A method for rapid identification of the origin of gray sandstone in red beds based on big data and its application

Abstract

The present application belongs to the technical field of mineral exploration and geological analysis, and discloses a rapid discrimination method for the genesis of gray sandstone in red beds based on big data and application, wherein the rapid discrimination method collects macro-geological data including lithology, color, structure and spatial distribution and geochemical data including carbon isotope (delta 13C) value, and inputs the data into a big data exploration database; a macro-preliminary judgment is made according to the macro-geological data; quantitative verification is made based on the carbon isotope; the macro-preliminary judgment and the quantitative verification result are integrated for comprehensive judgment to form a standardized process; the relative size of delta 13C is taken as a core quantitative criterion to realize rapid and accurate identification of the sedimentary origin and the epigenetic reduction origin. The discrimination result is directly applied to the delineation of sandstone-type uranium mine target area, ore body prediction and exploration deployment, solves the defects of subjectivity and low efficiency of the traditional method, significantly improves the accuracy and efficiency of uranium exploration, and provides technical support for ore prospecting breakthrough.

Description

Technical Field

[0001] This invention belongs to the field of mineral exploration and geological analysis technology, specifically involving key geological body identification technology in sandstone-type uranium deposit exploration, and in particular, a rapid identification method and application of the genesis of gray sandstone in red beds based on big data. Background Technology

[0002] Exploration of uranium deposits in sandstone-type uranium deposits within red beds is currently a hot topic and a frontier in mineral resource exploration. Extensive research and practice have shown that the spatial distribution of uranium orebodies is controlled by the distribution characteristics of gray sandstone within red beds, and the genesis of the gray sandstone directly determines whether it possesses a favorable mineralization environment and orebody location conditions. Therefore, accurately and quickly determining the genesis of gray sandstone (sedimentary primary or epigenetic reduction) is crucial for predicting the location of uranium orebodies, guiding exploration project deployment, and ultimately achieving breakthroughs in mineral exploration.

[0003] However, the genetic identification of gray sandstone in red beds remains highly controversial, becoming a bottleneck restricting exploration efficiency and results. Traditional genetic identification methods mainly rely on single macroscopic geological observations or scattered geochemical tests. Macroscopically, while preliminary inferences can be made based on the sandstone's occurrence (such as whether it crosses strata or exhibits color transition characteristics), this approach is highly subjective and prone to misjudgment in complex areas with multiple phases of alteration. Although some scholars have proposed using geochemical indicators for identification, the selection of effective and reliable indicators and the establishment of a systematic, efficient, and rapid identification process remain unresolved. Existing technologies lack standardized methods for systematically combining and comprehensively identifying macroscopic geological features with high-precision quantitative test data (such as carbon isotopes), and further fail to address how to integrate and rapidly analyze multi-source information using data analysis techniques. This results in a time-consuming and labor-intensive identification process with unstable accuracy, failing to meet the urgent demands for efficiency and accuracy in large-scale exploration.

[0004] Against this backdrop, developing a rapid identification method that can integrate multi-scale geological information, has clear quantitative indicators, and an efficient analysis process is of great theoretical significance and practical application value for improving the exploration technology level of sandstone-type uranium deposits and achieving accurate mineral exploration. Summary of the Invention

[0005] The purpose of this invention is to address the current situation where the genesis of gray sandstone in red beds is controversial and traditional identification methods are inefficient. This invention provides a rapid identification method for the genesis of gray sandstone in red beds based on big data, which can quickly and accurately identify the genesis of gray sandstone, thereby overcoming the key constraints on the spatial location and exploration breakthroughs of sandstone-type uranium ore bodies.

[0006] To address the aforementioned technical problems, the present invention provides a method for rapid identification of the genesis of gray sandstone in red beds based on big data. This method integrates macroscopic geological data and geochemical data to establish a standardized decision-making process, specifically including the following steps: S1. Data Acquisition and Storage: Collect macroscopic geological and geochemical data of the target strata, and input the collected data into a big data exploration database to complete structured integration; the geochemical data includes carbon isotope (δ¹³C) values ​​of gray sandstone and adjacent red sandstone; S2. Preliminary determination of macroscopic occurrence: Using macroscopic geological data from the big data exploration database, the genesis of the gray sandstone is preliminarily determined and the preliminary determination results are output. S3. Quantitative Verification: Call geochemical data from the big data exploration database, extract carbon isotope (δ¹³C) values ​​of gray sandstone and adjacent red sandstone from the same borehole profile or adjacent spatial locations for comparison, quantitatively verify the genesis of gray sandstone based on the comparison results, and output the quantitative verification results. S4. Comprehensive Judgment and Output: Integrate the preliminary judgment results of step S2 and the quantitative verification results of step S3. If the preliminary judgment results are consistent with the quantitative verification results, output a high-confidence conclusion on the genetic origin of gray sandstone. If the preliminary judgment results contradict the quantitative verification results, the quantitative verification results shall prevail and the spatial location and anomaly characteristics of the macroscopic anomalies shall be marked.

[0007] As a further description of the above technical solution, the macro-geological data mentioned in step S1 includes detailed observation and descriptive records of lithology, color, structure, contact relationship and cross-layer phenomena in the borehole core or well logging data of the target layer.

[0008] As a further description of the above technical solution, the preliminary determination of the origin of gray sandstone in step S2 is as follows: if the gray sandstone is distributed in a stable layered manner, the color of the contact zone with the red sandstone gradually changes and there is no obvious cross-bedding phenomenon in three-dimensional space, then it is preliminarily determined to be of primary sedimentary origin; if the gray sandstone is in the form of irregular masses or veins, with clear boundaries with the surrounding rocks and cross-bedding phenomenon, uneven color distribution, and clear and distinct boundaries with the surrounding rocks, it is preliminarily determined to be of secondary reduction origin.

[0009] As a further description of the above technical solution, the process of obtaining the carbon isotope (δ¹³C) values ​​of the gray sandstone and adjacent red sandstone is as follows: systematically collect paired gray sandstone samples and red sandstone samples from the macroscopically delineated target gray sandstone body and adjacent red sandstone body, and perform carbon isotope (δ¹³C) tests on the gray sandstone samples and red sandstone samples respectively to obtain quantitative data.

[0010] As a further description of the above technical solution, the quantitative verification in step S3 specifically involves: calling the carbon isotope (δ¹³C) values ​​of the corresponding samples in step S1, extracting the average δ¹³C values ​​of gray sandstone and red sandstone samples from the same borehole profile or adjacent spatial locations, and comparing them: if the average carbon isotope (δ¹³C) value of the gray sandstone is greater than that of the adjacent red sandstone, then the quantitative verification indicates a primary sedimentary origin; if the average carbon isotope (δ¹³C) value of the gray sandstone is less than that of the adjacent red sandstone, then the quantitative verification indicates an epigenetic reductive origin; if the average carbon isotope value of the gray sandstone equals that of the adjacent red sandstone, then the testing process needs to be reviewed to eliminate non-geological errors, and after error correction, the comparison is repeated. If the review finds no error, additional sampling and testing are conducted, and the combined average δ¹³C value is calculated and compared again. If they are still equal, then step S4 is taken to make a comprehensive judgment based on the macroscopic occurrence.

[0011] As a further description of the above technical solution, the method is embedded in a database-based exploration system to achieve automated or semi-automated rapid identification and zoning mapping of the genesis of gray sandstone from massive borehole data.

[0012] The genetic discrimination results of gray sandstone obtained by the method described in this invention can be directly applied to the exploration of sandstone-type uranium deposits, including delineating uranium prospecting target areas, prioritizing the distribution areas of post-reductive gray sandstone bodies as key exploration target areas, as these areas represent the most favorable spaces for uranium mineralization; predicting the spatial location of uranium ore bodies, accurately predicting the possible spatial range of uranium ore bodies based on the distribution characteristics of post-reductive gray sandstone; and guiding the deployment of exploration projects, adjusting the borehole layout scheme based on the genetic discrimination results, avoiding the distribution areas of sedimentary primary gray sandstone, focusing on favorable target areas to deploy exploration projects, and improving the mineralization rate.

[0013] Compared with the prior art, the beneficial effects of the present invention are: This invention, through a mandatory sequential process of macroscopic preliminary judgment, quantitative verification, and comprehensive determination, combined with a clear quantitative criterion of the relative carbon isotope (δ¹³C) values ​​between gray sandstone and adjacent red sandstone, completely transforms traditional subjective experience-based inference into objective data-driven judgment. This significantly reduces human error and ensures high comparability and reliability of causal identification results from different personnel and regions, thus significantly improving identification accuracy. Simultaneously, through the structured integration of unstructured geological phenomenon descriptions and structured test data, the method can be seamlessly embedded into database-based exploration systems, enabling automated and semi-automated analysis of massive regional borehole data. Unlike traditional zonal mapping, this method can efficiently perform batch screening and rapid classification of massive amounts of data, shortening the evaluation cycle for large areas from months / grades to weeks / days, significantly reducing the exploration evaluation cycle, improving exploration efficiency, and effectively freeing up exploration manpower. Moreover, the design of the entire set of technical methods is deeply integrated with the application scenarios of sandstone-type uranium deposit exploration. It can directly lock in favorable uranium mineralization spaces through accurate genetic identification results, promoting the focus of exploration deployment from "area survey" to "target area verification," significantly reducing exploration risks and ineffective investment. The application is highly targeted and has outstanding practical benefits, providing reliable technical support for breakthroughs in sandstone-type uranium exploration. Attached Figure Description

[0014] Figure 1 This is a flowchart of the method for rapid determination of the genesis of gray sandstone in red beds according to the present invention. Detailed Implementation

[0015] The claims of the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments, but this does not constitute any limitation on the present invention. Any limited modifications made by any person within the scope of protection of the claims of the present invention shall still be within the scope of protection of the claims of the present invention.

[0016] A rapid method for determining the genesis of gray sandstone in red beds based on big data, the process of which is as follows: Figure 1 As shown, it includes the following steps: S1. Data Acquisition and Storage: This step is the foundation of the entire method. Specifically, it involves: acquiring macroscopic geological and geochemical data of the target stratum and inputting the acquired data into a big data exploration database for structured integration; the macroscopic geological data includes detailed observations and descriptions of the lithology, color, structure, and spatial distribution (especially contact relationships and cross-strata phenomena) of the borehole cores (or well logs) of the target stratum; the geochemical data includes carbon isotope (δ¹³C) values ​​of gray sandstone and adjacent red sandstone, i.e., systematically collecting paired gray sandstone samples and red sandstone samples from the macroscopically delineated gray sandstone body and its adjacent red sandstone, and conducting carbon isotope (δ¹³C) tests to obtain quantitative data.

[0017] S2. Preliminary Macroscopic Occurrence Judgment: Logical judgment is made by calling macroscopic geological data from the big data exploration database. If the gray sandstone is distributed in a stable layered manner, and the color of the contact zone with the upper and lower red sandstones shows a gradual transition relationship, and no obvious cross-bedding phenomenon is observed in three-dimensional space, then it is preliminarily judged to be of primary sedimentary origin, and the preliminary judgment result is output as "possibly of primary sedimentary origin", and proceed to step S3 for verification; if the gray sandstone shows irregular clumps, veins or obvious cross-bedding of the original strata in space, and the color distribution is uneven, and the boundary with the surrounding rock is clear or even distinct, then it is preliminarily judged to be of secondary reductive origin, and the preliminary judgment result is output as "possibly of secondary reductive origin", and proceed to step S3 for verification.

[0018] S3. Quantitative Verification: This step is the core of the objective judgment in this invention. It involves calling geochemical data from a large-scale exploration database to extract and compare the average carbon isotope (δ¹³C) values ​​of gray sandstone and adjacent red sandstone from the same borehole profile or adjacent spatial locations. Based on the comparison results, the origin of the gray sandstone is quantitatively verified: if the δ¹³C value of the gray sandstone is greater than that of the adjacent red sandstone, the quantitative verification conclusion is "primordial sedimentary origin"; if the δ¹³C value of the gray sandstone is less than that of the adjacent red sandstone, the quantitative verification conclusion is "entecotic reduction". "Genesis"; if the δ¹³C value of gray sandstone equals that of adjacent red sandstone (belonging to an anomaly without clear direction in quantitative verification), it cannot be directly attributed to primary sedimentary origin or secondary reductive origin. A three-level supplementary judgment process of "testing process verification, supplementary sampling testing, and macroscopic occurrence-driven analysis" needs to be initiated. The final judgment should be based on a comprehensive analysis of multi-dimensional results, while also labeling data anomaly attributes to avoid misjudgment based on a single criterion. Specifically: first, a source tracing verification of the testing process should be conducted to exclude non-geological errors, prioritizing the verification of the entire carbon isotope testing process (sample collection, testing instruments, ...). (Data processing), simultaneously retrieving δ¹³C background data from the same region and stratum in the big data exploration database to eliminate non-geological errors such as human sampling, experimental testing, and data entry; if errors are found, correct the data and perform quantitative verification again; if no errors are found in the source verification, it indicates that there is no difference in the actual geological δ¹³C value, and it is necessary to double the number of paired samples collected from the target gray sandstone and red sandstone sections in the same borehole profile / adjacent geological continuous area, re-perform carbon isotope testing, calculate the combined average δ¹³C value of the new samples and the original samples, and compare them. If differences in elevation occur after supplementation, quantitative verification will be performed directly, and the supplementary test data will be entered into the big data exploration database. If the combined average δ¹³C value of gray sandstone and red sandstone is still equal after supplementary testing, the preliminary macroscopic occurrence judgment result of step S2 will be used as the main basis for judgment. At the same time, the final result will be clearly marked as "no significant difference in carbon isotope (δ¹³C) value, the cause is based on macroscopic occurrence judgment, and further verification will be required by combining other geochemical indicators". The spatial information and test data of the anomaly point will be included in the anomaly database of the big data exploration database.

[0019] S4. Comprehensive Judgment and Output: Integrate the preliminary macroscopic judgment from step S2 with the quantitative verification results from step S3. If the preliminary judgment results are consistent with the quantitative verification results, output a high-confidence final genetic judgment conclusion for gray sandstone. If the preliminary judgment results contradict the quantitative verification results, the quantitative verification results from step S3 shall prevail. At the same time, trigger the verification mechanism for macroscopic features, output the final judgment conclusion, and mark the spatial location and description of the anomalous features of the macroscopic anomalies that need to be verified.

[0020] The method described in this invention can be directly embedded into a database-based mineral exploration system. Through the structured integration and automated retrieval of big data exploration databases, it can achieve semi-automatic or automatic genetic identification of massive regional borehole data and automatically generate a gray sandstone genetic zoning map, providing visual data support for the deployment of uranium exploration projects.

[0021] Application examples: The following detailed explanation of the method and application of this invention is based on an implementation example from a uranium mine survey area in the Songliao Basin: Implementation conditions: A uranium mine survey area in the Songliao Basin was selected as the study area. Drill core logging equipment, carbon isotope testing instruments and data processing terminals were provided. Professional geologists completed the core observation, sample collection and data entry work.

[0022] Method implementation steps: S1. Data Acquisition and Storage: Ten boreholes were systematically selected in the study area for core logging, and the color, bedding and contact relationship of the target sandstone were recorded in detail. Twenty sets of paired samples were collected from the gray sandstone section and the adjacent red sandstone section of three boreholes for carbon isotope (δ¹³C) testing. S2. Preliminary macroscopic identification: Core observation shows that the gray sandstone is mainly distributed in layers, with a gradual transition contact with the overlying red sandstone. There is no obvious cross-bedding phenomenon. It is preliminarily determined to be of original sedimentary origin, and the output is "possibly of original sedimentary origin". S3. Quantitative Verification: Test data shows that the average δ¹³C value of the gray sandstone sample is -0.26‰, while the average δ¹³C value of the adjacent red sandstone sample is -1.61‰. The δ¹³C value of the gray sandstone is greater than that of the red sandstone. Quantitative verification indicates that this is a sedimentary origin, and the output is "Possibly a sedimentary origin".

[0023] S4. Comprehensive judgment: The preliminary macroscopic judgment and quantitative verification results are consistent, and the target layer of gray sandstone in the area is finally determined to be of original sedimentary origin.

[0024] Application Implementation Results: Based on the discrimination results, it was determined that the gray sandstone in this area had no post-reduction transformation and its uranium mineralization potential was low. Accordingly, the exploration unit promptly adjusted its exploration deployment, transferring resources from this area to other prospective areas with post-reduction gray sandstone development. This avoided ineffective drilling deployment and capital investment. The entire process of discrimination and deployment adjustment was completed within three weeks, fully demonstrating the core advantages of the method of this invention: speed, accuracy, and outstanding application effectiveness.

[0025] The rapid identification method of this invention places subjective macroscopic observation before and verifies objective quantitative testing, achieving a mandatory sequential process and ensuring the reliability of the conclusions. It uses the clear mathematical comparison of the relative magnitudes of δ¹³C between gray sandstone and adjacent red sandstone as the decisive criterion, clarifying the quantitative criteria and eliminating ambiguity. Through a standardized process, it structurally integrates unstructured geological phenomenon descriptions with structured test data, enabling batch and rapid analysis. Furthermore, this method can be embedded in database-based exploration systems to achieve automated or semi-automated rapid identification and genetic zoning mapping of gray sandstone genesis from large amounts of borehole data within a region.

[0026] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit them; those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions will not cause the essence of the corresponding technical solutions to deviate from the protection scope of the present invention.

Claims

1. A rapid method for determining the genesis of gray sandstone in red beds based on big data, characterized in that, Includes the following steps: S1. Data Acquisition and Storage: Collect macroscopic geological and geochemical data of the target strata, and input the collected data into a big data exploration database to complete structured integration; the geochemical data includes carbon isotope values ​​of gray sandstone and adjacent red sandstone; S2. Preliminary determination of macroscopic occurrence: Based on macroscopic geological data retrieved from the big data exploration database, the genesis of the gray sandstone is preliminarily determined and the preliminary determination results are output. S3. Quantitative Verification: Based on geochemical data retrieved from the big data exploration database, carbon isotope values ​​of gray sandstone and adjacent red sandstone from the same borehole profile or adjacent spatial locations are extracted and compared. The genesis of gray sandstone is quantitatively verified based on the comparison results, and the quantitative verification results are output. S4. Comprehensive Judgment and Output: Integrate the preliminary judgment results of step S2 and the quantitative verification results of step S3. If the preliminary judgment results are consistent with the quantitative verification results, output a high-confidence conclusion on the genetic identification of gray sandstone. If the preliminary judgment results contradict the quantitative verification results, the quantitative verification results shall prevail, and the spatial location and abnormal characteristics of the macroscopic anomalies shall be marked.

2. The method for rapid determination of the genesis of gray sandstone in red beds according to claim 1, characterized in that: The macroscopic geological data mentioned in step S1 includes lithology, color, structure, contact relationship, and cross-layer phenomena of borehole cores or well logs.

3. The method for rapid determination of the genesis of gray sandstone in red beds according to claim 2, characterized in that: The preliminary determination of the origin of gray sandstone in step S2 is as follows: if the gray sandstone is distributed in a stable layered manner, gradually transitions with the red sandstone and has no cross-layer phenomenon, it is preliminarily determined to be of primary sedimentary origin; if the gray sandstone is in the form of irregular masses or veins, has a clear boundary with the surrounding rock and exhibits cross-layer phenomenon, it is preliminarily determined to be of secondary reductive origin.

4. The method for rapid determination of the genesis of gray sandstone in red beds according to claim 1, characterized in that: The process of obtaining the carbon isotope values ​​of the gray sandstone and adjacent red sandstone is as follows: systematically collect paired gray sandstone samples and red sandstone samples from the macroscopically delineated target gray sandstone body and adjacent red sandstone body, and perform carbon isotope tests on the gray sandstone samples and red sandstone samples respectively.

5. The method for rapid determination of the genesis of gray sandstone in red beds according to claim 4, characterized in that: The quantitative verification in step S3 specifically involves comparing the average carbon isotope values ​​of the gray sandstone and the adjacent red sandstone. If the average carbon isotope value of the gray sandstone is greater than that of the adjacent red sandstone, then the quantitative verification indicates a primary sedimentary origin; otherwise, the quantitative verification indicates an epigenetic reductive origin.

6. The application of the rapid identification method for the genesis of gray sandstone in red beds as described in any one of claims 1 to 5 in the field of sandstone-type uranium deposit exploration, characterized in that, The genetic determination results of gray sandstone obtained by the above method are used for sandstone-type uranium deposit exploration.

7. The application according to claim 6, characterized in that: The application includes delineating uranium exploration target areas, prioritizing the distribution areas of post-reduction gray sandstone bodies as key exploration target areas.

8. The application according to claim 6, characterized in that: The applications include predicting the spatial location of uranium ore bodies and accurately delineating the potential occurrence range of uranium ore bodies based on the distribution characteristics of epigenetic reduction-genetic gray sandstone.

9. The application according to claim 6, characterized in that: The applications include guiding the deployment of exploration projects, adjusting borehole layout schemes based on the genetic identification results of gray sandstone, avoiding the distribution areas of sedimentary original gray sandstone, and focusing on deploying exploration projects in favorable target areas.

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