Geological mineral exploration data extraction method and system

Abstract

The invention relates to a geological mineral exploration data extraction method which comprises the following steps: S1, data acquisition: acquiring multi-source geological data through scientific drilling, remote sensing images and a geological radar; according to the method, through scientific drilling, remote sensing image and geological radar multi-source data collection, in combination with data preprocessing, feature extraction and three-dimensional model construction, massive geological data can be rapidly obtained and processed, and accurate positioning of mineral resources is achieved; the remote sensing image is combined to identify surface mineralization abnormity, the problem of surface and deep data separation in a traditional exploration method is effectively solved, meanwhile, the data preprocessing module ensures consistency and high-precision fusion of data from different sources through cleaning, format unification and geographical registration, and the data preprocessing module analyzes abundance and distribution rules of main metallogenic elements to obtain the data of different sources. And identifying combinations of elements closely related to mineralization.

Description

Technical Field

[0001] The present invention relates to the field of geological exploration technology, and in particular to a method and system for extracting geological and mineral exploration data. Background Art

[0002] With the continuous advancement of mineral resource development, surface and shallow mineral resources are gradually being mined out, and the global demand for exploration of deep hidden ore bodies has increased significantly. However, the exploration of deep mineral resources faces a series of technical and scientific challenges.

[0003] In the actual implementation process, the traditional geological and mineral exploration methods have the following main problems: data collection is limited to the surface and shallow areas, and it is difficult to obtain accurate information on deep hidden ore bodies; the multi-source data format is not unified, the processing is complex and the fusion accuracy is insufficient; the exploration process is blind and cannot effectively delineate high-potential areas, resulting in resource waste; the analysis of mineralization laws is not systematic and it is difficult to reveal key mineralization factors; the ore body model is mainly two-dimensional, and it is impossible to fully display the three-dimensional spatial distribution, and the resource evaluation lacks intuitiveness and scientific basis. These problems seriously restrict the efficiency and accuracy of mineral resource exploration. Summary of the invention

[0004] 1. Technical issues to be resolved

[0005] In order to solve the above problems in the prior art, the present invention provides a geological and mineral exploration data extraction method and system to solve the problems of traditional methods such as data limitation, complex processing, blind exploration, insufficient analysis and single model.

[0006] (II) Technical solution

[0007] In order to achieve the above object, the main technical solutions adopted by the present invention are:

[0008] A method for extracting geological and mineral exploration data comprises the following steps:

[0009] S1: Data acquisition, obtaining multi-source geological data through scientific drilling, remote sensing images and geological radar;

[0010] S2: Data preprocessing, cleaning, formatting and georeferencing of collected data;

[0011] S3: Feature extraction, analyzing the abundance, distribution and correlation of key mineral elements;

[0012] S4: Model construction, building a three-dimensional ore body distribution model based on geological data;

[0013] S5: Output the results to generate mineral distribution maps, three-dimensional models and exploration reports.

[0014] The data collection includes:

[0015] Use geological drilling techniques to obtain core samples;

[0016] Identify surface mineralization anomalies through remote sensing images;

[0017] Geological radar is used to detect the distribution of hidden ore bodies.

[0018] The data preprocessing includes:

[0019] Conduct physical and chemical tests on core samples to analyze their elemental composition;

[0020] Conduct spectral analysis on remote sensing images to extract mineral features;

[0021] Spatial correction and data fusion were performed using geographic information systems.

[0022] The feature extraction comprises:

[0023] Analyze the abundance and distribution patterns of the main ore-forming elements in the mineral resource area;

[0024] Identify element combinations closely related to mineralization through correlation studies;

[0025] High potential exploration areas are delineated based on mineralogical characteristics.

[0026] The model building steps include:

[0027] Construct a three-dimensional model through ore body cross-section and geological plan;

[0028] Combine geological radar detection data to mark the spatial distribution and depth of the ore body;

[0029] The spatial morphology of the ore body is determined based on regional geological background analysis.

[0030] A geological and mineral exploration data extraction system, applied to the extraction method described in any one of claims 1 to 5, comprising:

[0031] Data acquisition module: used to collect remote sensing images, geological radar and drilling data;

[0032] Data processing module: used to clean and integrate the collected data;

[0033] Feature analysis module: used to extract mineralization features from geological data;

[0034] Modeling module: used to generate three-dimensional distribution model of mineral resources;

[0035] Output module: used to generate geological maps, three-dimensional models and exploration reports.

[0036] The data acquisition module comprises:

[0037] High-precision remote sensing equipment for identifying surface mineralization anomalies;

[0038] Core drilling equipment, used for collecting deep core samples;

[0039] Geological radar equipment, used for the detection of concealed ore bodies.

[0040] The data processing module comprises:

[0041] Data cleaning unit, used to remove invalid or duplicate data;

[0042] Geographic information integration unit, used for spatial registration of multi-source geological data;

[0043] Element distribution analysis unit, used to calculate the abundance of mineral elements.

[0044] The modeling module can generate a dynamic three-dimensional mineral distribution model based on the collected ore body profile and mark important exploration areas.

[0045] The output module is capable of generating:

[0046] Two-dimensional mineral resource distribution map;

[0047] Three-dimensional ore body distribution model;

[0048] Comprehensive exploration report including resource estimation, ore distribution and development recommendations.

[0049] (III) Beneficial effects

[0050] The beneficial effects of the present invention are:

[0051] 1. A method and system for extracting geological and mineral exploration data provided by the present invention can quickly acquire and process massive geological data and realize accurate positioning of mineral resources through multi-source data collection of scientific drilling, remote sensing images and geological radar, combined with data preprocessing, feature extraction and three-dimensional model construction. In this method, the distribution of hidden ore bodies is detected by geological radar, and surface mineralization anomalies are identified in combination with remote sensing images, which effectively solves the problem of surface and deep data separation in traditional exploration methods. At the same time, the data preprocessing module ensures the consistency and high-precision fusion between data from different sources through cleaning, format unification and geographic registration. By analyzing the abundance and distribution laws of major ore-forming elements and identifying element combinations closely related to mineralization, this method can delineate high-potential exploration areas, greatly reduce exploration blindness and ineffective drilling, and improve resource utilization and exploration efficiency. In addition, the three-dimensional model construction module presents the distribution and spatial morphology of ore bodies in a visual form, which provides a more intuitive decision-making basis for the development and management of mineral resources, and greatly improves the scientificity and accuracy of mineral exploration.

[0052] 2. The geological and mineral exploration data extraction system proposed in the present invention realizes the automation and efficiency of geological and mineral exploration by integrating data acquisition, processing, analysis and output functions. The data acquisition module can comprehensively cover the spatial distribution information of surface and deep ore bodies through the coordinated application of high-precision remote sensing equipment, core drilling equipment and geological radar equipment, and adapt to various complex geological environments; the data processing module is designed with a data cleaning unit, a geographic information integration unit and an element distribution analysis unit, which provides reliable technical support for subsequent data modeling and analysis. The feature analysis module can accurately mark the key exploration areas by identifying the distribution characteristics of key elements in mineral resources, reducing the input of manpower and material resources. The modeling module combines the ore body profile and geological background to construct a dynamic three-dimensional model, which not only intuitively displays the spatial position of the ore body, but also can be adjusted in real time with the update of the collected data. The two-dimensional resource distribution map and three-dimensional model generated by the output module provide comprehensive support for exploration decisions. At the same time, the resource estimation and development suggestions contained in the comprehensive exploration report significantly improve the evaluation ability of mineral resources, and provide a complete and convenient technical solution for the geological exploration industry. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] Figure 1 It is a flow chart of the geological and mineral exploration data extraction method of the present invention;

[0054] Figure 2 It is a schematic diagram of the cross section of the survey line of the present invention;

[0055] Figure 3 It is the R-type cluster analysis pedigree diagram of the present invention;

[0056] Figure 4 This is a flow chart of the geological and mineral exploration data extraction system of the present invention. DETAILED DESCRIPTION

[0057] In order to better explain the present invention and facilitate understanding, the present invention is described in detail below through specific implementation modes in conjunction with the accompanying drawings.

[0058] Please refer to Figures 1 to 4 As shown, a method for extracting geological and mineral exploration data of the present invention comprises the following steps:

[0059] S1: Data acquisition, obtaining multi-source geological data through scientific drilling, remote sensing images and geological radar;

[0060] S2: Data preprocessing, cleaning, formatting and georeferencing of collected data;

[0061] S3: Feature extraction, analyzing the abundance, distribution and correlation of key mineral elements;

[0062] S4: Model construction, building a three-dimensional ore body distribution model based on geological data;

[0063] S5: Output the results, generate mineral distribution maps, three-dimensional models and exploration reports. In the actual implementation process, data collection (S1): obtain deep core samples through scientific drilling technology, combine remote sensing images to quickly identify surface mineralization anomalies on a large scale, and use geological radar to accurately detect the spatial distribution of hidden ore bodies. The combination of multiple technical means ensures the comprehensiveness and high accuracy of data collection, providing a solid foundation for subsequent analysis.

[0064] Data preprocessing (S2): The data processing module cleans the collected multi-source data to remove redundant and invalid data and ensure the purity of the data; standardizes data from different sources through the format unification module to solve the problem of format incompatibility; and uses the geographic information system (GIS) to spatially align the data so that various types of data can be aligned with high precision in geographic coordinates, laying the foundation for subsequent analysis.

[0065] Feature extraction (S3): The feature analysis module analyzes the element abundance, distribution and correlation of the mineral area, and focuses on marking the enrichment areas of key mineralization elements such as Au, W, and Mo. At the same time, the combination of mineralization elements is identified through correlation analysis, providing an important basis for subsequent model construction and the delineation of high-potential exploration areas.

[0066] Model construction (S4): Combine the feature extraction results with the geological profile and geological radar data to generate a three-dimensional distribution model of the ore body, clearly showing the spatial form, depth and reserve distribution of the ore body. The three-dimensional model can be dynamically adjusted according to the real-time updated data to ensure the real-time and reliability of the results.

[0067] Result output (S5): The output module generates a two-dimensional mineral distribution map, a three-dimensional model and a comprehensive exploration report, which records in detail the resource estimation, ore body distribution characteristics and development suggestions. The output results are presented in a visual form to provide intuitive decision support for the geological exploration team.

[0068] Optionally, data collection includes:

[0069] Use geological drilling techniques to obtain core samples;

[0070] Identify surface mineralization anomalies through remote sensing images;

[0071] Geological radar is used to detect the distribution of hidden ore bodies. In the actual implementation process, geological drilling technology is used to obtain core samples. Geological drilling technology is a key means to obtain deep geological information. High-precision drilling equipment is used to perform drilling operations in the target area to extract core samples. The core samples retain the original information of the geological layer, including mineral composition, physical properties and structural characteristics. These samples provide basic data for subsequent physical, chemical tests and elemental analysis, and can reflect the mineralization characteristics and spatial changes of deep geology;

[0072] Identify surface mineralization anomalies through remote sensing images, use remote sensing imaging technology to quickly scan and analyze large areas of the surface, extract the spectral characteristics of surface minerals through multi-spectral or hyperspectral images, and identify areas of mineralization anomalies. Remote sensing technology can efficiently cover a wide area, especially suitable for areas with complex surface features or difficult to reach by manpower, providing a macro perspective for mineral resource exploration and preliminary delineation of priority exploration areas;

[0073] Geological radar is used to detect the distribution of hidden ore bodies. Geological radar is a high-resolution geophysical exploration technology that emits high-frequency electromagnetic waves to detect the reflected signals of underground structures and obtain the spatial distribution information of hidden ore bodies. This technology can effectively identify the shape, depth and scale of underground ore bodies, and is particularly suitable for the exploration of deep mineral resources, providing accurate spatial data support for subsequent model construction.

[0074] Optionally, data preprocessing includes:

[0075] Conduct physical and chemical tests on core samples to analyze their elemental composition;

[0076] Conduct spectral analysis on remote sensing images to extract mineral features;

[0077] Use geographic information systems for spatial correction and data fusion. In the actual implementation process, physical and chemical tests are performed on core samples to analyze their elemental composition. Core samples are the core data source for geological exploration. Physical tests on core samples, such as density, magnetism, porosity, etc., can reveal the physical properties of the ore; chemical tests can be used to determine the content of major and trace elements related to mineral resources in the core (such as Au, W, Mo, etc.) to understand the distribution and enrichment of mineralizing materials. These test results can reflect the genesis of the ore deposit and its mineralization characteristics, and provide detailed geochemical data for subsequent exploration;

[0078] Spectral analysis is performed on remote sensing images to extract mineral features. Remote sensing images record the spectral features of minerals on the surface through multispectral or hyperspectral data. The spectral analysis process converts the pixel information in the image into the indication information of specific mineral types. By analyzing the reflectance spectrum of minerals, it is possible to identify abnormal mineralized areas on the surface, especially minerals with obvious spectral features (such as secondary oxides of iron ore and copper ore), providing a basis for delineating key target areas for geological exploration;

[0079] Use geographic information system for spatial correction and data fusion. Geographic Information System (GIS) is used to realize spatial correction and fusion of multi-source geological data in data preprocessing. First, core data, remote sensing images and geological radar data are uniformly projected into the same geographic coordinate system to ensure spatial accuracy and consistency. Then, data from different sources are integrated into a unified geological database through fusion analysis technology to build a comprehensive spatial model. This process can eliminate the deviation between data and improve the comprehensive application ability of exploration data.

[0080] Optionally, feature extraction includes:

[0081] Analyze the abundance and distribution patterns of the main ore-forming elements in the mineral resource area;

[0082] Identify element combinations closely related to mineralization through correlation studies;

[0083] Delineate high-potential exploration areas based on mineralogical characteristics. In the actual implementation process, analyze the abundance and distribution patterns of the main ore-forming elements in the mineral resource area. In the mineral resource exploration area, conduct statistical analysis on the abundance of the main ore-forming elements (such as gold (Au), tungsten (W), molybdenum (Mo), etc.) to determine their content distribution in different spatial locations. At the same time, combine geological profiles and sample chemical test data to study the distribution characteristics of ore-forming elements at different depths and geological units. This process can reveal the enrichment areas of ore-forming elements, clarify the potential reserves and spatial distribution patterns of mineral resources, and provide data basis for the subsequent optimization of exploration areas;

[0084] Identify the element combinations closely related to mineralization through correlation studies, and use statistical analysis methods to conduct in-depth research on the correlation of multiple elements in geological samples in the region to identify element combinations closely related to mineralization. For example, gold (Au) may be highly correlated with bismuth (Bi) or molybdenum (Mo). By analyzing these correlation characteristics, we can better infer the source of mineralizing materials and the control mechanism of mineralization. In addition, this analysis can also provide key data support for further model construction and improve the accuracy of resource prediction;

[0085] Based on the mineralogical characteristics, high-potential exploration areas are delineated. Combined with the mineral composition of core samples and the remote sensing image characteristics of the surface, the mineralogical characteristics of the area are comprehensively analyzed to identify key mineral combinations with mineralization conditions (such as sulfide minerals, oxide minerals, etc.). By marking and delineating areas with high-enriched minerals, the spatial location of high-potential exploration areas is clarified, providing precise guidance for subsequent drilling and sampling work.

[0086] Optionally, the model building step includes:

[0087] Construct a three-dimensional model through ore body cross-section and geological plan;

[0088] Combine geological radar detection data to mark the spatial distribution and depth of the ore body;

[0089] Determine the spatial morphology of the ore body based on regional geological background analysis. In the actual implementation process, a three-dimensional model is constructed through the ore body profile and geological plan. The ore body profile and geological plan obtained during the geological survey are used as the basic data source for the construction of the three-dimensional model. The ore body profile provides the thickness, shape and rock structure information of the ore body in the vertical direction; the geological plan reflects the distribution characteristics of the ore body on the horizontal plane and its relationship with the surrounding geological units. By combining the data of the two, the geometric shape and spatial distribution of the ore body are reconstructed into a three-dimensional model, so that the structural characteristics of the ore body can be intuitively presented;

[0090] Combined with geological radar detection data, the spatial distribution and depth of the ore body are marked. The geological radar detection data provides the spatial distribution and depth information of the ore body underground. By superimposing the high-resolution imaging results of the geological radar into the three-dimensional model, the location, depth and morphological characteristics of the ore body can be accurately marked. At the same time, by comparing the data with the profile and plane diagrams, the spatial error of the model can be corrected to ensure the accuracy of the three-dimensional model. This process can dynamically reflect the changes of the ore body under different geological conditions and provide support for resource reserve estimation;

[0091] The spatial morphology of the ore body is determined based on the regional geological background analysis. Combined with the regional geological background information (such as structural characteristics, magmatic activity, fault system, etc.), a comprehensive analysis is conducted on the formation mechanism and spatial distribution law of the ore body. By analyzing the relationship between the ore body and the surrounding rock mass, the occurrence (strike, dip and extension direction) of the ore body is determined. The integration of the regional geological background enables the three-dimensional model to better reflect the mineralization law and spatial morphological characteristics of the ore body, providing a scientific basis for resource development and planning.

[0092] Optionally, a geological and mineral exploration data extraction system comprises:

[0093] Data acquisition module: used to collect remote sensing images, geological radar and drilling data;

[0094] Data processing module: used to clean and integrate the collected data;

[0095] Feature analysis module: used to extract mineralization features from geological data;

[0096] Modeling module: used to generate three-dimensional distribution model of mineral resources;

[0097] Output module: used to generate geological maps, three-dimensional models and exploration reports. In the actual implementation process, the data acquisition module is used to obtain large-scale surface image data through high-precision remote sensing equipment to identify abnormal surface mineralization areas; combined with geological radar to detect the spatial distribution and structural characteristics of deep ore bodies; at the same time, drilling equipment is used to obtain deep core samples for physical and chemical analysis. This module ensures the comprehensive collection of multi-dimensional geological data from the surface to the depth, providing a reliable data source for subsequent analysis;

[0098] Operation of the data processing module: After data collection is completed, the data processing module begins to clean and integrate multi-source geological data. The cleaning process removes redundant and erroneous data to ensure data quality. The integration process uses geographic information system (GIS) technology to unify remote sensing images, geological radar and drilling data into a spatial coordinate system to form a complete geological database, laying the foundation for subsequent feature analysis and model construction.

[0099] The operation of the feature analysis module, which extracts geological features from the processed data, analyzes the abundance and spatial distribution of the main mineralizing elements (such as Au, W, Mo, etc.) in the mining area, identifies the element combination closely related to mineralization, and delineates high-potential exploration areas based on these data. The operation of this module provides scientific support for accurate resource prediction;

[0100] The operation of the modeling module, by inputting geological profiles, plane maps and geological radar detection data, the modeling module generates a three-dimensional ore body distribution model to display the shape, depth and reserve distribution characteristics of the ore body. At the same time, the model can be dynamically updated in combination with real-time collected data to ensure the accuracy and timeliness of the exploration results;

[0101] The output module runs, and the output module presents the analysis and modeling results in various forms, including two-dimensional geological distribution maps, three-dimensional models, and comprehensive exploration reports. The report records in detail the resource reserve estimation, ore body distribution characteristics, and development suggestions, providing a comprehensive and intuitive reference for decision makers.

[0102] Optionally, the data acquisition module includes:

[0103] High-precision remote sensing equipment for identifying surface mineralization anomalies;

[0104] Core drilling equipment, used for collecting deep core samples;

[0105] Geological radar equipment is used to detect hidden ore bodies. In actual implementation, high-precision remote sensing equipment is used to identify surface mineralization anomalies. High-precision remote sensing equipment uses multi-spectral or hyperspectral imaging technology to quickly scan and collect data on a large area of ​​the surface. The equipment can capture the spectral characteristics of surface minerals and identify areas of surface mineralization anomalies, such as the distribution characteristics of gold, tungsten and other minerals. Remote sensing data can also assist in the analysis of geological structures and geomorphological features, and provide a reference for the screening of priority areas for subsequent exploration work. The equipment is suitable for covering a wide range of geological environments, especially areas with complex surfaces or difficult to access;

[0106] Core drilling equipment is used to collect deep core samples. Core drilling equipment is the core tool for obtaining deep geological information. Through precise drilling technology, continuous core samples are extracted from the strata. The core samples retain the original information of deep geological structure and mineral composition, providing a reliable basis for subsequent physical and chemical analysis. The equipment can adapt to a variety of complex geological conditions and provide high-resolution deep data, providing direct evidence for the distribution and mineralization characteristics of ore bodies;

[0107] Geological radar equipment is used for the detection of hidden ore bodies. It emits high-frequency electromagnetic waves and receives their reflected signals to obtain the spatial distribution, depth and scale information of underground ore bodies. Geological radar can detect the structural characteristics of hidden ore bodies and their surrounding rock masses, and is particularly suitable for the detailed detection of shallow and medium-deep ore bodies. The equipment is non-destructive and has high data resolution. It can be combined with remote sensing images and drilling data to form a complete geological profile and three-dimensional model data basis.

[0108] Optionally, the data processing module includes:

[0109] Data cleaning unit, used to remove invalid or duplicate data;

[0110] Geographic information integration unit, used for spatial registration of multi-source geological data;

[0111] The element distribution analysis unit is used to calculate the abundance of mineral elements. In the actual implementation process, the data cleaning unit is used to remove invalid or duplicate data. The data cleaning unit is a key link in ensuring data quality. Its functions include detecting and eliminating invalid data, such as errors or incomplete records generated during the collection process; identifying and deleting duplicate data to avoid redundant information affecting the analysis accuracy. The unit can also repair a small range of missing data or inconsistent data formats, thereby improving the integrity and reliability of the data. Through data cleaning, ensure that the data entering the subsequent analysis and processing links has high accuracy and practicality;

[0112] Geographic Information Integration Unit: used for spatial registration of multi-source geological data. The Geographic Information Integration Unit unifies multi-source data such as remote sensing images, geological radar data, and drilling results into the same geographic coordinate system to achieve spatial alignment and integration of data from different sources. The unit can handle spatial offset problems caused by differences in data acquisition equipment accuracy or different regional ranges, ensuring that all data are consistent within the same spatial framework. At the same time, by combining with the Geographic Information System (GIS), multi-level geological information superposition is achieved to provide a complete geological background map for subsequent analysis;

[0113] Element distribution analysis unit: used to calculate the abundance of mineral elements. The element distribution analysis unit is responsible for statistical analysis of the collected geological samples and extracting the content information of key ore-forming elements (such as Au, W, Mo, etc.). The unit reveals the spatial distribution characteristics of ore-forming elements in the mining area by calculating the average abundance, dispersion and distribution law of elements in the samples. The analysis results not only provide a scientific basis for the identification of high-potential exploration areas, but also provide important data support for subsequent three-dimensional modeling and reserve estimation.

[0114] Optionally, the modeling module can generate a dynamic three-dimensional mineral distribution model based on the collected ore body profile and mark important exploration areas. In the actual implementation process, a dynamic three-dimensional mineral distribution model is generated based on the collected ore body profile. The modeling module uses the ore body profile as the core data source and integrates geological information at different depths and profile positions into a three-dimensional spatial model. By superimposing remote sensing images, geological radar detection data and core analysis results, a three-dimensional distribution model of mineral resources is generated to intuitively display the spatial morphology, depth and reserve distribution characteristics of the ore body. In addition, the model can be updated dynamically, that is, as new data is collected and processed, the model automatically adjusts parameters to reflect the latest geological conditions. This dynamic update capability ensures that the model results always maintain real-time and high precision;

[0115] Marking important exploration areas. During the model building process, the modeling module automatically identifies and marks high-potential exploration areas by analyzing the distribution characteristics and spatial enrichment patterns of ore-forming elements. These marked areas are highlighted with specific colors or symbols in the 3D model, helping geological surveyors to quickly lock in key areas and optimize exploration plans. In addition, the module can also provide detailed data for each marked area, including depth range, abundance of major elements and possible reserve estimates, to further support resource assessment and development decisions.

[0116] Optionally, the output module can generate:

[0117] Two-dimensional mineral resource distribution map;

[0118] Three-dimensional ore body distribution model;

[0119] Comprehensive exploration report, including resource estimation, ore body distribution and development suggestions. In the actual implementation process, a two-dimensional mineral resource distribution map is generated. The output module presents the processed and analyzed geological data in the form of a two-dimensional distribution map, showing the distribution range of mineral resources in the mining area, enrichment areas and spatial distribution characteristics of major ore-forming elements. The two-dimensional distribution map contains detailed geographic information, such as ore body boundaries, geological structures, fault locations, etc., providing a clear plane view for geological exploration, facilitating a quick understanding of the overall situation of the mining area and guiding subsequent exploration work;

[0120] Generate a three-dimensional ore body distribution model. The output module generates an intuitive three-dimensional ore body distribution model by integrating the three-dimensional modeling results. The model can clearly present the geometric shape, depth range and internal structural characteristics of the ore body, and supports multi-angle rotation and layered viewing, which is convenient for fully understanding the spatial characteristics of the ore body. The three-dimensional model can also superimpose analysis results, such as the abundance and distribution of ore-forming elements, to provide more comprehensive information support for decision makers;

[0121] Generate a comprehensive exploration report. The output module can automatically generate a comprehensive exploration report including the following contents:

[0122] Resource estimation: Based on geological data and models, provide estimated reserve data of mineral resources, including total amount and distribution;

[0123] Ore body distribution: detailed description of the spatial location, morphological characteristics and distribution patterns of the ore body;

[0124] Development suggestions: Based on the exploration results and resource distribution characteristics, propose specific resource development plans and priority exploration areas to help formulate scientific development strategies.

[0125] In order to further verify the technical effect of the present invention, the technical solution of the present invention is described in detail below in conjunction with specific embodiments:

[0126] Example 1: Deep mineral resource exploration based on scientific drilling technology

[0127] In the actual exploration of the Laowan gold ore belt, in order to study the distribution of deep mineral resources and mineralization laws, the geological mineral exploration data extraction method proposed in the present invention was applied, and the specific steps are as follows:

[0128] Background: Scientific drilling work is carried out in the Laowan gold belt to systematically obtain deep geological information and study the mineralization laws and deposit characteristics.

[0129] Implementation steps: Data collection, obtaining deep core samples through scientific drilling technology, and identifying surface mineralization anomalies in combination with remote sensing images; using geological radar to detect the spatial distribution of hidden ore bodies to ensure the comprehensiveness and high accuracy of data collection.

[0130] Data preprocessing: physical and chemical tests are performed on core samples to analyze their density, magnetism, abundance and distribution of major mineralizing elements (such as Au, W, Mo); GIS technology is used to perform spatial registration and data fusion of remote sensing images, core data and radar detection results.

[0131] Feature extraction, analysis of the abundance, spatial distribution and correlation of mineralizing elements, determination of the enrichment patterns of gold (Au), molybdenum (Mo), bismuth (Bi) and other elements; identification of high-potential exploration areas based on regional geological background.

[0132] Model construction and result output: construct an ore body distribution model based on three-dimensional modeling technology to intuitively display the ore body shape and depth; output a comprehensive report including two-dimensional distribution map, three-dimensional model and resource estimation to provide decision support for further exploration.

[0133] Achievements: The spatial distribution area of ​​the ore body was successfully marked, and the predicted gold resource volume reached 500 tons, providing a scientific basis for subsequent mineral development.

[0134] Example 2: Study on the element characteristics and mineralization mechanism of Laowan concealed granite

[0135] In order to verify the influence of concealed granite on gold mineralization, the following research work was carried out in combination with the technical solution of the present invention, and the steps and methods include:

[0136] Background: The Au, W, Mo and other elements are highly enriched locally in the Laowan concealed granite. Its geochemical characteristics and mineralization relationship are studied.

[0137] Implementation steps: Data collection, collecting 236 samples of concealed granite, focusing on the spatial distribution and element abundance of the concealed rock mass; using remote sensing imaging technology to quickly identify surface mineralization anomalies on a large scale.

[0138] Data preprocessing uses foam plastic enrichment-graphite furnace atomic absorption spectrometer, fluorescence photometer and other instruments to analyze 12 elements such as Au, Bi, W, and Mo in the samples; data cleaning and unified format processing are used to ensure data consistency and high accuracy.

[0139] Feature extraction, through correlation study, it was found that Au and Bi are highly correlated (correlation coefficient 0.6611), indicating that the concealed granite provides a material source for gold mineralization; cluster analysis shows that the elements exhibit high temperature, medium temperature and low temperature classification, further revealing the behavioral characteristics of the elements in the mineralization process.

[0140] Output and summarize the results, output the element abundance distribution map of the concealed granite and the mineralization mechanism report; it is proposed that the deep-source mantle-derived magmatic hydrothermal fluids enriched in the concealed granite are the main source of ore-forming materials for the gold deposit.

[0141] Achievements: The close relationship between concealed granite and gold mineralization was clarified, providing theoretical support for large-scale gold resource development.

[0142] Working principle: The geological and mineral exploration data extraction method and system of the present invention completes the full-process closed-loop operation from data collection to result output through modular design, ensuring the efficient and accurate completion of mineral resource exploration and evaluation. First, the data acquisition module integrates high-precision remote sensing equipment, core drilling equipment and geological radar equipment to comprehensively cover the spatial distribution information of surface and deep ore bodies. Among them, remote sensing imaging technology is used to identify surface mineralization anomalies, geological radar is used to detect the distribution of hidden ore bodies, and core drilling equipment obtains deep samples for physical and chemical composition analysis. The collected data is cleaned, formatted and georeferenced by the data processing module. The data cleaning unit removes redundant and invalid data, the format unification unit standardizes multi-source data, and the geographic information integration unit maps the data to the geographic coordinate system through spatial registration technology. To ensure data consistency and fusion accuracy, the processed geological data enters the feature analysis module, and key mineralizing elements are extracted through abundance, distribution and correlation analysis. The mineralization areas and high-potential exploration areas are identified in combination with the regional geological background. The feature analysis results are input into the modeling module. By combining the ore body profile, geological plan and geological radar data, a three-dimensional ore body distribution model is constructed to clearly mark the spatial form and resource potential of the ore body. At the same time, the model can be dynamically adjusted according to real-time updated data. Finally, the output module presents the analysis results in the form of a two-dimensional distribution map, a three-dimensional model and a comprehensive exploration report. The report includes resource reserve estimation, ore body distribution and development suggestions. Through the collaborative work of the above methods and systems, the exploration efficiency and accuracy of mineral resources have been significantly improved, providing a comprehensive and reliable technical solution for the field of geological exploration.

[0143] The above shows and describes the basic principles, main features and advantages of the present invention, and the standard parts used in the present invention can be purchased from the market, and special-shaped parts can be customized according to the description in the specification and the drawings. The specific connection methods of each part adopt the conventional means such as mature bolts, rivets, welding, etc. in the prior art. The machinery, parts and equipment all adopt the conventional models in the prior art, and the circuit connection adopts the conventional connection method in the prior art, which will not be described in detail here.

[0144] The above descriptions are merely embodiments of the present invention and are not intended to limit the patent scope of the present invention. Any equivalent transformations made using the contents of the present invention's specification and drawings, or directly or indirectly applied in related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A method for extracting geological and mineral exploration data, characterized in that: The following steps are involved: S1: Data acquisition, obtaining multi-source geological data through scientific drilling, remote sensing images and geological radar; S2: Data preprocessing, cleaning, formatting and georeferencing of collected data; S3: Feature extraction, analyzing the abundance, distribution and correlation of key mineral elements; S4: Model construction, building a three-dimensional ore body distribution model based on geological data; S5: Output the results to generate mineral distribution maps, three-dimensional models and exploration reports.

2. A method for extracting geological and mineral exploration data according to claim 1, characterized in that: The data collection includes: Use geological drilling techniques to obtain core samples; Identify surface mineralization anomalies through remote sensing images; Geological radar is used to detect the distribution of hidden ore bodies.

3. A method for extracting geological and mineral exploration data according to claim 1, characterized in that: The data preprocessing includes: Conduct physical and chemical tests on core samples to analyze their elemental composition; Conduct spectral analysis on remote sensing images to extract mineral features; Spatial correction and data fusion were performed using geographic information systems.

4. A method for extracting geological and mineral exploration data according to claim 1, characterized in that: The feature extraction comprises: Analyze the abundance and distribution patterns of the main ore-forming elements in the mineral resource area; Identify element combinations closely related to mineralization through correlation studies; High potential exploration areas are delineated based on mineralogical characteristics.

5. A method for extracting geological and mineral exploration data according to claim 1, characterized in that: The model building steps include: Construct a three-dimensional model through ore body cross-section and geological plan; Combine geological radar detection data to mark the spatial distribution and depth of the ore body; The spatial morphology of the ore body is determined based on regional geological background analysis.

6. A geological and mineral exploration data extraction system, characterized in that: The extraction method applied to any one of claims 1 to 5 comprises: Data acquisition module: used to collect remote sensing images, geological radar and drilling data; Data processing module: used to clean and integrate the collected data; Feature analysis module: used to extract mineralization features from geological data; Modeling module: used to generate three-dimensional distribution model of mineral resources; Output module: used to generate geological maps, three-dimensional models and exploration reports.

7. A geological and mineral exploration data extraction system according to claim 6, characterized in that: The data acquisition module comprises: High-precision remote sensing equipment for identifying surface mineralization anomalies; Core drilling equipment, used for collecting deep core samples; Geological radar equipment, used for the detection of concealed ore bodies.

8. A geological and mineral exploration data extraction system according to claim 6, characterized in that: The data processing module comprises: Data cleaning unit, used to remove invalid or duplicate data; Geographic information integration unit, used for spatial registration of multi-source geological data; Element distribution analysis unit, used to calculate the abundance of mineral elements.

9. A geological and mineral exploration data extraction system according to claim 6, characterized in that: The modeling module can generate a dynamic three-dimensional mineral distribution model based on the collected ore body profile and mark important exploration areas.

10. A geological and mineral exploration data extraction system according to claim 6, characterized in that: The output module is capable of generating: Two-dimensional mineral resource distribution map; Three-dimensional ore body distribution model; Comprehensive exploration report including resource estimation, ore distribution and development recommendations.

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