Deep concealed deposit detection method based on multi-source organic chemical exploration

Abstract

The invention discloses a deep concealed ore deposit detection method based on multi-source organic chemistry exploration, and belongs to the technical field of geographic information, and the method specifically comprises the following steps: carrying out grid division on a target area, collecting each grid soil sample, and determining the content of a specified element; selecting a certain element m, and adopting a C-A multi-fractal method to generate a scatter diagram taking a content value threshold as a horizontal coordinate and an accumulated area as a vertical coordinate; fitting the scatter diagram through piecewise linear regression to obtain a fitting straight line; if the slope of any fitting straight line is smaller than a preset threshold value, the grid region corresponding to the fitting straight line is calibrated as a background region; if the slope is greater than or equal to a threshold value, calibrating a grid region corresponding to the fitting straight line as an abnormal region; according to the deep concealed deposit detection method, the deep concealed deposit detection system and the deep concealed deposit detection method, a quantitative judgment basis is provided for accurate positioning of concealed parallel veins, and the efficiency and the accuracy of deep concealed deposit detection are improved.

Description

Technical Field

[0001] The present invention relates to the field of geographic information technology, and in particular to a method for detecting deep concealed mineral deposits based on multi-source organic chemical exploration. Background Art

[0002] Existing hydrocarbon-mercury geochemical exploration methods, primarily based on relevant regulatory requirements, define geochemical anomalies by analyzing and testing the mineralizing elements and organic hydrocarbon-mercury content in soil (rock) media. Deep mineralization potential is then assessed based on anomaly characteristic indicators (anomaly intensity, area, concentration zoning, anomaly center, etc.) combined with the mineralization geological background. This method generally focuses on studying the "background field" and the "anomaly field (superimposed field)" and suffers from the following three shortcomings: (1) There is a lack of a deep understanding of anomalies formed by different mineralization processes (ore-forming materials from strata and from deep sources), which leads to many uncertainties in deep prospecting evaluation. If the ore-forming materials only come from ore-bearing strata, good local anomalies will also be formed. Due to the limitation of the source of ore-forming materials, good mineral points or small deposits will generally be formed, and the deep prospecting potential is relatively small. (2) Regarding the study of the relationship between organic matter and metal mineralization, the existing exploration methods generally remain at the level of understanding that biogenic organic matter participates in metal mineralization. Organic hydrocarbon anomalies have multiple interpretations. Even if the hydrocarbon anomalies are well developed, they may not necessarily have good prospecting prospects at deep depths. (3) Deep hidden mineral deposits are affected by the burial depth or geochemical barriers in the overlying rock layer (soil) medium. Ore-forming elements and organic hydrocarbon mercury components generally form low-lying anomalies, and there is even a possibility of being lower than the geochemical background value. This makes the existing exploration methods lose their evaluation basis and miss the discovery of deep hidden mineral deposits. Summary of the Invention

[0003] The purpose of the present invention is to provide a method for detecting deep concealed mineral deposits based on multi-source organic chemical exploration, and to solve the following technical problems: Ore-forming materials mainly come from strata or deep sources. If they only come from mineral-bearing strata, the formed deposits are usually small and the potential for deep mineral exploration is limited. Existing exploration methods are still in the preliminary stage of understanding the participation of organic matter in metal mineralization. Organic hydrocarbon anomalies are multifaceted. Even if they are well-developed, they do not necessarily mean that there are good prospecting prospects at depth. Deep hidden minerals may be affected by the burial depth and geochemical barriers in the overlying rock or soil media. Anomalies of mineralizing elements and organic hydrocarbons may appear as low-lying anomalies, even below the geochemical background value, causing the existing exploration methods to lose their effective basis and miss the opportunity to discover deep mineral deposits.

[0004] The purpose of the present invention can be achieved through the following technical solutions: The method for detecting deep concealed mineral deposits based on multi-source organic chemical exploration includes the following steps: S1, divide the target area into several grid areas, collect soil from each grid area in turn and perform element determination to obtain the content values of all elements; Select any element m and sort the content values of the element m in all grid areas in descending order to obtain a sequence c1, c2, ..., cn. Select c1, c2, ..., cn in turn as the content value threshold ci. For each content value threshold ci, count the total area A(ci) of the grids whose content value is greater than or equal to the content value threshold ci. Draw a scatter plot with the content value threshold ci as the horizontal axis and the cumulative area A(ci) as the vertical axis. S2, fitting the scatter plot using a piecewise linear regression method to obtain several fitted straight lines. If the slope of any fitted straight line is less than a preset threshold, the grid area corresponding to the fitted straight line is marked as a background area; if the slope of any fitted straight line is greater than or equal to the preset threshold, the grid area corresponding to the fitted straight line is marked as an abnormal area; S3: Perform an anomaly determination on any abnormal area, construct a dual bimodal anomaly model based on the anomaly determination results, and perform mineral deposit exploration based on the dual bimodal anomaly model. As a further embodiment of the present invention: In S1, the elements include mineral elements, mercury, low carbon alkanes C1, and medium carbon alkanes C2, wherein the low carbon alkanes C1 include ethane and propane, and the medium carbon alkanes C2 include n-butane, isobutane, n-pentane, and isopentane.

[0005] As a further solution of the present invention: in S2, based on the piecewise linear regression results, the number of fitted straight line segments is counted to determine the type of fractal model: when the number of fitted straight line segments is two, the classification model type is determined to be Model I; when the number of fitted straight line segments is three, the classification model type is determined to be Model II.

[0006] As a further solution of the present invention: In S3, the specific process of abnormality determination is: S11, the content value corresponding to the intersection of the first and second segments of the fitted straight line is the boundary value Q1 between the background area and the low-value abnormal area, and the content value corresponding to the intersection of the second and third segments of the fitted straight line is the boundary value Q2 between the low-value abnormal area and the high-value abnormal area; S12, obtaining the content value Q of any element m in the abnormal area. If Q1≤Q<Q2, the element m is determined to be a low-abnormal element; if Q≥Q2, the element m is determined to be a high-abnormal element. The categories of all elements in the abnormal area are obtained. S13, if the category of mercury and low-carbon alkane C1 in the abnormal area is high-abnormal elements, and the category of medium-carbon alkane C2 is low-abnormal elements, then the abnormal area is marked as the head abnormal area; if the category of mercury and low-carbon alkane C1 is low-abnormal elements, and the category of medium-carbon alkane C2 is high-abnormal elements, then the abnormal area is marked as the tail abnormal area.

[0007] As a further solution of the present invention: in S3, the specific process of mineral deposit detection is: The geographical ranges of all head anomaly areas and tail anomaly areas are superimposed on the same map, and areas adjacent to but not directly overlapping with the head anomaly areas and tail anomaly areas are found and marked as low-value areas. Spatial interpolation is performed on the low-value areas to generate a continuous low-value transition zone, and the geographical location corresponding to the low-value transition zone is marked as the ore body location.

[0008] As a further solution of the present invention: if there are two consecutive head abnormal sections, it means that there are two parallel veins in the low-value area, and the peak position of the head abnormality is calibrated as the head position of the vein; if the head abnormality is composed of multiple peaks, it means that there are multiple parallel veins in the low-value area, and form a dual double-peak superposition pattern with the corresponding tail abnormality.

[0009] As a further solution of the present invention: S3 also includes calibrating the grid area corresponding to each fitting straight line as a scale area, thereby dividing the target area into different scale areas, and deeply mining the correlation between mineral elements and organic hydrocarbons in any scale area through SPSS software. If the mineral elements and organic hydrocarbons are uncorrelated and the R-type cluster analysis and factor analysis show that it is an element combination of a single mineralization period, then the scale area is calibrated as a syngenetic superposition anomaly area; if the mineral elements and organic hydrocarbons have a good positive correlation and the R-type cluster analysis and factor analysis show that it is an element combination of two periods of mineralization, then the scale area is calibrated as a deep-source superposition anomaly area.

[0010] As a further solution of the present invention: it also includes prioritizing the deep-source superimposed anomaly area as the deep target area, performing anomaly judgment on the deep target area, constructing a dual bimodal anomaly model based on the anomaly judgment result, and performing mineral deposit detection based on the dual bimodal anomaly model.

[0011] Beneficial effects of the present invention: The present invention uses grid sampling and multi-element determination to comprehensively acquire geochemical data of the target area, and uses piecewise linear regression to analyze the cumulative distribution characteristics of element content, scientifically distinguishing background areas from abnormal areas, thereby avoiding the limitations of subjective threshold setting in traditional methods; by combining the abnormal combination patterns of mercury, low-carbon alkanes (C1) and medium-carbon alkanes (C2) to construct a dual bimodal model, it can accurately identify the head and tail anomalies of the ore body, revealing the migration path and mineralization laws of deep mineralized fluids; further with the help of spatial superposition analysis and low-value transition zone interpolation technology, discrete anomaly information is converted into a continuous basis for ore body positioning, significantly improving the target area accuracy of concealed mineral deposit detection. The present invention reveals the spatial coupling relationship of parallel ore bodies formed by multi-stage mineralization through the vertical superposition effect of hydrocarbon migration differentiation and mineralized fluids, breaking through the limitations of traditional single anomaly analysis, providing a quantitative discrimination basis for the precise positioning of concealed parallel veins, and improving the efficiency and accuracy of deep concealed mineral deposit detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] The present invention will be further described below with reference to the accompanying drawings.

[0013] Figure 1 This is a schematic flow chart of a method for detecting deep concealed mineral deposits based on multi-source organic chemical exploration according to the present invention; Figure 2 This is the element geochemistry and engineering verification diagram of the present invention, in which: y1, Quaternary; y2, Cretaceous; y3, Sinian; y4, Wuqiangxi Formation; y5, Madiyi Formation; y6, alteration zone and number; y7, measured and inferred stratigraphic boundaries; y8, stratigraphic unconformity boundaries; y9, fault; y10, drill hole with ore; y11, low-grade drill hole; y12, drill hole without ore; y13, anomaly zone and number; Figure 3 This is the dual double-peak superposition model in the present invention. In the figure: 1, Quaternary System; 2, Wuqiangxi Formation of Banxi Group; 3, Madiyi Formation of Banxi Group; 4, floating soil; 5, slate; 6, sandy slate; 7, methane; 8, ethane and propane; 9, fault and number; 10, vein and number. DETAILED DESCRIPTION

[0014] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making any creative efforts shall fall within the scope of protection of the present invention.

[0015] See also Figure 1 As shown, the present invention is a method for detecting deep hidden mineral deposits based on multi-source organic chemical exploration, comprising the following steps: S1, divide the target area into several grid areas, collect soil from each grid area in turn and perform element determination to obtain the content values of all elements; Select any element m and sort the content values of the element m in all grid areas in descending order to obtain a sequence c1, c2, ..., cn. Select c1, c2, ..., cn in turn as the content value threshold ci. For each content value threshold ci, count the total area A(ci) of the grids whose content value is greater than or equal to the content value threshold ci. Draw a scatter plot with the content value threshold ci as the horizontal axis and the cumulative area A(ci) as the vertical axis. S2, fitting the scatter plot using a piecewise linear regression method to obtain several fitted straight lines. If the slope of any fitted straight line is less than a preset threshold, the grid area corresponding to the fitted straight line is marked as a background area; if the slope of any fitted straight line is greater than or equal to the preset threshold, the grid area corresponding to the fitted straight line is marked as an abnormal area; S3, performing an anomaly determination on any abnormal area, constructing a dual bimodal anomaly model according to the anomaly determination result, and performing mineral deposit detection according to the dual bimodal anomaly model.

[0016] The present invention uses grid sampling and multi-element determination to comprehensively acquire geochemical data of the target area, and uses piecewise linear regression to analyze the cumulative distribution characteristics of element content, scientifically distinguishing background areas from abnormal areas, thereby avoiding the limitations of subjective threshold setting in traditional methods; by combining the abnormal combination patterns of mercury, low-carbon alkanes (C1) and medium-carbon alkanes (C2) to construct a dual bimodal model, it can accurately identify the head and tail anomalies of the ore body, revealing the migration path and mineralization laws of deep mineralized fluids; further with the help of spatial superposition analysis and low-value transition zone interpolation technology, discrete anomaly information is converted into a continuous basis for ore body positioning, significantly improving the target area accuracy of concealed mineral deposit detection. The present invention reveals the spatial coupling relationship of parallel ore bodies formed by multi-stage mineralization through the vertical superposition effect of hydrocarbon migration differentiation and mineralized fluids, breaking through the limitations of traditional single anomaly analysis, providing a quantitative discrimination basis for the precise positioning of concealed parallel veins, and improving the efficiency and accuracy of deep concealed mineral deposit detection.

[0017] It is noteworthy that conventional hydrocarbon-mercury measurements generally rely on the theoretical understanding that organic matter participates in metal mineralization through "biogenic" processes. This project's research reveals significant differences in the characteristics of organic hydrocarbon anomalies between large and medium-sized gold deposits and surrounding mineralization, with distinct mineralization geological significance. Combining previous research on mantle rocks and mantle-derived fluids, this project proposes for the first time that hydrocarbon anomalies in gold mineralization can be distinguished between "biogenic" and "inorganic" origins. Biogenic organic matter originates from shallow-source fluids (metamorphic fluids, atmospheric precipitation, etc.), where organic matter is derived from the decomposition of plant, animal, and microbial remains during diagenesis, and ore-forming materials are derived from ore-bearing strata. Inorganic organic matter, on the other hand, evolves from mantle-derived fluids, bringing with it significant amounts of deep-seated ore-forming materials that overlay and modify shallow-source fluids. Although both have the characteristics of superimposed mineralization, they represent two completely different mineralization processes. Due to the different sources of mineralizing materials (stratum and mantle), their mineralization geological significance and deep prospecting significance are completely different. In order to solve the multi-solution problem of traditional "hydrocarbon mercury measurement" anomaly evaluation, the present invention proposes for the first time a new theoretical understanding of "biogenic" and "inorganic" organic matter participating in metal mineralization. In a preferred embodiment of the present invention, in S1, the elements include mineral elements, mercury, low-carbon alkanes C1 and medium-carbon alkanes C2, wherein low-carbon alkanes C1 include ethane and propane, and medium-carbon alkanes C2 include n-butane, isobutane, n-pentane and isopentane.

[0018] In another preferred embodiment of the present invention, in S2, based on the piecewise linear regression results, the number of fitted straight line segments is counted to determine the type of fractal model: when the number of fitted straight line segments is two, the classification model type is determined to be Model I; when the number of fitted straight line segments is three, the classification model type is determined to be Model II.

[0019] In another preferred embodiment of the present invention, the specific process of abnormality determination in S3 is as follows: S11, the content value corresponding to the intersection of the first and second segments of the fitted straight line is the boundary value Q1 between the background area and the low-value abnormal area, and the content value corresponding to the intersection of the second and third segments of the fitted straight line is the boundary value Q2 between the low-value abnormal area and the high-value abnormal area; S12, obtaining the content value Q of any element m in the abnormal area. If Q1≤Q<Q2, the element m is determined to be a low-abnormal element; if Q≥Q2, the element m is determined to be a high-abnormal element. The categories of all elements in the abnormal area are obtained. S13, if the category of mercury and low-carbon alkane C1 in the abnormal area is high-abnormal elements, and the category of medium-carbon alkane C2 is low-abnormal elements, then the abnormal area is marked as the head abnormal area; if the category of mercury and low-carbon alkane C1 is low-abnormal elements, and the category of medium-carbon alkane C2 is high-abnormal elements, then the abnormal area is marked as the tail abnormal area.

[0020] It can be understood that the formation of each anomaly zone (I, II, III, IV) stems from the CA multifractal analysis of the gold content in the target area grid soil. By fitting the cumulative area scatter plot of the element content through piecewise linear regression, the area with a slope greater than the preset threshold is marked as the gold element anomaly zone. If the number of fitted straight line segments is three (such as model II), the low-slow anomaly and high-value anomaly intervals can be further divided according to the intersection points Q1 and Q2. Then, the anomaly combination pattern of mercury, low-carbon alkane C1 and medium-carbon alkane C2 is used to determine whether each anomaly zone is a head anomaly or a tail anomaly. For example, if mercury and C1 are high anomalies and C2 are low anomalies in anomaly zone I, it is marked as a head anomaly zone, reflecting the position of the front end of the deep mineralized fluid; if anomaly zone II shows low mercury and C1 anomalies and high C2 anomalies, it is a tail anomaly zone, indicating the end of the mineralized fluid; To apply the four anomaly zones, the geographic ranges of the head and tail anomaly zones must be superimposed on the same map, and adjacent, non-overlapping low-value areas must be identified. The low-value transition zone generated by spatial interpolation in this area represents the ore body location. If anomaly zones I and II are continuously distributed and represent the head anomaly segment, this indicates the presence of two parallel veins at depth, and their peak locations can be demarcated as the vein heads. If gold and organic hydrocarbons in anomaly zone III show a good positive correlation, and R-type cluster analysis reveals a two-phase ore-forming element assemblage, it is identified as a deep-source superimposed anomaly zone. Due to its high deep prospecting potential, it is prioritized as a deep target. If anomaly zone IV is a syngenetic superimposed anomaly, its deep prospecting potential is relatively low, and a comprehensive assessment requires consideration of other anomaly zones. In this way, the four anomaly zones can be mapped to different ore body spatial locations or mineralization types, enabling precise delineation of prospecting targets, avoiding the blindness of traditional methods and providing a quantitative basis for target priority in the exploration of deep, concealed gold deposits, thereby improving prospecting efficiency and accuracy.

[0021] By determining the demarcation value through the intersection of piecewise linear regression, the background and abnormal intervals can be objectively divided based on the distribution characteristics of the data itself, avoiding the subjectivity of artificially setting thresholds. Combined with the abnormal combination characteristics of alkanes and mercury with different carbon chain lengths, it conforms to the differentiation law caused by differences in physical and chemical properties during the migration of mineralizing fluids, and can effectively reflect the geochemical characteristics of different parts of the ore body. Through quantitative demarcation values and combined judgment rules, accurate classification of abnormal areas is achieved, and head and tail anomalies are clearly distinguished, providing direct geochemical signs for the spatial positioning of ore bodies. The purpose is to establish a correspondence between surface anomaly characteristics and deep ore body morphology. Through the distribution pattern of head and tail anomalies, the extension direction and output location of the ore body are inferred, breaking through the limitation of traditional methods that rely solely on single anomaly feature evaluation. Through the construction of a dual bimodal anomaly model, accurate positioning of deep hidden ore bodies is achieved, providing a quantitative judgment basis for the detection of hidden parallel veins, enabling the detection process to more accurately grasp the migration path and mineralization law of mineralizing fluids, thereby significantly improving the efficiency and accuracy of deep hidden ore deposit detection and providing more scientific technical support for mineral resource exploration.

[0022] In another preferred embodiment of the present invention, the specific process of mineral deposit detection in S3 is as follows: The geographical ranges of all head anomaly areas and tail anomaly areas are superimposed on the same map, and areas adjacent to but not directly overlapping with the head anomaly areas and tail anomaly areas are found and marked as low-value areas. Spatial interpolation is performed on the low-value areas to generate a continuous low-value transition zone, and the geographical location corresponding to the low-value transition zone is marked as the ore body location.

[0023] In another preferred embodiment of the present invention, if there are two consecutive head anomaly sections, it means that there are two parallel veins in the low-value area, and the peak position of the head anomaly is calibrated as the head position of the vein; if the head anomaly is composed of multiple peaks, it means that there are multiple parallel veins in the low-value area, and form a dual double-peak superposition pattern with the corresponding tail anomaly.

[0024] It can be understood that if there are two head anomalies (AS1, AS2) and tail anomalies (AS3, AS4) that form a dual double-peak anomaly pattern in the two sections of AS1, AS3 and AS2, AS4 continuously, it means that there is another parallel blind vein (V2 vein is a hidden blind vein) in the low-value area of the dual double-peak anomaly field pattern formed by AS1 and AS3 (controlling the known V1 vein), and the peak position of its head anomaly (AS2) is calibrated as the head position of the blind vein; if the head anomaly is composed of multiple peaks, it means that there are multiple parallel veins in the area, and form a dual double-peak superposition pattern with the corresponding tail anomaly.

[0025] The number and location of deep parallel veins are determined by the number of consecutive head anomaly segments and peaks because the continuity and number of peaks in head anomaly segments are intrinsically correlated with the distribution of deep veins. The presence of two consecutive head anomaly segments indicates the presence of two parallel veins at depth. This is because the head of each vein forms a corresponding independent head anomaly segment, and the peak position directly reflects the projected position of the vein head on the surface. Calibrating the vein head position accurately determines the starting orientation of a single vein. If the head anomaly consists of multiple peaks, it indicates the presence of multiple parallel veins at depth. The head anomalies of different veins superimpose to form multiple peaks, and the tail anomaly of each vein forms a dual double-peak pattern with the corresponding head anomaly. This superposition pattern clearly identifies the spatial distribution of each vein. This approach allows for intuitive and quantitative inference of the number, location, and spatial arrangement of deep parallel veins based on surface anomaly characteristics, avoiding the ambiguity and uncertainty inherent in traditional empirical inference methods. The goal is to establish a direct correspondence between surface anomalies and deep ore bodies through analysis of the head anomaly morphology, providing a clear basis for accurate identification of concealed parallel veins. This contributes to the ultimate goal of the program by significantly improving the target area accuracy of deep concealed mineral deposit detection, expanding the detection process from the analysis of single anomalies to the overall understanding of the spatial coupling relationship of parallel ore bodies formed by multiple phases of mineralization. This effectively solves the technical difficulties of traditional methods in identifying parallel veins, thereby improving the efficiency and accuracy of deep concealed mineral deposit detection and providing scientific and reliable technical support for the efficient exploration of mineral resources.

[0026] In another preferred embodiment of the present invention, said S3 also includes calibrating the grid area corresponding to each fitting straight line as a scale area, thereby dividing the target area into different scale areas, and deeply mining the correlation between the mineral elements and organic hydrocarbons in any scale area through SPSS software. If the mineral elements and organic hydrocarbons are uncorrelated and the R-type cluster analysis and factor analysis show an element combination of a single mineralization period, then the scale area is calibrated as a syngenetic superposition anomaly area; if the mineral elements and organic hydrocarbons have a good positive correlation and the R-type cluster analysis and factor analysis show an element combination of two periods of mineralization, then the scale area is calibrated as a deep-source superposition anomaly area.

[0027] Traditional exploration geochemistry generally stays at the evaluation of "background field" and "abnormal field", lacks a deep understanding of the complex superimposed anomalies (syngenetic superposition and deep-source superposition anomalies) formed by two different mineralization processes of "shallow source and deep-source" fluids in the "abnormal field", and the accuracy of anomaly evaluation is not high. "Syngenetic superposition anomaly" refers to the mineralization of minerals coming from mineralized strata, and its mineralization fluids are mainly "shallow source fluids" mixed with regional metamorphic fluids + atmospheric precipitation, and organic matter comes from biogenic organic matter during the diagenesis process. Shallow source fluids continuously extract metal mineralization elements from the strata through water-rock reactions and precipitate into minerals in favorable tectonic spaces. The "hydrocarbon-mercury superposition anomaly" formed by the mineralization of such shallow source fluids has little potential for deep prospecting due to the lack of superposition of mineralization materials brought by deep sources. The "deep-source superposition anomaly" reflects the disturbance caused by plate subduction / collision or intra-plate mantle plume activity and deep faults. The fluid moves upward from the deep crust, penetrates the entire crustal rock layer, and mixes and evolves with the fluids in different spaces of the crust. In addition to bringing a large amount of mantle mineralizing materials including organic matter, it also absorbs useful components in the crustal strata to superimpose or transform the mineralized bodies formed by the mineralization of "shallow source fluids" to form complex superimposed anomalies. The deep prospecting potential is relatively large. Based on the coupling of the mineralization geological characteristics of gold deposits and peripheral mineralized bodies and the comprehensive anomaly characteristics of hydrocarbons and mercury, the present invention proposes the new concepts of "syngenetic superimposed anomalies" and "deep source superimposed anomalies" for the first time, providing new ideas for geochemical deep prospecting evaluation.

[0028] In another preferred embodiment of the present invention, the deep source superimposed anomaly area is prioritized as the deep target area, anomaly judgment is performed on the deep target area, a dual bimodal anomaly model is constructed according to the anomaly judgment result, and mineral deposit detection is performed according to the dual bimodal anomaly model.

[0029] The above is a detailed description of an embodiment of the present invention. However, the content described is only a preferred embodiment of the present invention and should not be considered to limit the scope of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. A method for detecting deep concealed mineral deposits based on multi-source organic chemical exploration, characterized in that: The following steps are involved: S1, grid the target area to obtain several grid areas, collect soil from each grid area in turn and perform element determination to obtain the content values of all elements; Select any element m and sort the content values of the element m in all grid areas in descending order to obtain a sequence c1, c2, ..., cn. Select c1, c2, ..., cn in turn as the content value threshold ci. For each content value threshold ci, count the total area A(ci) of the grids whose content value is greater than or equal to the content value threshold ci. Draw a scatter plot with the content value threshold ci as the horizontal axis and the cumulative area A(ci) as the vertical axis. S2, fitting the scatter plot using a piecewise linear regression method to obtain several fitted straight lines. If the slope of any fitted straight line is less than a preset threshold, the grid area corresponding to the fitted straight line is marked as a background area; if the slope of any fitted straight line is greater than or equal to the preset threshold, the grid area corresponding to the fitted straight line is marked as an abnormal area; S3, performing an anomaly determination on any abnormal area, constructing a dual bimodal anomaly model according to the anomaly determination result, and performing mineral deposit detection according to the dual bimodal anomaly model.

2. The method for detecting deep hidden mineral deposits based on multi-source organic chemical exploration according to claim 1, characterized in that: In the S1, the elements include mineral elements, mercury, low-carbon alkanes C1 and medium-carbon alkanes C2, wherein the low-carbon alkanes C1 include ethane and propane, and the medium-carbon alkanes C2 include n-butane, isobutane, n-pentane and isopentane.

3. The method for detecting deep hidden mineral deposits based on multi-source organic chemical exploration according to claim 2, characterized in that: In S2, based on the piecewise linear regression results, the number of fitted straight line segments is counted to determine the fractal model type: when the number of fitted straight line segments is two, the classification model type is determined to be Model I; when the number of fitted straight line segments is three, the classification model type is determined to be Model II.

4. The method for detecting deep hidden mineral deposits based on multi-source organic chemical exploration according to claim 3, characterized in that: In S3, the specific process of abnormality determination is as follows: S11, the content value corresponding to the intersection of the first and second segments of the fitted straight line is the boundary value Q1 between the background area and the low-value abnormal area, and the content value corresponding to the intersection of the second and third segments of the fitted straight line is the boundary value Q2 between the low-value abnormal area and the high-value abnormal area; S12, obtaining the content value Q of any element m in the abnormal area, and if Q1≤Q<Q2, determining that the element m is a low abnormal element; If Q≥Q2, the element m is determined to be a highly abnormal element; the categories of all elements in the abnormal area are obtained; S13, if the category of mercury and low-carbon alkane C1 in the abnormal area is high-abnormal elements, and the category of medium-carbon alkane C2 is low-abnormal elements, then the abnormal area is marked as the head abnormal area; if the category of mercury and low-carbon alkane C1 is low-abnormal elements, and the category of medium-carbon alkane C2 is high-abnormal elements, then the abnormal area is marked as the tail abnormal area.

5. The method for detecting deep hidden mineral deposits based on multi-source organic chemical exploration according to claim 1, characterized in that: In S3, the specific process of mineral deposit detection is as follows: The geographical ranges of all head anomaly areas and tail anomaly areas are superimposed on the same map, and areas adjacent to but not directly overlapping with the head anomaly areas and tail anomaly areas are found and marked as low-value areas. Spatial interpolation is performed on the low-value areas to generate a continuous low-value transition zone, and the geographical location corresponding to the low-value transition zone is marked as the ore body location.

6. The method for detecting deep hidden mineral deposits based on multi-source organic chemical exploration according to claim 5, characterized in that: If there are two consecutive head anomaly sections, it means that there are two parallel veins in the low-value area, and the peak position of the head anomaly is calibrated as the head position of the vein; if the head anomaly is composed of multiple peaks, it means that there are multiple parallel veins in the low-value area, and form a dual double-peak superposition pattern with the corresponding tail anomaly.

7. The method for detecting deep hidden mineral deposits based on multi-source organic chemical exploration according to claim 3, characterized in that: Said S3 also includes calibrating the grid area corresponding to each fitting straight line as a scale area, thereby dividing the target area into different scale areas, and deeply mining the correlation between the mineral elements and organic hydrocarbons in any scale area through SPSS software. If the mineral elements and organic hydrocarbons are uncorrelated and the R-type cluster analysis and factor analysis show that it is an element combination of a single mineralization period, then the scale area is calibrated as a syngenetic superposition anomaly area; if the mineral elements and organic hydrocarbons have a good positive correlation and the R-type cluster analysis and factor analysis show that it is an element combination of two-period mineralization, then the scale area is calibrated as a deep-source superposition anomaly area.

8. The method for detecting deep hidden mineral deposits based on multi-source organic chemical exploration according to claim 7, characterized in that: It also includes prioritizing deep-source superimposed anomaly areas as deep target areas, performing anomaly determination on the deep target areas, constructing a dual bimodal anomaly model based on the anomaly determination results, and performing mineral deposit detection based on the dual bimodal anomaly model.

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