment has different emphases. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0141] The above are all preferred embodiments of the present application and are not intended to limit the scope of protection of this application. Unless otherwise specified, any feature disclosed in this specification (including the abstract and drawings) may be replaced by other equivalent or similar features. In other words, unless otherwise specified, each feature is merely an example of a series of equivalent or similar features.

Claims

1. A method for predicting rare metal mineralization potential, characterized in that: The prediction method comprises: Acquire tourmaline distribution data in the target area; wherein the tourmaline distribution data includes the occurrence type and spatial distribution information of tourmaline samples in granite, the contact zone between rock mass and surrounding rock, and the surrounding rock; Based on the tourmaline distribution data, performing microlithographic analysis on the tourmaline sample to identify the genetic type and zoning structure characteristics of the tourmaline sample; According to the genesis type and ring-band structure characteristics of the tourmaline sample, the major element and trace element data of the tourmaline sample are detected to obtain the major element data and the trace element data; Based on the FeO in the main element data T The ratio of MgO and the contents of Nb and Sn in the trace element data, combined with the B isotope δ 11 B value, to establish a magma-hydrothermal evolution model; Determine the characteristic element thresholds of rare metal mineralization potential based on the magma-hydrothermal evolution model; Determining a favorable prospecting area in a target area based on the tourmaline distribution data and characteristic element thresholds; The steps of establishing the magma-hydrothermal evolution model include: Based on the FeO in the main element data T The magmatic-hydrothermal evolution stages of the tourmaline samples were divided according to the MgO ratio to generate stage classification results; According to the stage classification results and the B isotope δ 11 B value, to determine the B isotope fractionation coefficient α and the melt / fluid residual ratio f; Based on the FeO T / MgO ratio, the Nb and Sn contents in the trace element data, the fractionation coefficient α and the residual ratio f, to construct a three-dimensional model of the magma-hydrothermal evolution path; wherein the X-axis of the three-dimensional model represents FeO T / MgO ratio, Y axis represents δ 11 B value, z axis represents Nb / Sn concentration; The three-dimensional model is compared and verified with field geological exploration data, the fractionation coefficient α and the Nb / Sn threshold are adjusted, and the calibrated magma-hydrothermal evolution model is output.

2. The method for predicting rare metal mineralization potential according to claim 1, wherein: The genesis type and ring-band structure characteristics of the tourmaline sample were obtained by observing the tourmaline color, crystal form and mineral symbiosis through a polarizing microscope, combined with backscattered electron imaging technology.

3. The method for predicting rare metal mineralization potential according to claim 1, wherein: The main element data include SiO2, TiO2, Al2O3, FeO T , MnO, MgO, CaO, Na2O, K2O, F and Cl, the major element data are obtained by electron probe detection; the trace element data include Li, Zn, Ga, Sr, Nb, Sn, La, Ce, the trace element data and the B isotope δ 11 The B value was obtained by laser ablation inductively coupled plasma mass spectrometry.

4. A method for predicting rare metal mineralization potential according to claim 3, characterized in that: The formula for determining the melt / fluid residual ratio f is: d 11 B melt(fluid) =d 11 B initial melt（fluid） +(α−1)ln(f); In the above formula, δ 11 B melt(fluid) represents the δ in the melt / fluid at different stages of crystallization evolution 11 B value, δ 11 B initial melt（fluid） represents the δ in the initial melt / fluid 11 B value.

5. A method for predicting rare metal mineralization potential according to any one of claims 1 to 4, characterized in that: The characteristic element thresholds are: Nb content>10 ppm, Sn content>100 ppm; The determination of the favorable prospecting area is based on the following conditions: the tourmaline occurrence type is vein-like or cystic and meets the characteristic element threshold.

6. A rare metal mineralization potential prediction system, characterized in that: A method for predicting rare metal mineralization potential according to any one of claims 1 to 5, wherein the prediction system comprises: A data acquisition module is used to acquire tourmaline distribution data in a target area; wherein the tourmaline distribution data includes the occurrence type and spatial distribution information of tourmaline samples in granite, the contact zone between rock mass and surrounding rock, and the surrounding rock; an identification module for performing microlithographic analysis on the tourmaline sample based on the tourmaline distribution data to identify the genetic type and ring-zone structure characteristics of the tourmaline sample; An element detection module, configured to detect major elements and trace elements of the tourmaline sample according to the ring-shaped structural characteristics, and obtain major element data and trace element data; Evolution model building module, used for FeO based on the main element data T The ratio of MgO and the contents of Nb and Sn in the trace element data, combined with the B isotope δ 11 B value, to establish a magma-hydrothermal evolution model; A characteristic element threshold determination module is used to determine the characteristic element threshold of rare metal mineralization potential based on the magma-hydrothermal evolution model; A module for determining a favorable prospecting area is used to determine a favorable prospecting area in a target area based on the tourmaline distribution data and characteristic element thresholds; and the evolution model establishment module includes: The stage division unit is used for FeO based on the main element data. T The magmatic-hydrothermal evolution stages of the tourmaline samples were divided according to the MgO ratio to generate stage classification results; A parameter determination unit is used to determine the parameters of the phase classification result and the B isotope δ 11 B value, to determine the B isotope fractionation coefficient α and the melt / fluid residual ratio f; Three-dimensional model building unit for the FeO T / MgO ratio, the Nb and Sn contents in the trace element data, the fractionation coefficient α and the residual ratio f, to construct a three-dimensional model of the magma-hydrothermal evolution path; wherein the X-axis of the three-dimensional model represents FeO T / MgO ratio, Y axis represents δ 11 B value, z axis represents Nb / Sn concentration; The model calibration unit is used to compare and verify the three-dimensional model with field geological exploration data, adjust the fractionation coefficient α and the Nb / Sn threshold, and output the calibrated magma-hydrothermal evolution model.

7. A computer device, characterized in that: The method comprises a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the method according to any one of claims 1 to 5 when executing the program.

8. A computer-readable storage medium, characterized in that: A computer program is stored which can be loaded by a processor and execute the method according to any one of claims 1 to 5.

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