A gold magma identification method based on high-dimensional element ratio phase space differentiation

Abstract

The present invention discloses a method for identifying gold magma based on high-dimensional element ratio phase space differentiation, which solves the technical problem that gold magma cannot be accurately identified in the prior art. This method constructs a four-dimensional characteristic vector with ratios such as Ba / Zr, Nb / Y, U / Yb, and V / Y, projects it on the ratio phase space subdomain, and realizes the initial judgment, entropy state judgment and source area inversion of mineralization potential magma through distribution trend, trajectory disturbance and multi-factor clustering behavior. Multi-domain heterodimensional mapping and weighted fusion model are introduced to integrate the coupling effect of initial ratio disturbance, differentiation evolution trajectory and component source to form a set of high-order mineralization discrimination system for prospecting prediction. Through the above scheme, the present invention has the advantages of simple logic, accuracy and reliability, and has high practical value and promotion value in the field of mineral resource prediction and magma earth discrimination technology.

Description

Technical Field

[0001] The present invention relates to the technical field of mineral resource prediction and magma earth discrimination, in particular to a gold mine magma identification method based on high-dimensional element ratio phase space differentiation. Background Art

[0002] Gold deposit formation mechanisms and prospecting prediction are at the forefront of geoscience research. Research has shown that magmatic-hydrothermal processes are crucial for gold mineralization, with magma source characteristics, melting conditions, and subsequent evolution controlling gold enrichment and migration. Traditional research on gold mineralization potential relies heavily on local elemental content, post-discovery fluid characteristics, or post-discovery tracing of ore bodies. It lacks systematic identification methods based on primary information from magmatic systems, such as the published technology "A Method, System, Computer Equipment, and Medium for Predicting Gold Targets, Publication No. CN117993578A"; "A Method for Locating the Burial Depth of Carlin-Type Gold Deposits Using Rare Earth Elements and Carbon Isotopes, Publication No. CN117630147A"; and the article "Gold and Other Element Composition of Mesozoic Magmatic Rocks in Jiaodong and Its Implications for Gold Mineralization."

[0003] With the development of geochemical methods, the ratios of trace elements, particularly incompatible elements (such as Ba, Nb, U, Zr, Y, and Yb), have become sensitive indicators of partial melting, fluid replacement, and differentiation and evolution in magmatic source regions. However, existing methods are often limited to single-element indices or local ratio analysis (e.g., "Gold and Other Element Compositions of Mesozoic Magmatic Rocks in Jiaodong and Their Implications for Gold Mineralization"). There is a lack of a theoretical framework and technical approach to systematically combine multiple sets of element ratios into a high-dimensional feature space to comprehensively identify the mineralization potential of magmatic systems. In gold mineralization systems, in particular, weak differentiation signals within the magmatic system, source enrichment states, and water content variations are often difficult to effectively identify using conventional two-dimensional single-factor analysis.

[0004] Therefore, there is an urgent need to construct a set of discrimination methods based on high-dimensional element ratio phase space differentiation that can accurately reveal the mineralization potential of magma. Summary of the Invention

[0005] In view of the above problems, the present invention aims to provide a method for identifying gold magma based on high-dimensional element ratio phase space differentiation. The technical solution adopted by the present invention is as follows:

[0006] A method for identifying gold magma based on high-dimensional element ratio phase space differentiation comprises the following steps:

[0007] Step S1, constructing an element abundance spectrum for the collected magma sample and performing sample spectrum screening;

[0008] Step S2, generating an incompatible element ratio matrix using the screened element abundance spectrum and performing feature tensor quantization processing;

[0009] Step S3: construct a high-dimensional feature interface based on the feature tensor, perform preliminary screening of the mineralization potential, and mark the preliminary discrimination label;

[0010] Step S4, performing qualitative discrimination of the magma water entropy flow on the magma sample containing the preliminary discrimination label to obtain the entropy flow disturbance characteristics;

[0011] Step S5, based on the results of qualitative identification of magma water entropy flow, source area enrichment factor mapping and fluid enrichment inverse deduction are performed to obtain source area properties;

[0012] Step S6: Perform multi-domain discrimination fusion and comprehensive weighted evaluation of mineralization potential based on preliminary discrimination labels, entropy flow disturbance characteristics, and source area properties.

[0013] Furthermore, in step S1, constructing an element abundance spectrum for the collected magma sample and performing sample spectrum screening includes the following steps:

[0014] The collected magma samples were analyzed for the content of Ba, Zr, Nb, Y, U, Yb, V, and SiO2 to form an element abundance spectrum matrix. C ;

[0015] Magma samples with significant secondary transformation were screened and eliminated based on the degree of alteration, mineral fidelity and element ratio anomalies of the magma samples.

[0016] Furthermore, in step S2, the incompatible element ratio matrix is ​​generated using the screened element abundance spectrum and a feature tensor quantization process is performed, which includes the following steps:

[0017] Calculate the ratio for any set of magma samples, where:

[0018] Ba / Zr ratio The expression is: ;

[0019] Nb / Y ratio The expression is: ;

[0020] U / Yb ratio The expression is: ;

[0021] V / Y ratio The expression is: ;

[0022] in, Indicates the content of Ba in the magma sample; Indicates the content of Zr element in the magma sample; Indicates the content of Nb element in the magma sample; Indicates the content of element Y in the magma sample; Indicates the content of U element in the magma sample; Indicates the content of V element in the magma sample; Indicates the content of Yb element in the magma sample;

[0023] by{ , , , } as the basic feature component to construct the sample high-dimensional ratio feature tensor .

[0024] Furthermore, in step S3, a high-dimensional feature interface is constructed based on the feature tensor to perform preliminary screening of the mineralization potential and mark preliminary discrimination labels, including the following steps:

[0025] Preset classification threshold R 1. R 2. R 3. If > R 1, > R 2, > R 3; the magma sample is a gold mineralization potential magma; otherwise, it is a non-ore-forming magma;

[0026] Map the magma samples collected in step S1 onto the Ba / Zr–SiO2 two-dimensional projection plane to observe the differentiation and aggregation of gold mineralization potential magma and non-ore-forming magma;

[0027] According to the differentiation and aggregation of gold mineralization potential magma and non-ore-forming magma, the preliminary discrimination labels of magma samples in high-dimensional space are marked.

[0028] Furthermore, in step S4, the magma sample containing the preliminary identification label is subjected to a qualitative identification of the magma water entropy flow to obtain the entropy flow disturbance characteristics, which includes the following steps:

[0029] Plot the magma samples containing preliminary discrimination labels in step S3 in the V / Y–Ba / Zr projection subspace and determine their distribution patterns;

[0030] By analyzing the water content trend and entropy flow disturbance characteristics, the entropy flow disturbance characteristics are obtained and magma samples with mineralization potential are obtained.

[0031] Furthermore, in step S5, based on the result of qualitative identification of magma water entropy flow, source area enrichment factor mapping and fluid enrichment inverse deduction are performed to obtain source area properties, which includes the following steps:

[0032] The magma samples that were preliminarily screened and determined to be gold mineralization potential magmas in steps S3 and S4 were plotted in the U / Yb–Nb / Y two-dimensional subspace to construct a source area enrichment map, and the source area composition type and evolution characteristics were inferred based on the sample distribution trend.

[0033] Furthermore, in step S6, multi-domain discrimination fusion and comprehensive weighted evaluation of metallogenic potential are performed based on preliminary discrimination labels, entropy flow disturbance characteristics and source area properties, including the following steps:

[0034] The mineralization potential function S is constructed based on the preliminary discrimination labels, entropy flow disturbance characteristics and source area properties, and its expression is:

[0035]

[0036] in, Indicates Ba / Zr ratio , Nb / Y ratio and U / Yb ratio The mineralization potential information represented by the constructed high-dimensional tensor features; It represents the magma water content trend and entropy flow disturbance information revealed based on the V / Y–Ba / Zr projection relationship; Indicates the U / Yb ratio and Nb / Y ratio Constructed information on the enrichment properties and genetic types of the source area; A preliminary metallogenic potential scoring function representing a high-dimensional tensor space; Represents the scoring function for mapping magma water content trend and entropy flow disturbance; represents the source region enrichment factor mapping scoring function;

[0037] The mineralization potential function S is used to divide any magma sample and form the spatial distribution of gold mineralization potential of the magma system.

[0038] Compared with the prior art, the present invention has the following beneficial effects:

[0039] (1) The present invention constructs an element abundance spectrum for the collected magma samples, and uses the screened element abundance spectrum to generate an incompatible element ratio matrix, and performs feature tensor processing. It systematically constructs the element ratios into a high-dimensional feature tensor, comprehensively considering the source area enrichment, partial melting degree and fluid evolution state to ensure its accurate and reliable identification.

[0040] (2) The present invention plots the samples in the V / Y–Ba / Zr projection subspace and the U / Yb–Nb / Y two-dimensional subspace, and introduces phase space differentiation analysis to judge the mineralization affinity of the magma system through the characteristics of the samples such as aggregation and trajectory direction in high-dimensional space.

[0041] (3) The present invention uses the entropy flow perturbation theory to analyze the trajectory of magma water content changes from the V / Y–Ba / Zr projection surface, further improving the accuracy of mineralization potential identification.

[0042] (4) The present invention constructs a mineral potential function and uses preliminary discrimination labels, entropy flow disturbance characteristics and source area properties to perform multi-domain discrimination fusion and comprehensive weighted evaluation of mineralization potential, which is suitable for batch data processing and regional prospecting prediction.

[0043] In summary, the present invention has the advantages of simple logic, accuracy and reliability, and has high practical value and promotion value in the field of mineral resource prediction and magma earth identification technology. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following is a brief introduction to the drawings required for use in the embodiments. It should be understood that the following drawings only illustrate certain embodiments of the present invention and therefore should not be regarded as limiting the scope of protection. For those skilled in the art, other relevant drawings can be obtained based on these drawings without paying any creative work.

[0045] Figure 1 It is a logic flow chart of the present invention.

[0046] Figure 2 This is a scatter diagram for distinguishing gold mineralization magma and non-ore-forming magma on the Ba / Zr–SiO2 plane in the present invention.

[0047] Figure 3 Schematic diagram of the entropy flow disturbance characteristics revealed by the V / Y–Ba / Zr relationship in the present invention.

[0048] Figure 4 This is a schematic diagram of using U / Yb and Nb / Y to determine the enrichment degree of the source region in the present invention. DETAILED DESCRIPTION

[0049] To make the purpose, technical solutions, and advantages of this application more clear, the present invention is further described below with reference to the accompanying drawings and examples. Implementation methods of the present invention include, but are not limited to, the following examples. All other embodiments obtained by persons of ordinary skill in the art based on the examples in this application without creative effort are within the scope of protection of this application.

[0050] In this embodiment, the term "and / or" is merely a description of the association relationship between associated objects, indicating that three relationships may exist. For example, A and / or B can represent three situations: A exists alone, A and B exist at the same time, and B exists alone.

[0051] In the description and claims of this embodiment, the terms "first" and "second" are used to distinguish different objects rather than to describe a specific order of objects. For example, a first target object and a second target object are used to distinguish different objects rather than to describe a specific order of objects.

[0052] In the embodiments of this application, words such as "exemplary" or "for example" are used to indicate examples, illustrations, or descriptions. Any embodiment or design described as "exemplary" or "for example" in the embodiments of this application should not be interpreted as being preferred or advantageous over other embodiments or designs. Rather, the use of words such as "exemplary" or "for example" is intended to present the relevant concepts in a concrete manner.

[0053] In the description of the embodiments of this application, unless otherwise specified, "multiple" means two or more. For example, "multiple processing units" means two or more processing units; "multiple systems" means two or more systems.

[0054] like Figures 1 to 4 As shown, this embodiment provides a method for identifying gold magma based on high-dimensional element ratio phase space differentiation, which includes the following steps:

[0055] The first step is to construct the element abundance spectrum of the collected magma samples and perform sample spectrum screening. Specifically:

[0056] First, fresh or slightly altered igneous rock samples were collected and the contents of elements such as Ba, Zr, Nb, Y, U, Yb, V, and SiO2 were measured to form an element abundance spectrum matrix C. Samples were screened based on their degree of alteration, mineral fidelity, and element ratio anomalies, eliminating samples with significant secondary alteration to ensure that subsequent analysis was based on the primary magma system. This example uses magma samples from a certain region as an example, forming the basic dataset shown in Table 1.

[0057] Table 1 Basic dataset

[0058] Sample No. category SiO2(wt%) Ba / Zr Nb / Y U / Yb V / Y 1 Gold magma 58.3 3.6 1.3 1.9 0.82 2 Gold magma 56.7 3.2 1.1 1.7 0.79 … … … … … … … 51 Non-ore-bearing magma 59.1 1.9 0.7 0.8 1.5 52 Non-ore-bearing magma 60.5 1.6 0.6 0.9 1.7 … … … … … … …

[0059] The second step is to generate the incompatible element ratio matrix and quantize the feature tensor. Specifically:

[0060] Calculate the ratio for any set of magma samples, where:

[0061] Ba / Zr ratio The expression is: ;

[0062] Nb / Y ratio The expression is: ;

[0063] U / Yb ratio The expression is: ;

[0064] V / Y ratio The expression is: ;

[0065] in, Indicates the content of Ba in the magma sample; Indicates the content of Zr element in the magma sample; Indicates the content of Nb element in the magma sample; Indicates the content of element Y in the magma sample; Indicates the content of U element in the magma sample; Indicates the content of V element in the magma sample; Indicates the content of Yb element in the magma sample.

[0066] by{ , , , } as the basic feature component to construct the sample high-dimensional ratio feature tensor .

[0067] The third step is to construct a high-dimensional feature interface based on the feature tensor to conduct preliminary screening of mineralization potential and mark preliminary discrimination labels.

[0068] Here, set the classification criteria, if it meets > R 1, > R 2, > R 3, the sample is determined to be a magma with gold mineralization potential, otherwise it is a non-ore-forming magma. R 1. R 2. R 3 is the set discrimination threshold.

[0069] The samples were mapped to the Ba / Zr–SiO2 two-dimensional projection plane, and a preliminary discriminant scatter plot was drawn to observe the differentiation and clustering of mineralized and non-mineralized samples, and the preliminary discriminant labels of the samples in the high-dimensional space were recorded.

[0070] The fourth step is to qualitatively determine the entropy flow of magma water, which specifically includes the following steps:

[0071] Magma samples containing preliminary discriminant labels were plotted in the V / Y–Ba / Zr projection subspace to determine distribution patterns. Near-horizontal trends likely indicate high water content and late degassing in magma, which is favorable for gold mineralization; near-vertical trends likely indicate low water content and early degassing in magma, which is unfavorable for gold mineralization.

[0072] Here, the V / Y–Ba / Zr relationship is used to reveal the entropy flow disturbance characteristics, which serves as an important auxiliary indicator of mineralization potential.

[0073] The fifth step is to map the source area enrichment factor and reversely infer the fluid enrichment, which specifically includes the following steps:

[0074] (501) The magma samples identified as having mineralization potential in the third and fourth steps are plotted in the U / Yb–Nb / Y two-dimensional subspace to construct a source area enrichment map.

[0075] (502) Determine the nature of the source area, where: high U / Yb and high Nb / Y samples may indicate an enriched lithospheric mantle source; low U / Yb and low Nb / Y samples may indicate a depleted asthenosphere source. For example: when determining the nature of the source area, based on the ratio coordinates plotted in the U / Yb–Nb / Y projection space, set the following criteria: when the U / Yb ratio of the sample is not less than 1.5 and the Nb / Y ratio is not less than 1.0, it indicates that its source area may be an enriched lithospheric mantle with a gold mineralization geochemical origin; when the U / Yb ratio of the sample is not higher than 0.8 and the Nb / Y ratio is not higher than 0.6, it indicates that its source area may be a depleted asthenosphere or ordinary forearc mantle with weak mineralization potential; samples between the above ranges can be further comprehensively evaluated by combining the ratio information in steps 3 and 4.

[0076] The sixth step is to conduct multi-domain discrimination fusion and comprehensive weighted assessment of mineralization potential based on preliminary discrimination labels, entropy flow disturbance characteristics and source area properties.

[0077] Here, the mineralization potential function S is constructed based on the preliminary discrimination labels, entropy flow disturbance characteristics and source area properties, and its expression is:

[0078]

[0079] in, Indicates Ba / Zr ratio , Nb / Y ratio and U / Yb ratio The mineralization potential information represented by the constructed high-dimensional tensor features; It represents the magma water content trend and entropy flow disturbance information revealed based on the V / Y–Ba / Zr projection relationship; Indicates the U / Yb ratio and Nb / Y ratio Constructed information on source area enrichment properties and genesis types.

[0080] Table 2 is the specific correspondence table of functions

[0081]

[0082] Furthermore, the mineralization potential function S is used to divide any magma sample to form the spatial distribution of gold mineralization potential of the magma system.

[0083] like Figures 2 to 4 As shown, Figure 2 The distribution of gold-ore magma and non-ore magma samples on the Ba / Zr–SiO2 projection plane is shown. Figure 2 It can be seen that the two types of samples show an obvious partitioning and clustering trend in the two-dimensional space, indicating that the constructed high-dimensional ratio feature tensor has good differentiation ability and can effectively support the preliminary identification of mineralization potential, reflecting the discriminant visibility of the method of the present invention under low-dimensional projection. Figure 3 It can be seen that the distribution of magma samples with mineralization potential tends to be horizontal, while the distribution of non-ore-bearing samples is mostly vertical, reflecting significant differences in the magma's water content and degassing stage. This trend reveals the coupling relationship between entropy flow perturbation characteristics and mineralization affinity, verifying the effectiveness and explanatory power of this method in identifying magma evolution stages. Figure 4 The distribution pattern of samples in the two-dimensional space constructed by the ratios of U / Yb and Nb / Y is shown. Figure 4 It can be seen that the enriched source area samples and the depleted source area samples form two obvious trend zones, indicating that this method can effectively infer the source area composition type of the magma and identify the lithospheric mantle or asthenosphere source based on this. This further supports the advantages of the present invention in tracing the genesis and inferring the source area, and provides a reliable basis for judging the geochemical genesis of the gold mineralization system. Figures 2 to 4 The effectiveness, resolution and interpretation ability of this embodiment in identifying gold mineralization potential were verified from three aspects: preliminary differentiation, magma entropy flow characteristics and source area genesis, and it has good practical applicability and regional promotion prospects.

[0084] The above embodiments are only preferred embodiments of the present invention and are not intended to limit the scope of protection of the present invention. Any changes that adopt the design principles of the present invention and any changes made through non-creative work on this basis should fall within the scope of protection of the present invention.

Claims

1. A gold magma identification method based on high-dimensional element ratio phase space differentiation, characterized in that: The following steps are involved: Step S1, constructing an element abundance spectrum for the collected magma sample and performing sample spectrum screening; Step S2, generating an incompatible element ratio matrix using the screened element abundance spectrum and performing feature tensor quantization processing; Step S3: construct a high-dimensional feature interface based on the feature tensor, perform preliminary screening of the mineralization potential, and mark the preliminary discrimination label; Step S4, performing qualitative discrimination of the magma water entropy flow on the magma sample containing the preliminary discrimination label to obtain the entropy flow disturbance characteristics, which includes the following steps: Plot the magma samples containing preliminary discrimination labels in step S3 in the V / Y–Ba / Zr projection subspace and determine their distribution patterns; Analyze the water content trend and entropy flow disturbance characteristics, obtain the entropy flow disturbance characteristics, and obtain magma samples with mineralization potential; Step S5, based on the results of qualitative identification of magma water entropy flow, performs source area enrichment factor mapping and fluid enrichment inverse deduction to obtain source area properties, including the following steps: The magma samples that have been preliminarily screened and determined to be gold mineralization potential magmas in steps S3 and S4 are mapped in the U / Yb–Nb / Y two-dimensional subspace to construct a source enrichment map, and the source composition type and evolution characteristics are inferred based on the sample distribution trend; Step S6: Perform multi-domain discrimination fusion and comprehensive weighted evaluation of mineralization potential based on preliminary discrimination labels, entropy flow disturbance characteristics, and source area properties.

2. The method for identifying gold magma based on high-dimensional element ratio phase space differentiation according to claim 1, characterized in that: In step S1, the element abundance spectrum of the collected magma sample is constructed and the sample spectrum is screened, which includes the following steps: collecting the magma sample and measuring the content of Ba, Zr, Nb, Y, U, Yb, V, and SiO2 elements to form an element abundance spectrum matrix C ; Magma samples with significant secondary transformation were screened and eliminated based on the degree of alteration, mineral fidelity and element ratio anomalies of the magma samples.

3. The gold magma identification method based on high-dimensional element ratio phase space differentiation according to claim 2 is characterized in that: In step S2, the incompatible element ratio matrix is ​​generated using the screened element abundance spectrum and a feature tensor quantization process is performed, which includes the following steps: Calculate the ratio of any set of magma samples, where: Ba / Zr ratio The expression is: ; Nb / Y ratio The expression is: ; U / Yb ratio The expression is: ; V / Y ratio The expression is: ;in, Indicates the content of Ba in the magma sample; Indicates the content of Zr element in the magma sample; Indicates the content of Nb element in the magma sample; Indicates the content of element Y in the magma sample; Indicates the content of U element in the magma sample; Indicates the content of V element in the magma sample; Indicates the content of Yb element in magma sample; As the basic feature component, construct the sample high-dimensional ratio feature tensor .

4. The method for identifying gold magma based on high-dimensional element ratio phase space differentiation according to claim 3, characterized in that: In step S3, a high-dimensional feature interface is constructed based on the feature tensor to perform preliminary screening of the mineralization potential and mark preliminary discrimination labels, including the following steps: Preset classification threshold R 1. R 2. R 3. If , , ; then the magma sample is a gold mineralization potential magma; otherwise, it is a non-ore-forming magma; Map the magma samples collected in step S1 onto the Ba / Zr–SiO2 two-dimensional projection plane to observe the differentiation and aggregation of gold mineralization potential magma and non-ore-forming magma; According to the differentiation and aggregation of gold mineralization potential magma and non-ore-forming magma, the preliminary discrimination labels of magma samples in high-dimensional space are marked.

5. The method for identifying gold magma based on high-dimensional element ratio phase space differentiation according to claim 4, characterized in that: In the step S6, multi-domain discrimination fusion and comprehensive weighted evaluation of metallogenic potential are performed according to the preliminary discrimination labels, entropy flow disturbance characteristics and source area properties, including the following steps: constructing a metallogenic potential function S according to the preliminary discrimination labels, entropy flow disturbance characteristics and source area properties, and its expression is: in, Indicates Ba / Zr ratio , Nb / Y ratio and U / Yb ratio The mineralization potential information represented by the constructed high-dimensional tensor features; It represents the magma water content trend and entropy flow disturbance information revealed based on the V / Y–Ba / Zr projection relationship; Indicates the U / Yb ratio and Nb / Y ratio Constructed information on the enrichment properties and genetic types of the source area; A preliminary metallogenic potential scoring function representing a high-dimensional tensor space; Represents the scoring function for mapping magma water content trend to entropy flow disturbance; represents the source region enrichment factor mapping scoring function; The mineralization potential function S is used to divide any magma sample and form the spatial distribution of gold mineralization potential of the magma system.

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