A method, system, device and medium for metallogenic prediction based on the relationship between alteration structure and spatial gamma field

Abstract

This invention discloses a method, system, equipment, and medium for mineralization prediction based on the relationship between alteration structures and spatial gamma fields, relating to the field of metal ore detection technology. The method includes: acquiring target geological data; locating the ore body based on the delineation of the ore body on borehole profiles, and then constructing spatially independent or continuous multi-view maps in three-dimensional space along the corresponding structural alteration zone to obtain an ore body model; preprocessing borehole gamma logging data and borehole spatial data, and constructing a spatial gamma field model based on the preprocessed data; combining spatial gamma field models of different levels with the ore body model in profile, and determining the relationship between alteration structures and spatial gamma fields based on the combination within different survey areas; analyzing the rock mass distribution of the target ore using the relationship between alteration structures and spatial gamma fields, and delineating the final location of the target ore. This invention can predict favorable mineralization locations based on the relationship between alteration structures and spatial gamma fields.

Description

Technical Field

[0001] This invention relates to the field of metal ore detection technology, and in particular to a method, system, equipment and medium for predicting mineralization based on the relationship between alteration structures and spatial gamma fields. Background Technology

[0002] In the fields of geological exploration and mineral resource assessment, traditional geological modeling and ore body prediction methods mainly rely on two-dimensional geological maps and borehole data. These methods have limitations when dealing with complex geological structures and multi-source data. With the development of computer technology, three-dimensional geological modeling and spatial data analysis techniques have gradually become important tools in geological research. These techniques can more intuitively display the spatial relationships of geological bodies and improve the accuracy of ore body prediction.

[0003] Existing technologies have the following shortcomings when predicting ore bodies under complex geological conditions:

[0004] First, traditional geological modeling methods struggle to effectively integrate multi-source geological data, resulting in limited model accuracy. Second, existing spatial gamma-ray field models are mostly of a single type, failing to comprehensively reflect the spatial characteristics of ore bodies. Finally, quantitative three-dimensional spatial analysis is lacking regarding the spatial distribution characteristics of current ore deposits and their relationship with geological structures. Summary of the Invention

[0005] The purpose of this invention is to provide a mineralization prediction method, system, equipment and medium based on the relationship between alteration structure and spatial gamma field, which can perform spatial modeling of various geological bodies according to the data requirements of different geological objects, and predict favorable mineralization locations based on the relationship between alteration structure and spatial gamma field.

[0006] To achieve the above objectives, the present invention provides the following solution:

[0007] A mineralization prediction method based on the relationship between alteration structures and spatial gamma fields includes:

[0008] Acquire target geological data; the target geological data includes borehole profiles, borehole gamma logging data, and borehole spatial data;

[0009] Based on the location of the ore body delineated in the borehole profile, a spatially independent or continuous multi-faceted map is constructed in three-dimensional space along the corresponding structural alteration zone to obtain the ore body model.

[0010] The borehole gamma logging data and the borehole spatial data are preprocessed, and a spatial gamma field model is constructed based on the preprocessed data; the spatial gamma field model includes a spatial gamma high field model, a spatial gamma high field model, and a spatial gamma anomaly field model.

[0011] Different levels of spatial gamma field models are combined with the ore body model in profile, and the relationship between alteration structure and spatial gamma field is determined according to the combination situation in different survey areas.

[0012] The rock mass distribution of the target ore is analyzed by utilizing the relationship between the alteration structure and the spatial gamma field, and the final location of the target ore is delineated.

[0013] Optionally, the borehole gamma logging data and the borehole spatial data are preprocessed, and a spatial gamma field model is constructed based on the preprocessed data, specifically including:

[0014] The borehole gamma logging data is subjected to a set iterative rejection process, and the average value and root mean square error of the processed data are calculated. The intensity level of the spatial gamma field is determined based on the calculation results. The intensity level includes high field, high field and anomalous field.

[0015] Based on the borehole spatial data, spatial isometry calculations and mapping are performed using 3D modeling software, and the data is then processed in layers according to intensity levels to obtain spatial gamma high field model, spatial gamma high field model, and spatial gamma anomaly field model.

[0016] Optionally, before constructing the ore body model and the spatial gamma field model, the method further includes: constructing a spatial database; the spatial database is used to provide data services for spatial modeling.

[0017] Optionally, the construction requirements of the spatial database include: data input, data management, data processing, and data output; wherein, the data input includes the acquisition and input of well logging data, the acquisition and input of directional logging data, and the acquisition and input of logging data; the data management includes borehole management, project management, and user management; the data processing includes data preprocessing, well logging content calculation, well logging data statistics, well logging data mapping, and spatial coordinate calculation; and the data output includes well logging results output, well logging report output, and spatial data output.

[0018] Optionally, the system structure of the spatial database includes a surveying module, a well logging module, a logging module, a sampling module, and an instrument management module; wherein, the surveying module is used to store and manage surveying data from each borehole, and generate borehole spatial data by combining borehole coordinate data and well logging data; the well logging module is used to store and manage well logging data, and perform data preprocessing, content calculation, and generate well logging results; the logging module is used to store and manage borehole logging data and sampling analysis data to assist in result analysis; and the instrument management module is used to store and manage various instrument parameter data.

[0019] This invention also provides a mineralization prediction system based on the relationship between alteration structures and spatial gamma fields, comprising:

[0020] The data acquisition unit is used to acquire target geological data, including borehole profiles, borehole gamma logging data, and borehole spatial data.

[0021] The ore body model construction unit is used to locate the ore body based on the ore body delineation position of the borehole profile, and then construct a spatially independent or continuous spatial multi-faceted map in three-dimensional space along the corresponding structural alteration zone to obtain the ore body model.

[0022] The spatial gamma field model construction unit is used to preprocess the borehole gamma logging data and the borehole spatial data, and to construct a spatial gamma field model based on the preprocessed data; the spatial gamma field model includes a spatial gamma high field model, a spatial gamma high field model, and a spatial gamma anomaly field model.

[0023] The correlation analysis unit is used to combine spatial gamma field models of different levels with the ore body model in profile, and determine the relationship between alteration structure and spatial gamma field according to the combination situation in different survey areas.

[0024] The target ore delineation unit is used to analyze the rock mass distribution of the target ore by utilizing the relationship between the alteration structure and the spatial gamma field, and to delineate the final location of the target ore.

[0025] The present invention also provides an electronic device, including a memory and a processor, wherein the memory is used to store a computer program, and the processor runs the computer program to enable the electronic device to perform the mineralization prediction method based on the above-described relationship between alteration structure and spatial gamma field.

[0026] The present invention also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the mineralization prediction method based on the relationship between alteration structures and spatial gamma fields as described above.

[0027] According to specific embodiments provided by the present invention, the present invention discloses the following technical effects:

[0028] This invention discloses a method, system, equipment, and medium for mineralization prediction based on the relationship between alteration structures and spatial gamma-ray fields. The method includes acquiring target geological data; locating the ore body based on the delineation of the ore body position on borehole profiles; constructing spatially independent or continuous multi-view maps in three-dimensional space along the corresponding structural alteration zone to obtain an ore body model; preprocessing borehole gamma-ray logging data and borehole spatial data, and constructing a spatial gamma-ray field model based on the preprocessed data; combining spatial gamma-ray field models of different levels with the ore body model in profile, and determining the relationship between alteration structures and spatial gamma-ray fields based on the combination within different survey areas; analyzing the rock mass distribution of the target ore using the relationship between alteration structures and spatial gamma-ray fields, and delineating the final location of the target ore. This invention can perform spatial modeling of various geological bodies according to the data requirements of different geological objects, and predict favorable mineralization locations based on the relationship between alteration structures and spatial gamma-ray fields. Attached Figure Description

[0029] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0030] Figure 1 This is a structural design diagram of the geophysical database system in this embodiment;

[0031] Figure 2 This is a structural design diagram of the spatial database system in this embodiment;

[0032] Figure 3 This embodiment provides a flowchart for the database-supported modeling software to generate a 3D integrated model.

[0033] Figure 4 This is a diagram showing the relationship between alteration type and uranium ore grade in this embodiment;

[0034] Figure 5 This is a flowchart illustrating the mineralization prediction method based on the relationship between alteration structures and spatial gamma fields in this embodiment. Detailed Implementation

[0035] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0036] The purpose of this invention is to provide a mineralization prediction method, system, equipment and medium based on the relationship between alteration structure and spatial gamma field, which can perform spatial modeling of various geological bodies according to the data requirements of different geological objects, and predict favorable mineralization locations based on the relationship between alteration structure and spatial gamma field.

[0037] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0038] like Figures 1-5 As shown, this invention provides a mineralization prediction method based on the relationship between alteration structures and spatial gamma fields, comprising:

[0039] Step 100: Obtain target geological data; the target geological data includes borehole profile, borehole gamma logging data, and borehole spatial data.

[0040] Step 200: Locate the ore body based on the borehole profile, and then construct a spatially independent or continuous multi-faceted map in three-dimensional space along the corresponding structural alteration zone to obtain the ore body model.

[0041] Step 300: Preprocess the borehole gamma logging data and the borehole spatial data, and construct a spatial gamma field model based on the preprocessed data; the spatial gamma field model includes a spatial gamma high field model, a spatial gamma high field model, and a spatial gamma anomaly field model.

[0042] Step 400: Combine the spatial gamma field models of different levels with the ore body model in profile, and determine the relationship between alteration structure and spatial gamma field according to the combination situation in different survey areas.

[0043] Step 500: Analyze the rock mass distribution of the target ore by using the relationship between the alteration structure and the spatial gamma field, and delineate the final location of the target ore.

[0044] As a specific implementation method, a detailed processing procedure for each of the above steps is provided.

[0045] First, regarding the research approach: systematically collect borehole data, engineering survey data, geophysical data, etc. in the work area, and input them into the spatial database to form a spatial data set according to the modeling requirements. Based on the data requirements of different geological bodies, perform spatial modeling of various geological bodies, and then analyze the spatial distribution characteristics of uranium ore elements and their relationship with structure, alteration, lithological interfaces, etc., summarize the rules, and predict favorable mineralization locations.

[0046] Secondly, regarding the research content: the research content is mainly divided into three parts: spatial database construction, spatial model construction, and spatial model analysis.

[0047] (1) Main contents of spatial database research:

[0048] ① Design reasonable and scientific data tables to store various data; ② Design workflows suitable for work needs to facilitate data entry, storage, and processing; ③ Design relevant functional models to help data be collected, organized, calculated, converted, and output quickly and automatically; ④ Design intuitive and convenient operation interfaces to serve various operations.

[0049] (2) Main research contents of spatial model construction:

[0050] ① Scientific classification based on the nature, properties, and uses of geological bodies; ② Rapid and accurate modeling with the help of spatial databases; ③ 3D construction of different types of models; ④ Model integration between different platforms.

[0051] (3) Main research contents of spatial model analysis:

[0052] ① Observation and analysis of spatial characteristics of spatial models; ② Analysis and summary of the interrelationships between spatial models; ③ Prediction of favorable mineralization areas; ④ Production of spatial model result maps.

[0053] Finally, regarding the research methodology:

[0054] (1) The spatial database was compiled using Access+Vb.net in conjunction with the analysis of work requirements and reference to other geographic information databases.

[0055] (2) Spatial models are created using software such as 3Dmax, Autocad, and Surpac, and spatial models created by different software are integrated into the same working platform for inspection and analysis.

[0056] (3) Spatial model analysis uses mathematical statistics, combination, projection, and cross-section to conduct spatial comparison and observation, and combines the mineralization theory of granite-type uranium deposits to summarize the mineralization characteristics of uranium and predict favorable mineralization areas.

[0057] During the project implementation, VB.NET programming was first used to build a spatial database for storing and managing information such as borehole data, geophysical data, and measurement data. Then, relevant professional software was fully utilized to model related geological bodies. For example, Gocad's surface interpolation technology DSI (Discrete Smooth Interpolation) was used to interpolate and connect spatial structures and lithological interfaces. Voxler was used to calculate and draw spatial isosurfaces of gamma fields and alteration halos. Surpac was used to delineate spatial ore bodies and manage spatial data. Finally, the spatial model bodies were integrated and edited in 3ds Max.

[0058] Through the above work, models such as spatial tectonic model, spatial alteration model, spatial rock mass model, spatial gamma field model, spatial borehole model, three-dimensional terrain model, and survey network were completed. The spatial models were observed and compared from multiple angles. The distribution characteristics of the spatial gamma field and its relationship with the spatial tectonic model, spatial alteration model, and spatial rock mass model were summarized. Based on the distribution characteristics of the spatial gamma field, the tectonic distribution characteristics, and the alteration halo variation characteristics, the favorable mineralization areas in the working area were predicted.

[0059] Work practice has proven that the combination of database technology and 3D modeling technology has enhanced the ability to process large amounts of data, accelerated data processing speed, improved the presentation methods of geological research, and enhanced information integration capabilities, making a valuable contribution to deep mineral exploration research.

[0060] As another specific implementation method, spatial databases are mainly used to increase data storage capacity, facilitate data management, and provide data services for spatial modeling.

[0061] Spatial Database Requirements Analysis and Design Objectives:

[0062] In practical work, data processing mainly falls into four categories: data input, data management, data processing, and data output. The specific tasks are as follows: Figure 1 .

[0063] Data input tasks include: well logging data acquisition and input, directional logging data acquisition and input, and logging data acquisition and input; data management tasks include: borehole management, project management, and user management; data processing tasks include: data preprocessing, well logging content calculation, well logging data statistics, well logging data mapping, and spatial coordinate calculation; data output tasks include: well logging results output, well logging report output, and spatial data output.

[0064] The purpose of building a spatial database is mainly to serve the spatial modeling of geological bodies in the long-row work area, enabling rapid data collection, storage, management, processing, spatial data calculation, and output of results.

[0065] Spatial database system architecture design:

[0066] Based on the work requirements analysis, and with the goal of spatial modeling of geological bodies in the work area, a database system structure was designed according to existing conditions, such as... Figure 2 As shown.

[0067] The database system is mainly divided into five parts: inclination measurement module, well logging, logging, sampling and instrument management.

[0068] The inclination measurement section primarily stores and manages inclination measurement data from each borehole. Combined with borehole coordinate data and well logging data, it generates borehole spatial data, preparing for spatial modeling. The well logging section mainly stores and manages well logging data, performing preprocessing, content calculation, and generating well logging results. Well logging results can be appended to the borehole spatial data, providing uranium distribution information for the borehole spatial model. The logging and sampling section primarily stores and manages borehole logging data and sampling analysis data, aiding in results analysis. The instrumentation section primarily stores and manages various instrument parameter data, facilitating well logging content calculation and quality assessment.

[0069] Preparation of borehole radioactivity logging data:

[0070] The data on radioactive content in borehole logging needs to be statistically analyzed and classified in preparation for work such as space gamma field modeling.

[0071] The gamma irradiance of various rocks is related to lithology and ore-bearing tectonic alteration zones. In the center of these alteration zones, silicified breccia, hematized silicified breccia, breccia granite, silicified breccia granite, silicified hematized breccia granite, and sericitized silicified breccia granite have high gamma irradiance and are the main ore-bearing lithologies. On either side of the alteration zones, sericitized biotite granite, sericitized hematized biotite granite, and sericitized biotite granite have relatively high gamma irradiance. Normal surrounding rocks such as biotite granite and two-mica granite have relatively low gamma irradiance. Statistical analysis of gamma logging data shows a wide range of gamma irradiance variations and large standard deviations for various lithologies, reflecting frequent hydrothermal activity in the area. After hydrothermal alteration, uranium in the rocks is activated, modified, migrated, and redistributed, and then re-enriched under specific geochemical conditions, resulting in a highly uneven distribution of gamma irradiance.

[0072] The spatial data processing module of the spatial database can perform format rules, error checking and correction, iterative elimination, mathematical statistics and classification, and borehole spatial coordinate attribute assignment on radioactive well logging data to obtain data suitable for spatial modeling. Then, it can be grouped and classified according to different structural alteration zone control areas to construct independent models such as structural alteration zone No. 61, structural alteration zone No. 60, and structural alteration zone No. 9. Finally, it can be integrated into the same platform for comprehensive observation and comparative research.

[0073] Space model creation:

[0074] Different modeling software offers different modeling functions. For example, MapGIS and ArcGIS software can be used to easily edit and analyze basic geographic and geological features of the Earth's surface; 3ds Max software can be used for spatial extraction of geological profiles and editing of the spatial locations of geological elements; Surpac software can be used for spatial connection and 3D mapping of structural profiles, ore body profiles, and rock mass distributions, and supports spatial database management; Voxler software can generate 3D isosurface models of spatial gamma fields based on uranium element distribution and density levels. Combining relevant modeling software and using database support, the workflow for generating a comprehensive spatial model using 3D modeling software is as follows: Figure 3 .

[0075] The specific process is as follows: First, the geological profile map and plan view of the working area are placed and spliced ​​in three-dimensional space according to their positional relationship. Then, relevant structural and ore body profile elements are extracted and classified according to the rules and attributes such as the spatial location of the elements, the range of influence, and the spatial distribution trend of the geological bodies. The profile classification is then connected into a surface model through operations such as spatial connection, splicing, tracing, and interpolation. After node optimization and solidification, it is presented as a solid model of structure, ore body, alteration distribution, etc.

[0076] Spatial model results

[0077] Drilling model:

[0078] With the support of a spatial database, spatial models of 105 boreholes in the work area were created using 3D software. These borehole spatial models can display the spatial distribution and morphology of the boreholes, and can show the borehole number at the top of each model column. They can also display lithological stratification patterns, logging curves, logging content, and other information on or beside each model column, facilitating spatial observation and inspection of borehole data, as well as comparison with other geological body models. This allows for the assessment of the effectiveness of borehole detection locations and the spatial control over other geological bodies.

[0079] Each borehole model column can be accompanied by information such as lithological stratification, logging content, and alteration type, depending on the depth. This information can provide the spatial data required for modeling and calculation of the next step, such as spatial gamma field, spatial rock mass model, and spatial alteration model.

[0080] Model construction:

[0081] The structural model of the working area is mainly based on structural belts 61, 60, and 9, as well as secondary structural belts 8 and 52. Among them, structural alteration belt 60 is mainly controlled by the western area survey network, structural alteration belt 61 is mainly controlled by the central area survey network, and structural alteration belts 8, 9, and 52 are controlled by the eastern area survey network.

[0082] The spatial model of alteration zone No. 61 shows the following morphological characteristics: it generally extends stably along the strike and dip, with local branching, compositing, and twisting phenomena, exhibiting extensional tectonic properties during the mineralization stage. Secondary zones are also distributed on both sides of alteration zone No. 61, which may be favorable for mineralization.

[0083] In terms of spatial morphology, alteration zone No. 60 is generally distributed in a north-south direction, dips eastward, and may intersect with alteration zone No. 61 at a deeper level.

[0084] The morphological distribution of alteration zones No. 8, 9, and 52 is quite complex and varied, exhibiting extensional and torsional characteristics. These three alteration zones are distributed approximately parallel to each other in a north-northwest direction, with alteration zone No. 9 in the middle, bordered by alteration zone No. 8 to its west and alteration zone No. 52 to its east. There may be concealed secondary zones between these two alteration zones. All three alteration zones generally dip northeastward.

[0085] Alteration model:

[0086] The alteration space model of the working area is generally similar in distribution to the spatial structure model. Its range gradually expands with increasing depth and exhibits characteristics of branching, compounding, expansion and contraction.

[0087] The mineralization period within the zone was marked by intense hydrothermal activity, with common alterations closely related to uranium mineralization, including silicification, hematization, purplish-black fluoritization, sericitization, calcite alteration, and chloritization. Horizontally, these alterations exhibit zoning characteristics, progressing from the center of the tectonic zone outwards as follows: silicification → hematization → sericitization → chloritization → kaolinization. Post-mineralization hydrothermal activity was also significant, with banded fluorite-quartz veins observed, cementing breccia from the mineralization period, indicating a pronounced extensional tectonic activity in the later stages of mineralization.

[0088] To reflect the relationship between different alterations and uranium ore grades, borehole data on the ore-bearing lithology and well logging information of alteration zones 61, 60, and 9 were statistically analyzed. A graph showing the relationship between alteration type and uranium ore grade was created, as follows: Figure 4 As shown. From Figure 4 It is evident that silicification and purplish-black fluorite mineralization alteration are often associated with high-grade uranium ore, followed by hematite mineralization, while sericitization and chloritization are associated with abnormally high-grade uranium ore.

[0089] To reflect the spatial distribution of alteration, the alteration points distributed along the borehole model were assigned artificial digital values ​​based on the contribution of alteration type to uranium mineralization so that spatial calculations could be performed. The numerical values ​​corresponding to the alteration types are shown in Table 1. Then, an alteration spatial isosurface model was created using spatial isosurface calculations.

[0090] Table 1 Spatial Calculation Assignment Table of Alteration Types in the Yangtze Mineral Cluster Area

[0091]

[0092] Ore body model:

[0093] The ore body model is located based on the ore body delineation position on the borehole profile, and then a spatially independent or continuous spatial polyhedron is constructed in three-dimensional space along the corresponding structural alteration zone.

[0094] On the plane, the distribution of red-grade ore bodies is significantly less and more concentrated compared to blue-grade ore bodies. In the western survey area, they are distributed within alteration zone 60; in the central survey area, they appear in tectonic alteration zone 7; and in the eastern survey area, they are more densely distributed, possibly related to the large number of control boreholes in that area.

[0095] From the cross-sectional diagram, the vertical depth of the red-grade ore body ranges from -200 to 600 meters; overall, the ore body exhibits a northward sloping characteristic.

[0096] Spatial gamma field model:

[0097] Uranium, initially dispersed underground, undergoes complex physical and chemical processes, migrating towards specific spatial locations. Over a considerable period, it accumulates in favorable geological environments. The portion meeting industrial standards becomes ore body, while the portion not meeting these standards forms a radioactive halo. This halo envelops the ore body, its area significantly larger than the ore body, and its intensity gradually weakens with increasing diffusion distance. Therefore, locating radioactive halos can be used to trace and guide mineral exploration. Furthermore, the halo's much larger area compared to the ore body makes it easier to detect, reducing the difficulty of mineral exploration and possessing significant practical value.

[0098] The spatial gamma field model can simulate the distribution intensity and morphology of mineral halos underground. After iteratively filtering the borehole gamma logging data, the average value and standard deviation were calculated. Then, the spatial gamma field was divided into high-intensity field, high-intensity field, and anomalous field according to the intensity level (Table 2), providing a basis for the layering of 3D modeling.

[0099] Table 2. Spatial Gamma Field Division Table

[0100]

[0101] After importing the borehole spatial data into 3D modeling software, spatial isometry calculations and mapping are performed, and the data is layered according to intensity level to create spatial gamma high field, spatial gamma high field, and spatial gamma anomaly field models respectively.

[0102] Radioactive halos are concentrated in large quantities in the deep northern part of the central survey area, and there are also halos in the shallow part. They are relatively continuous but thinner and more dispersed, indicating that uranium has a tendency to diffuse from deep to shallow. In the western survey area, radioactive halos are mainly distributed in the southern part of the survey area and are vertically continuous, with some scattered distribution in the central part. In the eastern survey area, the distribution of radioactive halos is more dispersed, which should be due to the large number of tectonic intersections in this area.

[0103] To observe the distribution characteristics of the gamma field in the underground space of the work area as a whole, multiple horizontal cross-sections can be superimposed and integrated into a single cross-sectional view for overall information observation; similarly, vertical cross-sections can be made on the model, and multiple vertical cross-sections can be superimposed and merged into a single cross-sectional overlay view.

[0104] Spatial model analysis

[0105] Relationship between spatial gamma field and tectonic structure:

[0106] By combining spatial gamma field models and spatial tectonic models of different levels, it can be shown that the high field, high field and anomalous field of the spatial gamma field in the western survey area are all distributed at the intersection of tectonic alteration zone 60 and tectonic alteration zone 61, indicating that uranium elements accumulate at the intersection of the two tectonic zones.

[0107] In the central survey area, the large-scale continuous accumulation of space gamma field halos in the alteration zone of tectonic 61 indicates a favorable uranium mineralization environment in this section.

[0108] The spatial gamma field in the eastern survey area is relatively dispersed, mainly distributed in the deep intersection of the No. 8 and No. 9 tectonic alteration structures, reflecting a favorable mineralization environment.

[0109] Relationship between spatial gamma field and alteration:

[0110] By overlaying the profiles of the gamma field model and the spatial alteration halo model, it can be seen that the gamma field and alteration halo are closely related in the central and western survey areas, while the gamma field and alteration halo are relatively discrete in the eastern survey area.

[0111] By superimposing different levels of gamma fields and alteration halo models on a single plane, the overall distribution of alteration halos is approximately parallel to the structural trend and is strictly controlled by the structural attitude.

[0112] The overlap between the alteration halo and the space gamma field in the western survey area indicates a close relationship between uranium mineralization and alteration in this region.

[0113] The central survey area has a high-intensity halo distribution, which corresponds to the gamma anomaly field; and the halo distribution corresponds to the intersection of zone 61 and zone 78, indicating that the area has good mineral exploration potential.

[0114] In the eastern survey area, alteration halos are less distributed on alteration zone 8, and are mainly distributed in a discrete state along alteration zones 9 and 52, with strong alteration halos. There are corresponding space gamma anomaly fields, but they are separated at the corresponding positions, indicating that the tectonic distortion in alteration zone 9 is large and the uranium element migration activity is strong.

[0115] Relationship between gamma field and rock mass:

[0116] Different levels of spatial gamma fields and rock mass models are presented in cross-sectional combination, and observed separately in different survey areas. Due to perspective, rock masses that are not closely related to the gamma field or that obstruct the view are hidden to facilitate observation.

[0117] Lamprey veins are distributed in the northern part of the survey area, with surface widths reaching up to 20 meters. The presence of high and low spatial gamma fields correlates with these veins, indicating that the chemical barrier formed by the basic dikes contributes to uranium enrichment.

[0118] The rock mass in this area generally dips northward, and the spatial gamma field also shows a distribution trend of gradually sinking northward, indicating that the spatial gamma field is related to the spatial distribution of different rock masses.

[0119] The spatial gamma-ray fields are mostly distributed within the biotite granite intrusion body, indicating that the biotite granite makes a significant contribution to uranium mineralization and controls the distribution of the ore body. The biotite intrusion body is relatively continuous, and the spatial gamma-ray fields also exhibit a continuous distribution characteristic.

[0120] In terms of depth, above the 0m elevation, at the interface of biotite granite of different grain sizes, there are distributions of high spatial gamma fields and high spatial gamma fields, indicating that shallow uranium elements are easily enriched at the lithological interface due to lithological changes, and the mineralization regularity at the lithological interface is obvious.

[0121] Below the 0m elevation, the spatial gamma field is mainly found within the biotite granite intrusion body, and is located far from the interface between the biotite granite and other lithologies. Simultaneously, the size and grade of the spatial gamma field increase. This indicates that with increasing depth, the distribution of uranium is more significantly influenced by the distribution of the medium-grained biotite intrusion body and tectonic activity. The biotite granite is a uranium-rich intrusion body, providing abundant uranium sources for deep uranium mineralization. The intense and large-scale deep tectonic activity provides a larger mineralization space for uranium enrichment and brings deep uranium-rich hydrothermal fluids, creating favorable conditions for the formation of large-scale, high-grade uranium ore bodies.

[0122] (2) Relationship between spatial gamma field and rock mass distribution in western survey area

[0123] The rock mass in this area generally dips northward, and the spatial gamma field also shows a northward-sinking distribution trend. This indicates that the spatial gamma field is related to the distribution of different rock masses.

[0124] Spatial gamma fields are predominantly distributed within biotite granite intrusion bodies, indicating that the grainy biotite granite contributes significantly to uranium mineralization and controls the distribution of the ore bodies. The biotite granite intrusion bodies are relatively continuous, and the spatial gamma fields also exhibit a continuous distribution pattern.

[0125] In terms of depth, also above the 0m elevation, there are distributions of higher and higher spatial gamma fields at the contact interfaces of biotite granites of different grain sizes, indicating that shallow uranium elements have a mineralization pattern at lithological interfaces.

[0126] Below the 0m elevation, the spatial gamma field mainly appears in the biotite granite intrusion body and is far from the contact interface between the biotite granite and other lithologies, indicating that the deep biotite intrusion body can provide a richer uranium source for uranium mineralization and has the potential for large-scale mineralization under conditions such as tectonic movement and alteration.

[0127] However, the scale of alteration zone No. 60 is not as large as that of alteration zone No. 61, so the scale of mineralization is not as large as that of alteration zone No. 61, and the corresponding scale of spatial gamma field distribution is also relatively small.

[0128] (3) Relationship between spatial gamma field and rock mass in the eastern survey area

[0129] The rock mass in this area generally dips northeast, and the spatial gamma field is relatively dispersed, showing less influence from the rock mass's attitude. However, it still exhibits the characteristic of spatial gamma fields easily appearing at lithological contact interfaces and being predominantly distributed within biotite granite rock masses. The main spatial gamma anomalies in this area are mostly distributed below the 0m elevation, indicating that this area has a relatively deep uranium mineralization potential.

[0130] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. The same or similar parts between the various embodiments can be referred to each other.

[0131] This document uses specific examples to illustrate the principles and implementation methods of the present invention. The descriptions of the above embodiments are only for the purpose of helping to understand the core ideas of the present invention. Furthermore, those skilled in the art will recognize that, based on the ideas of the present invention, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. A mineralization prediction method based on the relationship between alteration structures and spatial gamma fields, characterized in that, include: Acquire target geological data; the target geological data includes borehole profiles, borehole gamma logging data, and borehole spatial data; Based on the location of the ore body delineated in the borehole profile, a spatially independent or continuous multi-faceted map is constructed in three-dimensional space along the corresponding structural alteration zone to obtain the ore body model. The borehole gamma logging data and the borehole spatial data are preprocessed, and a spatial gamma field model is constructed based on the preprocessed data; the spatial gamma field model includes a spatial gamma high field model, a spatial gamma high field model, and a spatial gamma anomaly field model. Different levels of spatial gamma field models are combined with the ore body model in profile, and the relationship between alteration structure and spatial gamma field is determined according to the combination situation in different survey areas. The distribution of the target mineral's rock mass is analyzed by utilizing the relationship between the alteration structure and the spatial gamma field, thus delineating the final location of the target mineral. Before constructing the ore body model and the spatial gamma field model, the method further includes: constructing a spatial database; the spatial database is used to provide data services for spatial modeling. The construction requirements for the spatial database include: data input, data management, data processing, and data output; wherein, data input includes the acquisition and input of well logging data, inclination data, and logging data; data management includes borehole management, project management, and user management; data processing includes data preprocessing, well logging content calculation, well logging data statistics, well logging data mapping, and spatial coordinate calculation; and data output includes well logging results output, well logging report output, and spatial data output. The spatial database system structure includes a surveying module, a well logging module, a logging module, a sampling module, and an instrument management module. The surveying module stores and manages surveying data from each borehole, and generates borehole spatial data by combining borehole coordinate data and well logging data. The well logging module stores and manages well logging data, performs data preprocessing, content calculation, and generates well logging results. The logging module stores and manages borehole logging data and sampling analysis data to aid in results analysis. The instrument management module stores and manages various instrument parameter data.

2. The mineralization prediction method based on the relationship between alteration structures and spatial gamma fields according to claim 1, characterized in that, The borehole gamma-ray logging data and the borehole spatial data are preprocessed, and a spatial gamma-ray field model is constructed based on the preprocessed data. Specifically, this includes: The borehole gamma logging data is subjected to a set iterative rejection process, and the average value and root mean square error of the processed data are calculated. The intensity level of the spatial gamma field is determined based on the calculation results. The intensity level includes high field, high field and anomalous field. Based on the borehole spatial data, spatial isometry calculations and mapping are performed using 3D modeling software, and the data is then processed in layers according to intensity levels to obtain spatial gamma high field model, spatial gamma high field model, and spatial gamma anomaly field model.

3. A mineralization prediction system based on the relationship between alteration structures and spatial gamma fields, employing the method as described in any one of claims 1-2, characterized in that, include: The data acquisition unit is used to acquire target geological data, including borehole profiles, borehole gamma logging data, and borehole spatial data. The ore body model construction unit is used to locate the ore body based on the ore body delineation position of the borehole profile, and then construct a spatially independent or continuous spatial multi-faceted map in three-dimensional space along the corresponding structural alteration zone to obtain the ore body model. The spatial gamma field model construction unit is used to preprocess the borehole γ logging data and the borehole spatial data, and to construct a spatial gamma field model based on the preprocessed data; the spatial gamma field model includes a spatial gamma high field model, a spatial gamma high field model, and a spatial gamma anomaly field model. The correlation analysis unit is used to combine spatial gamma field models of different levels with the ore body model in profile, and determine the relationship between alteration structure and spatial gamma field according to the combination situation in different survey areas. The target ore delineation unit is used to analyze the rock mass distribution of the target ore by utilizing the relationship between the alteration structure and the spatial gamma field, and to delineate the final location of the target ore.

4. An electronic device, characterized in that, The device includes a memory and a processor, wherein the memory stores a computer program and the processor runs the computer program to enable the electronic device to perform the mineralization prediction method based on the relationship between alteration structure and spatial gamma field according to any one of claims 1-2.

5. A computer-readable storage medium, characterized in that, It stores a computer program, which, when executed by a processor, implements the mineralization prediction method based on the relationship between alteration structures and spatial gamma fields as described in any one of claims 1-2.

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