Method for predicting lithium mineralization potential in pegmatites based on tourmaline spectral characteristics

Abstract

The present invention discloses a method for predicting the potential for pegmatite lithium mineralization based on the optical spectral characteristics of tourmaline and belongs to the field of mineral exploration technology. The method comprises the steps of: taking pegmatite samples at different borehole depths and classifying tourmaline samples from the taken pegmatite samples under a microscope; performing elemental measurements on the classified tourmaline; acquiring optical spectral data by performing spectroscopic measurements on the classified tourmaline using a spectrometer; extracting and processing optical spectral characteristic parameters; constructing a spectroscopic database after acquiring the spectroscopic characteristics of different types of tourmaline; constructing a correlation diagram between spectroscopic characteristic values ​​and lithium content based on the spectroscopic database; and finally, deriving the results of the potential evaluation of pegmatite-type lithium mineralization based on the spectroscopic characteristic values ​​of different types of tourmaline. The present invention enables accurate identification of pegmatite-type lithium mineralization and possesses advantages such as eliminating the need for large-scale data processing, having a wide range of applications, and high precision, thereby providing a powerful tool for studying geological evolution and mineral formation mechanisms.

Description

Technology Field

[0001] The present invention relates to the field of mineral exploration technology, and more specifically, to a method for predicting the lithium mineralization potential of pegmatite based on the optical spectrum characteristics of tourmaline. Background Technology

[0002] Pegmatites are generally formed during the magmatic stage and are genetically closely related to various intrusive rocks. Pegmatites consist of coarse to large-grained vein-like or lumpy rock bodies, and tourmaline exists within them in the form of coarse to large-grained crystals. In the early stages of pegmatite mineral formation, tourmaline coexists with minerals such as mica, quartz, and feldspar; in later stages, tourmaline with a compositional edifice structure is formed, characterized by a richer content of trace elements and rare elements (e.g., Li, Be, La, Nb, Ta, W, Sn, U, Th, etc.).

[0003] Pegmatite-type lithium resources are gradually becoming a major source of lithium due to their advantages, such as large thickness, high grade, ease of mining, and high value for comprehensive development and utilization. Currently, there is a lack of intuitive methods to determine the evolutionary process of pegmatites and the corresponding mineral formation conditions, and the formation of different types of pegmatite-type tourmaline typically entails the mineralization of rare earth metals. Based on these changes, the degree of rare earth metal mineralization can be determined through geochemical methods, geophysical methods, geological modeling and spatial analysis, machine learning and data mining, and comprehensive methods. This allows for the identification of the origin of pegmatites, guidance of mineral exploration, reflection of geological evolutionary processes, and promotion of mineral resource development. Furthermore, it enables the reduction of initial indiscriminate exploration, the narrowing of exploration scope, the identification of target areas rich in mineral resources, and the optimization of mining strategies.

[0004] (1) Geochemical methods: These are a series of technical means to study the chemical properties and geochemical processes of geological bodies by analyzing the chemical elements and isotopic composition of rocks, soils, water, and other geological materials, and further to identify mineralization anomalies and predict the location of ore deposits. Examples include whole-rock analysis, trace element analysis, isotopic analysis, fluid inclusion analysis, and soil geochemical measurement methods. These methods help to identify geochemical characteristics related to the chemical composition of rocks, the rules of elemental distribution, and mineral formation processes. ① Whole-rock analysis: This involves analyzing the total chemical composition of pegmatites to determine the content and distribution of lithium. This method is expensive, time-consuming, and requires the analysis of a large volume of samples.

[0005] ② Trace Element Analysis: Trace elements such as rubidium (Rb) and cesium (Cs) in pegmatite are analyzed. Since these elements often occur together with lithium, they can be used as indicator elements for lithium mineralization. However, complex analytical techniques are required, and specialized knowledge may be necessary for interpreting the results.

[0006] ③ Isotope analysis: Lithium isotopes (e.g., 7 Li and 6 The origin and incubation process of lithium are identified by utilizing changes in the ratio of Li. This method is technically complex, costly, and requires specialized laboratory equipment.

[0007] (2) Geophysical method: A technical means of exploring differences in underground geological structures and physical properties by utilizing changes in geophysical fields (gravitational field, magnetic field, electric field, etc.). By measuring and analyzing these physical field anomalies, it is possible to estimate the type, structure, and distribution of underground rocks and identify physical characteristics related to mineralization.

[0008] ① Magnetic Exploration: This method identifies the distribution of magnetic minerals within pegmatites through magnetic anomalies and indirectly estimates the distribution and structure of the pegmatites. This method requires specialized knowledge for interpreting magnetic anomalies and is heavily influenced by environmental factors.

[0009] ② Electrical Exploration: Methods such as resistivity and induced polarization are used to identify the electrical properties of pegmatites and evaluate their lithium mineralization potential. This method requires complex equipment and data processing technology, and is relatively expensive.

[0010] (3) Geological modeling and spatial analysis: Geological modeling intuitively represents the spatial distribution and structural characteristics of geological bodies by constructing a three-dimensional geological model using geological data (boreholes, outcrops, geophysical and geochemical data, etc.). Spatial analysis processes and analyzes geological data using tools such as Geographic Information Systems (GIS) and identifies spatial relationships and patterns between geological bodies to provide a basis for predicting mineralization potential.

[0011] ① 3D Geological Modeling: A 3D geological model of pegmatite is constructed, and lithium mineralization zones are predicted by integrating geological, geophysical, and geochemical data. This method requires a large amount of prior data, and the modeling process is complex.

[0012] ② GIS Spatial Analysis: Geographic Information System (GIS) technology is used to analyze the spatial relationships between the distribution rules of pegmatites and geological elements related to lithium mineralization. This method requires high-quality geological data and specialized knowledge for data processing and analysis.

[0013] ③ Structural Analysis: This involves studying the structural background of pegmatites (fault zones, magmatic activity, etc.) to identify structural environments favorable for mineral formation. This method requires detailed geological background knowledge, and subjectivity may be involved in the interpretation of the results.

[0014] (4) Remote sensing and spectroscopic analysis:

[0015] ① Hyperspectral Remote Sensing: Hyperspectral remote sensing data is used to identify the optical spectral characteristics of specific minerals (tourmaline, lithium mica, etc.) within pegmatites and to evaluate their lithium mineralization potential. This method involves complex data processing and is heavily influenced by weather and topography.

[0016] ② Thermal Infrared Remote Sensing: Thermal infrared remote sensing data is used to identify thermal anomalies in pegmatites and estimate lithium-enriched zones. However, this method is susceptible to external environmental influences and has low resolution, making it difficult to accurately identify minerals.

[0017] (5) Machine Learning and Data Mining: Machine learning is an artificial intelligence technology that automatically learns patterns and rules from large amounts of data by building algorithmic models. Data mining is the process of extracting useful information and knowledge from large amounts of data. In predicting mineralization potential, machine learning and data mining technologies can integrate various geological, geophysical, and geochemical data to identify features and patterns related to mineralization and build prediction models.

[0018] ① Supervised Learning: Machine learning models are trained using geological, geophysical, and geochemical data from known lithium mineralization zones to predict the lithium mineralization potential of unknown zones. This method requires a large amount of training data and has low interpretability of the model.

[0019] ② Unsupervised Learning: Geological features and patterns related to lithium mineralization are identified through methods such as cluster analysis. This method requires specialized knowledge to interpret the results and may necessitate multiple iterations.

[0020] ③ Multi-source Data Fusion: This method integrates various data sources (geological, geophysical, geochemical, and remote sensing data, etc.) and utilizes data mining techniques to identify potential lithium mineralization zones. This approach involves a complex data fusion process and requires specialized skills and tools.

[0021] In summary, current methods for predicting the lithium mineralization potential of pegmatites have the following disadvantages.

[0022] (1) It requires large-scale data sampling and complex processing and computation, and a related mathematical model must be built based on the processed data.

[0023] (2) The cost is excessively high and there is subjectivity in the interpretation of the data.

[0024] (3) It is not possible to accurately reflect and simulate the formation of mineral formation conditions.

[0025] (4) A comprehensive analysis must be performed by combining a large amount of geological information. The problem to be solved

[0026] The objective of the present invention is to provide a method for predicting the lithium mineralization potential of pegmatite based on the optical spectrum characteristics of tourmaline to solve the above problem. means of solving the problem

[0027] To realize the above objective, the technical solution adopted by the present invention is as follows: a method for predicting the lithium mineralization potential of pegmatite based on tourmaline optical spectrum characteristics, wherein

[0028] 1) A step of taking pegmatite samples from different borehole depths, classifying the taken samples under a microscope using a mineralophore microscope, and performing elemental measurements on the tourmaline among the classified pegmatite samples;

[0029] 2) A step of acquiring optical spectrum data by performing spectroscopic measurements on tourmaline among classified pegmatite samples using a spectrometer;

[0030] 3) A step of extracting and processing optical spectrum feature parameters;

[0031] 4) A step of constructing a spectroscopic database after acquiring the spectroscopic characteristics of different types of tourmaline;

[0032] 5) a step of constructing a diagram of the interrelationship between spectroscopy and lithium content; and

[0033] 6) A step of deriving the results of a potential evaluation of pegmatite-type lithium mineralization based on tourmaline optical spectrum characteristics according to the cross-relationship diagram obtained in step 5).

[0034] As a desirable technical solution, in step 1), the mineral microscope instrument is a digital polarizing microscope, classifies different types of tourmaline through features under the microscope, and performs elemental measurements on different types of tourmaline. The elemental measurements include measurements of major constituent elements and trace elements, and the features under the microscope include interference colors, texture, structure, symbiotic minerals, etc.

[0035] As a more desirable technical solution, the measurement of the major component elements is performed by adopting the JXA-iSP100 type electron probe microscope analyzer of Japan Electronics (JEOL), and the measurement of trace elements is performed by adopting the Element I type inductively coupled plasma mass spectrometer (Finnigan MAT LA-ICP-MS).

[0036] As a desirable technical solution, the specific method of the analysis in step 2) is to: wash and dry the sample before testing to prevent impurities from affecting the optical spectrum characteristics; perform point spectroscopic measurements on the classified tourmaline sample using a CSD350 full-wave band indicator spectrometer, and perform at least three optical spectrum measurements on the sample, preferably to calculate an average value after three measurements to ensure the accuracy of the sample data.

[0037] As a desirable technical solution, in Step 3), the Jiangsu Institute of Optical Spectrum Detection and Intelligent Cognitive Technology in China ( The Mineral Optical Spectrum Analysis Expert System (hereinafter referred to as 'MSA') developed by ) and Junggo Remote Sensing Information Technology Co., Ltd. ( We have adopted the optical spectrum geologist analysis software (hereinafter referred to as 'TSG') developed by the Commonwealth Scientific and Industrial Research Organisation (CSIRO) of Australia, which was introduced by ) to extract and process optical spectrum feature parameters, process optical spectrum data through MSA to derive optical spectrum feature and reflectance values, and derive absorption depth values ​​using TSG.

[0038] As a desirable technical solution, in step 4), spectroscopic characteristics of different types of tourmaline are derived based on MSA and TSG to construct a spectroscopic database, and statistical analysis is performed on the derived optical spectrum characteristics of different types of tourmaline to derive optical spectrum wavelength bands in which different types of tourmaline have an indicative meaning.

[0039] As a desirable technical solution, the method of constructing a diagram of the interrelationship between spectrometry and lithium content in step 5) is,

[0040] First, the task involves establishing a coupling relationship between wavelength bands with different indicative meanings and lithium content; that is, conducting a study on the coupling relationship between the spectral characteristics of different types of tourmaline and lithium content, and then deriving a quantitative inversion model between the optical spectral characteristics of wavelength bands with different indicative meanings and lithium content—namely, a diagram of the interrelationship between spectroscopy and lithium content.

[0041] As a desirable technical solution, the method for evaluating the potential of pegmatite-type lithium mineralization in step 6) is,

[0042] Based on the above diagram, tourmaline with different lithium contents is classified, and by reclassifying it according to lithium content into mineral-free, rarefaction, and richness tourmaline, an assessment of the potential for pegmatite-type lithium mineralization based on the optical spectrum characteristics of tourmaline is derived.

[0043] The formation of tourmaline is influenced by geological conditions such as temperature and pressure, and under different geological conditions, the chemical composition and short-wave infrared spectral characteristics of tourmaline exhibit corresponding changes. As the lithium content in tourmaline increases, the absorption peak of short-wave infrared radiation enlarges, the H2O wavelength (1900 nm) shifts toward the long-wave direction, and the Al-OH wavelength (2200 nm) shifts toward the short-wave direction. By measuring and analyzing the short-wave infrared optical spectral characteristics of tourmaline, identifying characteristic absorption bands associated with lithium content, and establishing a quantitative relationship between optical spectral characteristics and lithium content, the lithium mineralization potential of pegmatite is predicted.

[0044] The method of the present invention can be used to relatively intuitively elucidate the geological process of pegmatite formation by calculating the optical spectrum characteristics and lithium content of pegmatite-type tourmaline, and to study the formation conditions and evolutionary history of minerals within pegmatites and the mineral formation rules of rare metal mineral resources.

[0045] The present invention adopts methods such as short-wave infrared optical spectrum technology, microscopic observation, and electron probes to construct a correlation diagram and a quantitative inversion schematic of lithium content, and determines the coupling relationship between optical spectrum features and lithium content using a physical model-based method. Effects of the invention

[0046] Compared to conventional technology, the advantages of the present invention are as follows. The short-wave infrared prediction method possesses the capability for rapid measurement in the field; by combining MSA and TSG, optical spectrum data can be converted into intuitive charts and models, thereby simplifying data interpretation and reducing subjectivity. Through the analysis of optical spectrum features, information on minerals and surrounding rocks can be effectively extracted without relying on dating or elemental analysis steps; and by establishing a quantitative relationship between optical spectrum features and lithium content to implement back-calculation estimation of lithium content, the potential for lithium mineralization can be effectively evaluated. Compared to other traditional methods, the short-wave infrared prediction method of the present invention features a more efficient and direct back-calculation process, simple and clear result interpretation, and is not constrained by environmental factors, thereby reducing the amount of unnecessary field verification work. This method reduces lithological sampling and experimental analysis by more than 85% and improves prediction accuracy by more than 35%, as shown in Table 1.

[0047] Table 1. Comparison of Different Lithium Content Prediction Methods

[0048] Brief explanation of the drawing

[0049] Figure 1 is a flowchart of the present invention. Figure 2 is a diagram showing the relationship between different types of tourmaline H2O wavelengths (1900 nm) and lithium content in a pegmatite-type lithium ore deposit of an embodiment of the present invention. Figure 3 is a diagram showing the relationship between different types of tourmaline Al-OH wavelengths (2200 nm) and lithium content in a pegmatite-type lithium ore deposit of an embodiment of the present invention. Figure 4 is a diagram classifying the types of light-containing tourmaline with different wavelength characteristics of an embodiment of the present invention. Specific details for implementing the invention

[0050] The present invention will be described in more detail below by combining examples and drawings.

[0051] Example:

[0052] A method for predicting the lithium mineralization potential of pegmatite based on the optical spectrum characteristics of tourmaline comprises the following steps in sequence.

[0053] 1) Pegmatite samples were taken from different borehole depths, classified under a microscope, and elemental measurements were performed. The microscope instrument used was a digital polarizing microscope, and tourmaline was classified into two types based on microscopic characteristics: the magmatic phase and the magmatic-hydrothermal phase. Principal element measurements were performed using a JXA-iSP100 electron probe microscope analyzer, and trace element measurements were performed using an Inductively Coupled Plasma Mass Spectrometer (Finnigan MAT LA-ICP-MS) Element I. The cation counts of the different types of tourmaline are shown in Table 2.

[0054] Table 2. Water cations of different types of tourmaline

[0055]

[0056] 2) Before testing, the samples are washed and dried to prevent impurities from affecting the optical spectrum characteristics. A CSD350 full-wave band indicator spectrometer is adopted to perform point spectroscopic measurements on the classified tourmaline samples, and three optical spectrum measurements are performed on the samples to ensure the accuracy of the sample data. Spectral information is recorded by arranging the numbers according to the depth of the borehole where the samples are located.

[0057] 3) Optical spectrum feature parameters are extracted and processed using MSA and TSG. Optical spectrum data is processed using MSA to derive optical spectrum features and reflectance values, and absorption depth values ​​are derived using TSG. The optical spectrum wavelength characteristics of different classifications of tourmaline are shown in Table 3.

[0058] Table 3 Optical Spectral Characteristics of Different Types of Tourmaline

[0059]

[0060] 4) A spectroscopic database is constructed by deriving the spectroscopic characteristics of different types of tourmaline based on MSA and TSG, and a statistical analysis is performed on the derived optical spectrum characteristics of different types of tourmaline to derive wavelength bands that have an indicative meaning for different types of tourmaline.

[0061] 5) Establish a coupling relationship between wavelength bands with different indicative meanings and lithium content, that is, conduct a study on the coupling relationship between the spectral characteristic values ​​of different types of tourmaline and lithium content (Table 4), and derive an inverse model diagram between the optical spectral characteristic values ​​of wavelength bands with different indicative meanings and lithium content.

[0062] Table 4 Optical Spectral Characteristics and Lithium Content of Different Types of Tourmaline

[0063]

[0064] 6) Based on the results obtained in Step 5), the potential assessment of pegmatite-type lithium mineralization based on the characteristics of the tourmaline optical spectrum is derived as follows: If the Al-OH wavelength in the short-wave infrared optical spectrum of the tourmaline sample is greater than 2200.8 nm, it indicates that the pegmatite in the region where the sample is located has no potential for lithium mineralization, i.e., that lithium mineralization does not occur. If the Al-OH wavelength is located between 2198.7 nm and 2199.8 nm, it indicates that the pegmatite in the region where the sample is located has a relatively low potential for lithium mineralization, i.e., that lithium-lean mineralization occurs. If the Al-OH wavelength is less than 2198.6 nm, it indicates that the pegmatite in the region where the sample is located has a relatively high potential for lithium mineralization, i.e., that lithium-rich mineralization occurs. Meanwhile, the optical spectral feature boundaries at 1900 nm of lithium-lean mineralized and lithium-rich mineralized tourmaline did not show good correlation (Figs. 2, 3). To address this, a tourmaline optical spectral star model diagram (Fig. 4) was constructed based on optical spectral features at 2200 nm, and this model diagram and prospecting indicator provide strong support for further exploration of pegmatite-type lithium mines.

[0065] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. All modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention shall be included within the scope of protection of the present invention.

Claims

Claim 1 A method for predicting the lithium mineralization potential of pegmatite based on the optical spectral characteristics of tourmaline, comprising: 1) taking pegmatite samples from different borehole depths, classifying tourmaline in the taken pegmatite samples under a microscope using a mineral phase microscope, and performing elemental measurements on the classified tourmaline; 2) acquiring optical spectral data by performing spectroscopic measurements on the classified tourmaline using a spectrometer; 3) extracting and processing optical spectral characteristic parameters; 4) constructing a spectroscopic database after acquiring the spectroscopic characteristics of different types of tourmaline; and 5) constructing a diagram of the interrelationship between spectra and lithium content.and 6) a step of deriving a potential evaluation result for pegmatite-type lithium mineralization based on tourmaline optical spectrum characteristics according to the cross-relationship diagram obtained in step 5), wherein in step 1), the mineral phase microscope instrument is a digital polarizing microscope, classifies different types of tourmaline through characteristics under the microscope, performs elemental measurements on different types of tourmaline, and the elemental measurements include measurements of major constituent elements and trace elements, and the specific method of the spectroscopic measurement is to wash and dry the sample before testing, perform point spectroscopic measurements on the classified tourmaline samples by adopting a CSD350 full-wave band indicator spectrometer, and perform at least three optical spectrum measurements on the samples, and in step 4), constructs a spectroscopic database by deriving spectral characteristics of different types of tourmaline based on a mineral optical spectrum analysis expert system and optical spectrum geologist analysis software, and performs statistical analysis on the derived optical spectrum characteristics of different types of tourmaline so that different types of tourmaline have an indicative meaning A method for deriving optical spectrum wavelength bands and, in step 5), constructing a diagram of the interrelationship between spectra and lithium content, wherein the method involves performing coupling studies on the spectral characteristic values ​​and lithium content of different types of tourmaline to derive a quantitative inverse model between the optical spectrum characteristic values ​​of wavelength bands with different indicative meanings and lithium content, i.e., a diagram of the interrelationship between spectra and lithium content; and, in step 6), the method for evaluating the potential of pegmatite-type lithium mineralization, wherein the method involves classifying tourmaline with different lithium contents based on the above-mentioned interrelationship diagram, and reclassifying them according to lithium content into mineralless, rarefied, and rich mineral tourmaline, thereby deriving an evaluation of the potential of pegmatite-type lithium mineralization based on the optical spectrum characteristics of tourmaline, characterized by a method for predicting the potential of pegmatite lithium mineralization based on the optical spectrum characteristics of tourmaline. Claim 2 A method for predicting the lithium mineralization potential of pegmatite based on tourmaline optical spectrum characteristics, wherein, in claim 1, the measurement of the major component elements is performed by adopting a JXA-iSP100 type electron probe microscope analyzer, and the measurement of trace elements is performed by adopting an inductively coupled plasma mass spectrometer (Finnigan MAT LA-ICP-MS) Element I type. Claim 3 A method for predicting the lithium mineralization potential of pegmatite based on tourmaline optical spectrum characteristics, characterized in that, in step 3) of claim 1, optical spectrum geologist analysis software is adopted to extract and process optical spectrum feature parameters, optical spectrum data is processed through a mineral optical spectrum analysis expert system to derive optical spectrum feature and reflectance values, and absorption depth values ​​are derived using optical spectrum geologist analysis software.

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