Mining area three-dimensional modeling and target area positioning method based on air-ground-well data

Abstract

The invention relates to a mining area three-dimensional modeling and target area positioning method based on air-ground-well data. Comprising the steps of obtaining geological survey data corresponding to a target mining area; utilizing the geological survey data to construct a mining area three-dimensional geological model corresponding to the target mining area; and analyzing the three-dimensional geological model of the mining area to determine metallogenic characteristic information corresponding to the target mining area, and positioning a mine target area in the target mining area according to the metallogenic characteristic information. Therefore, the exploration range is effectively reduced, the exploration cost is reduced, and the probability of finding the ore body is improved.

Description

TECHNICAL FIELD

[0001] The present disclosure relates to the field of thermal automatic control, and in particular to a method for three-dimensional modeling of a mining area and positioning of a target area based on air-ground-well data. BACKGROUND

[0002] In related technologies, geological surveying data, drilling data and geophysical and geochemical exploration data can be collected to construct a three-dimensional geological model of a mining area. However, when the above data is used to construct a three-dimensional geological model of a mining area, there are usually problems such as high cost and low efficiency of data acquisition, poor data precision, and difficulty in integrating different types of data. SUMMARY

[0003] Therefore, the embodiments of the present disclosure provide a method for three-dimensional modeling of a mining area and positioning of a target area based on air-ground-well data to solve the problems in related technologies.

[0004] In a first aspect, the embodiments of the present disclosure provide a method for three-dimensional modeling of a mining area and positioning of a target area based on air-ground-well data, which comprises: obtaining geological survey data corresponding to a target mining area; constructing a three-dimensional geological model of the target mining area based on the geological survey data; analyzing the three-dimensional geological model of the mining area to determine the ore-forming characteristic information of the target mining area, and positioning the ore target area in the target mining area according to the ore-forming characteristic information.

[0005] In a second aspect, the embodiments of the present disclosure provide a device for three-dimensional modeling of a mining area and positioning of a target area based on air-ground-well data, which is applied to the method for three-dimensional modeling of a mining area and positioning of a target area based on air-ground-well data as in the first aspect, and comprises: an obtaining module configured to obtain geological survey data corresponding to a target mining area; a constructing module configured to construct a three-dimensional geological model of the target mining area based on the geological survey data; and a positioning module configured to analyze the three-dimensional geological model of the mining area to determine the ore-forming characteristic information of the target mining area, and to position the ore target area in the target mining area according to the ore-forming characteristic information.

[0006] In a third aspect, the embodiments of the present disclosure provide a computer program product, which comprises computer programs / instructions that are executed by a processor to implement the steps of the method for three-dimensional modeling of a mining area and positioning of a target area based on air-ground-well data.

[0007] The above at least one technical solution adopted by the embodiments of the present disclosure can achieve the following beneficial effects: by obtaining geological survey data corresponding to a target mining area, constructing a three-dimensional geological model of the target mining area based on the geological survey data, analyzing the three-dimensional geological model of the mining area to determine the ore-forming characteristic information of the target mining area, and positioning the ore target area in the target mining area according to the ore-forming characteristic information.

[0008] Based on this, the embodiment of the present disclosure can improve the scientificity and accuracy of target mining area exploration through processing and analysis of geological survey data. Meanwhile, the three-dimensional geological model constructed based on the geological survey data can visually present the complex geological structure, facilitating intuitive understanding of the stratum distribution and ore body shape. Further, through in-depth analysis of the three-dimensional geological model of the mining area, the ore-forming characteristic information can be systematically extracted, and the ore-forming geological conditions and ore-controlling factors can be accurately identified. Finally, the ore target area is located according to the ore-forming characteristics. In this way, the exploration range can be effectively reduced, the exploration cost can be reduced, and the probability of discovering ore bodies can be improved. It can be seen that compared with the traditional exploration method, the embodiment of the present disclosure can realize the whole-chain optimization from information collection to result output under the data driving, greatly improving the exploration efficiency and resource development benefit. BRIEF DESCRIPTION OF DRAWINGS

[0009] The above and other objects, features and advantages of the present disclosure will become more apparent from the following detailed description when taken in conjunction with the accompanying drawings in which like reference characters refer to like parts throughout the figures. The drawings provide further understanding of the embodiments of the present disclosure and form a part of the specification, together with the embodiments of the present disclosure, to explain the present disclosure and do not constitute a limitation of the present disclosure. In the drawings, the same reference numerals generally refer to the same parts or steps throughout the figures.

[0010] Figure 1 A flowchart of a mine area three-dimensional modeling and target area positioning method of air-ground-well data provided for an exemplary embodiment of the present disclosure;

[0011] Figure 2 A schematic diagram of an exploration line and drill hole distribution of a target mining area provided for an exemplary embodiment of the present disclosure;

[0012] Figures 3A to 3F A schematic diagram of a mine area three-dimensional geological model provided for an exemplary embodiment of the present disclosure, comprising:

[0013] Figure 3A A schematic diagram of a drill hole model provided for an exemplary embodiment of the present disclosure;

[0014] Figure 3B A schematic diagram of an ore body spatial distribution model provided for an exemplary embodiment of the present disclosure;

[0015] Figure 3C A schematic diagram of a stratum three-dimensional model provided for an exemplary embodiment of the present disclosure;

[0016] Figure 3D A schematic diagram of a pegmatite zoning model provided for an exemplary embodiment of the present disclosure;

[0017] Figure 3E A schematic diagram of a resistivity three-dimensional model provided for an exemplary embodiment of the present disclosure;

[0018] Figure 3F A schematic diagram of a lithium element distribution model provided by an example embodiment of the present disclosure;

[0019] Figure 4A A schematic diagram of a resistivity-ore body combined three-dimensional model provided by an example embodiment of the present disclosure;

[0020] Figure 4B A schematic diagram of a resistivity distribution profile numbered 3 provided by an example embodiment of the present disclosure;

[0021] Figure 4C A schematic diagram of a resistivity distribution profile numbered 7 provided by an example embodiment of the present disclosure;

[0022] Figure 5A A schematic diagram of Wordview-3 image interpretation provided by an example embodiment of the present disclosure;

[0023] Figure 5B A schematic diagram of a topographic image provided by an example embodiment of the present disclosure;

[0024] Figure 6A A schematic diagram of a resistivity-DEM combined three-dimensional model provided by an example embodiment of the present disclosure;

[0025] Figure 6B A schematic diagram of an AMT three-dimensional combined profile in a first direction provided by an example embodiment of the present disclosure;

[0026] Figure 6C A schematic diagram of an AMT three-dimensional combined profile in a second direction provided by an example embodiment of the present disclosure;

[0027] Figure 7A A schematic diagram of a F2 fault zone three-dimensional geological structure distribution map provided by an example embodiment of the present disclosure;

[0028] Figure 7B A schematic diagram of a F2 fault zone geological zoning three-dimensional provided by an example embodiment of the present disclosure;

[0029] Figure 7C A schematic diagram of a F1 fault zone three-dimensional geological structure distribution map provided by an example embodiment of the present disclosure;

[0030] Figure 7D A schematic diagram of a F1 fault zone geological zoning three-dimensional provided by an example embodiment of the present disclosure;

[0031] Figure 8A A schematic diagram of a F3 / F4 surface structure line and deep structure surface and pegmatite vein distribution relationship provided by an example embodiment of the present disclosure;

[0032] Figure 8B A diagram of spatial dislocation and extension characteristics of pegmatite veins and associated with structural planes is provided by an example embodiment of the present disclosure.

[0033] Figure 8C A diagram of stable extension direction and spatial distribution characteristics of geological anomaly bodies is provided by an example embodiment of the present disclosure.

[0034] Figure 8D A diagram of the influence of F3 left slip normal fault dislocation on spatial distribution of pegmatite veins is provided by an example embodiment of the present disclosure.

[0035] Figure 8E A diagram of three-dimensional distribution and predicted location of pegmatite veins under fault action is provided by an example embodiment of the present disclosure.

[0036] Figure 9A A diagram of F3 and F4 surface structural lines and deep structural planes, and pegmatite vein distribution correlation is provided by an example embodiment of the present disclosure.

[0037] Figure 9B A diagram of spatial dislocation and extension of inner and outer pegmatite veins and associated with structural planes and predicted veins is provided by an example embodiment of the present disclosure.

[0038] Figure 9C A diagram of geological anomaly closed area and different distribution characteristics of ore-bearing properties is provided by an example embodiment of the present disclosure.

[0039] Figure 9D A diagram of extension and different distribution of pegmatite veins after F3 left slip normal fault dislocation is provided by an example embodiment of the present disclosure.

[0040] Figure 9E A diagram of three-dimensional distribution and prediction of pegmatite veins under plane left slip-profile normal fault action is provided by an example embodiment of the present disclosure.

[0041] Figure 10 A structural diagram of a device for three-dimensional modeling of a mining area and target area positioning of air-ground-well data is provided by an example embodiment of the present disclosure.

[0042] Figure 11 A structural diagram of an electronic device is provided by an example embodiment of the present disclosure.

[0043] Figure 12 A structural diagram of a computer system is provided by an example embodiment of the present disclosure.

[0044] Figure 13 A diagram of a computer program product is provided by an example embodiment of the present disclosure. DETAILED DESCRIPTION

[0045] The following describes embodiments of the present disclosure in more detail with reference to the accompanying drawings. Although certain embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be construed as limited to the embodiments described herein. Rather, these embodiments are provided to provide a more thorough and complete understanding of the present disclosure. It should be understood that the drawings and embodiments of the present disclosure are for illustrative purposes only and are not intended to limit the scope of protection of the present disclosure.

[0046] It should be understood that the various steps described in the method embodiments of the present disclosure may be performed in different orders and / or in parallel. In addition, the method embodiments may include additional steps and / or omit the steps shown. The scope of the present disclosure is not limited in this respect.

[0047] The term "including" and its variations used in this document are open inclusions, that is, "including but not limited to". The term "based on" means "based at least in part on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one other embodiment"; the term "some embodiments" means "at least some embodiments". The relevant definitions of other terms will be given in the description below. It should be noted that the concepts of "first", "second", etc. mentioned in this disclosure are only used to distinguish different devices, modules or units, and are not used to limit the order or interdependence of the functions performed by these devices, modules or units.

[0048] It should be noted that the modifications of "one" and "multiple" mentioned in the present disclosure are illustrative rather than restrictive, and those skilled in the art should understand that unless otherwise clearly indicated in the context, they should be understood as "one or more".

[0049] The names of the messages or information exchanged between multiple devices in the embodiments of the present disclosure are only used for illustrative purposes and are not used to limit the scope of these messages or information.

[0050] Related technologies can collect geological mapping data, drill hole data, and geophysical and geochemical data to construct a 3D geological model of a mining area. However, using this data to build a 3D geological model of a mining area often faces problems such as high data acquisition costs, low acquisition efficiency, poor data accuracy, and difficulty integrating different types of data. For example, while drill hole data is an important basis for modeling, exploration costs and conditions limit the number and distribution of drill holes, resulting in inaccurate 3D geological models in certain areas. Furthermore, the large amount of paper geological maps and other materials are prone to errors and information loss during the digitization and data extraction process.

[0051] To solve the above problems, the embodiment of the present disclosure provides a mine area three-dimensional modeling and target area positioning method, device and product based on air-ground-well data, which comprises the following steps: obtaining geological survey data corresponding to a target mine area; constructing a mine area three-dimensional geological model corresponding to the target mine area by using the geological survey data; analyzing the mine area three-dimensional geological model to determine the ore-forming characteristic information corresponding to the target mine area, and positioning the ore target area in the target mine area according to the ore-forming characteristic information.

[0052] Based on this, the embodiment of the present disclosure can improve the scientificity and accuracy of the target mine area exploration through the processing and analysis of the geological survey data. At the same time, the three-dimensional geological model constructed based on the geological survey data can visualize the complex geological structure, which is convenient for intuitive understanding of the stratum distribution and ore body shape. Then, through the in-depth analysis of the mine area three-dimensional geological model, the ore-forming characteristic information can be systematically extracted, and the ore-forming geological conditions and ore-controlling factors can be accurately identified. Finally, the ore target area is positioned according to the ore-forming characteristics. In this way, the exploration range can be effectively reduced, the exploration cost can be reduced, and the probability of discovering ore bodies can be improved. Therefore, compared with the traditional exploration method, the embodiment of the present disclosure can realize the whole-chain optimization from information collection to result output under the data driving, which greatly improves the exploration efficiency and resource development benefit.

[0053] The mine area three-dimensional modeling and target area positioning method based on air-ground-well data provided by the embodiment of the present disclosure can be executed by a terminal or a chip applied to the terminal.

[0054] For example, the terminal can include one or more of a mobile phone, a tablet computer, a wearable device, a vehicle-mounted device, a notebook computer, an ultra-mobile personal computer (UMPC), a netbook, a personal digital assistant (PDA), and a wearable device based on augmented reality (AR) and / or virtual reality (VR) technology. The terminal can also include, but is not limited to, a remote control device, a wearable device, a street lamp, a smart terminal of household appliances, and the like. The embodiment of the present disclosure does not make specific limitations on this.

[0055] Figure 1 A flowchart of a mine area three-dimensional modeling and target area positioning method based on air-ground-well data provided by an exemplary embodiment of the present disclosure is shown in FIG. 1. Figure 1 As shown in FIG. 1, the method comprises the following steps:

[0056] S101, obtaining geological survey data corresponding to a target mine area.

[0057] In some embodiments, the geological survey data can include ore body data, core data, geochemical data, geophysical data, and remote sensing data, wherein the geological data can include ore body data and core data. The geological survey data corresponding to the target mining area can be obtained through multiple approaches. For example, first, traditional geological mapping methods can be used, geological personnel can conduct field investigation, observe and record rock types, stratigraphic contact relationships, structural characteristics, and the like, and collect core samples to obtain ore body data and core data. Second, geophysical exploration methods such as gravity exploration, magnetic exploration, electrical exploration, and seismic exploration can be used to detect the physical property differences of underground geological bodies and obtain geophysical data. Third, geochemical measurement can be carried out to collect soil, stream sediment, rock, and the like for chemical analysis to obtain geochemical data, and then the element anomaly area in the target mining area can be delineated.

[0058] In addition, remote sensing technology can be used to extract remote sensing data such as topography, lithology, and structure of the mining area through satellite or aerial images. In addition, previous research results, regional geological data, and mineral exploration reports can be integrated, and geographic information system (GIS) technology can be used for comprehensive management and analysis of data, so that the geological survey data corresponding to the target mining area can be obtained comprehensively and systematically. Here, the geographic information system (GIS) is a technical system integrating computer hardware, software, and geographic data, which is used to collect, store, manage, analyze, and visualize geographic spatial information. It is based on a geographic spatial database, and through processing and analysis of spatial data, it reveals the spatial distribution, mutual relationship, and dynamic change law of geographic elements, and has spatial and dynamic characteristics.

[0059] In some embodiments, after obtaining the geological survey data of the target mining area, the geological features of the target mining area can be analyzed from multiple dimensions. First, the basic geological data such as rock types and stratigraphic sequences can be sorted out to clarify the geological tectonic framework of the mining area. Second, the element content, distribution characteristics, and anomaly area can be analyzed through geochemical data to identify possible mineralization element combinations. Third, the underground geological body shape, structure, and burial depth can be inferred using geophysical data such as gravity, magnetic force, and resistivity measurement results. In addition, remote sensing data can be used to analyze the topography, linear structure, and the like of the mining area from a macroscopic perspective to assist in judging the favorable mineralization area. Finally, the various types of data are integrated, and statistical methods, GIS spatial analysis, and the like are used for cross-validation to mine the potential correlation between the data, so as to comprehensively evaluate the geological conditions and mineralization potential of the target mining area.

[0060] S102, constructing a three-dimensional geological model of the target mining area corresponding to the geological survey data.

[0061] In some embodiments, in the process of constructing a three-dimensional geological model corresponding to the target mining area by utilizing geological survey data, multi-source data integration and professional modeling techniques can be relied on. First, field exploration data such as rock types, stratigraphic layering, and occurrence of structural planes, as well as deep geological body boundaries interpreted from geophysical exploration and geochemical anomaly distribution data, can be uniformly entered into GIS to form basic data layers. Subsequently, by using three-dimensional modeling software, spatial analysis algorithms such as Kriging interpolation and inverse distance weighting can be used to convert discrete data into continuous three-dimensional body data, and the spatial form of geological structures such as strata, faults, and ore bodies can be constructed. In this process, the three-dimensional geological model of the mining area can also be corrected in combination with geological theoretical knowledge to ensure that the three-dimensional geological model of the mining area conforms to the geological evolution law, and finally a high-precision three-dimensional geological model of the mining area that intuitively reflects the geological characteristics of the mining area is generated, providing a visual and quantitative research basis for subsequent ore-forming analysis and ore target area positioning.

[0062] S103, analyzing the three-dimensional geological model of the mining area to determine the ore-forming characteristic information corresponding to the target mining area, and positioning the ore target area in the target mining area according to the ore-forming characteristic information.

[0063] In some embodiments, the analysis of the three-dimensional geological model of the mining area aims to deeply mine the ore-forming characteristic information through multidisciplinary cross-methods. First, the relationship between stratigraphic structure and fault distribution can be intuitively observed based on the three-dimensional geological model of the mining area to identify ore-controlling structural belts and favorable lithological assemblages; second, the visualization analysis of geochemical data in three-dimensional space can be used to delineate element anomaly concentration centers and their spatial coupling relationship with geological bodies; at the same time, the physical and chemical conditions of mineralization and fluid migration rules can be deduced in combination with microscopic geological information such as mineral paragenetic assemblage and alteration zoning. On this basis, the three-dimensional geological model of the mining area is established by integrating geological data, geophysical data, and geochemical data, and the contribution weight of each factor to mineralization is quantified. Finally, through spatial superposition analysis and probability prediction algorithms, the high-value area of mineralization potential is accurately delineated in the three-dimensional geological model of the mining area, and the location of the ore target area is locked, providing a scientific basis for subsequent exploration engineering layout, effectively reducing exploration risk and improving resource discovery efficiency.

[0064] Based on this, the embodiment of the present disclosure can improve the scientificity and accuracy of the target mining area exploration through the processing and analysis of the geological survey data. Meanwhile, the three-dimensional geological model constructed based on the geological survey data can visually present the complex geological structure, facilitating the intuitive understanding of the stratum distribution and the ore body shape. Then, through the in-depth analysis of the three-dimensional geological model of the mining area, the ore-forming characteristic information can be systematically extracted, and the ore-forming geological conditions and ore-controlling factors can be accurately identified. Finally, the ore target area can be located according to the ore-forming characteristics. In this way, the exploration range can be effectively reduced, the exploration cost can be reduced, and the probability of discovering ore bodies can be improved. It can be seen that compared with the traditional exploration method, the embodiment of the present disclosure can realize the whole-chain optimization from information collection to result output under the data driving, greatly improving the exploration efficiency and resource development benefit.

[0065] In some embodiments, the geological survey data includes ore body data, and obtaining the geological survey data corresponding to the target mining area includes: obtaining a plurality of exploration line profile data corresponding to a plurality of exploration lines in the target mining area, wherein one exploration line corresponds to one exploration line profile data; and determining the ore body data according to the plurality of exploration line profile data.

[0066] Figure 2 A schematic diagram of the distribution of exploration lines and drill holes in a target mining area is provided for an exemplary embodiment of the present disclosure. As shown in Figure 2 , it includes a plurality of exploration lines 201 and a plurality of drill holes 202, wherein the distance between two adjacent exploration lines 201 in the plurality of exploration lines 201 can be 100m-150m, and in general, the plurality of exploration lines 201 can be distributed in parallel at equal intervals, but in the area where the ore body shape or occurrence is complex and variable, the distance between two adjacent exploration lines 201 can be adjusted adaptively.

[0067] As shown in Figure 2 , the embodiment of the present disclosure selects 35 exploration lines 201 and 114 drill holes 202 for analysis in the target mining area, comprehensively analyzes a plurality of exploration line profile data corresponding to the 35 exploration lines with a spacing of 100-150m, and completes the vectorization work of 42 main ore body boundaries to obtain ore body data, which provides a basis for the subsequent construction of the three-dimensional geological model of the mining area. The above-mentioned dense and targeted exploration line arrangement can accurately capture the thickness variation, branching and compounding characteristics of the ore body in different profiles, and further provide key basis for subsequent mining design.

[0068] The vectorization of the boundaries of 42 ore bodies can convert complex geological information into quantifiable digital data, and then a three-dimensional geological model of the mining area can be constructed using GIS technology to intuitively present the spatial form and grade distribution of the ore body, effectively avoiding the details of the extension of the ore body that cannot be found in traditional drawings. In addition, the accumulation of these data also provides an important reference for subsequent deep and peripheral prospecting, helping the exploration team to successfully locate new mineralization zones in adjacent areas, greatly improving the efficiency and economic benefits of exploration.

[0069] In some embodiments, the geological survey data further includes core data, obtaining the corresponding geological survey data of the target mining area includes: obtaining a plurality of drilling data corresponding to a plurality of drill holes on a plurality of exploration lines respectively; collecting a plurality of core samples at a preset depth interval along the depth direction of the plurality of drill holes, wherein the opening angles of the plurality of drill holes are the same; determining core sub-data corresponding to each core sample according to the collection position information of each core sample and the drilling data of the corresponding drill hole; and determining the core data according to the core sub-data corresponding to the plurality of core samples. It should be understood that, in general, the plurality of drill holes will maintain the same opening angle to facilitate data comparison and analysis; however, in actual operation, the opening angles of the plurality of drill holes may differ due to factors such as topography, geological structure complexity, etc.

[0070] Specifically, in the exploration of the target mining area, the acquisition of core data relies on systematic drilling engineering and detailed logging work. For example, a plurality of drill holes can be arranged on a plurality of exploration lines, and 114 representative drill holes can be selected from the plurality of drill holes for exploration. For the 114 representative drill holes, sampling can be performed at an interval of 15 meters along the depth direction of the drill holes to obtain 1369 core samples, and the cumulative depth of all drill holes is 18300 meters. Here, to flexibly increase the sampling points for key geological interfaces such as lithological mutation, mineralization alteration zone, and tectonic fracture zone, the interval of core sample collection can be shortened to 3-5 meters, thereby accurately capturing subtle geological changes. Finally, the lithological characteristics of the full depth of the drill hole are recorded completely.

[0071] To ensure the spatial accuracy and traceability of the data, all core samples can be precisely positioned using a three-dimensional spatial coordinate system. Specifically, the drilling data corresponding to each core sample can be recorded, such as drilling number, three-dimensional coordinates of the drill hole, elevation data, opening azimuth angle and inclination angle, and the collection position information corresponding to each core sample can be determined, such as the three-dimensional coordinates of the core sample. In this way, each core sample can be accurately mapped in the three-dimensional geological model, providing high-precision data support for subsequent lithological analysis, stratigraphic correlation, and construction of a three-dimensional geological model of the mining area.

[0072] In some embodiments, the plurality of core samples can be classified into two categories of wall rock and pegmatite vein, wherein the wall rock is mainly Triassic Bayankela group of metamorphic fine-grained feldspar sandstone, metamorphic fine-grained feldspar quartz sandstone, metamorphic siltstone and diopside hornstone; the pegmatite vein is divided into seven types according to mineral combination, i.e., spodumene-quartz type, spodumene-albite-quartz type, spodumene-albite-quartz-muscovite type, albite-quartz type, muscovite-albite-quartz type, two-mica-albite-quartz type and tourmaline-albite-quartz type.

[0073] Based on this, in the aspect of geological research, the Triassic Bayankela group attribute and lithological characteristics of the wall rock are determined, which is helpful to trace the regional geological evolution and tectonic background; the pegmatite vein is subdivided into seven types according to mineral combination, which can accurately reveal the ore-forming processes such as magmatic differentiation and hydrothermal metasomatism; in the field of resource exploration, different types of pegmatite correspond to specific mineralization elements, which can quickly lock the target area of the mine to improve the efficiency of exploration; from the engineering point of view, the difference in rock type determines the hardness and the degree of fracture development, which provides a basis for the targeted design of mining technology and beneficiation scheme; in addition, the standardized classification also conforms to the geological industry standard, which is convenient for regional comparison, interdisciplinary analysis and application of research results, and significantly enhances the systematicness and practicality of research results.

[0074] In some embodiments, the geological survey data further includes geochemical data, and obtaining the geological survey data corresponding to the target mining area comprises: determining the geochemical sub-data corresponding to each core sample in the plurality of core samples; and determining the geochemical data according to the geochemical sub-data corresponding to each core sample. It should be understood that the geochemical data refers to the data obtained by means of geochemical investigation, analysis and testing, etc., which is used to characterize the distribution, content and occurrence state of chemical elements in a specific research area.

[0075] Specifically, the geochemical data can be analyzed by laser-induced breakdown spectroscopy technology on 1369 core samples of 114 drill holes. In the specific experiment process, a SciAps Z-903 portable LIBS analysis system can be used, which is composed of a wavelength 1064 nm, single pulse energy 5±0.2 mJ, repetition frequency 50 Hz Q Nd:YAG laser, detection range 190-950 nm, optical resolution better than 0.05 nm high-resolution spectral system, Hamamatsu S15254-2048 three-channel enhanced CCD detector, and automatic core sample table and computer control system. When analyzing 1369 core samples of 114 drill holes by laser-induced breakdown spectroscopy technology, high-energy laser such as Nd:YAG laser with wavelength 1064 nm can be used to focus on the surface of the core sample. High-temperature plasma is generated on the surface of the core sample at that moment, and the characteristic spectrum is released when the plasma cools down. Thus, the element composition and content in the sample can be determined by detecting the spectral wavelength and intensity.

[0076] Before testing the core sample, the core sample can be split or sawn to make the surface of the core sample flat, and then the contaminants on the surface of the core sample are removed by cleaning. On this basis, the core sample is measured by a 9-point grid method (3x3 array, point spacing 2 mm), the content of each type of element is obtained by arithmetic mean, and the data stability is ensured by 10% core sample repeat analysis. The elements analyzed by the embodiment of the disclosure include 17 major and trace elements, including lithium (Li), beryllium (Be), magnesium (Mg), aluminum (Al), silicon (Si), phosphorus (P), sulfur (S), titanium (Ti), vanadium (V), chromium (Cr), manganese (Mn), iron (Fe), cobalt (Co), nickel (Ni), copper (Cu), zinc (Zn), and lead (Pb).

[0077] After determining the element content corresponding to each core sample, the element content corresponding to each core sample and the core data corresponding to each core sample can be associated, that is, the element content corresponding to each core sample, the corresponding collection position information and the corresponding drill hole data can be associated. Through this association, the distribution trend and abnormal characteristics of elements in three-dimensional space can be intuitively presented, and the element enrichment area can be quickly located by geologists.

[0078] In some embodiments, the geological survey data further includes geophysical data and remote sensing data corresponding to the target mining area.

[0079] Specifically, for the geophysical data derived from audio-frequency magnetotellurics (AMT) profile measurement (Institute of Geology), the measurement work is completed by using the EH-4 continuous conductivity profile instrument. The system is composed of a transmitter with a working frequency of 500Hz-70kHz and a receiving mechanism configured with 4 electrodes, a 26-meter cable, a 10Hz-100kHz magnetic probe and a data acquisition unit. Here, the audio-frequency magnetotellurics (AMT) profile is a profile image of the underground resistivity distribution obtained by the audio-frequency magnetotellurics method (a geophysical exploration method). This method uses the natural electromagnetic field (the frequency range is usually 10Hz-100kHz) as the field source, measures the electromagnetic response of the underground medium at different frequencies, and after data processing and inversion, obtains the resistivity value at different depths of the underground, and displays it in the form of a profile, which is used to identify the spatial distribution and electrical characteristics of geological bodies such as faults and ore bodies.

[0080] During the test of the target mining area, 10 profiles with a cumulative length of 16160 meters can be laid out in the target mining area, and an observation network with a line distance of 300-500 meters and a point distance of 20 meters is used. The raw data collected is strictly quality controlled and processed, including data preprocessing such as rejecting bad channels, suppressing noise, and standardizing format; static effect correction such as terrain and near-field correction; impedance tensor analysis and rotation, and one-dimensional and two-dimensional inversion calculation processes. Finally, with the help of drilling data, the results obtained by inversion can be verified and corrected to ensure that the final resistivity profile and the actual position of the drill hole are consistent with each other.

[0081] For remote sensing data, it can be derived from WorldView-3 satellite images, covering an area of 21km 2 . Specifically, the remote sensing data has a super-high spatial resolution of 0.31m and 16 multi-spectral bands, including 8 new SWIR bands, with outstanding advantages in near-infrared and short-wave infrared bands. After obtaining the remote sensing data, the remote sensing data can be preprocessed to improve data quality, extract key information and realize the visualization identification of structural features. Here, the WorldView-3 satellite image refers to the earth surface image data obtained by the United States WorldView-3 satellite launched on August 13, 2014, with a panchromatic image resolution of 0.31 meters, multi-spectral, short-wave infrared and other multi-band data, which can provide high-precision earth observation data support for multiple fields.

[0082] Specifically, first, the remote sensing data can be pre-processed, such as radiation calibration, atmospheric correction, geometric correction, image fusion and the like, to ensure data quality; second, principal component analysis method is used to extract key structural information in multi-band image through dimension reduction processing; finally, RGB band synthesis technology can be used to optimize the band combination scheme, and specific bands are respectively assigned to red, green and blue channels, so that different lithology and structure show distinct color contrast due to spectral feature difference, thereby clearly identifying the structural form and spatial distribution characteristics. Here, RGB band refers to the spectral band corresponding to red (Red), green (Green) and blue (Blue) in the remote sensing image.

[0083] In some embodiments, a three-dimensional geological model of a target mining area is constructed using geological survey data, including: pre-processing the geological survey data, and constructing a geological survey data set according to the pre-processed geological survey data; importing the geological survey data set into a preset data processing platform to generate a three-dimensional format file corresponding to the geological survey data set; and constructing a three-dimensional geological model of the target mining area using the three-dimensional format file.

[0084] Specifically, the geological survey data can include ore body data, core data, geochemical data, geophysical data and remote sensing data, wherein the geological survey data includes geochemical sub-data corresponding to a plurality of core samples and core sub-data corresponding to the plurality of core samples. The pre-processing operation of the geological survey data includes: for any core sample, establishing an association between the geochemical sub-data corresponding to the core sample and the core sub-data.

[0085] For example, the core sub-data can include drilling data corresponding to the core sample, such as drilling number, three-dimensional coordinates of the drilling, elevation data, opening azimuth angle and inclination angle, and collection position information corresponding to the core sample, and the geochemical sub-data includes the content and distribution of each element in the core sample. Based on this, the core sub-data and the geochemical sub-data corresponding to the plurality of core samples can be associated respectively, and the spatial coupling of geological properties and chemical properties can be realized, forming a "position-lithology-element" three-in-one data chain, providing multi-dimensional support for ore body three-dimensional modeling and resource evaluation.

[0086] In some embodiments, the data collection can be performed in the same coordinate system for the ore body data, the core data, the geochemical data, the geophysical data and the remote sensing data. For example, the data collection can be performed in the Geodetic 2000 coordinate system, and then the structured correlation can be realized through the spatial database constructed by the ArcGIS platform: the drill hole coordinates in the ore body data, the collection location information corresponding to the core sample in the core data, the element content analysis results in the geochemical data, the AMT resistivity measurement point coordinates in the geophysical data, and the image geographic coordinates of the remote sensing data, are all associated with the data table through key fields such as drill hole number and core sample identification; and then the data with coordinates are imported into the EVS platform to generate a three-dimensional model, so that the geological body shape, element content distribution, resistivity anomaly area and surface structure interpreted by remote sensing are verified with each other in the three-dimensional space, such as the low-resistance zone inverted by AMT and the ore body position revealed by the drill hole, the fracture identified by remote sensing and the deep structure occurrence revealed by AMT are complementary, which jointly support the structural ore-controlling analysis and ore body positioning. Here, the ArcGIS platform is a complete geographic information system (GIS) software developed by the Environmental Systems Research Institute (ESRI) of the United States, which is used for collecting, managing, analyzing, displaying and sharing geospatial data; the EVS platform is the abbreviation of Earth Volumetric Studio, which is a 3D modeling and analysis software suitable for the field of earth science.

[0087] As shown in Figure 2 For the core sample identified as ZK0713-10, wherein ZK0713 identifies the identification of drill hole 203, 10 is the core sample identified as 10 collected in the ZK0713 drill hole, the collection location information corresponding to the core sample is (X1, Y1, Z1), the coordinates corresponding to the drill hole are (X, Y, Z), the lithium element content corresponding to the core sample is determined as 1.8% according to the geochemical data, there is a low-resistance anomaly area near the drill hole according to the geophysical data, and there is a fracture in the region corresponding to the drill hole according to the remote sensing data. Based on this, (X1, Y1, Z1), (X1, Y1, Z1), the lithium element content of 1.8%, the low-resistance anomaly area and the existence of the fracture can be associated, and then the region around the sample rock can be determined as a region with low resistance anomaly, high lithium content and fracture in the subsequent formed three-dimensional geological model of the mining area.

[0088] In some embodiments, a geological survey dataset corresponding to a target mining area can be built on the ArcGIS platform. The geological survey dataset can include a mineral body feature class, such as mineral body data; a borehole feature class, including borehole location, azimuth angle, inclination angle, and surface elevation; a prospecting line path feature class, such as a prospecting line and a plurality of borehole data corresponding to a plurality of boreholes on the prospecting line; a prospecting line mineral body event feature class, such as thickness of a mineral body and the like; a borehole logging object class, including lithology, minerals, structure, and tectonic features at different depths; a borehole LIBIS analysis object class, such as LIBIS element content analysis results; a borehole X-fluorescence analysis object class, such as desktop portable X-fluorescence analyzer element content analysis results; geochemical data; controlled source audio magnetotelluric sounding geophysical data; WorldView-3 visible light-near infrared-short wave infrared multi-spectral raster data; WorldView-3 various image enhancement and information extraction result raster data; study area DEM raster data, and the like. Here, the DEM (Digital Elevation Model) raster data is a model data expressing surface elevation information in a regular grid or an irregular triangular mesh digital manner.

[0089] Then, the preprocessed geological survey data can be analyzed by using the spatial analysis functions of the ArcGIS platform, such as path analysis, point value extraction analysis, coordinate value acquisition, and the like, and file conversion functions, to obtain a mineral body boundary point data table containing X, Y, and Z coordinates, a borehole lithology and mineral feature data table, an element content data table, an X-fluorescence analysis element content data table, and a controlled source audio magnetotelluric sounding data table.

[0090] Finally, the mineral body boundary point data table containing X, Y, and Z coordinates, the borehole lithology and mineral feature data table, the element content data table, the X-fluorescence analysis element content data table, and the controlled source audio magnetotelluric sounding data table are imported into the EVS platform to generate corresponding three-dimensional format files; at the same time, according to field observation, borehole logging, prospecting line profile revealed geological body occurrence and distribution characteristics, geophysical prospecting analysis, corresponding structure surface intersection line / structure line and occurrence are created in the ArcGIS platform; using the surface DEM data and the structure surface intersection line / structure line in the EVS, various structure surfaces and modeling partitions are generated; based on the numerical spatial distribution and occurrence characteristics of various logging and analysis data of the boreholes in the modeling partitions, anisotropy parameters are generated. Based on this, a mining area three-dimensional geological model corresponding to the target mining area can be built according to the three-dimensional format files, and further prospecting direction and prospecting space can be analyzed and determined in the three-dimensional space in combination with the research results of the metallogenic theory.

[0091] Figures 3A to 3F A schematic diagram of a mining area three-dimensional geological model is provided for an exemplary embodiment of the present disclosure. As shown in FIG. 1, the mining area three-dimensional geological model includes a surface DEM data layer 1, a structure surface intersection line / structure line layer 2, a borehole layer 3, a borehole lithology and mineral feature layer 4, a borehole element content layer 5, a borehole X-fluorescence analysis element content layer 6, a controlled source audio magnetotelluric sounding layer 7, a borehole LIBIS analysis layer 8, a borehole logging layer 9, a prospecting line layer 10, a prospecting line mineral body event layer 11, a mineral body layer 12, and a mineral body boundary point layer 13. Figures 3A to 3FAs shown in the figure, the topography and drill hole model of the target mining area are constructed by fusing WorldView-3 multispectral remote sensing images and DEM data to construct a high-precision drill hole model; the drill hole model integrates the drill hole data corresponding to 114 drill holes and the corresponding 1369 core sample analysis data, and records the lithological characteristics and mineral composition of each sampling point.

[0092] Figure 3A A schematic diagram of a drill hole model is provided for an exemplary embodiment of the present disclosure. As shown in the figure, the topography and drill hole model of the target mining area are constructed by fusing WorldView-3 multispectral remote sensing images and DEM data to construct a high-precision drill hole model; the drill hole model integrates the drill hole data corresponding to 114 drill holes and the corresponding 1369 core sample analysis data, and records the lithological characteristics and mineral composition of each sampling point. Figure 3A

[0093] A schematic diagram of a drill hole model is provided for an exemplary embodiment of the present disclosure. As shown in the figure, the topography and drill hole model of the target mining area are constructed by fusing WorldView-3 multispectral remote sensing images and DEM data to construct a high-precision drill hole model; the drill hole model integrates the drill hole data corresponding to 114 drill holes and the corresponding 1369 core sample analysis data, and records the lithological characteristics and mineral composition of each sampling point. Figure 3B Figure 3B Figure 3B A schematic diagram of a drill hole model is provided for an exemplary embodiment of the present disclosure. As shown in the figure, the topography and drill hole model of the target mining area are constructed by fusing WorldView-3 multispectral remote sensing images and DEM data to construct a high-precision drill hole model; the drill hole model integrates the drill hole data corresponding to 114 drill holes and the corresponding 1369 core sample analysis data, and records the lithological characteristics and mineral composition of each sampling point.

[0094] Figure 3C A schematic diagram of a drill hole model is provided for an exemplary embodiment of the present disclosure. As shown in the figure, the topography and drill hole model of the target mining area are constructed by fusing WorldView-3 multispectral remote sensing images and DEM data to construct a high-precision drill hole model; the drill hole model integrates the drill hole data corresponding to 114 drill holes and the corresponding 1369 core sample analysis data, and records the lithological characteristics and mineral composition of each sampling point. Figure 3C

[0095] A schematic diagram of a drill hole model is provided for an exemplary embodiment of the present disclosure. As shown in the figure, the topography and drill hole model of the target mining area are constructed by fusing WorldView-3 multispectral remote sensing images and DEM data to construct a high-precision drill hole model; the drill hole model integrates the drill hole data corresponding to 114 drill holes and the corresponding 1369 core sample analysis data, and records the lithological characteristics and mineral composition of each sampling point. Figure 3D Figure 3D A schematic diagram of a drill hole model is provided for an exemplary embodiment of the present disclosure. As shown in the figure, the topography and drill hole model of the target mining area are constructed by fusing WorldView-3 multispectral remote sensing images and DEM data to construct a high-precision drill hole model; the drill hole model integrates the drill hole data corresponding to 114 drill holes and the corresponding 1369 core sample analysis data, and records the lithological characteristics and mineral composition of each sampling point.

[0096] Figure 3E ​​​A schematic diagram of a resistivity 3D model is provided by an example embodiment of the present disclosure. As shown in Figure 3E The resistivity 3D model fuses resistivity data of 10 AMT profiles (total length 16 km), adopts inverse distance weighted interpolation method, constructs a three-dimensional resistivity distribution model in the depth range of 0-1000 meters underground, and clearly reflects the deep structural characteristics through the set resistivity color scale and model support for arbitrary direction profile cutting. Among them, the resistivity gradient change belt indicates the fracture zone, and red, orange, yellow, green and blue represent the change of resistivity from high to low.

[0097] Figure 3F A schematic diagram of a lithium element distribution model is provided by an example embodiment of the present disclosure. As shown in Figure 3F The element distribution model is based on the element content of 1369 drill samples, focuses on depicting the differential distribution characteristics of lithium element in 7 types of pegmatite veins, and supports the establishment of element combination models such as Al / Si ratio and Fe / Mn ratio, and the coupling relationship between element geochemical anomaly and spatial zoning of pegmatite veins. Among them, red / orange is high lithium content, and the inner belt is spodumene pegmatite; yellow is medium lithium content, and the middle belt is mica pegmatite; green is low lithium content, and the outer belt is barren pegmatite; blue is extremely low lithium content or non-mineralized area.

[0098] In some embodiments, the ore-forming feature information includes at least one of a geological structure rule, a pegmatite vein zoning rule, and a lithium element distribution rule in the target mining area. Among them, the lithium element distribution rule is determined by Figure 3F the corresponding lithium element distribution model.

[0099] Figure 4A A schematic diagram of a resistivity-ore body combined 3D model is provided by an example embodiment of the present disclosure. As shown in Figure 4A For the determination of the geological structure rule in the target mining area, the ore body in the mining area can be divided into a north belt with northeast inclination and a south belt with southwest inclination according to the inclination, and there are two views on the genesis, one is that the same group of pegmatite vein groups are bent and deformed in the later tectonic activity, and the other is that two groups of pegmatite vein groups are controlled by different tectonic systems.

[0100] Figure 4B A schematic diagram of a resistivity distribution profile No. 3 is provided by an example embodiment of the present disclosure. Figure 4C A schematic diagram of a resistivity distribution profile No. 7 is provided by an example embodiment of the present disclosure. As shown in Figures 4A to 4CAs shown, five resistivity distribution profiles numbered 47, 33, 19, 7 and 4 are shown, for three-dimensional resistivity distribution data that can be obtained by audio magnetotelluric measurement for the resistivity distribution profile, and further can provide key basis for analyzing structural elements such as faults, fissures and the like that control the formation and distribution of ore bodies in the mining area. For example, as for the resistivity distribution profile numbered 7, the F2 fault with north-east dip and gentle dip angle of 30-40° and the F1 fault with south-west dip and steep dip angle of 50-60° can be identified by the resistivity gradient change and the low-resistance anomaly distribution direction, and the F1 fault and the F2 fault also have obvious influence on the resistivity distribution profile numbered 33, wherein the occurrence of the F1 fault becomes steep, and the resistivity gradient change at the F2 fault is weakened and can gradually pinch out.

[0101] As shown in FIG. 4, Figures 4A to 4C As shown in FIG. 4, and

[0102] The F1 fault and the F2 fault can be outlined by analyzing the resistivity distribution profiles from east to west of the target mining area according to 4→7→19→33→47. Among them, the F1 fault has a steep dip angle first and then a gentle dip angle, and the F2 fault has a stable occurrence and gradually pinches out. Since the faults are consistent with the occurrence of the ore body in the target mining area, and the pegmatite vein group is distributed along the structural surface, the ore bodies with different dips are jointly controlled by the ore-controlling structures F1 and F2 with different occurrences. This structural ore-controlling mode is consistent with the observation results of the peripheral profiles of the mining area. For example, the south-west dipping ore body of the Aktas and Kalakka deposits in the Dahongliantan ore concentration area and the north-east dipping ore body of the Longmenshan deposit are all controlled by the fault system with the corresponding dip. It should be understood that the fault belongs to a structural surface. Figure 5A Figure 5B Figure 5A A schematic diagram of a topographic image provided by an example embodiment of the present disclosure. Figure 5B As shown in FIG. 4, and

[0103] Based on the PCA enhancement and RGB fusion of the WorldView-3 remote sensing image, three faults F3, F4 and F5 are identified in the region, wherein F3 and F4 pass through the target mining area 501 and are roughly north-east to south-west; F5 is located in the periphery of the target mining area 501 and is roughly north-west to south-east. These faults show typical linear structural characteristics on the image, with a linear color boundary formed by a sudden change in color tone, and a directional stretching deformation of texture, and a continuous valley and a topographic steep change zone in the topography. Figure 5A Figure 5B As shown in FIG. 4, Figure 5A and Figure 5BThe northwest-southeast trending ore body is offset by F3 and F4, and the northeast-oriented ore body of the structural surface is dragged and deformed toward the southwest, which also indicates a left-lateral strike-slip nature, with a horizontal strike-slip distance of ~200m.

[0104] Figure 6A A schematic diagram of a resistivity-DEM combined three-dimensional model provided by an exemplary embodiment of the present disclosure. Figure 6B An exemplary embodiment of the present disclosure provides a schematic diagram of a three-dimensional joint cross-section of an AMT in a first direction. Figure 6C The present disclosure provides a schematic diagram of a three-dimensional joint cross section of the AMT in the second direction according to an exemplary embodiment. Figures 6A to 6C As shown in the figure, the F3 and F4 faults appear as gullies on the surface of the mining area, but the structural nature is difficult to determine due to construction and Quaternary cover. The AMT three-dimensional joint profile will once again reveal the deep structural characteristics.

[0105] like Figures 6A to 6C As shown, the southwest-oriented AMT section shows a resistivity gradient variation, with the field strength position corresponding to F3. Inversion results indicate that the deep F3 dips southeastward, with a dip angle ranging from 70° to 80°. On either side of the F3 structural surface, the low-resistivity anomaly on the hanging wall is relatively downward, while the low-resistivity anomaly on the hanging wall is relatively upward, indicating that F3 is a normal fault with a vertical displacement of approximately 200 m. Simultaneously, the northeast-oriented AMT section also indicates that F3 is a normal fault, but the structural surface dips more gently, dipping 40° to 50° southeastward. Ignoring the high-resistivity effect caused by near-surface gullies, the high-resistivity anomaly has undergone significant displacement.

[0106] Due to the length limitation of the AMT profile, resistivity inversion is difficult to determine the resistivity change in the southeast extension direction; however, an obvious low-resistivity effect appears near the surface of the F4 profile, which may correspond to a deep low-resistivity anomaly. Combined with the spatial extension and pinch-out (continuity) of the ore body and pegmatite vein, it is judged that F4 may also dip to the southeast, with a dip angle of 40 to 50° and no obvious vertical displacement.

[0107] In summary, the geological structure in the target mining area is jointly controlled by the northeast-dipping F1 and the southwest-dipping F2, and is faulted by the southeast-dipping F3 and F4 in the late mineralization stage. It shows left-hand strike-slip characteristics in the plane and normal fault properties in the section.

[0108] In some embodiments, regarding the zoning rules of pegmatite veins, since the occurrence of southern pegmatites is different from that of northern pegmatites, the spatial zoning rules of the occurrence of southern pegmatites and northern pegmatites are explained below respectively.

[0109] Figure 7A An exemplary embodiment of the present disclosure provides a schematic diagram of a three-dimensional geological structure distribution map of the F2 fault zone. Figure 7BAn F2 fracture zone geological zoning three-dimensional schematic diagram is provided by an example embodiment of the present disclosure. As shown in Figure 7A and Figure 7B As shown, for the south zone pegmatite vein group, along the F2 fracture, in the pegmatite vein spatial zoning model, different colors can be used to mark the pegmatite vein types, at this time, according to the content changes of characteristic minerals such as spodumene, muscovite and tourmaline in the pegmatite vein, from the southwest shallow part to the northeast deep part of the mining area, along the mineralization periphery to the mineralization center, the pegmatite vein group can be divided into outer, middle and inner zones.

[0110] Among them, the outer zone is distinguished by green color, characterized by poor ore, and develops tourmaline-albite-quartz, albite-quartz and other types of pegmatite veins; the middle zone is divided into yellow zones, characterized by the presence of muscovite, and develops muscovite-albite-quartz, two clouds-albite-quartz and other types of pegmatite veins; the inner zone is distinguished by pink color, characterized by the presence of spodumene, and develops spodumene-muscovite-albite-quartz, spodumene-albite-quartz, spodumene-quartz and other types of pegmatite veins. It is worth noting that the above zoning model appears abnormal in local sections, which may be related to the development of left-lateral normal faulting in the area.

[0111] Figure 7C An F1 fracture zone three-dimensional geological structure distribution diagram is provided by an example embodiment of the present disclosure. Figure 7D An F1 fracture zone geological zoning three-dimensional schematic diagram is provided by an example embodiment of the present disclosure. As shown in Figure 7C and Figure 7D As shown, the zoning sequence of tourmaline-muscovite-spodumene developed from the periphery of mineralization to the center of mineralization (quartz ± albite as a through mineral), not only consistent with the zoning sequence of tourmaline-muscovite-spodumene developed from the periphery of the southwest granite diorite body, but also consistent with the regional remote sensing mineral mapping zoning sequence, in line with the LCT type pegmatite zoning model.

[0112] As shown in Figure 7C and Figure 7D The north zone pegmatite vein group, along the F1 structure surface, from the northeast shallow part to the southwest deep part, along the periphery of mineralization to the center of mineralization, appears the same outer-middle-inner three-zone as the south vein zone, and the pegmatite zoning model of the symmetrical distribution of the north and south zones in the study area is inconsistent with the ore-forming model of the single magmatic hydrothermal source area in the southwest. Based on this, combined with the analysis of regional geological characteristics, it can be considered that the ore-forming parent magma may have intruded in the form of multiple rock stocks, forming a multi-source concurrent magmatic hydrothermal mineralization event in Dahongliantan area.

[0113] The specific supporting evidence for this argument includes:

[0114] 1. The north-west-south-east trending ore-bearing pegmatite veins in the Bailongshan area have exposed outcrops of the second mica granite (209 Ma) of the same mineralization period, proving that the ore-forming rock mass is exposed on both sides of the pegmatite veins.

[0115] 2. The complete LCT-type pegmatite zoning sequence developed in the Dahongliantan East and Akexaie areas proves that there may be a concealed rock stock in the lower part.

[0116] Figure 8A An F3 / F4 surface structure line and deep structure surface and pegmatite vein distribution relationship diagram is provided by an example embodiment of the present disclosure. Figure 8B A pegmatite vein spatial dislocation and extension feature and structure surface correlation diagram is provided by an example embodiment of the present disclosure. Figure 8C A geological anomaly body stable extension direction and spatial distribution feature diagram is provided by an example embodiment of the present disclosure. Figure 8D An F3 left slip normal fault dislocation effect on the spatial distribution of pegmatite veins diagram is provided by an example embodiment of the present disclosure. Figure 8E A pegmatite vein three-dimensional distribution and predicted location diagram under the action of faults is provided by an example embodiment of the present disclosure. As shown in Figures 8A to 8E The target mine area in the target mine area is located according to the geological structure law, pegmatite zoning law and lithium element distribution law in the target mine area.

[0117] As shown in Figures 8A to 8E For the north pegmatite vein group, the spatial distribution model of lithium element and the zoning model of pegmatite vein can be compared by the upward angle, and the pink inner zone (lithium feldspar-quartz ± muscovite ± albite) is highly consistent with the lithium element enrichment area, indicating that the inner zone pegmatite is the main ore-bearing part. F3 and F4 are expressed as gully landforms on the surface, and the structure surface cuts the pegmatite vein in the deep part, and the cut inner zone pegmatite vein presents a left step en echelon distribution (upward angle is right step en echelon), which is consistent with the F3 left-lateral strike-slip property obtained by remote sensing interpretation.

[0118] As shown in Figures 8A to 8E Deep extension docking shows that the Peg-1 ore-bearing pegmatite vein still has obvious extension in the north-east direction after being dislocated by F3 fault, and may form a complete left step en echelon distribution pattern together with Peg-2 controlled by F4. At the same time, the lithium element anomaly of pegmatite vein Peg-1 is obvious and not closed, also indicating that it is dislocated by F3, not natural pinch-out. Based on this, combined with the F3 normal fault property revealed by the resistivity three-dimensional model, it is inferred that Peg-predicted I should be located on the hanging wall of F3 and may have a certain degree of drop.

[0119] Combined with Figure 3A and Figures 8A to 8EAs shown, the drill holes marked as ZK0311 and ZK0713 only exposed the outer zone (green) pegmatite veins, and the lower part has not been effectively controlled, and the lower part has not been controlled, which may be the occurrence position of Peg prediction-I. In addition, after passing F4 in the northeast direction of the mining area, Peg-2 vein body shows good stability, and lithium anomaly characteristics are significant, and still shows great exploration potential along the occurrence direction of the ore body, that is, there is an occurrence position of Peg prediction-II along the occurrence direction of the ore body. Among them, the deep extension docking refers to the simulation and verification of the spatial extension form of the geological body (such as ore body, fault) at the deep underground by three-dimensional modeling technology.

[0120] Figure 9A An example embodiment of the present disclosure provides a schematic diagram of the correlation of F3 and F4 surface structure lines and deep structure surfaces, pegmatite vein distribution. Figure 9B An example embodiment of the present disclosure provides a schematic diagram of the correlation of the spatial dislocation extension of the inner and outer zone pegmatite veins and the structure surface and the predicted vein. Figure 9C An example embodiment of the present disclosure provides a schematic diagram of the geological anomaly closed area and the difference distribution characteristics of ore-bearing properties. Figure 9D An example embodiment of the present disclosure provides a schematic diagram of the difference distribution of pegmatite extension after F3 left slip normal faulting. Figure 9E An example embodiment of the present disclosure provides a schematic diagram of the three-dimensional distribution and prediction of pegmatite veins under the action of planar left slip-profile normal faulting. As shown in Figures 9A to 9E and Figure 3F As shown, for the south zone pegmatite vein group, the lithium element spatial distribution model corresponds well to the pegmatite vein zoning model, but the ore-bearing property is poorer than the north zone. And due to the influence of F3 left-lateral strike-slip, the inner zone pegmatite veins Peg-3 and Peg-4 show left-step en echelon distribution, which still extends in the northeast direction. Among them, Peg-4 shows better ore-bearing property, and the lithium element anomaly is obvious and not closed, so it is speculated that there may be a pegmatite vein Peg prediction-III.

[0121] As shown in Figures 9A to 9E Due to the influence of F4 left-lateral strike-slip, the outer zone (green) pegmatite veins show left-step en echelon distribution, and the prediction area may correspond to Peg-5 due to the influence of F4 left-lateral strike-slip, and Peg-4→Peg prediction-III→Peg-5 together form a left-step en echelon pattern. However, due to the influence of F3 and F4 normal faulting, the predicted ore-bearing pegmatite vein body Peg prediction-III may have a significant drop in the vertical direction, and currently this prediction position has not been controlled by drilling. In addition, two areas with significant lithium element enrichment are identified in the south zone, but the vein body continuity and extension are poor, and the lithium element anomaly gradually closes to the deep part, showing limited prospecting potential.

[0122] In summary, it can be determined that the Peg prediction-I, the Peg prediction-II and the Peg prediction-III are the ore target areas in the target mining area.

[0123] It can be seen that the embodiments of the present disclosure can improve the scientificity and accuracy of the exploration of the target mining area through the processing and analysis of the geological survey data. Meanwhile, the three-dimensional geological model constructed based on the geological survey data can visually present the complex geological structure, facilitating intuitive understanding of the stratum distribution and the ore body shape. Further, the ore-forming characteristic information can be systematically extracted, and the ore-forming geological conditions and ore-controlling factors can be accurately identified through the in-depth analysis of the three-dimensional geological model of the mining area. Finally, the ore target area is located according to the ore-forming characteristics. In this way, the exploration range can be effectively reduced, the exploration cost can be reduced, and the probability of discovering the ore body can be improved. It can be seen that compared with the traditional exploration method, the embodiments of the present disclosure can realize the whole-chain optimization from information collection to output under the data driving, and greatly improve the exploration efficiency and resource development benefit.

[0124] The above describes the scheme provided by the embodiments of the present disclosure mainly from the perspective of the server. It can be understood that the server includes the hardware structure and / or software module corresponding to the execution of each function in order to implement the above functions. Those skilled in the art should easily realize that the units and algorithm steps of each example described in combination with the embodiments disclosed herein can be realized in the form of hardware or the combination of hardware and computer software. Whether a certain function is executed in the form of hardware or computer software driven hardware depends on the specific application and design constraints of the technical solution. The skilled person can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the present disclosure.

[0125] The embodiments of the present disclosure can divide the function units of the server according to the above method examples. For example, each function module can be divided corresponding to each function, or two or more functions can be integrated in one management module. The integrated module can be realized in the form of hardware or software function module. It should be noted that the division of the modules in the embodiments of the present disclosure is illustrative, and is only a logical function division. There can be another division method when actually implemented.

[0126] In the case of dividing each function module corresponding to each function, the exemplary embodiments of the present disclosure provide an air-ground-well data mining area three-dimensional modeling and target area positioning device. The air-ground-well data mining area three-dimensional modeling and target area positioning device can be a server or a chip applied to the server. Figure 10 A structural schematic diagram of an air-ground-well data mining area three-dimensional modeling and target area positioning device provided by an embodiment of the present disclosure is shown in FIG. 1. As shown in FIG. 1, the air-ground-well data mining area three-dimensional modeling and target area positioning device can include a data acquisition module 101, a data preprocessing module 102, a three-dimensional geological modeling module 103, a target area positioning module 104 and a result output module 105. Figure 10As shown, the air-ground-well data-based mine area three-dimensional modeling and target area positioning apparatus 1000 comprises:

[0127] An acquisition module 1001 is configured to acquire geological survey data corresponding to a target mine area;

[0128] A construction module 1002 is configured to construct a mine area three-dimensional geological model corresponding to the target mine area by using the geological survey data;

[0129] A positioning module 1003 is configured to analyze the mine area three-dimensional geological model to determine ore-forming characteristic information corresponding to the target mine area, and locate a mine target area in the target mine area according to the ore-forming characteristic information.

[0130] In an optional manner, the geological survey data comprises ore body data, the acquisition module 1001 is further configured to acquire a plurality of exploration line profile data corresponding to a plurality of exploration lines in the target mine area, wherein one exploration line corresponds to one exploration line profile data; and determine the ore body data according to a plurality of the exploration line profile data.

[0131] In an optional manner, the geological survey data further comprises core data, the acquisition module 1001 is further configured to acquire a plurality of drill hole data corresponding to a plurality of drill holes on a plurality of exploration lines respectively; collect a plurality of core samples at a preset depth interval along a depth direction of the plurality of drill holes, wherein the plurality of drill holes have the same opening angle; determine core sub-data corresponding to each of the core samples according to collection position information corresponding to each of the core samples and the drill hole data corresponding to the drill holes; and determine the core data according to core sub-data corresponding to a plurality of the core samples.

[0132] In an optional manner, the geological survey data further comprises geochemical data, the acquisition module 1001 is further configured to determine geochemical sub-data corresponding to each of a plurality of the core samples; and determine the geochemical data according to the geochemical sub-data corresponding to each of the core samples.

[0133] In an optional manner, the geological survey data further comprises geophysical data and remote sensing data corresponding to the target mine area.

[0134] In an optional manner, the construction module 1002 is further configured to perform a preprocessing operation on the geological survey data, and construct a geological survey data set according to the preprocessed geological survey data; import the geological survey data set into a preset data processing platform to generate a three-dimensional format file corresponding to the geological survey data set; and construct the mine area three-dimensional geological model corresponding to the target mine area by using the three-dimensional format file.

[0135] In an optional mode, the geological survey data includes geochemical sub-data corresponding to a plurality of core samples and core sub-data corresponding to the plurality of core samples, and the construction module 1002 is further configured to, for any core sample, establish a correlation between the geochemical sub-data corresponding to the core sample and the core sub-data.

[0136] In an optional mode, the ore-forming feature information includes at least one of a geological structure rule, a pegmatite vein zoning rule, and a lithium element distribution rule in the target mining area.

[0137] The electronic device provided by the embodiment of the present disclosure includes at least one processor, a memory for storing at least one processor-executable instruction, and the processor is configured to execute the instruction to implement the steps of the above method.

[0138] Figure 11 The electronic device provided by the embodiment of the present disclosure includes at least one processor, a memory for storing at least one processor-executable instruction, and the processor is configured to execute the instruction to implement the steps of the above method. Figure 11 As shown in the structural schematic diagram of the electronic device 1100, the electronic device 1100 includes at least one processor 1101 and a memory 1102 coupled to the processor 1101, and the processor 1101 can execute the corresponding steps in the above method disclosed by the embodiment of the present disclosure.

[0139] The processor 1101 can also be called a central processing unit (CPU), which can be an integrated circuit chip with signal processing capability. Each step in the above method disclosed by the embodiment of the present disclosure can be completed by the integrated logic circuit of hardware or the instruction in the form of software in the processor 1101. The processor 1101 can be a general-purpose processor, a digital signal processor (DSP), an ASIC, a field-programmable gate array (FPGA) or other programmable logic device, a discrete gate or transistor logic device, a discrete hardware component. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor. The steps of the method disclosed in conjunction with the embodiment of the present disclosure can be directly embodied as a hardware decoding processor for execution, or a combination of hardware and software modules in the decoding processor for execution. The software module can be located in the memory 1102, such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory, an electrically erasable programmable memory, a register, and other mature storage media in the art. The processor 1101 reads the information in the memory 1102 and completes the steps of the above method in combination with the hardware thereof.

[0140] In addition, various operations / processes according to the present disclosure, in the case of being implemented by software and / or firmware, can be implemented by a computer system having a dedicated hardware structure, from a storage medium or a network, to a computer system having a dedicated hardware structure, for example, Figure 12 The computer system 1200 shown is intended to Figure 12 A structural schematic diagram of a computer system provided for an embodiment of the present disclosure.

[0141] The computer system 1200 is intended to represent various forms of digital electronic computer devices, such as laptops, desktops, tablets, personal digital assistants, servers, blade servers, mainframes, and other appropriate computer devices. Electronic devices can also represent various forms of mobile devices, such as personal digital assistants, cellular telephones, smart phones, wearable devices, and other similar computing devices. The components shown here, their connections and relationships, and their functions, are meant to be examples only, and are not intended to limit implementations of the present disclosure described and / or claimed in this document.

[0142] As shown, Figure 12 The computer system 1200 includes a computing unit 1201 that can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 1202 or a computer program loaded from a storage unit 1208 into a random access memory (RAM) 1203. In the RAM 1203, various programs and data required for the operation of the computer system 1200 can also be stored. The computing unit 1201, the ROM 1202, and the RAM 1203 are connected to each other through a bus 1204. An input / output (I / O) interface 1205 is also connected to the bus 1204.

[0143] Multiple components within computer system 1200 are connected to I / O interface 1205, including an input unit 1206, an output unit 1207, a storage unit 1208, and a communication unit 1209. Input unit 1206 can be any type of device capable of inputting information into computer system 1200. Input unit 1206 can receive input numeric or character information and generate key input signals related to user settings and / or function control of an electronic device. Output unit 1207 can be any type of device capable of presenting information and may include, but is not limited to, a display, a speaker, a video / audio output terminal, a vibrator, and / or a printer. Storage unit 1208 may include, but is not limited to, a magnetic disk or an optical disk. Communication unit 1209 allows computer system 1200 to exchange information / data with other devices over a network, such as the Internet, and may include, but is not limited to, a modem, a network card, an infrared communication device, a wireless communication transceiver and / or chipset, such as a Bluetooth™ device, a WiFi device, a WiMax device, a cellular communication device, and / or the like.

[0144] The computing unit 1201 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the computing unit 1201 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various computing units that run machine learning model algorithms, digital signal processors (DSPs), and any appropriate processors, controllers, microcontrollers, etc. The computing unit 1201 performs the various methods and processes described above. For example, in some embodiments, the above-mentioned method disclosed in the embodiments of the present disclosure may be implemented as a computer software program, which is tangibly included in a machine-readable medium, such as a storage unit 1208. In some embodiments, part or all of the computer program may be loaded and / or installed on an electronic device via ROM 1202 and / or communication unit 1209. In some embodiments, the computing unit 801 may be configured to perform the above-mentioned method disclosed in the embodiments of the present disclosure by any other appropriate means (e.g., by means of firmware).

[0145] An embodiment of the present disclosure further provides a computer-readable storage medium, wherein when instructions in the computer-readable storage medium are executed by a processor of an electronic device, the electronic device is enabled to execute the above method disclosed in the embodiment of the present disclosure.

[0146] The computer-readable storage medium in the embodiments of the present disclosure can be a tangible medium that can contain or store a program for use by an instruction execution system, device or equipment or used in combination with an instruction execution system, device or equipment. The above-mentioned computer-readable storage medium can include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the above. More specifically, the above-mentioned computer-readable storage medium can include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above.

[0147] The computer-readable medium may be included in the electronic device, or may exist independently without being incorporated into the electronic device.

[0148] Figure 13 Schematic diagram of a computer program product provided by an embodiment of the present disclosure. Figure 13 As shown, the computer program product 1300 includes a computer program 1301 , wherein the computer program 1301 implements the above method disclosed in the embodiment of the present disclosure when executed by a processor.

[0149] In embodiments of the present disclosure, computer program code for performing the operations of the present disclosure may be written in one or more programming languages ​​or combinations thereof, including but not limited to object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer.

[0150] The flow diagrams and the block diagrams in the drawings are illustrations of architectures, functionalities, and operations of possible implementations of systems, methods, and computer program products according to various embodiments of present disclosure. In this regard, each block in the flow diagrams or block diagrams can represent a module, a segment, or a portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that in some alternative implementations, the functions noted in the block can occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and / or flow diagrams, and combinations thereof, can be implemented by special purpose hardware-based systems that perform the specified functions or operations, or combinations of special purpose hardware and computer instructions.

[0151] The modules, components or units described in the embodiments of the present disclosure can be implemented by software or by hardware. In some cases, the name of the module, component or unit does not constitute a limitation on the module, component or unit itself.

[0152] The functions described above can be performed by one or more hardware logic components. For example, non-limiting examples of hardware logic components that can be used include field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), system-on-a-chip (SOCs), complex programmable logic devices (CPLDs), etc.

[0153] The above description is merely some embodiments of the present disclosure and a description of principles of technology used. Those skilled in the art should understand that the disclosed scope of the present disclosure is not limited to the technical solutions formed by the specific combinations of the above technical features, and should also cover other technical solutions formed by any combinations of the above technical features or equivalent features without departing from the above disclosed concept. For example, technical solutions formed by replacing the above features with technical features disclosed in the present disclosure (but not limited to) having similar functions.

[0154] Although some specific embodiments of the present disclosure have been described in detail by way of examples, those skilled in the art should understand that the above examples are only for illustration, and are not intended to limit the scope of the present disclosure. Those skilled in the art should understand that the above embodiments can be modified without departing from the scope and spirit of the present disclosure. The scope of the present disclosure is defined by the appended claims.

Claims

1. A method for three-dimensional modeling and target location of a mining area based on air-ground-well data, characterized in that: include: Obtain geological survey data corresponding to the target mining area; constructing a three-dimensional geological model of the mining area corresponding to the target mining area using the geological survey data; The three-dimensional geological model of the mining area is analyzed to determine the metallogenic characteristic information corresponding to the target mining area, and the target area of ​​the target mining area is located according to the metallogenic characteristic information.

2. The method according to claim 1, characterized in that The geological survey data includes ore body data, and the geological survey data corresponding to the target mining area is obtained, including: Acquire a plurality of exploration line profile data corresponding to a plurality of exploration lines in the target mining area, wherein one exploration line corresponds to one piece of exploration line profile data; The ore body data is determined based on a plurality of the exploration line profile data.

3. The method according to claim 2, characterized in that The geological survey data also includes core data, and the geological survey data corresponding to the target mining area is obtained, including: respectively acquiring a plurality of drilling data corresponding to a plurality of drilling holes on a plurality of the exploration lines; Collecting multiple core samples along the depth direction of the multiple boreholes at preset depth intervals, wherein the multiple boreholes have the same opening angle; Determining the core sub-data corresponding to each core sample according to the collection position information corresponding to each core sample and the drilling data corresponding to the borehole; The core data is determined based on the core sub-data corresponding to the plurality of core samples.

4. The method according to claim 3, characterized in that The geological survey data also includes geochemical data. The geological survey data corresponding to the target mining area is obtained, including: Determining geochemical sub-data corresponding to each of the plurality of core samples; The geochemical data is determined according to the geochemical sub-data corresponding to each core sample.

5. The method according to claim 1, wherein The geological survey data also includes geophysical data and remote sensing data corresponding to the target mining area.

6. The method according to claim 1, characterized in that The method of constructing a three-dimensional geological model of a mining area corresponding to the target mining area using the geological survey data includes: performing a preprocessing operation on the geological survey data, and constructing a geological survey data set based on the preprocessed geological survey data; Importing the geological survey data set into a preset data processing platform to generate a three-dimensional format file corresponding to the geological survey data set; The three-dimensional format file is used to construct a three-dimensional geological model of the mining area corresponding to the target mining area.

7. The method according to claim 6, characterized in that The geological survey data includes geochemical sub-data corresponding to a plurality of core samples and core sub-data corresponding to a plurality of the core samples. The pre-processing operation on the geological survey data includes: For any core sample, an association relationship between the geochemical sub-data and the core sub-data corresponding to the core sample is established.

8. The method according to claim 1, characterized in that The mineralization characteristic information includes at least one of the geological structure law, the pegmatite vein zoning law and the element distribution law in the target mining area.

9. A mining area three-dimensional modeling and target area positioning device based on air-ground-well data, characterized in that: include: An acquisition module is used to obtain geological survey data corresponding to the target mining area; A construction module, configured to construct a three-dimensional geological model of a mining area corresponding to the target mining area using the geological survey data; The positioning module is used to analyze the three-dimensional geological model of the mining area to determine the metallogenic characteristic information corresponding to the target mining area, and locate the mineral target area in the target mining area according to the metallogenic characteristic information.

10. A computer program product comprising a computer program / instructions, characterized in that When the computer program / instruction is executed by a processor, the steps of the method according to any one of claims 1 to 8 are implemented.

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