AI-based multivariate heterogeneous geological data fusion prospecting analysis method and system

Abstract

The invention relates to the technical field of geological exploration, in particular to an AI-based multivariate heterogeneous geological data fusion prospecting analysis method and system. The method comprises the steps of obtaining a remote sensing image; acquiring sampling data; analyzing the remote sensing image, and determining three-dimensional coordinates of the to-be-detected area; analyzing the sampling data, and determining a geological growth vein between any adjacent sampling columns of the to-be-detected area; according to the geological growth venation between any adjacent sampling columns, determining whether a vein exists in the to-be-detected area or not; and if the vein exists, determining the vein trend based on the three-dimensional coordinates. According to the scheme, multiple data sources are fused, more comprehensive geological information is obtained, and the geological features of the to-be-detected area can be deeply known; the time and workload of manual operation are reduced; by analyzing geological growth veins and vein features, the trend and distribution of the veins are predicted more accurately, and an important basis is provided for mineral resource exploration; the accuracy of vein recognition is improved; and the efficiency and the success rate of mineral resource exploration can be improved.

Description

Technical Field

[0001] The present application relates to the field of geological exploration technology, and in particular to an AI-based multi-heterogeneous geological data fusion prospecting and analysis method and system. Background Art

[0002] With the continuous development of science and technology, geological exploration technology plays an increasingly important role in mineral resource exploration. Especially in the field of mineral resource exploration, the fusion prospecting analysis method of multi-heterogeneous geological data has gradually attracted widespread attention as an emerging technical means. This method analyzes geological characteristics by combining multiple data sources such as remote sensing images and sampling data, thereby improving the success rate and accuracy of prospecting.

[0003] However, the traditional geological prospecting method mainly relies on the experience and intuition of geologists, which has certain limitations. The existing multivariate heterogeneous geological data fusion prospecting analysis method has certain shortcomings in the implementation process, such as the processing and analysis of sampling data is relatively complicated, and there are certain limitations in the mining of a large amount of multivariate heterogeneous data. Therefore, it is necessary to study a new multivariate heterogeneous geological data fusion prospecting analysis method to improve the efficiency and accuracy of prospecting. Summary of the invention

[0004] This application provides an AI-based multi-heterogeneous geological data fusion prospecting and analysis method and system to solve the above problems.

[0005] In a first aspect, the present application provides an AI-based multi-heterogeneous geological data fusion prospecting and analysis method, the method comprising:

[0006] Acquire remote sensing images; acquire sampling data; analyze the remote sensing images to determine the three-dimensional coordinates of the area to be measured;

[0007] Analyze the sampling data to determine the geological growth veins between any adjacent sampling columns in the area to be tested;

[0008] Determine whether there is a mineral vein in the area to be tested based on the geological growth veins between any adjacent sampling columns;

[0009] If a mineral vein exists, the direction of the mineral vein is determined based on the three-dimensional coordinates.

[0010] Through this solution, by integrating multiple data sources, such as remote sensing images, sampling data, etc., more comprehensive geological information can be obtained, which helps to gain a deeper understanding of the geological characteristics of the area to be tested; through the automated processing and analysis of a large amount of remote sensing images and sampling data by AI technology, the efficiency of mineral exploration can be significantly improved, and the time and workload of manual operations can be reduced; by analyzing the geological growth veins and mineral vein characteristics, the direction and distribution of mineral veins can be more accurately predicted, providing an important basis for mineral resource exploration; the three-dimensional coordinates and geological growth veins of the area to be tested can be more accurately determined, thereby improving the accuracy of mineral vein identification; it can provide more scientific decision-making support for the field of geological exploration, which helps to improve the efficiency and success rate of mineral resource exploration.

[0011] Optionally, the acquiring sampling data includes:

[0012] Acquire cross-sectional images and cylinder images of several sampling columns;

[0013] Extracting image features of the cross-sectional image, and determining an initial sampling direction according to the image features;

[0014] Based on the initial sampling direction, analyzing the cross-sectional image to determine the cross-sectional change;

[0015] Based on the sampling initial direction, analyzing the cylinder image to determine the cylinder change;

[0016] The cross-section change and the column change are used as the sampling data.

[0017] Through this scheme, by directly observing the cross-section and column images of rocks, the structure and properties of rocks can be intuitively understood; the features extracted using image processing technology are more objective and not affected by the subjective judgment of geologists; through precise feature extraction, the sampling direction can be determined more accurately and the sampling efficiency can be improved; by systematically analyzing the cross-section images, the evolution process of geological structures can be fully understood, and by identifying the change patterns, the change trends of geological structures in the future can be predicted. The column images provide a three-dimensional perspective, which helps to more fully understand the three-dimensional morphology of geological structures and can more carefully analyze the physical and chemical properties of rocks, such as mineral content, porosity, etc.

[0018] Optionally, determining the initial sampling direction according to the image feature includes:

[0019] Obtain ground images before sampling;

[0020] According to the image features of each sampling column, the geographical location of each sampling column before sampling is determined;

[0021] According to the geographical location, the ground image is screened to determine an exclusive image corresponding to each sampling column;

[0022] For each sampling column, the exclusive image is analyzed to determine the original ground features, and the directional features are selected based on the preset direction;

[0023] The directional feature is compared with the image feature, and an initial sampling direction is determined according to the comparison result.

[0024] Through this solution, using image processing and pattern recognition technology, features can be objectively extracted from images, subjective errors can be avoided, and the analysis results can be made more reliable. Automating large amounts of data processing and analysis processes can significantly improve work efficiency and save a lot of time and manpower. Through positioning technologies such as GPS, the geographical location of the sampling column can be accurately determined. Combining ground images and sampling column images can achieve the fusion of multi-source data and provide more comprehensive geological information. By analyzing image features and directional features, the distribution of geological structures and mineral veins can be more accurately predicted, thereby improving the success rate of prospecting.

[0025] Optionally, analyzing the sampling data to determine the geological growth veins between any adjacent sampling columns in the area to be tested includes:

[0026] Determine the geological surface structure and surface rock type according to the cross-sectional changes;

[0027] Determine the characteristics of the rock layers and the geological changes of each rock layer according to the changes in the column;

[0028] For each sampling column, according to the rock formation characteristics and geological changes of each rock formation, determine the geological structural sequence of the rock formation corresponding to each sampling column;

[0029] According to the geological structure sequence, the geological growth veins between any adjacent sampling columns in the area to be tested are determined.

[0030] Through this solution, relying on objective data and image processing technology, the influence of personal experience and intuition is reduced, and the objectivity and repeatability of the analysis are improved; through high-resolution images and precise geographic location information, geological structures and rock types can be determined more accurately, thereby improving the accuracy of prospecting; combined with cross-sectional and cylindrical image analysis, a comprehensive geological perspective can be provided, including geological surface structures, rock formation characteristics, and geological changes, so as to more systematically understand the geological growth context; automated data processing and analysis processes can process large amounts of data, improve work efficiency, and shorten the prospecting cycle; automated image analysis and feature extraction reduce errors caused by human operations and improve data reliability; by analyzing the sequence of geological structures, the distribution of geological structures and ore veins can be more accurately predicted, thereby improving the success rate of prospecting; the collected data can be used to construct a three-dimensional geological model to more intuitively display the geological growth context, facilitating analysis and decision-making.

[0031] Optionally, determining the geological growth veins between any adjacent sampling columns in the area to be tested according to the geological structure sequence includes:

[0032] For each sampling column, based on the initial sampling direction, any sampling column is used as a base column, and any other sampling column is selected as a reference column; the reference column is a reference object of any base column, and the reference column is not any base column;

[0033] Determine the reference cylindrical coordinates and the reference cylindrical coordinates according to the three-dimensional coordinates of the area to be measured;

[0034] Taking the sampling initial direction as the connection direction, based on the reference column coordinates and the reference column coordinates, determining the surface to be measured between the reference column and the reference column;

[0035] Predicting the geological changes of the surface to be measured according to the geological structural sequence of the rock layer corresponding to each sampling column;

[0036] According to the geological changes of the surface to be tested, the geological growth veins between any adjacent sampling columns in the area to be tested are determined.

[0037] Through this solution, by analyzing the geological structure sequence, the geological changes in the area to be tested can be predicted more accurately, thereby improving the accuracy of predictions on the distribution of ore veins and geological characteristics; it provides detailed information on geological structures and development trends, and more accurate geological growth vein analysis can help reduce exploration risks; by understanding geological growth veins, the economic value of mineral resources can be more effectively evaluated, thereby optimizing resource development decisions; through precise exploration, damage to the environment can be reduced because they can guide more targeted exploration activities; automated data processing and analysis processes can process large amounts of data, improve work efficiency, and shorten the prospecting cycle; automated image analysis and feature extraction reduce errors caused by human operations and improve data reliability.

[0038] Optionally, determining the surface to be measured between the reference column and the reference column based on the reference column coordinates includes:

[0039] Taking the preset storey height as the interval standard, traverse the center coordinates of the reference column at each storey height and the center coordinates of the reference column at each storey,

[0040] Connect the coordinates of the center of the circle of the reference column at each floor height with the coordinates of the center of the circle of the reference column at the corresponding floor height to obtain a number of connecting lines until the centers of all the reference columns at each floor height are connected;

[0041] For each reference column, interpolation processing is performed on the reference column to determine whether there is a possibility of a layer gap outside the spacing standard;

[0042] If it exists, the reference height of the reference column is determined according to the interlayer gap height, and the coordinates of the center of the circle at the interlayer gap height are connected to obtain an interlayer gap connection line;

[0043] According to the plurality of connection lines and the layer gap connection lines, a surface to be measured between the benchmark column and the reference column is determined.

[0044] Through this scheme, by interpolating the coordinates of the benchmark column and the reference column and analyzing the connecting lines, the geological structure, especially the contact relationship between geological sequences and strata, can be understood more intuitively; interpolation processing can help identify interlayer gaps, which may indicate important geological features such as faults, sedimentary discontinuities or magmatic intrusions; based on accurate coordinate data and interpolation results, a more accurate geological model can be constructed, which is crucial for geological exploration and resource assessment; by determining the surface to be tested, the exploration strategy can be optimized and resources can be concentrated on the most promising areas for exploration; by analyzing interlayer gaps and connecting lines, potential changes between strata can be predicted, and trends in geological changes, such as tilt, folding or faulting of strata, can be identified, which enhances the ability to predict geological growth veins; the determined surface to be tested can be used to predict the direction and position of the veins, which is of direct significance for mineral deposit exploration.

[0045] Optionally, after determining the geological growth veins between any adjacent sampling columns in the area to be tested according to the geological changes of the surface to be tested, the method further includes:

[0046] For each surface to be tested, any three or more surfaces to be tested are connected to form a three-dimensional area;

[0047] Predicting geological growth changes in the three-dimensional area according to geological changes in the surface to be measured;

[0048] Traversing all three-dimensional regions, and determining the geological growth veins of the region to be measured according to the geological growth changes of the three-dimensional regions;

[0049] Determining whether there is a mineral vein in the area to be tested based on the geological growth veins between any adjacent sampling columns includes:

[0050] Determine whether there is a mineral vein in the area to be tested based on the geological growth veins in the area to be tested.

[0051] Through this scheme, by connecting the surface to be tested into three-dimensional areas, a more accurate geological model can be constructed to understand the geological structure and predict geological changes. Analyzing the geological changes of the surface to be tested can help predict the geological growth changes in the three-dimensional area; traversing all three-dimensional areas and analyzing their geological growth changes can more comprehensively determine the geological growth veins of the area to be tested, providing more accurate guidance for geological exploration; based on the geological growth veins between any adjacent sampling columns, it is possible to more accurately predict whether there are mineral veins in the area to be tested, thereby improving the success rate of prospecting; the collected data can be used to construct a three-dimensional geological model to more intuitively display the geological growth veins, which is convenient for analysis and decision-making.

[0052] Optionally, determining whether there is a mineral vein in the area to be tested based on the geological growth veins between any adjacent sampling columns includes:

[0053] Determine the rock type present in each rock layer based on the rock layer characteristics;

[0054] Acquiring the regional position of the area to be tested, and determining the possible type of the mineral vein according to the regional position;

[0055] Based on the possible types of the mineral veins, the rock types and the geological growth veins between any adjacent sampling columns, it is determined whether there are mineral veins in the area to be tested.

[0056] Through this scheme, through detailed analysis of rock formation characteristics, because different rock types may indicate different geological environments and mineralization potentials, the rock type of each rock formation can be accurately determined, providing basic data for subsequent vein predictions, which helps to build a more accurate geological model. According to the regional location, the possible types of veins that match the geological conditions of the area can be determined, improving the pertinence of prospecting, avoiding ineffective exploration in areas without potential vein types, and reducing risks and costs. By comprehensively considering the possible types of veins, rock types, and geological growth veins, the comprehensiveness and accuracy of the analysis are improved; based on multi-factor analysis, it is possible to more accurately predict whether there are veins in the area to be tested.

[0057] Optionally, after determining whether there is a mineral vein in the area to be tested based on the possible mineral vein type, rock type and the geological growth veins between any adjacent sampling columns, the method further includes:

[0058] If it is determined that there is no mineral vein in the test area, determining whether there is a possibility of mineral vein development in the test area according to the geological growth veins between any adjacent sampling columns;

[0059] If so, predicting the geological changes of the area to be tested within a preset distance range according to the geological growth veins between any adjacent sampling columns;

[0060] According to the geological changes in the area to be measured within a preset distance range, the location of the mineral vein is inferred, and based on the location of the mineral vein, it is determined whether there is mining value.

[0061] Through this plan, unnecessary exploration and mining activities can be avoided in areas without mineral veins, saving human, material and financial resources; reducing risk investment in areas without mineral veins and protecting the financial security of enterprises; deepening the understanding of geological structure and mineralization environment, providing a theoretical basis for subsequent mineral exploration; integrating data from different sampling columns to form a continuous geological information chain, which is conducive to comprehensive analysis of regional geological characteristics; clarifying the prospecting goals and directions of the area to be tested and improving exploration efficiency; determining the possible locations of mineral veins through geological change predictions to guide exploration activities; and increasing the success rate of exploration at possible locations of mineral veins.

[0062] In the second aspect, the present application provides an AI-based multi-heterogeneous geological data fusion prospecting analysis system, comprising:

[0063] A coordinate analysis module is used to obtain remote sensing images; obtain sampling data; analyze the remote sensing images to determine the three-dimensional coordinates of the area to be measured;

[0064] A vein analysis module, used to analyze the sampling data and determine the geological growth veins between any adjacent sampling columns in the area to be tested;

[0065] A mineral vein judgment module, used to determine whether there is a mineral vein in the area to be tested based on the geological growth veins between any adjacent sampling columns;

[0066] The trend analysis module is used to determine the direction of the vein based on the three-dimensional coordinates if a vein exists.

[0067] Optionally, when acquiring sampling data, the coordinate analysis module is used to:

[0068] Acquire cross-sectional images and cylinder images of several sampling columns;

[0069] Extracting image features of the cross-sectional image, and determining an initial sampling direction according to the image features;

[0070] Based on the initial sampling direction, analyzing the cross-sectional image to determine the cross-sectional change;

[0071] Based on the sampling initial direction, analyzing the cylinder image to determine the cylinder change;

[0072] The cross-section change and the column change are used as the sampling data.

[0073] Optionally, when determining the initial sampling direction according to the image features, the coordinate analysis module is used to:

[0074] Obtain ground images before sampling;

[0075] According to the image features of each sampling column, the geographical location of each sampling column before sampling is determined;

[0076] According to the geographical location, the ground image is screened to determine an exclusive image corresponding to each sampling column;

[0077] For each sampling column, the exclusive image is analyzed to determine the original ground features, and the directional features are selected based on the preset direction;

[0078] The directional feature is compared with the image feature, and an initial sampling direction is determined according to the comparison result.

[0079] Optionally, when analyzing the sampling data to determine the geological growth veins between any adjacent sampling columns in the area to be tested, the vein analysis module is used to:

[0080] Determine the geological surface structure and surface rock type according to the cross-sectional changes;

[0081] Determine the characteristics of the rock layers and the geological changes of each rock layer according to the changes in the column;

[0082] For each sampling column, according to the rock formation characteristics and geological changes of each rock formation, determine the geological structural sequence of the rock formation corresponding to each sampling column;

[0083] According to the geological structure sequence, the geological growth veins between any adjacent sampling columns in the area to be tested are determined.

[0084] Optionally, when determining the geological growth veins between any adjacent sampling columns in the area to be tested according to the geological structure sequence, the vein analysis module is used to:

[0085] For each sampling column, based on the initial sampling direction, any sampling column is used as a base column, and any other sampling column is selected as a reference column; the reference column is a reference object of any base column, and the reference column is not any base column;

[0086] Determine the reference cylindrical coordinates and the reference cylindrical coordinates according to the three-dimensional coordinates of the area to be measured;

[0087] Taking the sampling initial direction as the connection direction, based on the reference column coordinates and the reference column coordinates, determining the surface to be measured between the reference column and the reference column;

[0088] Predicting the geological changes of the surface to be measured according to the geological structural sequence of the rock layer corresponding to each sampling column;

[0089] According to the geological changes of the surface to be tested, the geological growth veins between any adjacent sampling columns in the area to be tested are determined.

[0090] Optionally, when determining the surface to be measured between the reference column and the reference column based on the reference column coordinates and the reference column coordinates, the context analysis module is used to:

[0091] Taking the preset storey height as the interval standard, traverse the center coordinates of the reference column at each storey height and the center coordinates of the reference column at each storey,

[0092] Connect the coordinates of the center of the circle of the reference column at each floor height with the coordinates of the center of the circle of the reference column at the corresponding floor height to obtain a number of connecting lines until the centers of all the reference columns at each floor height are connected;

[0093] For each reference column, interpolation processing is performed on the reference column to determine whether there is a possibility of a layer gap outside the spacing standard;

[0094] If it exists, the reference height of the reference column is determined according to the interlayer gap height, and the coordinates of the center of the circle at the interlayer gap height are connected to obtain an interlayer gap connection line;

[0095] According to the plurality of connection lines and the layer gap connection lines, a surface to be measured between the benchmark column and the reference column is determined.

[0096] Optionally, the multi-heterogeneous geological data fusion prospecting and analysis system further includes a three-dimensional analysis module for:

[0097] For each surface to be tested, any three or more surfaces to be tested are connected to form a three-dimensional area;

[0098] Predicting geological growth changes in the three-dimensional area according to geological changes in the surface to be measured;

[0099] Traversing all three-dimensional regions, and determining the geological growth veins of the region to be measured according to the geological growth changes of the three-dimensional regions;

[0100] Determining whether there is a mineral vein in the area to be tested based on the geological growth veins between any adjacent sampling columns includes:

[0101] Determine whether there is a mineral vein in the area to be tested based on the geological growth veins in the area to be tested.

[0102] Optionally, when determining whether a mineral vein exists in the area to be tested based on the geological growth veins between any adjacent sampling columns, the mineral vein judgment module is used to:

[0103] Determine the rock type present in each rock layer based on the rock layer characteristics;

[0104] Acquiring the regional position of the area to be tested, and determining the possible type of the mineral vein according to the regional position;

[0105] Based on the possible types of the mineral veins, the rock types and the geological growth veins between any adjacent sampling columns, it is determined whether there are mineral veins in the area to be tested.

[0106] Optionally, the multi-heterogeneous geological data fusion prospecting analysis system further includes a value analysis module for:

[0107] If it is determined that there is no mineral vein in the test area, determining whether there is a possibility of mineral vein development in the test area according to the geological growth veins between any adjacent sampling columns;

[0108] If so, predicting the geological changes of the area to be tested within a preset distance range according to the geological growth veins between any adjacent sampling columns;

[0109] According to the geological changes in the area to be measured within a preset distance range, the location of the mineral vein is inferred, and based on the location of the mineral vein, it is determined whether there is mining value. BRIEF DESCRIPTION OF THE DRAWINGS

[0110] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, a brief introduction will be given below to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0111] Figure 1 A schematic diagram of an application scenario provided for an embodiment of the present application;

[0112] Figure 2 A flowchart of a multi-heterogeneous geological data fusion prospecting analysis method based on AI provided in one embodiment of the present application;

[0113] Figure 3 A schematic diagram of the structure of a multi-heterogeneous geological data fusion prospecting and analysis system based on AI is provided in one embodiment of the present application. DETAILED DESCRIPTION

[0114] In order to make the purpose, technical scheme and advantages of the embodiments of the present application clearer, the technical scheme in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0115] In addition, the term "and / or" in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article, unless otherwise specified, generally means that the associated objects before and after are in an "or" relationship.

[0116] The embodiments of the present application are further described in detail below in conjunction with the drawings in the specification.

[0117] Traditional geological prospecting methods mainly rely on the experience and intuition of geologists and have certain limitations. The existing prospecting and analysis methods that integrate multivariate heterogeneous geological data have certain shortcomings in their implementation, such as the complexity of processing and analyzing sampling data and certain limitations in mining large amounts of multivariate heterogeneous data.

[0118] Based on this, the present application provides a prospecting analysis method and system for multivariate heterogeneous geological data fusion based on AI, acquiring remote sensing images; acquiring sampling data; analyzing the remote sensing images to determine the three-dimensional coordinates of the area to be tested; analyzing the sampling data to determine the geological growth veins between any adjacent sampling columns in the area to be tested; determining whether there is a vein in the area to be tested based on the geological growth veins between any adjacent sampling columns; if there is a vein, determining the direction of the vein based on the three-dimensional coordinates. By integrating multiple data sources, such as remote sensing images, sampling data, etc., more comprehensive geological information can be obtained, which helps to have a deeper understanding of the geological characteristics of the area to be tested; through the automated processing and analysis of a large number of remote sensing images and sampling data by AI technology, the efficiency of prospecting can be significantly improved, and the time and workload of manual operation can be reduced; by analyzing the geological growth veins and vein characteristics, the direction and distribution of the vein can be more accurately predicted, providing an important basis for mineral resource exploration; the three-dimensional coordinates and geological growth veins of the area to be tested can be more accurately determined, thereby improving the accuracy of vein identification; more scientific decision support can be provided for the field of geological exploration, which helps to improve the efficiency and success rate of mineral resource exploration.

[0119] Figure 1A schematic diagram of an application scenario provided for this application. When conducting prospecting operations in geological exploration, the method provided by this application is applied. Specifically, the method provided by this application is applied to any server, and the server interacts with the remote sensing system and the sampling system. Remote sensing images can cover a large area and provide high-resolution geological information from an aerial or satellite perspective, which helps to quickly identify surface geological features and potential mineral deposits. Sampling data obtained by ground drilling, trenching and other means can provide detailed information on underground geological structures. Remote sensing image analysis combined with high-precision GPS positioning can determine the three-dimensional coordinates of the area to be tested and improve the accuracy of geological exploration. Sampling data analysis can provide an in-depth understanding of subtle changes in geological structures and determine geological growth veins; through analysis of geological growth veins, the extension direction and shape of the veins can be accurately tracked; based on the analysis of geological growth veins, the existence of veins can be predicted more scientifically and blind exploration can be reduced; through geological growth vein analysis, resource waste and exploration risks caused by misjudgment can be reduced; using three-dimensional coordinate information, the direction of the vein can be accurately determined, providing precise guidance for subsequent mining work; based on the direction of the vein, the mine design and mining plan can be optimized to improve resource utilization.

[0120] For specific implementation methods, please refer to the following embodiments.

[0121] Figure 2 This is a flowchart of a multi-heterogeneous geological data fusion prospecting analysis method based on AI provided in one embodiment of the present application. The method of this embodiment can be applied to the server in the above scenario. Figure 2 As shown, the method includes:

[0122] S201, acquiring remote sensing images; acquiring sampling data; analyzing the remote sensing images to determine the three-dimensional coordinates of the area to be measured.

[0123] Remote sensing images can be images of the earth's surface obtained from a distance through remote sensing technology (such as satellite remote sensing, aerial photography, drone photography, etc.), such as information such as the physical characteristics, geographical distribution, vegetation coverage, hydrological conditions, etc. of the earth's surface.

[0124] Sampling data can be geological, environmental, ecological and other data collected from the field; including rock samples, soil samples, water samples, etc.

[0125] The area to be surveyed may be a specific geographical area where geological survey, exploration or monitoring is required.

[0126] Three-dimensional coordinates can be the three sets of coordinate values ​​required to determine the position of a point in three-dimensional space, expressed as longitude, latitude and altitude; three-dimensional coordinates are used to locate geological structures such as geological bodies and mineral veins.

[0127] Specifically, remote sensing technology is used to obtain remote sensing images of the area to be measured; cross-sectional images and column images of the sampling column are obtained through ground drilling, trenching, etc.; the remote sensing images are processed using AI algorithms, and the three-dimensional coordinates of the area to be measured are determined through image recognition and pattern recognition technology.

[0128] S202, analyzing the sampling data to determine the geological growth veins between any adjacent sampling columns in the area to be tested.

[0129] The geological growth context can be the spatial distribution and evolutionary characteristics of geological bodies formed by geological actions (such as sedimentation, metamorphism, magmatic activity, etc.) during the development of the earth's crust; including the distribution pattern, form, scale and mutual relationship of geological structures such as rock layers, faults, joints, and mineralized belts.

[0130] Specifically, feature extraction is performed on the cross-sectional image and column image of the sampling column, and the geographical location of each sampling column before sampling is determined by combining the ground image and sampling column image features, thereby determining the initial sampling direction; based on the sampling data, the geological structure sequence of each sampling column is analyzed to determine the geological growth veins between any adjacent sampling columns.

[0131] S203, determining whether there is a mineral vein in the area to be tested based on the geological growth veins between any adjacent sampling columns.

[0132] A mineral vein may be composed of one or more minerals that are distributed in a continuous or discontinuous linear or banded manner in space.

[0133] Specifically, based on the results of geological growth vein analysis, determine whether there is a mineral vein in the area to be tested.

[0134] Extract key features from the geological growth vein data set, such as lithology changes, fault distribution, joint density, structural style, etc., and use machine learning algorithms such as support vector machine (SVM), random forest (RF) or deep learning (such as convolutional neural network CNN) to perform pattern recognition on the extracted features; set the geological feature threshold for the existence of mineral veins based on geological knowledge and experience, such as specific lithology combinations, fault distribution patterns, joint density, etc.; analyze the geological growth veins to find abnormal features that match the set thresholds, which may indicate the existence of mineral veins; based on the analysis results, use logical rules to determine whether there are mineral veins in the area to be tested. For example: if there are multiple abnormal features in the geological growth vein data set, and these features conform to the typical pattern of mineral veins, it is judged that there is a mineral vein. If the abnormal features are insufficient or do not conform to the mineral vein pattern, it is judged that there is no mineral vein.

[0135] S204. If a mineral vein exists, determine the direction of the mineral vein based on the three-dimensional coordinates.

[0136] The direction of a vein may be the direction in which the vein extends in space.

[0137] Specifically, if there is a mineral vein, the geological features and sampling data are converted into a three-dimensional geological model using the three-dimensional coordinates of the area to be tested and three-dimensional geological modeling software; trend surface analysis techniques, such as polynomial fitting and radial basis function (RBF), are used to extract the trend surface of the mineral vein from the geological data; the contour lines of the mineral vein cross-section image are analyzed to determine the direction of the mineral vein; and clustering algorithms, such as K-means or DBSCAN, are used to cluster points with similar features to determine the direction of the mineral vein.

[0138] Through this solution, by integrating multiple data sources, such as remote sensing images, sampling data, etc., more comprehensive geological information can be obtained, which helps to gain a deeper understanding of the geological characteristics of the area to be tested; through the automated processing and analysis of a large amount of remote sensing images and sampling data by AI technology, the efficiency of mineral exploration can be significantly improved, and the time and workload of manual operations can be reduced; by analyzing the geological growth veins and mineral vein characteristics, the direction and distribution of mineral veins can be more accurately predicted, providing an important basis for mineral resource exploration; the three-dimensional coordinates and geological growth veins of the area to be tested can be more accurately determined, thereby improving the accuracy of mineral vein identification; it can provide more scientific decision-making support for the field of geological exploration, which helps to improve the efficiency and success rate of mineral resource exploration.

[0139] In some embodiments, cross-sectional images and cylinder images of several sampling cylinders are taken; image features of the cross-sectional images are extracted, and the initial sampling direction is determined based on the image features; based on the initial sampling direction, the cross-sectional images are analyzed to determine cross-sectional changes; based on the initial sampling direction, the cylinder images are analyzed to determine cylinder changes; and the cross-sectional changes and cylinder changes are used as sampling data.

[0140] The cross-sectional image may be a longitudinal cross-sectional image of rock or soil obtained from a sampling column produced by geological drilling or other geological sampling.

[0141] The cylinder image may be an image of the outer surface of a sampling cylinder produced from geological drilling or other geological sampling.

[0142] Image features can be extracted from images to describe features such as bedding, cracks, and mineral distribution inside the rock in the image.

[0143] The initial sampling direction may be the sampling direction first determined during geological sampling or drilling, and is used to identify the orientation of the sampling column, so as to facilitate the positioning of the sampling column orientation in the subsequent data fusion.

[0144] The cross-sectional changes may be changes in rock or soil characteristics observed on the cross-sectional image, including inclination of bedding, changes in lithology, the appearance of faults, and the like.

[0145] The column changes may be changes in rock or soil characteristics on the outer surface of the sampling column observed on the column image, including uplift, subsidence, erosion, magma activity, etc. of the strata.

[0146] Geological changes can be changes in geological phenomena observed during geological exploration.

[0147] Specifically, appropriate sampling points are selected according to the geological characteristics of the area to be tested and the results of remote sensing image analysis. At the selected sampling points, geological drilling equipment is used to obtain underground rock samples, and cross-sectional images and cylindrical images are obtained using special imaging equipment; pre-processing operations such as denoising, contrast enhancement, and grayscale are performed on the cross-sectional images to improve image quality, and image processing techniques such as edge detection, texture analysis, and morphological operations are applied to extract image features. Based on the extracted image features, the inclination and direction of the rock formation are analyzed to determine the initial direction of sampling. The accuracy of the initial sampling direction is verified by comparing the cross-sectional image features of multiple sampling points. Based on the initial sampling direction, the change trend of the rock formation and geological structure in the cross-sectional image is analyzed to identify the changes in the cross-sectional image; the cylindrical image is analyzed to extract the geometric characteristics and lithological characteristics of the cylinder; the changes in the cylindrical image are detected, such as the bending, fracture, and mineralization of the rock formation; the cross-sectional changes and cylindrical changes obtained by analyzing the cross-sectional image and the cylindrical image are integrated to form recorded sampling data.

[0148] Through this scheme, by directly observing the cross-section and column images of rocks, the structure and properties of rocks can be intuitively understood; the features extracted using image processing technology are more objective and not affected by the subjective judgment of geologists; through precise feature extraction, the sampling direction can be determined more accurately and the sampling efficiency can be improved; by systematically analyzing the cross-section images, the evolution process of geological structures can be fully understood, and by identifying the change patterns, the change trends of geological structures in the future can be predicted. The column images provide a three-dimensional perspective, which helps to more fully understand the three-dimensional morphology of geological structures and can more carefully analyze the physical and chemical properties of rocks, such as mineral content, porosity, etc.

[0149] In some embodiments, a ground image before sampling is obtained; based on the image features of each sampling column, the geographical location of each sampling column before sampling is determined; based on the geographical location, the ground image is screened to determine an exclusive image corresponding to each sampling column; for each sampling column, the exclusive image is analyzed to determine the original ground features, and the directional features are selected based on a preset direction; the directional features are compared with the image features, and based on the comparison results, the initial sampling direction is determined.

[0150] Ground images can be images of the earth's surface acquired through remote sensing technology, which can show the features of the earth's surface, including terrain, vegetation, water bodies, and other types of surface cover.

[0151] Geographic location refers to the exact location of a particular place on the Earth, usually expressed in terms of longitude, latitude, and altitude.

[0152] Dedicated images can be image areas cropped from ground images that specifically correspond to a specific sampling column.

[0153] The preset direction may be a reference direction pre-set in geological exploration and used to establish a unified coordinate system to facilitate analysis and comparison of data from different sampling points.

[0154] The directional feature may be a feature associated with a preset direction in a dedicated image, such as the slope direction of the terrain, the flow direction of a river, the arrangement direction of vegetation, and the like.

[0155] Specifically, use drones, satellite remote sensing or ground photography equipment to obtain high-resolution ground images of the sampling area, ensure that the image covers the location of all sampling columns and has sufficient clarity for subsequent analysis; use GPS or other positioning technology to record the precise geographic location of each sampling column. Match the geographic location of the sampling column with the corresponding pixel location in the ground image; based on the geographic location of the sampling column, crop the area around each sampling column from the ground image to form a dedicated image; ensure that the dedicated image contains sufficient surrounding environment information to analyze ground features; apply image processing techniques, such as edge detection, texture analysis, etc., to extract ground features in the dedicated image; identify ground features, such as terrain, vegetation, soil type, etc.; in the dedicated image, select a set of directional features based on a preset direction (such as north), such as the slope of the terrain, the distribution pattern of vegetation, etc.; use these directional features as a reference for comparison with image features; compare and analyze the extracted image features with the selected directional features, and use methods such as correlation coefficients and angle differences to analyze the similarities or differences between the features to determine the best match; based on the comparison results, determine the initial direction of the sampling column, that is, the direction to be taken when sampling.

[0156] Through this solution, using image processing and pattern recognition technology, features can be objectively extracted from images, subjective errors can be avoided, and the analysis results can be made more reliable. Automating large amounts of data processing and analysis processes can significantly improve work efficiency and save a lot of time and manpower. Through positioning technologies such as GPS, the geographical location of the sampling column can be accurately determined. Combining ground images and sampling column images can achieve the fusion of multi-source data and provide more comprehensive geological information. By analyzing image features and directional features, the distribution of geological structures and mineral veins can be more accurately predicted, thereby improving the success rate of prospecting.

[0157] In some embodiments, the geological surface structure and surface rock type are determined based on cross-sectional changes; the rock formation characteristics and geological changes of each rock formation are determined based on column changes; for each sampling column, the geological structural sequence of the rock formation corresponding to each sampling column is determined based on the rock formation characteristics and geological changes of each rock formation; and the geological growth veins between any adjacent sampling columns in the area to be tested are determined based on the geological structural sequence.

[0158] The geological surface structure can be the overall layout of shallow rocks and geological features below the surface, including geological phenomena such as the tilt, fracture, fold, and joint of the strata.

[0159] The surface rock type can be the type of rock that makes up the geological surface structure. Rock types include sedimentary rocks (such as sandstone and shale), igneous rocks (such as granite and basalt), and metamorphic rocks (such as gneiss and marble).

[0160] Rock formation characteristics can be the physical, chemical and structural properties of the rocks that make up the formation, including the thickness, bedding, color, mineral composition, cracks and joints of the rock formation.

[0161] Geological changes can be changes in the structure and morphology of geological bodies in time and space, including crustal movement, magmatic activity, sedimentation, weathering and erosion, etc., which can be determined based on the age, lithology, fossils and structural characteristics of the rock strata.

[0162] The geological tectonic sequence can be the order in which different rock layers are deposited or formed during the formation of the strata.

[0163] Specifically, analyze the bedding, cracks, mineral distribution and other characteristics on the cross-sectional image to determine the structural type of the geological surface; determine the type of surface rock based on the color, texture and composition analysis in the cross-sectional image and the column image; analyze the rock layer characteristics on the column image, such as layer thickness, bedding direction, interlayer type, etc.; observe the geological changes of each rock layer, such as erosion, sedimentation, faults, etc.; assign a geological structural sequence to each rock layer in each sampling column according to the rock layer characteristics and geological changes, usually numbering them from the bottom to the top; analyze the superposition and contact relationships of the rock layers to determine the relative time sequence of their formation; compare the rock layer characteristics and geological structural sequences of adjacent sampling columns to determine the similarities and differences between them; analyze the continuity and discontinuity of the rock layers to determine the geological growth context, that is, the changes and development trends of the geological structure over time.

[0164] Through this solution, relying on objective data and image processing technology, the influence of personal experience and intuition is reduced, and the objectivity and repeatability of the analysis are improved; through high-resolution images and precise geographic location information, geological structures and rock types can be determined more accurately, thereby improving the accuracy of prospecting; combined with cross-sectional and cylindrical image analysis, a comprehensive geological perspective can be provided, including geological surface structures, rock formation characteristics, and geological changes, so as to more systematically understand the geological growth context; automated data processing and analysis processes can process large amounts of data, improve work efficiency, and shorten the prospecting cycle; automated image analysis and feature extraction reduce errors caused by human operations and improve data reliability; by analyzing the sequence of geological structures, the distribution of geological structures and ore veins can be more accurately predicted, thereby improving the success rate of prospecting; the collected data can be used to construct a three-dimensional geological model to more intuitively display the geological growth context, facilitating analysis and decision-making.

[0165] In some embodiments, for each sampling column, based on the initial sampling direction, any sampling column is used as a base column, and any other sampling column is selected as a reference column; the reference column is a reference object of any base column, and the reference column is not any base column; according to the three-dimensional coordinates of the area to be measured, the base column coordinates and the reference column coordinates are determined; with the initial sampling direction as the connection direction, based on the base column coordinates and the reference column coordinates, the surface to be measured between the base column and the reference column is determined; according to the geological structural sequence of the rock formation corresponding to each sampling column, the geological changes of the surface to be measured are predicted; according to the geological changes of the surface to be measured, the geological growth veins between any adjacent sampling columns in the area to be measured are determined.

[0166] A reference column can be a sampling column used as a reference point in geological exploration.

[0167] A reference column can be another sampling column connected to a benchmark column in geological exploration.

[0168] The connection direction may be a straight line direction between the datum column and the reference column.

[0169] The surface to be measured may be an imaginary plane between the datum column and the reference column, the plane passing through the connection direction and being perpendicular to the ground.

[0170] Specifically, one is selected from the sampling columns as a reference column, which will be used as a reference point; any sampling column other than the reference column is selected as a reference column, ensuring that the reference column is not the reference column itself; the three-dimensional coordinates of the reference column and the reference column are obtained using GPS or ground measurement technology; these coordinates are recorded and stored for subsequent analysis; based on the initial sampling direction, the coordinates of the reference column and the reference column are used to determine the connection between them; the connection is extended to create an imaginary plane, i.e., the surface to be measured, which will be used to predict geological changes; according to the geological structural sequence of the rock layer corresponding to each sampling column, the distribution and change trend of the rock layer are analyzed; the geological structural sequence information is used to predict the geological characteristics and changes that may occur on the surface to be measured; the geological changes between the reference column and the reference column are analyzed to identify the pattern and direction of the geological growth veins; the geological growth veins between adjacent sampling columns are determined in combination with the geological change information of the surface to be measured.

[0171] Through this solution, by analyzing the geological structure sequence, the geological changes in the area to be tested can be predicted more accurately, thereby improving the accuracy of predictions on the distribution of ore veins and geological characteristics; it provides detailed information on geological structures and development trends, and more accurate geological growth vein analysis can help reduce exploration risks; by understanding geological growth veins, the economic value of mineral resources can be more effectively evaluated, thereby optimizing resource development decisions; through precise exploration, damage to the environment can be reduced because they can guide more targeted exploration activities; automated data processing and analysis processes can process large amounts of data, improve work efficiency, and shorten the prospecting cycle; automated image analysis and feature extraction reduce errors caused by human operations and improve data reliability.

[0172] In some embodiments, taking the preset floor height as the interval standard, the center coordinates of the reference column at each floor height and the center coordinates of the reference column at each floor are traversed, and the center coordinates of the reference column at each floor height are connected with the center coordinates of the reference column at the corresponding floor height to obtain a number of connecting lines, until the centers of all reference columns at each floor height are connected; for each reference column, the reference column is interpolated to determine whether there is a possibility of a layer gap outside the interval standard; if so, the reference height of the reference column is determined according to the layer gap height, and the center coordinates of the position of the layer gap height are connected to obtain the layer gap connecting line; based on the several connecting lines and the layer gap connecting lines, the surface to be measured between the reference column and the reference column is determined.

[0173] The preset layer height may be used in geological exploration to determine the height standard of stratum division and is stored in a preset database.

[0174] The interval standard can be the distance or time interval between two adjacent points (such as sampling columns, formations) within a certain range.

[0175] A gap may be a space or discontinuity between strata in a geological sequence caused by geological processes (such as faults and unconformities).

[0176] The interlayer height may be the vertical distance of the interlayer, ie, the thickness of the gap or discontinuity between two adjacent strata.

[0177] The interlayer connection line can be a straight line or a curve connecting the strata at both ends of the interlayer in a geological cross section or a three-dimensional model.

[0178] Specifically, the coordinate data of the benchmark column and the reference column are collected, and the center coordinates of the benchmark column and the reference column at each layer are traversed with the preset layer height as the interval standard; the center coordinates of the benchmark column at each layer height are connected with the center coordinates of the reference column at the corresponding layer height to generate a connecting line; the above steps are repeated until the center coordinates of all benchmark columns at each layer height are connected; for each benchmark column, interpolation processing is performed to determine whether there is a possibility of layer gap outside the interval standard; the interpolation processing can use linear interpolation, polynomial interpolation or more advanced interpolation methods, such as Kriging interpolation; if the interpolation processing result shows that there is a layer gap, the reference height of the reference column is determined according to the height of the layer gap; the center coordinates of the benchmark column and the reference column at the position of the layer gap height are connected to generate a layer gap connecting line; according to the generated connecting line and the layer gap connecting line, the surface to be measured between the benchmark column and the reference column is determined.

[0179] Through this scheme, by interpolating the coordinates of the benchmark column and the reference column and analyzing the connecting lines, the geological structure, especially the contact relationship between geological sequences and strata, can be understood more intuitively; interpolation processing can help identify interlayer gaps, which may indicate important geological features such as faults, sedimentary discontinuities or magmatic intrusions; based on accurate coordinate data and interpolation results, a more accurate geological model can be constructed, which is crucial for geological exploration and resource assessment; by determining the surface to be tested, the exploration strategy can be optimized and resources can be concentrated on the most promising areas for exploration; by analyzing interlayer gaps and connecting lines, potential changes between strata can be predicted, and trends in geological changes, such as tilt, folding or faulting of strata, can be identified, which enhances the ability to predict geological growth veins; the determined surface to be tested can be used to predict the direction and position of the veins, which is of direct significance for mineral deposit exploration.

[0180] In some embodiments, for each surface to be tested, any three or more surfaces to be tested are connected into a three-dimensional area; based on the geological changes of the surface to be tested, the geological growth changes of the three-dimensional area are predicted; all three-dimensional areas are traversed, and the geological growth veins of the area to be tested are determined based on the geological growth changes of the three-dimensional area; based on the geological growth veins between any adjacent sampling columns, it is determined whether there is a mineral vein in the area to be tested, including: determining whether there is a mineral vein in the area to be tested based on the geological growth veins of the area to be tested.

[0181] The three-dimensional area may be a three-dimensional area formed by connecting and enclosing three surfaces to be measured and having closed edges when viewed from a top-down angle.

[0182] Specifically, any three or more surfaces to be tested are connected to form a three-dimensional area; a three-dimensional model is constructed using geological modeling software or programming tools to display the spatial relationship of the surfaces to be tested; the geological changes on the surfaces to be tested are analyzed, such as analysis of geological structural features such as stratum dip, faults, and folds; geological growth changes in the three-dimensional area are predicted using geological models and software tools; all constructed three-dimensional areas are traversed, and the geological growth changes in each area are analyzed and recorded; based on the traversal results, the geological growth veins in the area to be tested are determined, the geological connections between different areas are analyzed, and the main directions and paths of geological growth are identified; based on the geological growth veins between any adjacent sampling columns, the possible distribution of mineral veins is analyzed; and based on the geological model and geological theory, the presence of mineral veins in the area to be tested is predicted.

[0183] Through this scheme, by connecting the surface to be tested into three-dimensional areas, a more accurate geological model can be constructed to understand the geological structure and predict geological changes. Analyzing the geological changes of the surface to be tested can help predict the geological growth changes in the three-dimensional area; traversing all three-dimensional areas and analyzing their geological growth changes can more comprehensively determine the geological growth veins of the area to be tested, providing more accurate guidance for geological exploration; based on the geological growth veins between any adjacent sampling columns, it is possible to more accurately predict whether there are mineral veins in the area to be tested, thereby improving the success rate of prospecting; the collected data can be used to construct a three-dimensional geological model to more intuitively display the geological growth veins, which is convenient for analysis and decision-making.

[0184] In some embodiments, the rock type existing in each rock layer is determined based on the characteristics of the rock layer; the regional position of the area to be tested is obtained, and the possible type of the vein is determined based on the regional position; based on the possible type of the vein, the rock type and the geological growth veins between any adjacent sampling columns, it is determined whether there is a vein in the area to be tested.

[0185] The possible types of mineral veins can be classified according to the characteristics of mineral types, genesis and output form.

[0186] Specifically, a characteristic analysis is performed on each rock layer in the area to be tested, including rock type, lithology, structure, and construction, to determine the rock type of each rock layer, such as sandstone, shale, limestone, etc.; the regional location information of the area to be tested is obtained, including geographic coordinates, topography, etc.; based on the regional location, combined with the regional geological background and known geological laws, the possible types of veins are determined, such as metal veins, non-metallic veins, etc.; the geological growth veins between any adjacent sampling columns are analyzed, including stratigraphic contact relationships, faults, folds and other geological structural characteristics; the main direction and path of geological growth, as well as the influence of geological structure on vein formation are determined; based on the possible types of veins, rock types and geological growth vein analysis results, it is judged whether there are veins in the area to be tested.

[0187] Through this scheme, through detailed analysis of rock formation characteristics, because different rock types may indicate different geological environments and mineralization potentials, the rock type of each rock formation can be accurately determined, providing basic data for subsequent vein predictions, which helps to build a more accurate geological model. According to the regional location, the possible types of veins that match the geological conditions of the area can be determined, improving the pertinence of prospecting, avoiding ineffective exploration in areas without potential vein types, and reducing risks and costs. By comprehensively considering the possible types of veins, rock types, and geological growth veins, the comprehensiveness and accuracy of the analysis are improved; based on multi-factor analysis, it is possible to more accurately predict whether there are veins in the area to be tested.

[0188] In some embodiments, if it is determined that there is no mineral vein in the area to be tested, then based on the geological growth veins between any adjacent sampling columns, it is determined whether there is a possibility of mineral vein development in the area to be tested; if so, the geological changes in the area to be tested within a preset distance range are predicted based on the geological growth veins between any adjacent sampling columns; based on the geological changes in the area to be tested within a preset distance range, the location of the mineral vein is inferred, and based on the location of the mineral vein, it is determined whether there is value in mining.

[0189] Mineral vein development may be an assessment of the probability that a mineral vein may form in a certain area in the future based on geological conditions and historical data.

[0190] The preset distance range may be a distance range pre-set during geological exploration for use in evaluating and analyzing geological changes, mineral vein distribution or resource potential.

[0191] The location of the mineral vein can be the specific location where the mineral vein may be formed based on geological surveys and predictive analysis.

[0192] Specifically, if it is determined that there are no mineral veins in the area to be tested, the geological data between any adjacent sampling columns will be collected and analyzed, and based on the geological growth veins and known mineral vein formation conditions, it will be evaluated whether the geological conditions for the development of mineral veins exist in the area to be tested; the geological model and the geodynamic model will be used to predict the geological changes in the area to be tested within a preset distance range; the prediction results, such as stratum deformation, fault activity, etc., will be analyzed; based on the predicted geological changes, the possible geological location of the mineral vein will be speculated; the speculation will be further refined in combination with the geological history and the formation location of the known mineral veins; the relationship between the speculated location of the mineral vein and the current technology, market demand and mining costs will be evaluated; and the mining value of the mineral vein will be determined in combination with the scale, grade and ore type of the mineral vein.

[0193] Through this plan, unnecessary exploration and mining activities can be avoided in areas without mineral veins, saving human, material and financial resources; reducing risk investment in areas without mineral veins and protecting the financial security of enterprises; deepening the understanding of geological structure and mineralization environment, providing a theoretical basis for subsequent mineral exploration; integrating data from different sampling columns to form a continuous geological information chain, which is conducive to comprehensive analysis of regional geological characteristics; clarifying the prospecting goals and directions of the area to be tested and improving exploration efficiency; determining the possible locations of mineral veins through geological change predictions to guide exploration activities; and increasing the success rate of exploration at possible locations of mineral veins.

[0194] Figure 3 A schematic diagram of a multi-heterogeneous geological data fusion prospecting and analysis system based on AI is provided in one embodiment of the present application, as shown in FIG. Figure 3 As shown, the AI-based multi-heterogeneous geological data fusion prospecting and analysis system 300 of this embodiment includes: a coordinate analysis module 301, a vein analysis module 302, a vein judgment module 303, and a trend analysis module 304.

[0195] The coordinate analysis module 301 is used to obtain remote sensing images; obtain sampling data; analyze the remote sensing images to determine the three-dimensional coordinates of the area to be measured;

[0196] A vein analysis module 302 is used to analyze the sampling data and determine the geological growth veins between any adjacent sampling columns in the area to be tested;

[0197] A mineral vein determination module 303 is used to determine whether a mineral vein exists in the area to be tested according to the geological growth veins between any adjacent sampling columns;

[0198] The trend analysis module 304 is used to determine the direction of the vein based on the three-dimensional coordinates if a vein exists.

[0199] Optionally, when acquiring sampling data, the coordinate analysis module 301 is used to:

[0200] Acquire cross-sectional images and cylinder images of several sampling columns;

[0201] Extracting image features of the cross-sectional image, and determining an initial sampling direction according to the image features;

[0202] Based on the initial sampling direction, analyzing the cross-sectional image to determine the cross-sectional change;

[0203] Based on the sampling initial direction, analyzing the cylinder image to determine the cylinder change;

[0204] The cross-section change and the column change are used as the sampling data.

[0205] Optionally, when determining the initial sampling direction according to the image features, the coordinate analysis module 301 is used to:

[0206] Obtain ground images before sampling;

[0207] According to the image features of each sampling column, the geographical location of each sampling column before sampling is determined;

[0208] According to the geographical location, the ground image is screened to determine an exclusive image corresponding to each sampling column;

[0209] For each sampling column, the exclusive image is analyzed to determine the original ground features, and the directional features are selected based on the preset direction;

[0210] The directional feature is compared with the image feature, and an initial sampling direction is determined according to the comparison result.

[0211] Optionally, when analyzing the sampling data to determine the geological growth veins between any adjacent sampling columns in the area to be tested, the vein analysis module 302 is used to:

[0212] Determine the geological surface structure and surface rock type according to the cross-sectional changes;

[0213] Determine the characteristics of the rock layers and the geological changes of each rock layer according to the changes in the column;

[0214] For each sampling column, according to the rock formation characteristics and geological changes of each rock formation, determine the geological structural sequence of the rock formation corresponding to each sampling column;

[0215] According to the geological structure sequence, the geological growth veins between any adjacent sampling columns in the area to be tested are determined.

[0216] Optionally, when determining the geological growth veins between any adjacent sampling columns in the area to be tested according to the geological structure sequence, the vein analysis module 302 is used to:

[0217] For each sampling column, based on the initial sampling direction, any sampling column is used as a base column, and any other sampling column is selected as a reference column; the reference column is a reference object of any base column, and the reference column is not any base column;

[0218] Determine the reference cylindrical coordinates and the reference cylindrical coordinates according to the three-dimensional coordinates of the area to be measured;

[0219] Taking the sampling initial direction as the connection direction, based on the reference column coordinates and the reference column coordinates, determining the surface to be measured between the reference column and the reference column;

[0220] Predicting the geological changes of the surface to be measured according to the geological structural sequence of the rock layer corresponding to each sampling column;

[0221] According to the geological changes of the surface to be tested, the geological growth veins between any adjacent sampling columns in the area to be tested are determined.

[0222] Optionally, when determining the surface to be measured between the reference column and the reference column based on the reference column coordinates and the reference column coordinates, the context analysis module 302 is configured to:

[0223] Taking the preset storey height as the interval standard, traverse the center coordinates of the reference column at each storey height and the center coordinates of the reference column at each storey,

[0224] Connect the coordinates of the center of the circle of the reference column at each floor height with the coordinates of the center of the circle of the reference column at the corresponding floor height to obtain a number of connecting lines until the centers of all the reference columns at each floor height are connected;

[0225] For each reference column, interpolation processing is performed on the reference column to determine whether there is a possibility of a layer gap outside the spacing standard;

[0226] If it exists, the reference height of the reference column is determined according to the interlayer gap height, and the coordinates of the center of the circle at the interlayer gap height are connected to obtain an interlayer gap connection line;

[0227] According to the plurality of connection lines and the layer gap connection lines, a surface to be measured between the benchmark column and the reference column is determined.

[0228] Optionally, the multi-heterogeneous geological data fusion prospecting analysis system 300 further includes a three-dimensional analysis module 305 for:

[0229] For each surface to be tested, any three or more surfaces to be tested are connected to form a three-dimensional area;

[0230] Predicting geological growth changes in the three-dimensional area according to geological changes in the surface to be measured;

[0231] Traversing all three-dimensional regions, and determining the geological growth veins of the region to be measured according to the geological growth changes of the three-dimensional regions;

[0232] Determining whether there is a mineral vein in the area to be tested based on the geological growth veins between any adjacent sampling columns includes:

[0233] Determine whether there is a mineral vein in the area to be tested based on the geological growth veins in the area to be tested.

[0234] Optionally, when determining whether there is a mineral vein in the test area according to the geological growth veins between any adjacent sampling columns, the mineral vein determination module 303 is used to:

[0235] Determine the rock type present in each rock layer based on the rock layer characteristics;

[0236] Acquiring the regional position of the area to be tested, and determining the possible type of the mineral vein according to the regional position;

[0237] Based on the possible types of the mineral veins, the rock types and the geological growth veins between any adjacent sampling columns, it is determined whether there are mineral veins in the area to be tested.

[0238] Optionally, the multi-heterogeneous geological data fusion prospecting analysis system 300 further includes a value analysis module 306 for:

[0239] If it is determined that there is no mineral vein in the test area, determining whether there is a possibility of mineral vein development in the test area according to the geological growth veins between any adjacent sampling columns;

[0240] If so, predicting the geological changes of the area to be tested within a preset distance range according to the geological growth veins between any adjacent sampling columns;

[0241] According to the geological changes in the area to be measured within a preset distance range, the location of the mineral vein is inferred, and based on the location of the mineral vein, it is determined whether there is mining value.

[0242] The system of this embodiment can be used to execute the method of any of the above embodiments. The implementation principles and technical effects are similar and will not be described in detail here.

Claims

1. A multi-heterogeneous geological data fusion prospecting analysis method based on AI, characterized in that: include: Acquisition of remote sensing images; Get sampling data; Analyzing the remote sensing image to determine the three-dimensional coordinates of the area to be measured; Analyze the sampling data to determine the geological growth veins between any adjacent sampling columns in the area to be tested; Determine whether there is a mineral vein in the area to be tested based on the geological growth veins between any adjacent sampling columns; If a mineral vein exists, the direction of the mineral vein is determined based on the three-dimensional coordinates.

2. The method according to claim 1, characterized in that The acquiring of sampling data comprises: Acquire cross-sectional images and cylinder images of several sampling columns; Extracting image features of the cross-sectional image, and determining an initial sampling direction according to the image features; Based on the initial sampling direction, analyzing the cross-sectional image to determine the cross-sectional change; Based on the sampling initial direction, analyzing the cylinder image to determine the cylinder change; The cross-section change and the column change are used as the sampling data.

3. The method according to claim 2, characterized in that The step of determining the initial sampling direction according to the image feature includes: Obtain ground images before sampling; According to the image features of each sampling column, the geographical location of each sampling column before sampling is determined; According to the geographical location, the ground image is screened to determine an exclusive image corresponding to each sampling column; For each sampling column, the exclusive image is analyzed to determine the original ground features, and the directional features are selected based on the preset direction; The directional feature is compared with the image feature, and an initial sampling direction is determined according to the comparison result.

4. The method according to claim 2, characterized in that: The analyzing the sampling data to determine the geological growth veins between any adjacent sampling columns in the area to be tested includes: Determine the geological surface structure and surface rock type according to the cross-sectional changes; Determine the characteristics of the rock layers and the geological changes of each rock layer according to the changes in the column; For each sampling column, according to the rock formation characteristics and geological changes of each rock formation, determine the geological structural sequence of the rock formation corresponding to each sampling column; According to the geological structure sequence, the geological growth veins between any adjacent sampling columns in the area to be tested are determined.

5. The method according to claim 4, characterized in that Determining the geological growth veins between any adjacent sampling columns in the area to be tested according to the geological structure sequence includes: For each sampling column, based on the initial sampling direction, any sampling column is used as a base column, and any other sampling column is selected as a reference column; the reference column is a reference object of any base column, and the reference column is not any base column; Determine the reference cylindrical coordinates and the reference cylindrical coordinates according to the three-dimensional coordinates of the area to be measured; Taking the sampling initial direction as the connection direction, based on the reference column coordinates and the reference column coordinates, determining the surface to be measured between the reference column and the reference column; Predicting the geological changes of the surface to be measured according to the geological structural sequence of the rock layer corresponding to each sampling column; According to the geological changes of the surface to be tested, the geological growth veins between any adjacent sampling columns in the area to be tested are determined.

6. The method according to claim 5, characterized in that The step of determining the surface to be measured between the reference column and the reference column based on the reference column coordinates and the reference column coordinates comprises: Taking the preset storey height as the interval standard, traverse the center coordinates of the reference column at each storey height and the center coordinates of the reference column at each storey, Connect the coordinates of the center of the circle of the reference column at each floor height with the coordinates of the center of the circle of the reference column at the corresponding floor height to obtain a number of connecting lines until the centers of all the reference columns at each floor height are connected; For each reference column, interpolation processing is performed on the reference column to determine whether there is a possibility of a layer gap outside the spacing standard; If it exists, the reference height of the reference column is determined according to the interlayer gap height, and the coordinates of the center of the circle at the interlayer gap height are connected to obtain an interlayer gap connection line; According to the plurality of connection lines and the layer gap connection lines, a surface to be measured between the benchmark column and the reference column is determined.

7. The method according to claim 5, characterized in that After determining the geological growth veins between any adjacent sampling columns in the area to be tested according to the geological changes of the surface to be tested, the method further includes: For each surface to be tested, any three or more surfaces to be tested are connected to form a three-dimensional area; Predicting geological growth changes in the three-dimensional area according to geological changes in the surface to be measured; Traversing all three-dimensional regions, and determining the geological growth veins of the region to be measured according to the geological growth changes of the three-dimensional regions; Determining whether there is a mineral vein in the area to be tested based on the geological growth veins between any adjacent sampling columns includes: Determine whether there is a mineral vein in the area to be tested based on the geological growth veins in the area to be tested.

8. The method according to claim 4, characterized in that Determining whether there is a mineral vein in the area to be tested based on the geological growth veins between any adjacent sampling columns includes: Determine the rock type present in each rock layer based on the rock layer characteristics; Acquiring the regional position of the area to be tested, and determining the possible type of the mineral vein according to the regional position; Based on the possible types of the mineral veins, the rock types and the geological growth veins between any adjacent sampling columns, it is determined whether there are mineral veins in the area to be tested.

9. The method according to claim 8, characterized in that After determining whether there is a vein in the area to be tested based on the possible type of the vein, the rock type and the geological growth veins between any adjacent sampling columns, the method further includes: If it is determined that there is no mineral vein in the test area, determining whether there is a possibility of mineral vein development in the test area according to the geological growth veins between any adjacent sampling columns; If so, predicting the geological changes of the area to be tested within a preset distance range according to the geological growth veins between any adjacent sampling columns; According to the geological changes in the area to be measured within a preset distance range, the location of the mineral vein is inferred, and based on the location of the mineral vein, it is determined whether there is mining value.

10. An AI-based multi-heterogeneous geological data fusion prospecting analysis system, characterized in that: include: Coordinate analysis module, used to obtain remote sensing images; Get sampling data; Analyzing the remote sensing image to determine the three-dimensional coordinates of the area to be measured; A vein analysis module, used to analyze the sampling data and determine the geological growth veins between any adjacent sampling columns in the area to be tested; A mineral vein judgment module, used to determine whether there is a mineral vein in the area to be tested based on the geological growth veins between any adjacent sampling columns; The trend analysis module is used to determine the direction of the vein based on the three-dimensional coordinates if a vein exists.

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