A method and system for extracting data from geological and mineral exploration

Abstract

The present invention discloses a method and system for extracting data from geological and mineral exploration, which relates to the technical field of geological and mineral exploration data extraction. The method comprises the following steps: using a multi-source data collection method to collect data from a target area, obtaining satellite remote sensing data, unmanned aerial vehicle (UAV) aerial survey data, and ground geophysical data, and obtaining an original data set; using a preliminary data processing method to pre-process the collected data, remove noise, and correct errors, and obtain a high-quality data set; using a weighted fusion algorithm to integrate data from different sources in the high-quality data set, generating a comprehensive database, and obtaining a comprehensive data set; using geophysical exploration technology to perform high-resolution geophysical exploration on the fused comprehensive data set, and obtaining underground structure information; using geophysical inversion technology to analyze the exploration data, identify the location of potential ore bodies, and obtain an ore body distribution map; and based on the comprehensive data set, the underground structure information, and the ore body distribution map.

Description

Technical Field

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

[0002] Geological and mineral exploration extracted data refers to various information about the geological characteristics of the target area collected through various technologies and means during the geological and mineral exploration process. The data may include but is not limited to topography, stratigraphic structure, rock type, mineral composition and its distribution, etc.

[0003] In the field of geological and mineral exploration data extraction, traditional geological and mineral exploration often relies on a single data source, which leads to a one-sided and limited understanding of the target area. Data from different sources are subject to noise interference, scale differences and errors, which affect the accuracy of subsequent analysis. In addition, existing geophysical exploration technology cannot provide sufficiently detailed underground structure information, which limits the accurate identification of the location and morphology of potential ore bodies. Summary of the Invention

[0004] In view of the above existing problems, the present invention is proposed.

[0005] Therefore, the present invention provides a method for extracting data from geological and mineral exploration to solve the problem that traditional geological and mineral exploration often relies on a single data source, which leads to a one-sided and limited understanding of the target area, and data from different sources are subject to noise interference, scale differences and errors, affecting the accuracy of subsequent analysis.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0007] In a first aspect, the present invention provides a method for extracting data from geological and mineral exploration, comprising:

[0008] A multi-source data collection method is used to collect data in the target area, obtaining satellite remote sensing data, drone aerial survey data, and ground geophysical data, and obtaining the original data set;

[0009] Preliminary data processing methods are used to preprocess the collected data, remove noise and correct errors to obtain a high-quality data set;

[0010] A weighted fusion algorithm is used to integrate data from different sources in a high-quality dataset to generate a comprehensive database and obtain a comprehensive dataset;

[0011] Use geophysical exploration technology to conduct high-resolution geophysical exploration on the integrated data set to obtain underground structure information;

[0012] Use geophysical inversion technology to analyze exploration data, identify the location of potential ore bodies, and obtain ore body distribution maps;

[0013] Based on comprehensive data sets, underground structure information, and ore body distribution maps, a three-dimensional geological model of the target area is created. The three-dimensional geological model is visualized and analyzed using virtual reality technology to obtain ore body distribution display data.

[0014] As a preferred embodiment of the method for extracting data from geological and mineral exploration of the present invention, wherein: the multi-source data collection method is used to collect data from the target area to obtain satellite remote sensing data, drone aerial survey data and ground geophysical data, and obtain the original data set, the specific steps are as follows:

[0015] Drones equipped with LiDAR sensors and high-resolution cameras were used for detailed mapping of target areas;

[0016] During the flight of the UAV, the flight altitude is monitored and adjusted to obtain the UAV aerial survey data;

[0017] The UAV aerial survey data includes terrain model DTM and digital surface model;

[0018] Select multiple key points in the target area to conduct gravity surveys, magnetic surveys, and electrical surveys;

[0019] Import the data into a unified data processing platform and convert it to the same geographic coordinates. The expression is:

[0020] ;

[0021] in, represents satellite remote sensing data, Represents the spatial resolution, specifically the grayscale value of the image, Represents drone aerial survey data, represents the height change, specifically the surface reflectivity, represents ground geophysical data, Represents the detection depth, specifically the geophysical parameters.

[0022] As a preferred embodiment of the method for extracting data from geological and mineral exploration of the present invention, the method adopts a preliminary data processing method to pre-process the collected data, remove noise and correct errors to obtain a high-quality data set, and the specific steps are as follows:

[0023] Apply adaptive filtering technology to process the original data set;

[0024] Applying a least squares-based error correction model to the filtered data;

[0025] The noise-removed and error-corrected data are standardized to eliminate the scale differences between data from different sources and obtain a high-quality dataset.

[0026] As a preferred embodiment of the method for extracting data from geological and mineral exploration of the present invention, the weighted fusion algorithm is used to integrate data from different sources in the high-quality data set to generate a comprehensive database and obtain a comprehensive data set. The specific steps are as follows:

[0027] According to the quality and applicability of each data source, a weight function is defined, which is expressed as:

[0028] ;

[0029] in, is a tuning parameter used to control the concentration of weight distribution, Indicates the number of all available data sources, Indicates the data source type;

[0030] For each data point, calculate the fusion coefficient based on the weight function , the expression is:

[0031] ;

[0032] in, Indicates the number of data sources, Indicates the The data source is in The value of the data point;

[0033] Use the calculated fusion coefficient To build a comprehensive database;

[0034] The fusion coefficient of each data point is combined with its corresponding geographic location information to form the final comprehensive dataset.

[0035] As a preferred embodiment of the method for extracting data from geological and mineral exploration of the present invention, the method employs geophysical exploration technology to perform high-resolution geophysical exploration on the integrated data set to obtain underground structure information, and the specific steps are as follows:

[0036] Design a regular exploration grid within the target area;

[0037] Conduct field measurements using selected geophysical survey equipment according to a pre-designed survey grid;

[0038] Record data from each survey point and correlate it with the corresponding location information in the comprehensive dataset;

[0039] For each exploration point, calculate its outlier value relative to the background field, and the expression is:

[0040] ;

[0041] in, Indicates that the exploration point is at coordinates The actual measured value at is the background field value of the area, and are the maximum and minimum measured values ​​in the area, respectively;

[0042] Import all collected exploration data into professional software for processing, remove noise and correct errors;

[0043] Use inversion algorithms to convert measurements in two-dimensional or three-dimensional space into information about underground geological structures;

[0044] Combining all exploration data and their analysis results, a detailed underground structure information map is generated, and the underground structure information is obtained. The expression is:

[0045] ;

[0046] in, , , Representing the The three-dimensional coordinate position of the analysis point, Indicates the geological structure type or parameters at this point. is the total number of parsing points.

[0047] As a preferred embodiment of the method for extracting data from geological and mineral exploration of the present invention, the method employs geophysical inversion technology to analyze the exploration data, identify the location of potential ore bodies, and obtain an ore body distribution map. The specific steps are as follows:

[0048] Construct a preliminary underground geological model based on existing geological data and known underground structure information;

[0049] The underground geological model includes the estimated values ​​of stratum interfaces, rock types and their physical parameters, and its expression is:

[0050] ;

[0051] in, Indicates the The stratigraphic density of each unit, represents the unit volume, is the total number of elements in the model;

[0052] Perform forward simulations of the initial model using the selected inversion model to calculate the expected geophysical fields;

[0053] The simulation results are compared with the actual measurement data to evaluate the accuracy of the model. The result expression of the forward simulation is:

[0054] ;

[0055] in, is the forward simulation function of the geophysical field, is the initial model;

[0056] Calculate the difference between the simulation results and the actual measured data and define the error function To quantify this difference, the expression is:

[0057] ;

[0058] in, Indicates the The simulation results of the points, is the corresponding observation data, is the total number of data points;

[0059] According to the results of the error analysis, adjust the parameters in the initial model and re-run the forward simulation until the error Reach a minimum value;

[0060] When the error After reaching the predetermined threshold, the ore body distribution map is generated based on the final optimized underground model , the expression is:

[0061] ;

[0062] in, , , Representing the The three-dimensional coordinates of the ore body location, Indicates the properties of the ore body, is the total number of ore bodies.

[0063] As a preferred embodiment of the method for extracting data from geological and mineral exploration according to the present invention, the method comprises the following steps: creating a three-dimensional geological model of the target area based on a comprehensive data set, underground structure information, and an ore body distribution map; and visually analyzing the three-dimensional geological model using virtual reality technology to obtain ore body distribution display data.

[0064] Using GOCAD, a 3D geological modeling software, to construct a preliminary 3D geological model framework based on underground structural information, the preliminary 3D geological model framework including stratigraphic interfaces and geological units;

[0065] The information in the ore body distribution map is integrated into the three-dimensional geological model, and the expression is:

[0066] ;

[0067] in, Indicates the The property value of the ore body, is the ore body volume, is the total number of ore bodies;

[0068] Refine the 3D geological model based on additional information provided by the comprehensive dataset;

[0069] Select VR software Unreal Engine and import the optimized 3D geological model into the virtual reality VR platform;

[0070] Utilize the tools provided by the VR platform to generate detailed ore body distribution display data.

[0071] In a second aspect, the present invention provides a geological and mineral exploration data extraction system, comprising:

[0072] Data acquisition module, data preprocessing module, data integration module, geophysical exploration module, geophysical inversion module and visualization analysis module;

[0073] The data acquisition module is used to collect data from the target area using a multi-source data collection method, obtain satellite remote sensing data, drone aerial survey data, and ground geophysical data, and generate an original data set;

[0074] The data preprocessing module is used to perform preliminary processing on the collected data, remove noise and correct errors to obtain a high-quality data set;

[0075] The data integration module is used to integrate data from different sources in the high-quality data set using a weighted fusion algorithm to generate a comprehensive database and obtain a comprehensive data set;

[0076] The geophysical exploration module is used to perform high-resolution geophysical exploration on the fused comprehensive data set to obtain underground structure information;

[0077] The geophysical inversion module is used to analyze the exploration data, identify the location of potential ore bodies, and obtain an ore body distribution map;

[0078] The visualization analysis module is used to create a three-dimensional geological model of the target area based on a comprehensive data set, underground structure information and ore body distribution map, and perform visualization analysis through virtual reality technology to obtain ore body distribution display data.

[0079] In a third aspect, the present invention provides a computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: when the computer program is executed by the processor, any step of the method for extracting data from geological and mineral exploration as described in the first aspect of the present invention is implemented.

[0080] In a fourth aspect, the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein: when the computer program is executed by a processor, it implements any step of the method for extracting data from geological and mineral exploration as described in the first aspect of the present invention.

[0081] The beneficial effects of the present invention are as follows: by performing preliminary processing on the collected data, removing noise and correcting errors, the generation of high-quality data sets is achieved; the high-quality data sets reduce the uncertainty in subsequent analysis and improve the consistency and reliability of the data; by adopting a weighted fusion algorithm to integrate data from different sources in the high-quality data sets, the creation of a comprehensive database is achieved, and a comprehensive data set is obtained; through weighted fusion, the advantages of each data source are maximized, thereby providing more comprehensive and accurate geological information, which not only improves the comprehensive utilization rate of the data, but also provides stronger support for geophysical exploration, and helps to discover the location and morphology of potential ore bodies; the application of high-resolution geophysical exploration technology can not only depict the underground structure in detail, but also help identify areas that may contain ore bodies; by calculating the outliers of the exploration points relative to the background field, the location and morphology of the potential ore bodies can be more accurately located. BRIEF DESCRIPTION OF THE DRAWINGS

[0082] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0083] Figure 1 This is a flow chart of the method for extracting data from geological and mineral exploration in Example 1.

[0084] Figure 2 Schematic diagram of the system for extracting data from geological and mineral exploration in Example 1. DETAILED DESCRIPTION

[0085] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0086] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0087] Secondly, the term "one embodiment" or "embodiment" herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in various places throughout this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive of other embodiments.

[0088] Example 1, with reference to Figure 1 and Figure 2 , which is the first embodiment of the present invention, provides a method for extracting data from geological and mineral exploration, comprising the following steps:

[0089] S1. Use multi-source data collection methods to collect data in the target area, obtain satellite remote sensing data, UAV aerial survey data, and ground geophysical data, and obtain the original data set;

[0090] Going a step further, drones equipped with LiDAR sensors and high-resolution cameras are used for detailed mapping of target areas;

[0091] During the flight of the UAV, the flight altitude is monitored and adjusted to obtain the UAV aerial survey data;

[0092] UAV aerial survey data includes terrain model DTM and digital surface model;

[0093] Select multiple key points in the target area to conduct gravity surveys, magnetic surveys, and electrical surveys;

[0094] Import the data into a unified data processing platform and convert it to the same geographic coordinates. The expression is:

[0095] ;

[0096] in, represents satellite remote sensing data, Represents the spatial resolution, specifically the grayscale value of the image, Represents drone aerial survey data, represents the height change, specifically the surface reflectivity, represents ground geophysical data, Represents the detection depth, specifically geophysical parameters;

[0097] It should be noted that by integrating multiple data sources such as satellite remote sensing, drone aerial surveys, and ground geophysical exploration, it is possible not only to obtain comprehensive information about the target area, but also to ensure that these data are accurately aligned in a unified geographic coordinate system, thus laying a solid foundation for subsequent data processing and analysis.

[0098] S2. Preprocess the collected data using preliminary data processing methods to remove noise and correct errors to obtain a high-quality data set;

[0099] Furthermore, adaptive filtering technology is applied to process the original data set;

[0100] Applying a least squares-based error correction model to the filtered data;

[0101] Normalize the noise-removed and error-corrected data to eliminate scale differences between data from different sources and obtain a high-quality dataset;

[0102] It should be noted that the application of adaptive filtering technology and the error correction model based on the least squares method in the preliminary data processing step can not only effectively remove noise and correct errors, but also significantly improve the quality of the data and ensure the accuracy and reliability of subsequent analysis results.

[0103] S3, using weighted fusion algorithms to integrate data from different sources in high-quality datasets to generate a comprehensive database and obtain a comprehensive dataset;

[0104] Furthermore, a weight function is defined based on the quality and applicability of each data source, and the expression is:

[0105] ;

[0106] in, is a tuning parameter used to control the concentration of weight distribution, Indicates the number of all available data sources, Indicates the data source type;

[0107] For each data point, calculate the fusion coefficient based on the weight function , the expression is:

[0108] ;

[0109] in, Indicates the number of data sources, Indicates the The data source is in The value of the data point;

[0110] Use the calculated fusion coefficient To build a comprehensive database;

[0111] Combine the fusion coefficient of each data point with its corresponding geographic location information to form the final comprehensive data set;

[0112] It should be noted that when using a weighted fusion algorithm to integrate data from different sources, weights are assigned according to the quality and applicability of each data source, which can maximize the advantages of each data type and generate a more comprehensive and accurate integrated database, providing strong support for subsequent geophysical exploration.

[0113] S4. Use geophysical exploration technology to conduct high-resolution geophysical exploration on the integrated data set to obtain underground structure information;

[0114] Furthermore, a regular exploration grid is designed in the target area;

[0115] Conduct field measurements using selected geophysical survey equipment according to a pre-designed survey grid;

[0116] Record data from each survey point and correlate it with the corresponding location information in the comprehensive dataset;

[0117] For each exploration point, calculate its outlier value relative to the background field, and the expression is:

[0118] ;

[0119] in, Indicates that the exploration point is at coordinates The actual measured value at is the background field value of the area, and are the maximum and minimum measured values ​​in the area, respectively;

[0120] Import all collected exploration data into professional software for processing, remove noise and correct errors;

[0121] Use inversion algorithms to convert measurements in two-dimensional or three-dimensional space into information about underground geological structures;

[0122] Combining all exploration data and their analysis results, a detailed underground structure information map is generated, and the underground structure information is obtained, which is expressed as:

[0123] ;

[0124] in, , , Representing the The three-dimensional coordinate position of the analysis point, Indicates the geological structure type or parameters at this point, is the total number of parsing points;

[0125] It should be noted that the application of high-resolution geophysical exploration technology can not only obtain detailed underground structural information, but also identify the location and morphology of potential ore bodies by calculating the anomaly values ​​of the exploration points relative to the background field, which is crucial for subsequent geological analysis.

[0126] S5. Use geophysical inversion technology to analyze exploration data, identify the location of potential ore bodies, and obtain ore body distribution maps;

[0127] Furthermore, a preliminary underground geological model is constructed based on the existing geological data and known underground structural information;

[0128] The underground geological model includes the estimated values ​​of stratigraphic interfaces, rock types and their physical parameters, and its expression is:

[0129] ;

[0130] in, Indicates the The stratigraphic density of each unit, represents the unit volume, is the total number of elements in the model;

[0131] Perform forward simulations of the initial model using the selected inversion model to calculate the expected geophysical fields;

[0132] The simulation results are compared with the actual measurement data to evaluate the accuracy of the model. The result expression of the forward simulation is:

[0133] ;

[0134] in, is the forward simulation function of the geophysical field, is the initial model;

[0135] Calculate the difference between the simulation results and the actual measured data and define the error function To quantify this difference, the expression is:

[0136] ;

[0137] in, Indicates the The simulation results of the points, is the corresponding observation data, is the total number of data points;

[0138] According to the results of the error analysis, adjust the parameters in the initial model and re-run the forward simulation until the error Reach a minimum value;

[0139] When the error After reaching the predetermined threshold, the ore body distribution map is generated based on the final optimized underground model , the expression is:

[0140] ;

[0141] in, , , Representing the The three-dimensional coordinates of the ore body location, Indicates the properties of the ore body, is the total number of ore bodies;

[0142] It should be noted that geophysical inversion technology can effectively identify the specific location and properties of potential ore bodies through in-depth analysis of exploration data, and ensure the accuracy and scientific nature of the final ore body distribution map by continuously adjusting the initial model parameters until the error reaches the minimum value.

[0143] S6. Create a 3D geological model of the target area based on the comprehensive data set, underground structure information, and ore body distribution map. Use virtual reality technology to visualize and analyze the 3D geological model to obtain ore body distribution display data.

[0144] Furthermore, a preliminary 3D geological model framework was constructed based on the underground structure information using GOCAD, a 3D geological model software. The preliminary 3D geological model framework includes stratigraphic interfaces and geological units.

[0145] The information in the ore body distribution map is integrated into the three-dimensional geological model, and the expression is:

[0146] ;

[0147] in, Indicates the The property value of the ore body, is the ore body volume, is the total number of ore bodies;

[0148] Refine the 3D geological model based on additional information provided by the comprehensive dataset;

[0149] Select VR software Unreal Engine and import the optimized 3D geological model into the virtual reality VR platform;

[0150] Use the tools provided by the VR platform to generate detailed ore body distribution display data;

[0151] It should be noted that using 3D geological modeling software combined with virtual reality technology to create a 3D geological model of the target area can not only intuitively display the distribution of ore bodies, but also improve data analysis efficiency through immersive experience, enhance the scientific nature and accuracy of the decision-making process. In addition, this method also allows users to further refine the model as needed to meet the needs of specific application scenarios.

[0152] This embodiment also provides a geological and mineral exploration data extraction system, including:

[0153] Data acquisition module, data preprocessing module, data integration module, geophysical exploration module, geophysical inversion module and visualization analysis module;

[0154] The data acquisition module is used to collect data from the target area using a multi-source data collection method, obtain satellite remote sensing data, drone aerial survey data, and ground geophysical data, and generate the original data set;

[0155] The data preprocessing module is used to perform preliminary processing on the collected data, remove noise and correct errors to obtain a high-quality data set;

[0156] The data integration module is used to integrate data from different sources in high-quality data sets using a weighted fusion algorithm to generate a comprehensive database and obtain a comprehensive data set;

[0157] The geophysical exploration module is used to perform high-resolution geophysical exploration on the integrated data set to obtain underground structure information;

[0158] Geophysical inversion module, used to analyze exploration data, identify the location of potential ore bodies, and obtain ore body distribution maps;

[0159] The visualization analysis module is used to create a three-dimensional geological model of the target area based on comprehensive data sets, underground structure information and ore body distribution maps, and perform visualization analysis through virtual reality technology to obtain ore body distribution display data.

[0160] This embodiment also provides a computer device suitable for the method of extracting data from geological and mineral exploration, including: a memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute computer-executable instructions to implement the method of extracting data from geological and mineral exploration proposed in the above embodiment.

[0161] The computer device may be a terminal, comprising a processor, memory, a communication interface, a display, and an input device connected via a system bus. The processor of the computer device provides computing and control capabilities. The memory of the computer device includes non-volatile storage media and internal memory. The non-volatile storage media stores an operating system and computer programs. The internal memory provides an environment for the operating system and computer programs stored in the non-volatile storage media. The communication interface of the computer device is used to communicate with external terminals via wired or wireless communication. Wireless communication may be achieved via Wi-Fi, a carrier network, NFC (near-field communication), or other technologies. The display of the computer device may be a liquid crystal display or an electronic ink display. The input device of the computer device may be a touchscreen layer covering the display, buttons, a trackball, or a touchpad provided on the computer device housing, or an external keyboard, touchpad, or mouse.

[0162] This embodiment also provides a storage medium having a computer program stored thereon, which, when executed by a processor, implements the method for extracting data from geological and mineral exploration as proposed in the above embodiment; the storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk.

[0163] In summary, the present invention achieves the generation of high-quality data sets by performing preliminary processing on the collected data, removing noise and correcting errors. The high-quality data sets reduce the uncertainty in subsequent analysis and improve the consistency and reliability of the data. By adopting a weighted fusion algorithm to integrate data from different sources in the high-quality data sets, the creation of a comprehensive database is achieved, and a comprehensive data set is obtained. Through weighted fusion, the advantages of each data source are maximized, thereby providing more comprehensive and accurate geological information, which not only improves the comprehensive utilization rate of data, but also provides stronger support for geophysical exploration, and helps to discover the location and morphology of potential ore bodies. The application of high-resolution geophysical exploration technology can not only depict the underground structure in detail, but also help identify areas that may contain ore bodies. By calculating the outliers of the exploration points relative to the background field, the location and morphology of potential ore bodies can be more accurately located.

[0164] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A method for extracting data from geological and mineral exploration, characterized by: include: A multi-source data collection method is used to collect data in the target area, obtaining satellite remote sensing data, drone aerial survey data, and ground geophysical data, and obtaining the original data set; Preliminary data processing methods are used to preprocess the collected data, remove noise and correct errors to obtain a high-quality data set; A weighted fusion algorithm is used to integrate data from different sources in a high-quality dataset to generate a comprehensive database and obtain a comprehensive dataset; Use geophysical exploration technology to conduct high-resolution geophysical exploration on the integrated data set to obtain underground structure information; Use geophysical inversion technology to analyze exploration data, identify the location of potential ore bodies, and obtain ore body distribution maps; Based on comprehensive data sets, underground structural information, and ore body distribution maps, a 3D geological model of the target area is created. This model is then visualized and analyzed using virtual reality technology to obtain ore body distribution data. The geophysical exploration technology is used to perform high-resolution geophysical exploration on the integrated data set to obtain underground structure information. The specific steps are as follows: Design a regular exploration grid within the target area; Conduct field measurements using selected geophysical survey equipment according to a pre-designed survey grid; Record data from each survey point and correlate it with the corresponding location information in the comprehensive dataset; For each exploration point, calculate its outlier value relative to the background field, and the expression is: ； in, Indicates that the exploration point is at coordinates The actual measured value at is the background field value of the area, and are the maximum and minimum measured values ​​in the area, respectively; Import all collected exploration data into professional software for processing, remove noise and correct errors; Use inversion algorithms to convert measurements in two-dimensional or three-dimensional space into information about underground geological structures; Combining all exploration data and their analysis results, a detailed underground structure information map is generated, and the underground structure information is obtained. The expression is: ; in, , , Representing the The three-dimensional coordinate position of the analysis point, Indicates the geological structure type or parameters at this point. is the total number of parsing points; The geophysical inversion technology is used to analyze the exploration data, identify the location of potential ore bodies, and obtain an ore body distribution map. The specific steps are: Construct a preliminary underground geological model based on existing geological data and known underground structure information; The underground geological model includes the estimated values ​​of stratum interfaces, rock types and their physical parameters, and its expression is: ; in, Indicates the The stratigraphic density of each unit, represents the unit volume, is the total number of elements in the model; Perform forward simulations of the initial model using the selected inversion model to calculate the expected geophysical fields; The simulation results are compared with the actual measurement data to evaluate the accuracy of the model. The result expression of the forward simulation is: ; in, is the forward simulation function of the geophysical field, is the initial model; Calculate the difference between the simulation results and the actual measured data and define the error function To quantify this difference, the expression is: ; in, Indicates the The simulation results of the points, is the corresponding observation data, is the total number of data points; According to the results of the error analysis, adjust the parameters in the initial model and re-run the forward simulation until the error Reach a minimum value; When the error After reaching the predetermined threshold, the ore body distribution map is generated based on the final optimized underground model , the expression is: ; in, , , Representing the The three-dimensional coordinates of the ore body location, Indicates the properties of the ore body, is the total number of ore bodies.

2. The method for extracting data from geological and mineral exploration according to claim 1, wherein: The multi-source data collection method is used to collect data from the target area, obtain satellite remote sensing data, drone aerial survey data, and ground geophysical data, and obtain the original data set. The specific steps are as follows: Drones equipped with LiDAR sensors and high-resolution cameras were used for detailed mapping of target areas; During the flight of the UAV, the flight altitude is monitored and adjusted to obtain the UAV aerial survey data; The UAV aerial survey data includes terrain model DTM and digital surface model; Select multiple key points in the target area to conduct gravity surveys, magnetic surveys, and electrical surveys; Import the data into a unified data processing platform and convert it to the same geographic coordinates. The expression is: ； in, represents satellite remote sensing data, Represents the spatial resolution, specifically the grayscale value of the image, Represents drone aerial survey data, represents the height change, specifically the surface reflectivity, represents ground geophysical data, Represents the detection depth, specifically the geophysical parameters.

3. The method for extracting geological and mineral exploration data according to claim 2, wherein: The preliminary data processing method is used to pre-process the collected data, remove noise and correct errors to obtain a high-quality data set. The specific steps are as follows: Apply adaptive filtering technology to process the original data set; Applying a least squares-based error correction model to the filtered data; The noise-removed and error-corrected data are standardized to eliminate the scale differences between data from different sources and obtain a high-quality dataset.

4. The method for extracting data from geological and mineral exploration according to claim 3, wherein: The weighted fusion algorithm is used to integrate data from different sources in the high-quality data set to generate a comprehensive database and obtain a comprehensive data set. The specific steps are: According to the quality and applicability of each data source, a weight function is defined, which is expressed as: ; in, is a tuning parameter used to control the concentration of weight distribution, Indicates the number of all available data sources, Indicates the data source type; For each data point, calculate the fusion coefficient based on the weight function , the expression is: ; in, Indicates the number of data sources, Indicates the The data source is in The value of the data point; Use the calculated fusion coefficient To build a comprehensive database; The fusion coefficient of each data point is combined with its corresponding geographic location information to form the final comprehensive dataset.

5. The method for extracting data from geological and mineral exploration according to claim 4, wherein: The method is based on a comprehensive data set, underground structure information, and ore body distribution map to create a three-dimensional geological model of the target area, and uses virtual reality technology to perform visualization analysis on the three-dimensional geological model to obtain ore body distribution display data. The specific steps are as follows: Using GOCAD, a 3D geological modeling software, to construct a preliminary 3D geological model framework based on underground structural information, the preliminary 3D geological model framework including stratigraphic interfaces and geological units; The information in the ore body distribution map is integrated into the three-dimensional geological model, and the expression is: ; in, Indicates the The property value of the ore body, is the ore body volume, is the total number of ore bodies; Refine the 3D geological model based on additional information provided by the comprehensive dataset; Select VR software Unreal Engine and import the optimized 3D geological model into the virtual reality VR platform; Utilize the tools provided by the VR platform to generate detailed ore body distribution display data.

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