Geological text data prospecting method and system

Abstract

The invention relates to the technical field of geological data processing, in particular to a prospecting method and system based on geological text data, and the method comprises the following steps: obtaining exploration drilling data, extracting lithologic description, mineral composition and fracture filling conditions of a rock core, calculating the correlation index of drilling depth and mineralization thickness, screening the change trend of ore grade, and obtaining the geological text data. And obtaining mining area borehole lithology distribution data. According to the method, by deeply analyzing drilling data and lithologic characteristics, accurately recognizing a mineralized fluid accumulation area and improving the prediction precision of an ore body occurrence position, boundary control of a mineralized zone is optimized through measurement and calculation of spatial homogeneity, the extension precision of the mineralized zone is enhanced, scientific adjustment of a prospecting range is ensured through detailed analysis of altered mineral characteristics, and the method is suitable for large-scale popularization and application. The reasonability of demarcation of the prospecting target area is improved, multi-dimensional data and parameter analysis are integrated, a complete prospecting logic chain is constructed, and mineral product prediction precision and resource exploration efficiency are remarkably improved.

Description

Technical Field

[0001] The present invention relates to the technical field of geological data processing, and particularly to a method and system for prospecting for minerals from geological text data. Background Art

[0002] The technical field of geological data processing includes the acquisition, storage, analysis, and interpretation of various data types such as geophysical, geochemical, remote sensing images, and geological exploration. The core content of this technical field is to structurally organize geological information using computer technology and data analysis methods, and extract useful information through means such as pattern recognition and data mining. Generally speaking, this field covers multiple directions such as geological exploration data management, mineral prediction, stratigraphic division, and structural analysis, and improves the accuracy of geological research and resource exploration through database technology, big data processing, and artificial intelligence algorithms.

[0003] Among them, a system for prospecting for minerals based on geological text data refers to a technical solution that uses a computer system to process geological text data and extract prospecting information from it. This technical solution is aimed at a large amount of unstructured text data such as geological reports, papers, and survey records during the geological exploration process, and uses natural language processing methods for lexical analysis, syntactic analysis, and entity recognition, and combines a geological knowledge graph to achieve associated reasoning of prospecting information. Specifically, a text data preprocessing method is used for formatting and normalization operations, a feature extraction method is used to identify information such as mineral types, ore deposit characteristics, and metallogenic conditions, and a prospecting potential area is evaluated based on pattern matching and statistical analysis methods.

[0004] In the process of processing geological text data in the prior art, it mainly focuses on the analysis of unstructured data. Although it can extract some mineral-related information, there are deficiencies in the correlation analysis of lithology description, mineral assemblage, and fracture filling characteristics, resulting in a less detailed overall description of the geological characteristics of the mining area. The analysis methods for fracture connectivity and fluid migration paths are relatively single, and cannot accurately reflect the spatial distribution of mineralized fluid accumulation areas, making it easy to deviate in predicting the occurrence position of ore bodies. The spatial homogeneity of mineralization thickness has not been systematically measured, and the accuracy of delineating the boundaries of ore-forming belts is relatively low, affecting the effective control of the mineralization range. The identification of the distribution characteristics of altered minerals is not deep enough, resulting in a decrease in the accuracy of the prospecting adjustment range, and may cause some potential prospecting areas to be missed. The screening method for high-mineralization intervals relies on limited parameters, and there is uncertainty in setting prospecting target areas, affecting the accuracy of prospecting decisions, increasing the exploration cost while increasing the risk of ineffective operations. Summary of the Invention

[0005] The purpose of the present invention is to solve the deficiencies existing in the prior art. Embodiments of the present invention provide a method and system for prospecting for minerals from geological text data. The technical solution is as follows:

[0006] To achieve the above object, the present invention adopts the following technical solutions: A method for prospecting based on geological text data, comprising the following steps:

[0007] S1: Obtain exploration borehole data, extract the lithological description, mineral composition and fracture filling conditions of the core, calculate the correlation index between the borehole depth and the mineralized thickness, screen the change trend of the ore grade, and obtain the lithological distribution data of the borehole in the mining area;

[0008] S2: Based on the lithological distribution data of the borehole in the mining area, calculate the fracture extension direction, filling minerals and fracture zone density, screen the change intervals of fracture connectivity and fluid flow capacity, combine with the mineralization depth, analyze the fluid migration trend, calculate the pressure gradient change rate, screen the fluid enrichment area, and obtain the mineralized fluid migration path data;

[0009] S3: Based on the mineralized fluid migration path data, calculate the occurrence position of the ore body, the mineralization range and the mineral composition ratio, screen the mineralized area, analyze the change of the mineralization intensity on the migration path, and measure the extension range of the mineralized zone to obtain the spatial distribution data of the mineralized zone;

[0010] S4: Based on the spatial distribution data of the mineralized zone, identify the distribution ratio of altered minerals, the thickness of the alteration zone and its spatial relationship with the ore body, screen the adjustment range of prospecting parameters, calculate the adjustment index of the prospecting target area, and obtain the prospecting adjustment data.

[0011] As a further solution of the present invention, the lithological distribution data of the borehole in the mining area includes the ore mineral combination type, the change range of the mineralized thickness, and the change interval of the ore grade; the mineralized fluid migration path data includes the fracture connectivity characteristics, the fluid flow capacity interval, the pressure gradient change rate, and the mineralized fluid aggregation area; the spatial distribution data of the mineralized zone includes the occurrence range of the ore body, the distribution of the mineralization degree, the mineral composition ratio of the ore, and the extension direction of the mineralized zone; the prospecting adjustment data includes the altered mineral type, the thickness of the alteration zone, the spatial correspondence between the alteration zone and the ore body, and the characteristic parameters of the prospecting target area.

[0012] As a further solution of the present invention, the specific steps of obtaining the exploration borehole data, extracting the lithological description, mineral composition and fracture filling conditions of the core, calculating the correlation index between the borehole depth and the mineralized thickness, and screening the change trend of the ore grade to obtain the lithological distribution data of the borehole in the mining area are as follows:

[0013] S101: Obtain exploration borehole data, extract the lithological description, ore color, mineral composition and fracture filling conditions of the borehole core, classify the borehole data, calculate the mineral content ratio and the fracture filling value, and obtain the mineral index data of the borehole core;

[0014] S102: Based on the mineral index data of the borehole cores, analyze the change rate of mineral content and the distribution range of key minerals, screen the mineral distribution gradient in different borehole depth ranges, calculate the thickness value of the mineralized layer, establish the corresponding relationship between borehole depth and mineralization thickness, count the mineralized layer thickness at different depths, screen the depth interval where the mineralized layer thickness index is concentrated, and obtain the mineralized layer thickness index data;

[0015] S103: Invoke the mineralized layer thickness index data, analyze the amplitude of the change in ore grade with depth, screen the fluctuation range of ore grade, count the average value and variation degree of ore grade in the depth interval, and obtain the lithological distribution data of the boreholes in the mining area.

[0016] As a further solution of the present invention, based on the lithological distribution data of the boreholes in the mining area, calculate the fracture extension direction, filling minerals and fracture zone density, screen the change interval of fracture connectivity and fluid flow ability, combine with the mineralization depth, analyze the fluid migration trend, calculate the change rate of pressure gradient, screen the fluid enrichment area, and the specific steps for obtaining the mineralized fluid migration path data are as follows:

[0017] S201: Based on the lithological distribution data of the boreholes in the mining area, calculate the fracture extension direction, filling minerals and fracture zone distribution density, classify the fracture azimuth angle, extension length and filling mineral types, calculate the fracture distribution density, and obtain the fracture distribution value;

[0018] S202: Invoke the fracture distribution value, screen the change interval of fracture connectivity and fluid flow ability, analyze the influence of fracture width and filling minerals on fluid flow ability, count the fracture permeability coefficient at different depths, calculate the change amplitude of fluid migration rate, screen the area with prominent fluid flow, combine with the mineralization depth data revealed by the boreholes, and calculate the change rate of pressure gradient during fluid migration to obtain the fluid migration pressure change result;

[0019] S203: Based on the fluid migration pressure change result, screen the mineralized fluid aggregation area, calculate the mineralized fluid distribution index in the pressure gradient change area, and obtain the mineralized fluid migration path data.

[0020] As a further solution of the present invention, based on the mineralized fluid migration path data, calculate the occurrence position of the ore body, mineralization range and mineral composition ratio, screen the mineralized area, analyze the change of mineralization intensity on the migration path, and measure the extension range of the mineralized zone to obtain the specific steps of the spatial distribution data of the mineralized zone are as follows:

[0021] S301: Based on the mineralized fluid migration path data, analyze and identify the occurrence position of the ore body and the ore mineral composition ratio, count the mineral content distribution in the mining area, calculate the mineralization thickness in the ore body area, and obtain the spatial distribution data of the ore body;

[0022] S302: Call the spatial distribution data of the ore body, set the threshold of the mineralization thickness, screen the mineralized areas, calculate the change value of the mineralization degree in the differential area, count the fluctuation range of the proportion of the mineral composition in the mineralized area, obtain the change relationship between the mineralization degree and the spatial homogeneity, screen the areas with deviation in mineralization homogeneity, measure the extension range of the mineralized zone, and obtain the spatial change data of the mineralized zone;

[0023] S303: Based on the spatial change data of the mineralized zone, calculate the boundary position of the mineralized zone, count the mineralization thickness index of the mineralization depth, measure the spatial extension value of the mineralized zone, and obtain the spatial distribution data of the mineralized zone.

[0024] As a further solution of the present invention, the specific formula for the mineralization thickness of the ore body area is:

[0025]

[0026] Among them, H m represents the mineralization thickness of the ore body area, C i represents the mineral content at the occurrence depth i of the ore body, d i represents the thickness of the ore body at the depth i, and n represents the total number of layers of the occurrence depth of the ore body.

[0027] As a further solution of the present invention, based on the spatial distribution data of the mineralized zone, to identify the distribution ratio of altered minerals, the thickness of the alteration zone and its spatial relationship with the ore body, and the specific steps for screening the adjustment range of prospecting parameters and calculating the adjustment index of the prospecting target area are:

[0028] S401: Based on the spatial distribution data of the mineralized zone, analyze the distribution ratio of altered minerals, count the types and contents of altered minerals in the mining area, calculate the thickness of the alteration zone at different depths, and obtain the distribution range of altered minerals;

[0029] S402: Call the distribution range of the altered minerals, establish the spatial position relationship between the thickness of the alteration zone and the ore body, obtain the prospecting adjustment range of the mining area, analyze the variation degree of the distribution of altered minerals in the differential area, count the proportion of the overlapping area between the thickness of the alteration zone and the mineralized zone, screen the key alteration areas within the prospecting adjustment range, calculate the prospecting target area index, and count the spatial distribution of the prospecting target area in the differential mining area to obtain the characteristic value of the prospecting target area;

[0030] S403: Based on the characteristic value of the prospecting target area, screen the areas that meet the prospecting conditions, analyze the spatial distribution range of the prospecting target area, and measure the mineralization potential of the differential area to obtain the prospecting adjustment data.

[0031] As a further solution of the present invention, the specific formula for the thickness of the alteration zone at different depths is:

[0032]

[0033] Among them, H eb represents the thickness of the altered zone indicating the depth of differentiation, C eb,j represents the content of altered minerals in the j-th depth interval, D eb,j represents the thickness of the altered zone in the j-th depth interval, W eb,j represents the weighting factor in the j-th depth interval, which is calculated based on the distribution density of altered minerals in the mining area, and m represents the total number of depth intervals in the mining area.

[0034] As a further solution of the present invention, the method further includes S5: Based on the prospecting adjustment data, calculate the extension trend of the prospecting target area, screen high-mineralization intervals, obtain the prospecting feasibility range, analyze the occurrence depth of the ore body, the ore grade and the mineralization continuity, adjust the drilling layout and the exploration scope, adjust the exploration target, and generate a prospecting plan for the high-mineralization area;

[0035] The prospecting plan for the high-mineralization area includes the extension trend of the prospecting target area, the range of high-mineralization intervals, and the prospecting feasibility evaluation result;

[0036] S501: Based on the prospecting adjustment data, analyze the extension trend of the prospecting target area, count the change in the mineralization degree of the differentiated mining area, measure the spatial distribution range of the mineralized area, and obtain the extension value of the prospecting target area;

[0037] S502: Call the extension value of the prospecting target area, screen high-mineralization intervals, calculate the mineralization enrichment degree at the differentiated depth, count the fluctuation range of the mineral content and the ore grade in the mineralized intervals, analyze the spatial variation coefficient of the mineralized intervals, obtain the area with relatively stable mineralization enrichment characteristics, measure the prospecting feasibility range of the differentiated mining area, and identify the mineralization potential of the prospecting area to obtain the prospecting feasibility of the high-mineralization area;

[0038] S503: Based on the prospecting feasibility of the high-mineralization area, screen the areas that meet the prospecting requirements, analyze the potential mineralized thickness of the prospecting area, calculate the spatial distribution index of the prospecting area, and obtain the prospecting plan for the high-mineralization area.

[0039] A prospecting system based on geological text data includes:

[0040] The borehole lithology analysis module obtains exploration borehole data, extracts the lithology description, ore color, mineral composition and fracture filling conditions of the borehole cores, calculates the spatial distribution characteristics of the ore mineral assemblage, and calls the ore grade value to screen the depth change trend interval for the correlation between the borehole depth and the mineralized thickness, so as to obtain the borehole lithology distribution data of the mining area;

[0041] Based on the lithology distribution data of boreholes in the mining area, the fluid migration calculation module calculates the fracture extension direction, filling mineral type, and fracture zone distribution density, screens the variation range of fracture connectivity and fluid flow capacity, calls the mineralization depth parameters revealed by boreholes, calculates the pressure gradient change rate during fluid migration, and obtains the mineralized fluid migration path data;

[0042] Based on the mineralized fluid migration path data, the mineralized zone spatial analysis module calculates the occurrence position of the ore body, the mineralization range, and the proportion of ore minerals, calls the mineralization thickness threshold to screen the mineralized area, measures the variation relationship between the mineralization degree and spatial homogeneity, and obtains the mineralized zone spatial distribution data;

[0043] Based on the mineralized zone spatial distribution data, the prospecting target area screening module calculates the distribution proportion of altered minerals, the thickness of the altered zone, and its spatial position relationship with the ore body, calls the altered distribution characteristics to screen the prospecting adjustment range of the mining area, obtains the prospecting target area indicators, and gets the prospecting adjustment data;

[0044] Based on the prospecting adjustment data, the high-mineralization area evaluation module obtains the extension trend of the prospecting target area, screens the high-mineralization intervals within the prospecting range, calculates the prospecting feasibility range of the mining area, and gets the prospecting plan for the high-mineralization area.

[0045] Compared with the prior art, the advantages and positive effects of the present invention are as follows:

[0046] In the present invention, by deeply analyzing borehole data and lithological characteristics, the mineralized fluid aggregation area is accurately identified, the prediction accuracy of the occurrence position of the ore body is improved, the boundary control of the mineralized zone is optimized by measuring the spatial homogeneity, the extension accuracy of the ore-forming zone is enhanced, the detailed analysis of the altered mineral characteristics ensures the scientific adjustment of the prospecting range, improves the rationality of the delineation of the prospecting target area, integrates multi-dimensional data and parameter analysis, constructs a complete prospecting logic chain, and significantly improves the mineral prediction accuracy and resource exploration efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0048] Figure 1 It is a schematic flow chart of the steps of the present invention;

[0049] Figure 2 It is a system module diagram of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0050] The following will describe the technical solutions in the present invention with reference to the drawings.

[0051] In the embodiments of the present invention, words such as "exemplarily" and "for example" are used to represent examples, illustrations or explanations. Any embodiment or design solution described as an "example" in the present invention should not be construed as being more preferred or having more advantages than other embodiments or design solutions. Rather, the use of the word "example" is intended to present concepts in a specific manner. In addition, in the embodiments of the present invention, the meaning expressed by "and / or" can be both, or either one of the two.

[0052] In the embodiments of the present invention, "image" and "picture" can sometimes be used interchangeably. It should be noted that when the difference is not emphasized, the meanings they express are the same. "(of)", "corresponding", and "corresponding" can sometimes be used interchangeably. It should be noted that when the difference is not emphasized, the meanings they express are the same.

[0053] In the embodiments of the present invention, sometimes a subscript such as W 1 may be written in a non-subscript form such as W1. When the difference is not emphasized, the meanings they express are the same.

[0054] To make the technical problems to be solved, technical solutions and advantages of the present invention clearer, the following will be described in detail with reference to the accompanying drawings and specific embodiments.

[0055] Please refer to Figure 1 , a method for prospecting based on geological text data, comprising the following steps:

[0056] S1: Obtain exploration borehole data, extract the lithological description, ore color, mineral composition and fracture filling conditions of the borehole cores, analyze the spatial variation trend of the ore mineral assemblage, calculate the correlation index between the borehole depth and the mineralized thickness, screen the trend interval of the ore grade variation with depth, and obtain the borehole lithology distribution data of the mining area;

[0057] S2: Based on the borehole lithology distribution data of the mining area, calculate the fracture extension direction, filling minerals and fracture zone distribution density, screen the variation interval of the fracture connectivity and fluid flow capacity, combine the variation of the mineralized depth revealed by the boreholes, analyze the migration path of the fluid along the fractures, calculate the change rate of the pressure gradient during the fluid migration process, screen the aggregation area of the mineralized fluid, and obtain the mineralized fluid migration path data;

[0058] S3: Based on the mineralized fluid migration path data, calculate the occurrence position of the ore body, the mineralized range and the proportion of the ore mineral composition, set the mineralized thickness threshold, screen the mineralized area, calculate the variation relationship between the mineralization degree and the spatial homogeneity, and measure the extension range of the mineralized zone to obtain the spatial distribution data of the mineralized zone;

[0059] S4: Based on the spatial distribution data of mineralized zones, calculate the distribution ratio of altered minerals, the thickness of altered zones, and the spatial position relationship with the ore body, screen the scope of prospecting adjustment in the mining area, calculate the prospecting target area indicators according to the altered distribution characteristics, and obtain the prospecting adjustment data;

[0060] S5: Based on the prospecting adjustment data, calculate the extension trend of the prospecting target area, screen the high-mineralization intervals within the prospecting scope, calculate the prospecting feasibility scope of the mining area, and obtain the prospecting plan for the high-mineralization area.

[0061] The lithology distribution data of drill holes in the mining area include the types of ore mineral combinations, the variation range of mineralization thickness, and the variation interval of ore grade; the migration path data of mineralization fluids include the fracture connectivity characteristics, the fluid flow capacity interval, the pressure gradient change rate, and the mineralization fluid accumulation area; the spatial distribution data of mineralized zones include the occurrence range of the ore body, the distribution of mineralization degree, the proportion of ore mineral composition, and the extension direction of the mineralized zone; the prospecting adjustment data include the types of altered minerals, the thickness of altered zones, the spatial correspondence between the altered zone and the ore body, and the characteristic parameters of the prospecting target area; the prospecting plan for the high-mineralization area includes the extension trend of the prospecting target area, the range of high-mineralization intervals, and the prospecting feasibility evaluation results.

[0062] The specific steps of S1 are as follows:

[0063] S101: Obtain the exploration drill hole data, extract the lithology description, ore color, mineral composition, and fracture filling conditions of the drill core, classify the drill hole data, calculate the mineral content ratio and fracture filling values, and obtain the drill core mineral index data;

[0064] First, it is necessary to call the drilling database to extract the drilling number, drilling depth, coordinate information, and sampling interval. At the same time, obtain the corresponding geological description data of the core, including lithological characteristics, mineral composition, and fracture filling conditions. When extracting the lithological description of the core, the core is cut according to the established depth interval. For each section of the core, image acquisition and color measurement are required. The color data is recorded through the RGB color analysis method and classified by comparison with the standard geological color card. During the mineral composition analysis process, thin section identification is combined with X-ray diffraction (XRD) testing to obtain the specific composition of the core minerals. Combining scanning electron microscopy (SEM) and energy dispersive spectroscopy (EDS) testing, the crystal structure and element content of the minerals are analyzed to further refine the mineral types. At the same time, the results of X-ray fluorescence spectroscopy (XRF) testing are called to analyze the chemical composition of the core, identify the main minerals, and calculate their mass fractions. In the analysis of fracture filling conditions, first, high-precision image analysis technology is used to extract the fracture width data, and microscopic identification of the filling minerals inside the fracture is carried out to determine the mineral composition of the filling materials and calculate the proportion of each filling material in the fracture volume. When classifying the drilling data, it is classified according to the lithology, mineral types, and their contents of the core, and the proportion of each type of mineral at different depths is counted. For the fracture filling conditions, the proportion of the filling materials in each drilling depth range is calculated according to the mineral types, and finally, the mineral index data of the core is obtained.

[0065] S102: Based on the mineral index data of the core, analyze the change rate of mineral content and the distribution range of key minerals, screen the mineral distribution gradient in the differential drilling depth range, calculate the thickness value of the mineralized layer, establish the corresponding relationship between the drilling depth and the mineralized thickness, count the mineralized layer thickness at different depths, screen the depth interval where the mineralized layer thickness index is concentrated, and obtain the mineralized layer thickness index data;

[0066] When analyzing the change rate of mineral content, it is necessary to calculate the content data of each mineral at different depths to obtain the change trend of the mineral with depth. For the distribution range of key minerals, combined with the change of mineral content, screen the depth range with significant content change. By calculating the mean and standard deviation of each mineral, determine the interval with large fluctuations in mineral content. At the same time, based on the change of mineral content, screen the drilling depth range with a large change gradient, and further calculate the thickness of the mineralized layer. The calculation of the mineralized layer thickness requires counting the cumulative change value of specific minerals in different depth ranges. When the cumulative change value of the mineral exceeds a certain threshold, determine that this depth interval is the mineralized layer and record its thickness data. After establishing the corresponding relationship between the drilling depth and the mineralized thickness, count the mineralized thickness of all drillings, calculate the mean and distribution of the mineralized layer thickness in different depth intervals, and finally screen out the depth interval where the mineralized layer thickness is concentrated and output the mineralized layer thickness index data.

[0067] S103: Call the data of the thickness index of the mineralized layer, analyze the amplitude of the change in ore grade with depth, screen the fluctuation range of ore grade, count the average value and variation degree of ore grade in the depth interval, and obtain the borehole lithology distribution data of the mining area;

[0068] After calling the data of the thickness index of the mineralized layer, it is necessary to analyze the change amplitude of the ore grade with depth, extract the ore grade data of each borehole, and calculate its change trend in different depth intervals. For the screening of the fluctuation range of ore grade, it is necessary to count the ore grade data in different depth intervals, calculate its fluctuation range, set a fluctuation threshold, and screen out the depth intervals with large fluctuations in ore grade. When counting the average value of ore grade in different depth intervals, it is necessary to calculate its average value and standard deviation, and analyze the dispersion degree of the grade data in combination with the coefficient of variation to judge the stability of ore grade in different depth intervals. Finally, according to the average value and variation degree of ore grade in different depth intervals, the borehole lithology distribution data of the mining area is obtained.

[0069] The specific steps of S2 are as follows:

[0070] S201: Based on the borehole lithology distribution data of the mining area, calculate the fracture extension direction, filling minerals and fracture zone distribution density, classify the fracture azimuth angle, extension length and filling mineral types, calculate the fracture distribution density, and obtain the fracture distribution value;

[0071] First, extract the fracture direction, filling mineral information and fracture zone distribution density in the borehole data, and perform spatial coordinate registration on the borehole lithology data, project the borehole data into a unified coordinate system to ensure data consistency. When calculating the fracture extension direction, extract the coordinates of the two endpoints of the fracture, and calculate the fracture strike angle and dip angle. The fracture strike angle calculates the relative azimuth through the coordinate difference of the endpoints, and the dip angle is calculated by the ratio of the height difference in the vertical direction and the length in the horizontal direction of the fracture. During the classification of filling minerals, call the mineral composition analysis data, classify according to the main components of the minerals, record sulfides, carbonate minerals, oxides and other mineral types respectively, and calculate their proportion in the fracture volume. In the calculation of the fracture zone distribution density, count the depth intervals where the fracture zone appears in the borehole lithology data, calculate the number of fracture zones per unit depth, and count the fracture zone distribution in different depth intervals. When classifying the fracture azimuth angle, group the fractures according to the azimuth angle interval, with 30 degrees as a grouping interval, and count the number of fractures in different intervals respectively. The fracture extension length is calculated by obtaining the straight-line distance between the endpoints and classified according to the length range. Finally, calculate the fracture distribution density according to the number of fractures, length and the number of fractures per unit volume to obtain the fracture distribution value.

[0072] S202: Invoke the numerical values of fracture distribution, screen the variation ranges of fracture connectivity and fluid flow capacity, analyze the influence of fracture width and filling minerals on fluid flow capacity, statistically calculate the fracture permeability coefficients at different depths, calculate the variation amplitude of fluid migration rate, screen the regions with prominent fluid flow, and in combination with the mineralization depth data revealed by boreholes, calculate the variation rate of pressure gradient during fluid migration to obtain the results of fluid migration pressure variation;

[0073] First, screen the regions with relatively high fracture connectivity. When judging fracture connectivity, analyze the adjacent fracture spacing and calculate the connectivity probability between fractures. If the adjacent fracture spacing is less than the set connectivity threshold, it is determined that the fracture may have connectivity, and further evaluation is carried out in combination with the types of filling minerals. When analyzing the influence of fracture width on fluid flow capacity, extract the fracture width data in different depth intervals and calculate the fracture porosity per unit volume. If the fracture width is large and the porosity is high, the fracture has a relatively high fluid flow capacity. For the analysis of the influence of filling minerals on fluid flow capacity, calculate the permeability of fractures filled with different minerals respectively, and compare the mineral density, particle morphology and solubility of the filling minerals to judge their influence on fluid penetration capacity. When statistically calculating the fracture permeability coefficients at different depths, extract the permeability data in different depth intervals and calculate the influence of depth change on the permeability coefficient. When calculating the variation amplitude of fluid migration rate, statistically calculate the migration rates of fluid at different depths and calculate their variation trends at different depths, and screen out the regions with prominent fluid flow rates. When calculating the variation rate of pressure gradient during fluid migration, invoke the borehole mineralization depth data and calculate the pressure change amount on the fluid migration path. In combination with the pressure change conditions in different depth intervals, calculate the pressure change rate per unit depth, and finally obtain the results of fluid migration pressure variation.

[0074] S203: Based on the results of fluid migration pressure variation, screen the mineralized fluid aggregation areas, calculate the distribution indexes of mineralized fluids in the pressure gradient change areas to obtain the data of mineralized fluid migration paths;

[0075] First, screen the mineralized fluid aggregation areas. During the screening process, statistically calculate the fluid enrichment degrees in different pressure gradient change areas and calculate the areas with relatively large fluid pressure gradients. When calculating the distribution indexes of mineralized fluids in the pressure gradient change areas, statistically calculate the mineralized fluid concentrations in different depth intervals and calculate the mineralized fluid content per unit volume. At the same time, in combination with the fracture distribution density and fluid flow capacity data, analyze the distribution of mineralized fluids on the fluid migration path, and finally obtain the data of mineralized fluid migration paths.

[0076] The specific steps of S3 are as follows:

[0077] S301: Based on the data of the migration path of mineralized fluid, analyze and identify the occurrence position of the ore body and the proportion of ore minerals, statistically analyze the mineral content distribution in the mining area, calculate the mineralization thickness in the ore body area, and obtain the spatial distribution data of the ore body;

[0078] The specific formula for calculating the mineralization thickness in the ore body area is as follows:

[0079]

[0080] Wherein, H m represents the mineralization thickness in the ore body area, C i represents the mineral content at the occurrence depth i of the ore body, d i represents the thickness of the ore body at the depth i, and n represents the total number of layers of the occurrence depth of the ore body;

[0081] This formula is used to calculate the average mineralization thickness in the ore body area, where H m represents the average mineralization thickness. The mineralization thickness is the weighted average of the mineral content and the thickness of the ore body at the depth. By specifically measuring the mineral content C i at each depth and the thickness d i of the ore body at the corresponding depth, we can obtain the average mineralization thickness of the entire ore body area. This weighted average method takes into account the variation of the mineralization thickness at different depths and can more accurately reflect the overall mineralization situation of the ore body.

[0082] Set the following specific example:

[0083] Suppose there are three sampling points at different depths in a certain mining area, and the mineral content and ore body thickness data of each point are obtained through geological exploration. The specific data are as follows: Depth 1 (i = 1): C 1 = 15%, d 1 = 5 m; Depth 2 (i = 2): C 2 = 20%, d 2 = 3 m; Depth 3 (i = 3): C 3 = 10%, d 3 = 2 m

[0084] Substitute these data into the formula:

[0085]

[0086] The calculation steps here show how to multiply the mineral content at each depth by the corresponding ore body thickness, then sum up the product results of all depths, and divide by the total thickness to obtain the average mineralization thickness of the entire mining area. This result indicates that, on average, the mineralization thickness of the entire mining area is 0.155 m, which reflects the overall mineralization degree and the distribution characteristics of the mineralization quality of the ore body. By comparing the H mValues can be used to evaluate the mineralization potential of the mining area, which has important guiding significance for mining development.

[0087] S302: Call the spatial distribution data of ore bodies, set the threshold of mineralization thickness, screen the mineralized areas, calculate the change value of the mineralization degree in the differential areas, count the fluctuation range of the proportion of mineral composition in the mineralized areas, obtain the change relationship between the mineralization degree and spatial homogeneity, screen the areas with deviation in mineralization homogeneity, measure the extension range of the mineralized zone, and obtain the spatial change data of the mineralized zone;

[0088] After calling the spatial distribution data of ore bodies, first set the threshold of mineralization thickness and screen the mineralization thickness data. When screening the mineralized areas, count the mineralization thickness data of all drill holes, judge which drill hole areas have a mineralization thickness exceeding the set threshold, and define these areas as the mineralized zone. For the calculation of the differentiation degree of the mineralized areas, extract the mineral content data in different depth ranges of the mineralized areas and calculate their spatial change amplitude. When counting the fluctuation range of the proportion of mineral composition in the mineralized areas, call the mass fraction of minerals in each depth interval and calculate its change trend. When screening the areas with deviation in mineralization homogeneity, calculate the variation degree of the mineral composition in different mineralized areas. If the standard deviation of the mineral composition in a certain area is higher than a specific threshold of the mining area average value, it is determined that there is a deviation in the mineralization homogeneity of this area. When measuring the extension range of the mineralized zone, call the spatial distribution data of the mineralized layers between different drill holes, calculate the connectivity between adjacent mineralized zones, and count the horizontal and vertical distribution ranges of the mineralized zone. Finally, combine the change trends of all mineralized areas to obtain the spatial change data of the mineralized zone.

[0089] S303: Based on the spatial change data of the mineralized zone, calculate the boundary position of the mineralized zone, count the mineralization thickness index at the mineralization depth, measure the spatial extension value of the mineralized zone, and obtain the spatial distribution data of the mineralized zone;

[0090] First calculate the boundary position of the mineralized zone, extract the area where the mineralization thickness changes most significantly, and define the depth range of the mineralized zone boundary. When counting the mineralization thickness index at the mineralization depth, call the mineralized layer thickness data in different depth intervals and calculate the change trend of the mineralization thickness at different depths. For the calculation of the spatial extension value of the mineralized zone, count the spatial coverage range of the mineralized layer in the horizontal and vertical directions and calculate the spatial expansion rate of the mineralized zone. Finally, combine all the drill hole data in the mining area to obtain the spatial distribution data of the mineralized zone.

[0091] The specific steps of S4 are as follows:

[0092] S401: Based on the spatial distribution data of the mineralized zone, analyze the distribution proportion of altered minerals, count the types and contents of altered minerals in the mining area, calculate the thickness of the alteration zone at different depths, and obtain the distribution range of altered minerals;

[0093] The calculation formula for the thickness of the altered zone with differential depth is specifically as follows:

[0094]

[0095] Among them, H eb represents the thickness of the altered zone with differential depth, C eb,j represents the altered mineral content in the j-th depth interval, D eb,j represents the thickness of the altered zone in the j-th depth interval, W eb,j represents the weight factor in the j-th depth interval, which is calculated based on the distribution density of altered minerals in the mining area, and m represents the total number of depth intervals in the mining area;

[0096] This formula is used to calculate the thickness of the altered zone with differential depth, and a weighted average is performed on the altered mineral content, the thickness of the altered zone, and the corresponding weight factor. The altered mineral content and the thickness of the altered zone in each depth interval are obtained through actual data, and a weight factor is assigned to each depth interval according to the geological characteristics of the mining area, so as to calculate the average thickness of the altered zone more accurately.

[0097] The following is a specific example:

[0098] Suppose the altered mineral surveys at three different depths are carried out in a mining area. Through field sampling and laboratory analysis, the following data are obtained: Depth interval 1 (j = 1): C eb,1 = 12%, D eb,1 = 4 m, weight W eb,1 = 0.5 Depth interval 2 (j = 2): C eb,2 = 18%, D eb,2 = 3 m, weight W eb,2 = 1.0 Depth interval 3 (j = 3): C eb,3 = 9%, D eb,3 = 5 m, weight W eb,3 = 0.8

[0099] Substitute these data into the formula for calculation:

[0100]

[0101] The result shows that, on average, the thickness of the altered zone in this mining area is about 0.496 m. This value provides key data for the mining area planning and further development, indicating the average depth of the concentrated area of altered minerals and serving as the basis for further mineralization assessment and resource volume estimation.

[0102] S402: Invoke the distribution range of altered minerals, establish the relationship between the thickness of the alteration zone and its spatial position relative to the ore body, obtain the scope of prospecting adjustment in the mining area, analyze the variation degree of the distribution of altered minerals in the differential area, count the proportion of the overlapping area between the thickness of the alteration zone and the mineralization zone, screen the key alteration areas within the scope of prospecting adjustment, calculate the prospecting target area indicators, count the spatial distribution of the prospecting target areas in the differential mining areas, and obtain the characteristic values of the prospecting target areas;

[0103] First, establish the corresponding relationship between the thickness of the alteration zone and the spatial position of the ore body, extract the data of the thickness of the alteration zone, and analyze its relative position with the spatial distribution of the mineralization zone. When obtaining the scope of prospecting adjustment in the mining area, screen the areas with a high degree of overlap between the alteration zone and the ore body, and define these areas as the key prospecting scope. For calculating the variation degree of the distribution of altered minerals in the differential area, extract the content data of altered minerals at different depths, and calculate their mean value and standard deviation. If the standard deviation of the content of altered minerals in a certain area is greater than the set threshold, it is considered that the variation degree of the distribution of altered minerals in this area is large. When counting the proportion of the overlapping area between the thickness of the alteration zone and the mineralization zone, calculate the spatial overlapping area between the alteration zone and the mineralization zone, and obtain the proportion of it in the total area of the mineralization zone. When screening the key alteration areas within the scope of prospecting adjustment, extract the areas with a high degree of overlap between the mineralization zone and the alteration zone and a high concentration of altered minerals, and define these areas as the key prospecting areas. When calculating the prospecting target area indicators, extract the content of altered minerals, the occurrence depth of the ore body, and the mineralization thickness data of the key prospecting areas, and calculate the comprehensive prospecting potential of different prospecting areas. Finally, combine the data of all mining areas, count the spatial distribution of the prospecting target areas in the differential mining areas, and obtain the characteristic values of the prospecting target areas.

[0104] S403: Based on the characteristic values of the prospecting target areas, screen the areas that meet the prospecting conditions, analyze the spatial distribution range of the prospecting target areas, measure the mineralization potential of the differential areas, and obtain the prospecting adjustment data;

[0105] First, screen the areas that meet the prospecting conditions. During the screening process, extract the mineralization thickness, the content of altered minerals, and the occurrence depth data of the ore body of each prospecting target area, and calculate their similarity with the typical mineralization area. If the parameters of a certain area are close to the mean value of the typical mineralization area, it is considered that it meets the prospecting conditions. When analyzing the spatial distribution range of the prospecting target areas, calculate the horizontal and vertical expansion ranges of each prospecting target area, and count the spatial connectivity of different prospecting areas. When measuring the mineralization potential of the differential areas, extract the mineralization thickness data of the prospecting areas, and calculate the content of mineralized substances per unit area. At the same time, combine the occurrence depth of the ore body and the spatial distribution of the mineralization zone to analyze the mineralization enrichment degree of different areas. Finally, combine the comprehensive calculation results of all prospecting areas to obtain the prospecting adjustment data.

[0106] The specific steps of S5 are as follows:

[0107] S501: Based on the prospecting adjustment data, analyze the extension trend of the prospecting target area, statistically analyze the change in mineralization degree of different differentiated mining areas, measure the spatial distribution range of the mineralized area, and obtain the extension value of the prospecting target area;

[0108] First, extract the spatial coordinate information of the prospecting target area and analyze the distribution trend of the mineralized layer in different prospecting areas. When analyzing the extension trend of the prospecting target area, extract the mineralization thickness data of each drill hole, calculate the horizontal and vertical change ranges of the mineralized zone, and at the same time compare the change rates of the mineralization thickness in different prospecting areas to judge the spatial development direction of the prospecting target area. When statistically analyzing the change in mineralization degree of different differentiated mining areas, extract the mineralization thickness, mineral content, and ore grade data of different mining areas, and calculate the average value and standard deviation of the mineralization degree of each mining area. If the mineralization thickness of a certain mining area is higher than the overall average and the mineral content is relatively concentrated, it is judged that the mineralization degree of this mining area is relatively high. When measuring the spatial distribution range of the mineralized area, calculate the spatial distribution range of the mineralized layer in different depth intervals, and statistically analyze the horizontal expansion rate and vertical extension length of the mineralized layer. Finally, combine the data of all mining areas, calculate the overall extension of the prospecting target area, and obtain the extension value of the prospecting target area.

[0109] S502: Call the extension value of the prospecting target area, screen high-mineralization intervals, calculate the mineralization enrichment degree at different differentiated depths, statistically analyze the fluctuation range of the mineral content and ore grade in the mineralized interval, analyze the spatial change coefficient of the mineralized interval, obtain the area with relatively stable mineralization enrichment characteristics, measure the prospecting feasibility range of different differentiated mining areas, identify the mineralization potential of the prospecting area, and obtain the prospecting feasibility of the high-mineralization area;

[0110] First, screen the high-mineralization intervals. During the screening process, extract data on mineralization thickness, mineral content, and ore grade, and calculate the comprehensive mineralization index of the mineralized layers in each depth interval. If the mineralization thickness and mineral content in a certain interval both exceed the set threshold, then define this interval as a high-mineralization area. When calculating the mineralization enrichment degree at different depths, extract the mass fraction of minerals in each depth interval and calculate the mineral enrichment degree per unit volume. If the mass fraction of minerals in a certain depth interval is higher than the average value of the adjacent depth intervals, then determine that the mineralization enrichment degree in this interval is relatively high. When statistically analyzing the fluctuation range of mineral content and ore grade in the mineralization intervals, calculate the change in the types of minerals in different mineralization intervals and statistically analyze the coefficient of variation of the ore grade. If the coefficient of variation of the ore grade in a certain interval is less than the set threshold, then determine that its mineralization degree is relatively stable. When analyzing the spatial variation coefficient of the mineralization intervals, calculate the spatial distribution uniformity of the mineral content in each mineralization interval and statistically analyze the standard deviation of the change in mineral concentration. If the standard deviation of the mineral content in a certain interval is small, then consider that the mineralization enrichment characteristics in this interval are relatively stable. When measuring the prospecting feasibility range of different mineralization areas, calculate the connectivity of the prospecting target areas in different mineralization regions and statistically analyze the spatial connectivity rate of the mineralization belts. Finally, combine the prospecting potential evaluation data of different mining areas to identify the areas with relatively high mineralization enrichment potential and obtain the prospecting feasibility of the high-mineralization areas.

[0111] S503: Based on the prospecting feasibility of the high-mineralization areas, screen the areas that meet the prospecting requirements, analyze the potential mineralization thickness in the prospecting areas, calculate the spatial distribution index of the prospecting areas, and obtain the prospecting plan for the high-mineralization areas;

[0112] First, screen the areas that meet the prospecting requirements. During the screening process, extract data on mineralization thickness, mineral content, and ore grade of different prospecting target areas and calculate their prospecting potential indices. If the prospecting potential index of a certain area exceeds the set threshold, then define this area as an optimized prospecting area. When analyzing the potential mineralization thickness in the prospecting areas, statistically analyze the distribution data of the mineralized layers in different prospecting areas and calculate the average value and distribution range of the mineralized layer thickness in each prospecting area. When calculating the spatial distribution index of the prospecting areas, extract the spatial coordinate information of each prospecting area and calculate the spatial coverage area and the distribution of the occurrence depth of the ore bodies in the prospecting areas. Finally, combine the comprehensive evaluation data of all prospecting areas to determine the prospecting plan for the high-mineralization areas and obtain the prospecting plan for the high-mineralization areas.

[0113] Please refer to Figure 2 , a prospecting system based on geological text data, including:

[0114] The borehole lithology analysis module obtains exploration borehole data, extracts the lithology description, ore color, mineral composition, and fracture filling conditions of the borehole cores, calculates the spatial distribution characteristics of the ore mineral assemblage, and calls the ore grade values to screen the depth change trend intervals for the correlation between borehole depth and mineralization thickness, and obtains the borehole lithology distribution data of the mining area;

[0115] Based on the lithological distribution data of boreholes in the mining area, the fluid migration calculation module calculates the fracture extension direction, filling mineral type and fracture zone distribution density, screens the change intervals of fracture connectivity and fluid flow capacity, calls the mineralization depth parameters revealed by boreholes, calculates the pressure gradient change rate during fluid migration, and obtains the fluid migration path data of mineralized fluids;

[0116] Based on the fluid migration path data of mineralized fluids, the mineralized zone spatial analysis module calculates the occurrence position of ore bodies, the mineralized range and the proportion of ore minerals, calls the mineralization thickness threshold to screen the mineralized area, measures the change relationship between mineralization degree and spatial homogeneity, and obtains the spatial distribution data of mineralized zones;

[0117] Based on the spatial distribution data of mineralized zones, the prospecting target area screening module calculates the distribution proportion of altered minerals, the thickness of altered zones and their spatial position relationship with ore bodies, calls the altered distribution characteristics to screen the prospecting adjustment range of the mining area, obtains the prospecting target area indicators, and gets the prospecting adjustment data;

[0118] Based on the prospecting adjustment data, the high-mineralization area evaluation module obtains the extension trend of the prospecting target area, screens the high-mineralization intervals within the prospecting range, calculates the prospecting feasibility range of the mining area, and gets the prospecting plan for high-mineralization areas.

[0119] As mentioned above, it is only the specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention can easily think of changes or substitutions, which should all be covered within the protection scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claimed rights.

Claims

1. A method for prospecting based on geological text data, characterized in that: The following steps are involved: S1: Obtain exploration drilling data, extract the lithology description, mineral composition and fracture filling of the core, calculate the correlation index between drilling depth and mineralization thickness, screen the change trend of ore grade, and obtain the lithology distribution data of the drilling holes in the mining area; S2: Based on the lithology distribution data of the drilling holes in the mining area, calculate the extension direction of the fractures, the density of the filling minerals and the fracture zone, screen the change intervals of the fracture permeability and the fluid flow capacity, analyze the fluid migration trend in combination with the mineralization depth, calculate the pressure gradient change rate, screen the fluid enrichment area, and obtain the mineralization fluid migration path data; S3: Based on the mineralized fluid migration path data, calculate the ore body location, mineralization range and mineral composition ratio, screen the mineralized area, analyze the change of mineralization intensity along the migration path, calculate the extension range of the mineralized zone, and obtain the spatial distribution data of the mineralized zone; S4: Based on the spatial distribution data of the mineralized zone, identify the distribution ratio of altered minerals, the thickness of the altered zone and its spatial relationship with the ore body, screen the adjustment range of prospecting parameters, calculate the adjustment index of the prospecting target area, and obtain the prospecting adjustment data.

2. The method for prospecting using geological text data according to claim 1, characterized in that: The drilling lithology distribution data of the mining area include the ore mineral combination type, the range of mineralization thickness variation, and the ore grade variation interval; the mineralization fluid migration path data include the fracture penetration characteristics, the fluid flow capacity interval, the pressure gradient change rate, and the mineralization fluid aggregation area; the spatial distribution data of the mineralized zone include the ore body occurrence range, the mineralization degree distribution, the ore mineral composition ratio, and the extension direction of the mineralized zone; the prospecting adjustment data include the altered mineral type, the alteration zone thickness, the spatial correspondence between the alteration zone and the ore body, and the characteristic parameters of the prospecting target area.

3. The method for prospecting using geological text data according to claim 1, characterized in that: The specific steps of obtaining the exploration drilling data, extracting the lithology description, mineral composition and fracture filling of the core, calculating the correlation index between the drilling depth and the mineralization thickness, screening the change trend of the ore grade, and obtaining the lithology distribution data of the mining area drilling holes are as follows: S101: Acquire exploration drilling data, extract lithology description, ore color, mineral composition and fracture filling of the drilling core, classify the drilling data, calculate the mineral content ratio and fracture filling value, and obtain the mineral index data of the drilling core; S102: Based on the mineral index data of the drill core, analyze the mineral content change rate and the distribution range of key minerals, screen the mineral distribution gradient of the differentiated drilling depth range, calculate the thickness value of the mineralized layer, establish the corresponding relationship between the drilling depth and the mineralized thickness, count the thickness of the mineralized layer at the differentiated depth, screen the depth range where the mineralized layer thickness index is concentrated, and obtain the mineralized layer thickness index data; S103: calling the mineralized layer thickness index data, analyzing the amplitude of ore grade variation with depth, screening the ore grade fluctuation range, statistically analyzing the mean and variation degree of ore grade in depth intervals, and obtaining the lithology distribution data of the mining area boreholes.

4. The method for prospecting using geological text data according to claim 1, characterized in that: Based on the lithology distribution data of the drilling holes in the mining area, the fracture extension direction, filling minerals and fracture zone density are calculated, the fracture permeability and fluid flow capacity change interval are screened, and the fluid migration trend is analyzed in combination with the mineralization depth. The pressure gradient change rate is calculated, the fluid enrichment area is screened, and the specific steps for obtaining the mineralization fluid migration path data are as follows: S201: Based on the lithology distribution data of the drilling holes in the mining area, the fracture extension direction, the filling minerals and the distribution density of the fault zone are calculated, the fracture azimuth, the extension length and the filling mineral types are classified, the fracture distribution density is calculated, and the fracture distribution value is obtained; S202: calling the fracture distribution value, screening the change range of fracture permeability and fluid flow capacity, analyzing the influence of fracture width and filling minerals on fluid flow capacity, statistically analyzing fracture permeability coefficients of different depths, calculating the change amplitude of fluid migration rate, screening areas with prominent fluid flow, and calculating the change rate of pressure gradient during fluid migration in combination with mineralization depth data revealed by drilling, to obtain the result of fluid migration pressure change; S203: Based on the fluid migration pressure change result, the mineralized fluid gathering area is screened, and the mineralized fluid distribution index in the pressure gradient change area is calculated to obtain the mineralized fluid migration path data.

5. The method for prospecting using geological text data according to claim 1, characterized in that: Based on the mineralized fluid migration path data, the specific steps of calculating the ore body location, mineralization range and mineral composition ratio, screening the mineralized area, analyzing the change of mineralization intensity along the migration path, and calculating the extension range of the mineralized zone to obtain the spatial distribution data of the mineralized zone are as follows: S301: Based on the mineralized fluid migration path data, analyze and identify the ore body location and ore mineral composition ratio, count the mineral content distribution in the mining area, calculate the mineralization thickness of the ore body area, and obtain the ore body spatial distribution data; S302: calling the spatial distribution data of the ore body, setting a mineralization thickness threshold, screening the mineralized area, calculating the change value of the mineralization degree of the differentiated area, counting the fluctuation range of the mineral composition ratio in the mineralized area, obtaining the change relationship between the mineralization degree and the spatial homogeneity, screening the area with the deviation of the mineralization homogeneity, calculating the extension range of the mineralized belt, and obtaining the spatial change data of the mineralized belt; S303: Based on the spatial variation data of the mineralized zone, the boundary position of the mineralized zone is calculated, the mineralization thickness index of the mineralized depth is counted, and the spatial extension value of the mineralized zone is calculated to obtain the spatial distribution data of the mineralized zone.

6. The method for prospecting using geological text data according to claim 5, characterized in that: The calculation formula for the mineralization thickness of the ore body area is specifically: Among them, H m Represents the mineralization thickness of the ore body area, C i represents the mineral content at the ore body depth i, d i represents the thickness of the ore body at depth i, and n represents the total number of layers at the depth of the ore body.

7. The method for prospecting using geological text data according to claim 1, characterized in that: Based on the spatial distribution data of the mineralized zone, the specific steps of identifying the distribution ratio of altered minerals, the thickness of the altered zone and its spatial relationship with the ore body, screening the adjustment range of prospecting parameters, and calculating the adjustment index of the prospecting target area are as follows: S401: Based on the spatial distribution data of the mineralized zone, the distribution ratio of altered minerals is analyzed, the types and contents of altered minerals in the mining area are counted, the thickness of the altered zone at different depths is calculated, and the distribution range of the altered minerals is obtained; S402: calling the altered mineral distribution range, establishing the altered zone thickness and the spatial position relationship with the ore body, obtaining the prospecting adjustment range of the mining area, analyzing the variation degree of altered mineral distribution in the differentiated area, counting the ratio of the altered zone thickness to the overlapping area of ​​the mineralized zone, screening the key altered areas within the prospecting adjustment range, calculating the prospecting target area index, counting the spatial distribution of the prospecting target area in the differentiated mining area, and obtaining the prospecting target area characteristic value; S403: Based on the characteristic values ​​of the prospecting target area, screen the areas that meet the prospecting conditions, analyze the spatial distribution range of the prospecting target area, calculate the mineralization potential of the differentiated areas, and obtain the prospecting adjustment data.

8. The method for prospecting using geological text data according to claim 7, characterized in that: The calculation formula of the thickness of the alteration zone at the differential depth is specifically: Among them, H eb The thickness of the alteration zone representing the differential depth, C eb,j represents the alteration mineral content in the jth depth interval, D eb,j represents the thickness of the alteration zone in the jth depth interval, W eb,j Represents the weight factor of the jth depth interval, which is calculated based on the distribution density of altered minerals in the mining area, and m represents the total number of depth intervals in the mining area.

9. The method for prospecting using geological text data according to claim 1, characterized in that: The method further includes, S5: based on the prospecting adjustment data, calculating the extension trend of the prospecting target area, screening the high mineralization interval, obtaining the feasibility range of prospecting, analyzing the ore body occurrence depth, ore grade and mineralization continuity, adjusting the drilling layout and exploration range, adjusting the exploration target, and generating a prospecting plan for the high mineralization area; The prospecting plan for the highly mineralized area includes the extension trend of the prospecting target area, the range of the highly mineralized interval, and the feasibility assessment results of the prospecting; S501: Based on the prospecting adjustment data, analyzing the extension trend of the prospecting target area, statistically analyzing the change of the mineralization degree of the differentiated mineral area, calculating the spatial distribution range of the mineralized area, and obtaining the extension value of the prospecting target area; S502: calling the extended value of the prospecting target area, screening the high mineralization interval, calculating the differentiated depth mineralization enrichment degree, statistically analyzing the mineral content and ore grade fluctuation range of the mineralization interval, analyzing the spatial variation coefficient of the mineralization interval, obtaining the area with relatively stable mineralization enrichment characteristics, calculating the feasibility range of prospecting in the differentiated mineral area, identifying the mineralization potential of the prospecting area, and obtaining the feasibility of prospecting in the high mineralization area; S503: Based on the feasibility of prospecting in the highly mineralized area, screen the area that meets the prospecting requirements, analyze the potential mineralization thickness of the prospecting area, calculate the spatial distribution index of the prospecting area, and obtain a prospecting plan for the highly mineralized area.

10. A system for prospecting based on geological text data, characterized in that: According to the method for prospecting based on geological text data according to any one of claims 1 to 9, the system comprises: The borehole lithology analysis module obtains exploration drilling data, extracts the lithology description, ore color, mineral composition and fracture filling of the borehole core, calculates the spatial distribution characteristics of the ore mineral combination, and uses the ore grade value to screen the depth change trend interval according to the correlation between the drilling depth and the mineralization thickness, and obtains the borehole lithology distribution data of the mining area; The fluid migration calculation module calculates the fracture extension direction, filling mineral type and fault zone distribution density based on the lithology distribution data of the drilling holes in the mining area, selects the change interval of fracture permeability and fluid flow capacity, calls the mineralization depth parameters revealed by the drilling holes, calculates the pressure gradient change rate during fluid migration, and obtains the mineralization fluid migration path data; The mineralized zone spatial analysis module calculates the ore body location, mineralization range and ore mineral composition ratio based on the mineralized fluid migration path data, calls the mineralized thickness preset value to screen the mineralized area, calculates the relationship between the mineralization degree and spatial homogeneity, and obtains the mineralized zone spatial distribution data; The prospecting target area screening module calculates the distribution ratio of altered minerals, the thickness of the altered zone and its spatial position relationship with the ore body based on the spatial distribution data of the mineralized zone, calls the alteration distribution characteristics to screen the prospecting adjustment range of the mining area, obtains the prospecting target area indicators, and obtains the prospecting adjustment data; Based on the prospecting adjustment data, the high mineralization area assessment module obtains the extension trend of the prospecting target area, screens the high mineralization intervals within the prospecting range, calculates the feasibility range of prospecting in the mining area, and obtains the prospecting plan for the high mineralization area.

Images