A method for comprehensively optimizing a prospecting target area

Abstract

The application relates to the technical field of geological prospecting, and provides a method for comprehensively optimizing a prospecting target area. In the method, a grade interval boundary limit value of a target area metallogenic possibility is determined, a comment set score model corresponding to the grade interval is constructed, a score matrix of a geochemical exploration index of the prospecting target area and a score matrix of a geological index are generated; then, according to a corresponding weight matrix, a membership score matrix of the geochemical exploration index and the geological index of the prospecting target area in the grade interval is calculated respectively, so as to determine an index score comment of the prospecting target area in the grade interval; and according to the grade membership of the prospecting target area in the grade interval and the interval upper limit value of the grade interval in the index score comment, the comprehensive membership of the prospecting target area is calculated, and the optimized prospecting target area is output by sorting the comprehensive memberships of all the prospecting target areas. Therefore, the optimized prospecting target area is scientifically determined through theoretical calculation, and the deviation and interference of human factors are effectively avoided.

Description

Technical Field

[0001] This application relates to the field of geological prospecting technology, and in particular to a method for comprehensively optimizing prospecting target areas. Background Technology

[0002] The formation of mineral deposits involves complex geological processes coupled with temporal and spatial factors. Precise location of prospecting target areas is a crucial method for discovering mineral deposits and holds significant practical importance in the field of geological prospecting. In complex geological processes and metallogenic environments, efficient and low-cost selection of prospecting target areas is key to finding strategic and critical mineral resources.

[0003] Traditional mineral exploration target areas involve obtaining basic data such as geological, geophysical, geochemical, and remote sensing information through geological surveys or by setting up sampling points along survey lines and terrain within the target area or regional anomaly target area. Then, professionals process and interpret the basic data according to standards. Based on the data interpretation results, potential mineral resource-rich areas within the target area or regional anomaly target area are identified, and then verified through mining engineering. Summary of the Invention

[0004] The purpose of this application is to provide a method for comprehensively optimizing mineral exploration target areas to solve or alleviate the problems existing in the prior art.

[0005] To achieve the above objectives, this application provides the following technical solution:

[0006] This application provides a method for comprehensively optimizing mineral exploration target areas, including: determining the mineralization probability level of the target area. The boundary limits of each level interval; where, It is a positive integer; through the construction of the AND The comment collection corresponding to each level range Scoring Model and The boundary limits of each level interval are used to generate the first optimal target area within the defined target area. Scoring matrix of geochemical indicators for a mineral exploration target area Scoring matrix of geological indicators ;

[0007] Based on the scoring matrix of geochemical indicators Scoring matrix of geological indicators and the corresponding weight matrix, respectively calculate the first The geochemical and geological indicators of each prospecting target area are in The membership score matrix of the nth level interval is used to determine the nth level interval. A mineral exploration target area in Indicator score comments for each level range ;in, , For the first The first mineral exploration target area in the first The degree of membership of each level interval;

[0008] Comments based on indicator scores The Middle A mineral exploration target area in The degree of membership of each level interval and The upper limit of the interval of the first level interval is calculated. Comprehensive affiliation of a mineral exploration target area Based on the ranking of the comprehensive membership of all prospecting target areas within the determined preferred target area range, the preferred prospecting target area is output.

[0009] Preferably, the target area mineralization probability level is constructed. Level judgment matrix for each level range And the level judgment matrix Perform a consistency check;

[0010] Response to the level judgment matrix Through consistency verification, the initial weights of each level interval are normalized to obtain the normalized weights of the level intervals.

[0011] Based on the normalized weights of the grade intervals, the grade differences of the determined mineralization probability grades of the target area are distributed proportionally to determine the boundary limits of adjacent grade intervals.

[0012] Preferably, through the construction of and The comment collection corresponding to each level range The scoring model, based on the determined preferred target area, is used to assign scores to the target region. Evaluation scores for each geological indicator in each prospecting target area as well as The boundary limits of the i-th level interval are generated to produce the i-th level interval. Each geological indicator in a prospecting target area is rated in each grade range to construct the first... Scoring matrix of geological indicators for mineral exploration target areas ;in, , , For the first The geological indicators of the first prospecting target area were in the first Grade ratings for each grade range;

[0013] as well as,

[0014] Through the construction and The comment collection corresponding to each level range The scoring model, based on the determined preferred target area, is used to assign scores to the target region. Evaluation scores for each geochemical index in a mineral exploration target area as well as The boundary limits of the i-th level interval are generated to produce the i-th level interval. For each geochemical index in a prospecting target area, a grade score is assigned within each grade range to construct the first... Scoring matrix of geochemical indicators for mineral exploration target areas ;in, , For the first Geophysical indicators of the first mineral exploration target area in the first The rating scale is divided into several levels.

[0015] Preferably, based on the generated integrated soil geochemical anomaly map, the first... Anomaly analysis was performed on the first prospecting target area to calculate the first... Standardized surface metal content of each element in a mineral exploration target area;

[0016] For the The elements in each prospecting target area are sorted according to their normalized surface metallicity, and then sorted according to their position in the target area. The preset proportions of each level range are used to generate evaluation scores for geochemical indicators. .

[0017] Preferably, according to the formula:

[0018]

[0019] Calculate the first The surface metal content of each element in each prospecting target area In the formula, For the first The average abnormal value of a single element in a mineral exploration target area; For the first The lower limit of anomalies for a single element in a mineral exploration target area; For the first The number of outliers of a single element in a mineral exploration target area; For the first Soil density of a mineral exploration target area; For the first Sampling depth of each mineral exploration target area; For the first The sampling unit area of ​​a mineral exploration target area.

[0020] Preferably, all prospecting target areas within the determined preferred target area range are projected onto an engineering geological map of a preset scale;

[0021] After cropping the corresponding area of ​​each prospecting target area on the engineering geological map, the geological factors within the cropped area of ​​each prospecting target area are identified.

[0022] The different types of geological factors in all identified prospecting target areas were sorted separately, and each type of geological factor was further classified into... The preset proportions of each grade range are used to generate evaluation scores for geological indicators in each prospecting target area. .

[0023] Preferably, the mineralization potential of the target area is divided into four levels, with corresponding evaluation sets. The scoring model is as follows:

[0024]

[0025] In the formula, These are the grade ratings of the prospecting target area in four grade ranges; These are the boundary limits between the four defined level intervals; This represents the evaluation score for the corresponding indicator. hour, , representing the evaluation score of geochemical indicators; hour, , representing the evaluation score of geological indicators; For mineral exploration target areas in The preset total score for each level range.

[0026] Preferably, all prospecting target areas within the defined preferred target area range are constructed. Correlation matrix of individual geochemical indicators The elements in the correlation matrix represent the correlation values ​​between any two geochemical indicators.

[0027] Response to the correlation matrix significance test value and applicability test value If the corresponding preset test conditions are met, then the correlation matrix is ​​calculated. The initial eigenvalues ​​are determined, and the initial eigenvalues ​​greater than 1 are identified as principal component sets. ;

[0028] For the correlation matrix The eigenmatrix composed of the initial eigenvalues ​​is orthogonally rotated to determine the eigenvalues ​​of all orthogonal rotation factor loadings of all elements.

[0029] Extract the element with the largest orthogonal rotation factor loading eigenvalue from each principal component group to construct an element combination; wherein the number of element combinations is equal to the number of principal component groups. The quantities are equal;

[0030] Each principal component group The initial feature values ​​are normalized to obtain the element combination weights of the corresponding element combinations. Furthermore, in each element combination, the orthogonal rotation factor loading eigenvalues ​​of each element are normalized to obtain the element weights of the corresponding elements. .

[0031] Preferably, according to the formula:

[0032]

[0033] Determine the correlation matrix The Middle Rotation angle of row elements In the formula, These are all intermediate variables and have no practical significance.

[0034] According to the formula:

[0035]

[0036] Determine element Factor loading eigenvalues In the formula, Correlation matrix medium elements and elements The initial eigenvalues, Correlation matrix medium elements and elements The initial eigenvalues.

[0037] Preferably, according to the formula:

[0038]

[0039] Calculate the first Among the geochemical indicators of a mineral exploration target area, the first one is... The combination of elements Membership score matrix for each level interval In the formula, For the first Among the geochemical indicators of a mineral exploration target area, the first one is... The element weight matrix of a combination of elements; For the first Among the geochemical indicators of a mineral exploration target area, the first one is... A score matrix consisting of combinations of elements; , For the first The number of element combinations classified by geochemical indicators for each mineral exploration target area; among which...

[0040]

[0041] For the first The first geochemical index classification of the mineral exploration target area In the combination of elements, the first element is... The element weight of each element; , For the first The first geochemical index classification of the mineral exploration target area The number of ore-forming elements contained in each element combination;

[0042]

[0043] In the formula, For the first The first geochemical index classification of the mineral exploration target area In the combination of elements, the first element is... The element in the first... The rating scale for each level range , The number of grade intervals for the mineralization probability level of the target area;

[0044] According to the formula:

[0045]

[0046] Calculate the first Geophysical indicators of a mineral exploration target area Membership score matrix for each level interval ;

[0047] In the formula, For the first A combined weight matrix of geochemical indicators for a mineral exploration target area; For the first The scoring matrix of geochemical indicators for each mineral exploration target area; where...

[0048]

[0049] In the formula, For the first The first geochemical index classification of the mineral exploration target area The element combination weight of a combination of elements;

[0050]

[0051] In the formula, For the first Among the geochemical indicators of a mineral exploration target area, the first one is... The score matrix of combinations of elements, For the first Among the geochemical indicators of a mineral exploration target area, the first one is... The combination of elements Membership score matrix for each level interval.

[0052] Preferably, according to the formula:

[0053]

[0054] Calculate the first Geological indicators of a mineral exploration target area Membership score matrix for each level interval In the formula, This is the weight matrix for geological indicators; For the first The score matrix of geological indicators for each mineral exploration target area

[0055]

[0056] For the first Among the geological indicators of a mineral exploration target area, the first is... The geological factors in the first The rating scale for each level range , This refers to the number of geological factors included in the geological indicators; , The number of grade intervals for the mineralization probability level of the target area; All are positive integers.

[0057] Preferably, according to the formula:

[0058]

[0059] Calculate the first A mineral exploration target area in Indicator score comments for each level range ;

[0060] In the formula, This is a combined index weight matrix;

[0061]

[0062] According to the formula:

[0063]

[0064] In the formula, For the first A graded score matrix for each mineral exploration target area; For the first Geophysical indicators of a mineral exploration target area Membership score matrix for each level interval, For the first Geological indicators of a mineral exploration target area Membership score matrix for each level interval.

[0065] Preferably, according to the formula:

[0066]

[0067] Calculate the first Comprehensive affiliation of a mineral exploration target area ;

[0068] In the formula, For the first The first mineral exploration target area in the first The degree of membership of each level interval, The target area is classified as the mineralization probability level. The upper limit of each level range.

[0069] Preferred,

[0070] Beneficial effects:

[0071] The method for comprehensively optimizing mineral exploration target areas provided in this application determines the mineralization probability level of the target area. The boundary limits of each level interval are determined, and the boundary limits are constructed using the... The comment collection corresponding to each level range Scoring Model and The boundary limits of each level interval are used to generate the first optimal target area within the defined target area. Scoring matrix of geochemical indicators for a mineral exploration target area Scoring matrix of geological indicators Furthermore, based on the scoring matrix of geochemical indicators... Scoring matrix of geological indicators and the corresponding weight matrix, respectively calculate the first The geochemical and geological indicators of each prospecting target area are in The membership score matrix of the nth level interval is used to determine the nth level interval. A mineral exploration target area in Indicator score comments for each level range Next, comments based on indicator scores. The Middle A mineral exploration target area in Calculate the membership degree and boundary limit of the level interval, and calculate the level interval. Comprehensive affiliation of a mineral exploration target area Furthermore, by ranking all prospecting target areas within the determined preferred target area range based on their comprehensive membership degree, the optimal prospecting target area is output. In this way, by inputting geological data such as stratigraphy, structure, and igneous rocks, along with basic soil chemical data in the form of weights and scores, and comprehensively considering different factors affecting mineralization, prospecting target areas can be located. High-resolution geological remote sensing images are no longer needed, and human bias and interference can be effectively avoided. The optimal prospecting target area is scientifically and rationally determined through theoretical calculations, resulting in stronger dynamic adaptability and higher discrimination accuracy. Attached Figure Description

[0072] The accompanying drawings, which form part of this application, are used to provide a further understanding of this application. The illustrative embodiments and descriptions of this application are used to explain this application and do not constitute an undue limitation of this application. Wherein:

[0073] Figure 1 This is a flowchart illustrating a method for comprehensively optimizing mineral exploration target areas according to some embodiments of this application;

[0074] Figure 2 This is a logical schematic diagram of a method for comprehensively optimizing mineral exploration target areas according to some embodiments of this application;

[0075] Figure 3 This is a profile of an exploration line of a target area determined according to the comprehensive and optimized prospecting target area method of this embodiment;

[0076] Figure 4 This is a profile of the exploration line of another target area determined according to the comprehensive optimization method for prospecting target areas in this embodiment. Detailed Implementation

[0077] The present application will now be described in detail with reference to the accompanying drawings and embodiments. Various examples are provided by way of explanation and not by way of limitation. In fact, those skilled in the art will understand that modifications and variations can be made to the present application without departing from the scope or spirit of the present application. For example, a feature shown or described as part of one embodiment may be used in another embodiment to produce yet another embodiment. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention should fall within the scope of protection of the embodiments of the present invention.

[0078] Precisely locating mineral exploration target areas within regional anomaly zones and prioritizing the deployment of effective exploration projects are crucial for discovering mineral deposits and hold significant practical value in the field of geological prospecting. However, traditional prospecting methods suffer from limitations such as requiring large numbers of personnel, equipment, and funds, resulting in long timeframes and low efficiency. Furthermore, due to differences in geological knowledge, capabilities, and experience among various geological disciplines, the potential mineral resource enrichment target areas provided inevitably contain biases and misjudgments. This makes it difficult to accurately and comprehensively optimize target areas within the target area or anomaly zones by integrating data from different geological disciplines, and thus hinders guidance for the deployment of subsequent exploration projects.

[0079] Currently, mineral exploration methods are primarily based on regional anomalies such as geochemical, gravity, magnetic, and hydrological data. However, a multi-level evaluation framework has not been established, making it difficult to quantitatively integrate metallogenic geological conditions with metallogenic anomaly elements. Therefore, this embodiment provides a method for comprehensively optimizing mineral exploration target areas. By embedding basic soil geochemical data, including stratigraphic, tectonic, and igneous rock conditions, into a mathematical model using weighted and scored methods through theoretical calculations, this method comprehensively considers various influencing factors of mineralization, couples multi-dimensional geological and geochemical information, and obtains more comprehensive and integrated information. Through theoretical calculations, the optimal mineral exploration target areas are scientifically and rationally determined, effectively avoiding biases and interference from human factors. This method exhibits stronger dynamic adaptability, higher discrimination accuracy, and more precise target area location, resulting in more accurate target area boundaries and improved accuracy and reliability of target area optimization.

[0080] In this embodiment, the classification of the mineralization probability level of the target area into four levels is used as an example for explanation; the principle for classifying other numbers of levels is the same. For example... Figures 1 to 4 As shown, the method for comprehensively optimizing mineral exploration target areas includes:

[0081] Step S101: Determine the mineralization probability level of the target area. Boundary limits for each level range.

[0082] In this embodiment, a set of evaluation criteria for the mineralization potential of the target area is constructed. According to the comment collection The number of rating levels is used to divide the rating range. For example, by referring to traditional geophysical and geochemical exploration results and geological information of exposed landmarks, the quality of mineral exploration target areas is judged, and a rating set of the mineralization potential of the target area is constructed. Correspondingly, the mineralization potential of the target area is divided into four levels: {excellent, good, medium, and poor}.

[0083] In this embodiment, geochemical data and metallogenic geological information of the target area are acquired to establish a comprehensive evaluation index system for the mineral exploration target area. In the comprehensive evaluation index system, metallogenic geological information and soil geochemical information are used as the target layers. The metallogenic geological information is decomposed into criterion layers such as stratigraphy, structure, and igneous rocks, and the enrichment of each element in the target area is used as the criterion layer for soil geochemical information.

[0084] Then, pairwise comparisons were made between different rating levels to quantify the relative importance of different rating levels and construct a mineralization probability rating system for the target area. ( A level judgment matrix containing (positive integer) level intervals. In this embodiment, each level interval is divided according to a preset ratio. For example, for each target area, the ratio of the relative importance of the levels in adjacent level intervals—Excellent-Good (D1), Good-Medium (D2), and Medium-Poor (D3)—is 2:2:3, resulting in:

[0085] Table 1. Distribution of relative importance of target zones.

[0086]

[0087] Furthermore, a target level judgment matrix is ​​constructed based on the target level importance distribution. ,have:

[0088]

[0089] Then, the consistency ratio is calculated using the analytic hierarchy process. Level judgment matrix Perform a consistency check, when the consistency ratio At that time, the level judgment matrix Consistency verification passed. At this point, the initial weights for each level interval are normalized to obtain the normalized weights for the corresponding level interval. In other words, first, the level judgment matrix is ​​calculated. The geometric mean of each row of elements is used as the initial weight for the relative importance of the corresponding level.

[0090] For example, for a relative importance level of Excellent-Good (D1), its geometric mean is: For the relative importance level of Excellent-Good (D2), the geometric mean is: For the relative importance level of Excellent-Good (D3), the geometric mean is: Correspondingly, the initial weight of the grade with relative importance of excellent-good (D1) is 0.88, the initial weight of the grade with relative importance of excellent-good (D2) is 0.88, and the initial weight of the grade with relative importance of excellent-good (D3) is 1.31.

[0091] Next, the initial weights of the relative importance of each level are normalized to obtain the normalized weights of the relative importance of each level. For example, the normalized weights of the initial weights of the relative importance of Excellent-Good (D1) level are:

[0092]

[0093] After normalizing the initial weights of the rank relative importance (D2) from good to medium, we have:

[0094]

[0095] After normalizing the initial weights of the relative importance of the ranks (D3), we have:

[0096]

[0097] In other words, the normalized weights for the relative importance of grades excellent-good (D1), good-medium (D2), and medium-poor (D3) are 0.29, 0.29, and 0.42, respectively.

[0098] Next, based on the normalized weights of relative importance, the grade differences of the determined mineralization probability grades of the target area are proportionally allocated to determine the boundary limits of adjacent grade intervals. For example, the grade differences of the target area's mineralization probability grades with relative importance of Excellent-Good (D1), Good-Medium (D2), and Medium-Poor (D3) are as follows: (for example, The total score difference of the mineralization probability level of the target area is ( For example, positive integers Then, the grade difference between the grade interval Excellent (D1) and the grade interval Good (D2) is:

[0099]

[0100] In other words, the grade difference between the "Excellent" and "Good" grade ranges is... (15 points). Using the same method, the grade difference between the grade interval "Good" and the grade interval can be obtained as follows: (15 points); The grade difference between the grade interval and the grade interval difference is: (20 points)

[0101] Then, set the total score for each level. The intervals are divided according to the grade difference, resulting in the numerical range of each grade interval. For example, the grade difference between the "Excellent" and "Good" grade intervals is... (15 points), then the numerical range of the grade interval "excellent" is:

[0102]

[0103] The difference between the grade range "Good" and the grade range within the grade range is (15 points), then the numerical range of the grade interval "Good" (D2) is:

[0104]

[0105] The grade difference between the grade interval and the grade interval difference is: (20 points), then the numerical range of (D3) in the grade interval is:

[0106]

[0107] The numerical range of the grade interval difference (D4) is:

[0108]

[0109] Step S102, through the construction and The comment collection corresponding to each level range Scoring Model and The boundary limits of each level interval are used to generate the first optimal target area within the defined target area. Scoring matrix of geochemical indicators for a mineral exploration target area Scoring matrix of geological indicators .

[0110] In this embodiment, The mineralization potential of the target area is divided into four levels, and a system is constructed based on this. The comment collection corresponding to each level range The scoring model will be used as an example for explanation; at the same time, the boundary limits between the grade intervals of Excellent, Good, and Medium and the grade intervals of Poor are defined as follows: ,have:

[0111]

[0112] Correspondingly constructed comment set The scoring model is as follows:

[0113]

[0114] In the formula, These are the grade ratings of the prospecting target area in four grade ranges; These are the boundary limits between the four defined level intervals; This represents the evaluation score for the corresponding indicator. hour, , representing the evaluation score of geochemical indicators; hour, , which represents the evaluation score of geological indicators.

[0115] In this embodiment, the evaluation score of the geological indicators is determined. Based on the acquired regional and mining area geological data, all prospecting target areas within the determined preferred target area are projected onto an engineering geological map at a preset scale (e.g., 1:10000 or 1:5000). The corresponding area of ​​each prospecting target area on the engineering geological map is then cropped, and the geological factors (strata, structures, igneous rocks) within the cropped area of ​​each prospecting target area are identified. It should be noted that the identification of geological factors (strata, structures, igneous rocks) within the cropped area of ​​the prospecting target area can employ neural network methods (image recognition methods, etc.) or identification methods based on large-scale artificial intelligence models. Specifically, the image of the cropped area of ​​the prospecting target area is input into a neural network or large-scale artificial intelligence model, which automatically identifies the geological factors and outputs the identification results.

[0116] Next, the different types of geological factors in all identified prospecting target areas were sorted, and each type of geological factor was ranked according to its... The evaluation score of geological indicators in each prospecting target area is obtained by calculating the preset proportions of each grade interval. For example, regarding geological factors (igneous rocks), all identified prospecting target areas containing geological factors (igneous rocks) are categorized according to the proportion of each grade range: excellent, good, medium, and poor. (for example, The data is divided into levels, and the number of geological elements (igneous rocks) contained in each level interval is obtained; and the difference is used to determine the number of geological elements (igneous rocks) contained in each level interval. Total Score (for example, The evaluation scores of geological factors (igneous rocks) for different prospecting target areas within each grade interval are determined. The specific process is the same as the method for determining the boundary limits of the grade interval, and will not be described in detail here.

[0117] Evaluation scores for geochemical indicators in determining mineral exploration target areas First, based on the generated integrated soil geochemical anomaly map, the first... Anomaly analysis was performed on a mineral exploration target area according to the formula:

[0118]

[0119] Calculate the first The surface metal content of each element in each prospecting target area In the formula, For the first The average abnormal value of a single element in a mineral exploration target area; For the first The lower limit of anomalies for a single element in a mineral exploration target area; For the first The number of outliers of a single element in a mineral exploration target area; For the first Soil density of a mineral exploration target area; For the first Sampling depth of each mineral exploration target area; For the first The sampling unit area of ​​a mineral exploration target area.

[0120] Then, for the first The elemental surface metal content of each prospecting target area was normalized, and the normalized surface metal content was sorted according to the element's position in the target area. The preset proportions of each level range are used to generate an evaluation score for each element. The specific process is the same as that for geological factors, and will not be described in detail here.

[0121] The evaluation scores of geochemical indicators for the mineral exploration target area were determined. and evaluation scores of geological indicators. Afterwards, through the construction and The comment collection corresponding to each level range Scoring model, combined with The boundary limits of the level intervals are generated respectively. The geological indicators of each prospecting target area are rated in each grade range and the grade score of the first prospecting target area. The grade score of geochemical indicators for each mineral exploration target area in each grade range.

[0122] In other words, the evaluation score of geochemical indicators in the mineral exploration target area will be used to determine the target area. as well as Input comment set for the boundary limits of each level interval The scoring model calculates the geochemical indicators for each mineral exploration target area. Level ratings for each level range ,in, For the first Geophysical indicators of the first mineral exploration target area in the first A rating system for each grade range. In a specific scenario, the elements of the prospecting target area are... The rating scores for each rating range are shown in Table 1, as follows:

[0123] Table 1 Scoring Table for Geochemical Exploration Indicators

[0124]

[0125] Evaluation scores of geological indicators of mineral exploration target areas as well as Input comment set for the boundary limits of each level interval The scoring model calculates the geological indicators of each prospecting target area. Level ratings for each level range ,in, For the first Geological factors of the first prospecting target area in the first The rating is divided into several grade ranges. In a specific scenario, the geological indicators of the prospecting target area are... The rating scores for each rating range are shown in Table 2, as follows:

[0126] Table 2 Scoring Table for Geological Indicators

[0127]

[0128] Furthermore, through the first Geological indicators of a mineral exploration target area Level ratings for each level range Construct the first Scoring matrix of geological indicators for mineral exploration target areas ; through the first Geophysical indicators of a mineral exploration target area Level ratings for each level range Construct the first Scoring matrix of geochemical indicators for mineral exploration target areas It should be noted that the rating for each element is calculated based on its evaluation score within each rating range. (No. The first geochemical index classification of the mineral exploration target area In the combination of elements, the first element is... The element in the first... (Level rating for each level range); calculate the level rating for each element combination in each level range based on the evaluation score of the element combination. (No. Among the geochemical indicators of a mineral exploration target area, the first one is... (a score matrix of combinations of elements); where...

[0129]

[0130] Step S103: Based on the scoring matrix of geochemical indicators Scoring matrix of geological indicators and the corresponding weight matrix, respectively calculate the first The geochemical and geological indicators of each prospecting target area are in The membership score matrix of the nth level interval is used to determine the nth level interval. A mineral exploration target area in Indicator score comments for each level range .

[0131] In this embodiment, when determining the weights of each layer related to geochemical indicators, firstly, the correlation value between any two geochemical indicators (e.g., Pearson correlation coefficient) is calculated to measure the degree of correlation between the geochemical indicators, and then all prospecting target areas within the determined preferred target area are constructed based on the correlation values ​​between the geochemical indicators. Correlation matrix of individual geochemical indicators .

[0132] Then, calculate the correlation matrix. significance test value and applicability test value When the correlation matrix significance test value and applicability test value Each satisfies the corresponding preset test conditions (significance test value). And applicability test value When ), it indicates the mineral exploration target area. There is a strong correlation between the individual geochemical indicators. Next, the correlation matrix that meets the preset testing conditions is calculated. The initial eigenvalues ​​are determined, and the corresponding elements with initial eigenvalues ​​greater than 1 are identified as principal component groups. .

[0133] Specifically, for the correlation matrix that meets the preset test conditions Standardization is performed, and then through a diagonal matrix. (The eigenvalue of the diagonal elements is) , (positive integers) on the correlation matrix Perform decomposition calculations ( , (where the matrix is ​​orthogonal), and construct the characteristic polynomial. and Solving for the given information yields the following results. That is, the correlation matrix that meets the preset test conditions. The initial eigenvalues ​​are selected, and those with values ​​greater than 1 are used to divide the components into principal component groups. As shown in Table 3 below:

[0134] Table 3 Initial eigenvalues ​​and principal component sets of the correlation matrix R

[0135]

[0136] Next, the correlation matrix that meets the preset test conditions is... The eigenmatrix composed of the initial eigenvalues ​​is orthogonally rotated. Specifically, according to the formula:

[0137]

[0138] Determine the correlation matrix The Middle Rotation angle of row elements And according to the formula:

[0139]

[0140] Determine element Factor loading eigenvalues In the formula, These are all intermediate variables and have no practical significance. Correlation matrix medium elements and elements The initial eigenvalues, Correlation matrix medium elements and elements The initial eigenvalues. It should be noted here that... Correlation matrix No. Line number The data in the columns, and the diagonal matrix The Middle Line number If the eigenvalues ​​of the diagonal elements of a column are equal, then in the diagonal matrix... It has The eigenvalues ​​of the diagonal elements illustrate the correlation matrix. for OK The matrix of columns also indicates that the target area has a total of Each element has an orthogonal rotation factor load characteristic value. In a specific scenario, the orthogonal rotation factor load characteristic values ​​of each element are shown in Table 4. Table 4 is as follows:

[0141] Table 4. Orthogonal rotation factor loading eigenvalues ​​of elements

[0142]

[0143] After determining all orthogonal rotation factor loading eigenvalues ​​for all elements, each principal component group is extracted. Construct an element combination from the elements that have the largest orthogonal rotation factor loading eigenvalue. For example, for the element... Its largest orthogonal rotation factor loading eigenvalue is 0.535, which corresponds to the classification into principal component groups. For elements Its largest orthogonal rotation factor loading eigenvalue is 0.950, which corresponds to the classification into principal component groups. Other elements are partitioned into principal component groups using the same method. Finally, the principal component groups... The combination of elements in is: Principal component groups The combination of elements in is: Principal Components The combination of elements in is: Principal component groups The combination of elements in is: .

[0144] Then, each principal component group The initial feature values ​​are normalized to obtain the element combination weights of the corresponding element combinations. That is, for each principal component group The initial feature values ​​corresponding to the elements in the element combination are normalized to obtain the weight of the element combination. For example, principal component groups Element combination: , for elements ,element ,element The corresponding initial eigenvalues ​​are normalized to obtain the element combination ( The weight of ) Here, it is necessary to explain the correlation matrix. for OK The matrix of columns also indicates that the target area has a total of There are elements, therefore, the initial eigenvalue of any element should have . One, in element combination ( ) together have One data point, for By normalizing the data, we can obtain the element combination ( The weight of ) The weights of all element combinations can be obtained using the same method.

[0145] Simultaneously, by normalizing the orthogonal rotation factor loading eigenvalues ​​of each element combination, the element weights of the corresponding elements can be obtained. For example, for principal component groups Element combination ( ), for elements orthogonal rotation factor loading eigenvalues ​​( Normalizing the elements will yield the element(s). element weights Furthermore, by normalizing the elements in each combination of principal component groups, the element weight of each element can be obtained. .

[0146] Finally, based on the scoring matrix of geochemical indicators And the relative weights of geochemical indicators at each layer (element combination weights) Element weight ) Calculate the geochemical indicators of the prospecting target area The membership score matrix for each level interval. Specifically, firstly, according to the formula:

[0147]

[0148] Calculate the first Among the geochemical indicators of a mineral exploration target area, the first one is... The combination of elements Membership score matrix for each level interval In the formula, For the first Among the geochemical indicators of a mineral exploration target area, the first one is... The element weight matrix of a combination of elements; For the first Among the geochemical indicators of a mineral exploration target area, the first one is... A score matrix consisting of combinations of elements; , For the first The number of element combinations classified by geochemical indicators for each mineral exploration target area; among which...

[0149]

[0150] For the first The first geochemical index classification of the mineral exploration target area In the combination of elements, the first element is... The element weight of each element; , For the first The first geochemical index classification of the mineral exploration target area The number of elements contained in a combination of elements;

[0151]

[0152] In the formula, For the first The first geochemical index classification of the mineral exploration target area In the combination of elements, the first element is... The element in the first... The rating scale for each level range , This refers to the number of grade intervals for the mineralization probability level of the target area.

[0153] Then, according to the formula:

[0154]

[0155] Calculate the first Geophysical indicators of a mineral exploration target area Membership score matrix for each level interval In the formula, For the first The index weight matrix of geochemical indicators for a mineral exploration target area; For the first The scoring matrix of geochemical indicators for each mineral exploration target area; where...

[0156]

[0157] In the formula, For the first The first geochemical index classification of the mineral exploration target area The element combination weight of a combination of elements;

[0158]

[0159] In the formula, For the first Among the geochemical indicators of a mineral exploration target area, the first one is... The score matrix of combinations of elements, For the first Among the geochemical indicators of a mineral exploration target area, the first one is... The combination of elements Membership score matrix for each level interval.

[0160] In this embodiment, when determining the weights of geological factors, firstly, the importance value between any two geological factors is calculated to measure the degree of importance between them, and then the target area is constructed based on the importance values ​​between the geological factors. Importance matrix of geological factors The importance matrix is ​​calculated. of eigenvalues, and for Normalize the eigenvalues ​​to obtain Factor weights for each geological factor: Here, the importance matrix of The calculation method for each eigenvalue is the same as the calculation method for the normalized weights of the relative importance of the rank, and will not be repeated here.

[0161] Next, based on the scoring matrix of geological indicators And the weight matrix of geological indicators, calculate the first Geological indicators of a mineral exploration target area The membership score matrix for each level interval. Specifically, according to the formula:

[0162]

[0163] Calculate the first Geological indicators of a mineral exploration target area Membership score matrix for each level interval In the formula, This is the weight matrix for geological indicators; For the first The scoring matrix of geological indicators for each mineral exploration target area, where...

[0164]

[0165] In the formula, For the first The factor weights of each geological factor;

[0166]

[0167] For the first Among the geological indicators of a mineral exploration target area, the first is... The geological factors in the first The rating scale for each level range , This refers to the number of geological factors included in the geological indicators; , The number of grade intervals for the mineralization probability level of the target area; All are positive integers.

[0168] In this embodiment, based on the scoring matrix of geochemical indicators... Scoring matrix of geological indicators And the corresponding weight matrix, respectively, to obtain the first The geochemical and geological indicators of each prospecting target area are in Membership score matrix for each level interval Then, according to the formula:

[0169]

[0170] Determine the first Grade score matrix of mineral exploration target areas Furthermore, according to the formula:

[0171]

[0172] Calculate the first A mineral exploration target area in Indicator score comments for each level range In the formula, This is a combined index weight matrix for mineral exploration target areas. It should be noted here that the combined index weight matrix... In this embodiment, the combined weight matrix of geochemical and geological indicators is presented. That is, in the first Within each mineral exploration target area, geochemical and geological indicators have equal weights, with a weight value of 0.5 for each.

[0173] In the A mineral exploration target area in Indicator score comments for each level range The elements in the matrix are the element values ​​(numerical values) corresponding to each level range, i.e., the matrix. The elements in are respectively the first The evaluation of the indicator scores for each prospecting target area in each grade range ( That is to say, the first The prospecting target area belongs to the first The membership degree of each level interval is , by the A mineral exploration target area in The membership degree of each level interval constitutes a matrix. That is, the first A mineral exploration target area in Indicator score comments for each level range , For the first The first mineral exploration target area in the first The degree of membership of the rank interval indicates the rank of the rank interval. The first mineral exploration target area in the first The probability of each mineralization potential level.

[0174] Step S104: Comments based on indicator scores The Middle A mineral exploration target area in The degree of membership of each level interval and The upper limit of the interval of the first level interval is calculated. Comprehensive affiliation of a mineral exploration target area Based on the ranking of the comprehensive membership of all prospecting target areas within the determined preferred target area range, the preferred prospecting target area is output.

[0175] In this embodiment, the set total score for the grade will be... The intervals are divided according to the grade difference, resulting in the numerical range of each grade interval. For example, the grade difference between the "Excellent" and "Good" grade intervals is... (15 points), then the numerical range of the grade interval "excellent" is:

[0176]

[0177] The difference between the grade range "Good" and the grade range within the grade range is (15 points), then the numerical range of the grade interval "Good" is:

[0178]

[0179] The grade difference between the grade interval and the grade interval difference is: (20 points), then the numerical range in the grade interval is:

[0180]

[0181] The numerical range of the grade interval difference is:

[0182]

[0183] In other words, the upper limit of the "excellent" range is... The upper limit of the "good" grade range is [value missing]. The upper limit of the level range is The upper limit of the interval difference of the grade interval is .

[0184] After determining the upper limit of the grade range, follow the formula:

[0185]

[0186] Calculate the first Comprehensive affiliation of a mineral exploration target area In the formula, For the first The first mineral exploration target area in the first The degree of membership of each level interval, The target area is classified as the mineralization probability level. The upper limit of each level range.

[0187] When the mineralization probability level of the target area is divided into 4 levels, the upper limit of the optimal level range is [value missing]. The upper limit of the "good" grade range is [value missing]. The upper limit of the level range is The upper limit of the interval difference of the grade interval is ,at this time,

[0188]

[0189] Correspondingly, the first The overall membership degree of each prospecting target area is:

[0190]

[0191] Finally, the comprehensive membership degree of all prospecting target areas within the determined preferred target area is calculated and sorted, and the preferred prospecting target areas are output based on the sorting results.

[0192] In this embodiment, it is only necessary to deploy geochemical scanning surfaces, stream sediments, and gully soil sampling points in the target area or regional anomaly area to obtain basic analytical data of each element. The mineralization potential of the target area is comprehensively evaluated from two target layers and multiple factor layers, namely geological indicators (strata, structure, igneous rocks, etc.) and geochemical indicators. A multi-level comprehensive optimization model for mineral exploration target areas is established, and the optimized mineral exploration target areas are output. This effectively overcomes the problems of traditional mineral exploration methods, such as large number of personnel, equipment, funds, long time, and low efficiency, and provides reference and guidance for subsequent mineral exploration.

[0193] In the description of this invention, it should be understood that the terms "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0194] The above description is merely a preferred embodiment of this application and is not intended to limit this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A method for comprehensively optimizing mineral exploration target areas, characterized in that, include: Determining the mineralization probability level of the target area The boundary limits of each level interval; where, It is a positive integer; Through the construction and The comment collection corresponding to each level range Scoring Model and The boundary limits of each level interval are used to generate the first optimal target area within the defined target area. Scoring matrix of geochemical indicators for a mineral exploration target area Scoring matrix of geological indicators ; Based on the scoring matrix of geochemical indicators Scoring matrix of geological indicators and the corresponding weight matrix, respectively calculate the first The geochemical and geological indicators of each prospecting target area are in The membership score matrix for each level interval, and according to the formula: Calculate the first A mineral exploration target area in Indicator score comments for each level range ; , For the first The first mineral exploration target area in the first The degree of membership of each level interval; among which... This is a combined index weight matrix; According to the formula: Determine the first Grade score matrix of mineral exploration target areas In the formula, For the first Geophysical indicators of a mineral exploration target area Membership score matrix for each level interval, For the first Geological indicators of a mineral exploration target area Membership score matrix for each level interval; Comments based on indicator scores The Middle A mineral exploration target area in The degree of membership of each level interval and The upper limit of each level interval is determined by the formula: Calculate the first Comprehensive affiliation of a mineral exploration target area Based on the ranking of the comprehensive membership degrees of all prospecting target areas within the determined preferred target area range, the preferred prospecting target area is output; among which, For the first The first mineral exploration target area in the first The degree of membership of each level interval, The target area is classified as the mineralization probability level. The upper limit of each level range.

2. The method according to claim 1, characterized in that, Constructing the mineralization probability level of the target area Level judgment matrix for each level range and the level judgment matrix Perform a consistency check; Response to the level judgment matrix Through consistency verification, the initial weights of each level interval are normalized to obtain the normalized weights of the level intervals. Based on the normalized weights of the grade intervals, the grade differences of the determined mineralization probability grades of the target area are distributed proportionally to determine the boundary limits of adjacent grade intervals.

3. The method according to claim 1, characterized in that, Through the construction and The comment collection corresponding to each level range The scoring model, based on the determined preferred target area, is used to assign scores to the target region. Evaluation scores for each geological indicator in each prospecting target area as well as The boundary limits of the i-th level interval are generated to produce the i-th level interval. Each geological indicator in a prospecting target area is rated in each grade range to construct the first... Scoring matrix of geological indicators for mineral exploration target areas ;in, , , For the first The geological indicators of the first prospecting target area were in the first Grade ratings for each grade range; as well as, Through the construction and The comment collection corresponding to each level range The scoring model, based on the determined preferred target area, is used to assign scores to the target region. Evaluation scores for each geochemical index in a mineral exploration target area as well as The boundary limits of the i-th level interval are generated to produce the i-th level interval. For each geochemical index in a prospecting target area, a grade score is assigned within each grade range to construct the first... Scoring matrix of geochemical indicators for mineral exploration target areas ;in, , For the first Geophysical indicators of the first mineral exploration target area in the first The rating scale is divided into several levels.

4. The method according to claim 1, characterized in that, The mineralization potential of the target area is divided into four levels, with corresponding evaluation criteria. The scoring model is as follows: In the formula, These are the grade ratings of the prospecting target area in four grade ranges; These are the boundary limits between the four defined level intervals; This represents the evaluation score for the corresponding indicator. hour, , representing the evaluation score of geochemical indicators; hour, , representing the evaluation score of geological indicators; For mineral exploration target areas in The preset total score for each level range.

5. The method according to claim 1, characterized in that, Construct all mineral exploration target areas within the defined preferred target area range. Correlation matrix of individual geochemical indicators The elements in the correlation matrix represent the correlation values ​​between any two geochemical indicators. Response to the correlation matrix significance test value and applicability test value If the corresponding preset test conditions are met, then the correlation matrix is ​​calculated. The initial eigenvalues ​​are determined, and the initial eigenvalues ​​greater than 1 are identified as principal component sets. ; For the correlation matrix The eigenmatrix composed of the initial eigenvalues ​​is orthogonally rotated to determine the eigenvalues ​​of all orthogonal rotation factor loadings of all elements. Extract the element with the largest orthogonal rotation factor loading eigenvalue from each principal component group to construct an element combination; wherein the number of element combinations is equal to the number of principal component groups. The quantities are equal; Each principal component group The initial feature values ​​are normalized to obtain the element combination weights of the corresponding element combinations. Furthermore, in each element combination, the orthogonal rotation factor loading eigenvalues ​​of each element are normalized to obtain the element weights of the corresponding elements. .

6. The method according to claim 5, characterized in that, According to the formula: Determine the correlation matrix The Middle Rotation angle of row elements In the formula, These are all intermediate variables and have no practical significance. According to the formula: Determine element Factor loading eigenvalues In the formula, Correlation matrix Middle elements and elements The initial eigenvalues, Correlation matrix Middle elements and elements The initial eigenvalues.

7. The method according to claim 5, characterized in that, According to the formula: Calculate the first Among the geochemical indicators of a mineral exploration target area, the first one is... The combination of elements Membership score matrix for each level interval In the formula, For the first Among the geochemical indicators of a mineral exploration target area, the first one is... The element weight matrix of a combination of elements; For the first Among the geochemical indicators of a mineral exploration target area, the first one is... A score matrix consisting of combinations of elements; , For the first The number of element combinations classified by geochemical indicators for each mineral exploration target area; among which... For the first The first geochemical index classification of the mineral exploration target area In the combination of elements, the first element is... The element weight of each element; , For the first The first geochemical index classification of the mineral exploration target area The number of elements contained in a combination of elements; In the formula, For the first The first geochemical index classification of the mineral exploration target area In the combination of elements, the first element is... The element in the first... The rating scale for each level range , The number of grade intervals for the mineralization probability level of the target area; According to the formula: Calculate the first Geophysical indicators of a mineral exploration target area Membership score matrix for each level interval ; In the formula, For the first A combined weight matrix of geochemical indicators for a mineral exploration target area; For the first The scoring matrix of geochemical indicators for each mineral exploration target area; where... In the formula, For the first The first geochemical index classification of the mineral exploration target area The element combination weight of a combination of elements; In the formula, For the first Among the geochemical indicators of a mineral exploration target area, the first one is... The score matrix of combinations of elements, For the first Among the geochemical indicators of a mineral exploration target area, the first one is... The combination of elements Membership score matrix for each level interval.

8. The method according to claim 1, characterized in that, According to the formula: Calculate the first Geological indicators of a mineral exploration target area Membership score matrix for each level interval In the formula, This is the weight matrix for geological indicators; For the first The score matrix of geological indicators for each mineral exploration target area For the first Among the geological indicators of a mineral exploration target area, the first is... The geological factors in the first The rating scale for each level range , This refers to the number of geological factors included in the geological indicators; , The number of grade intervals for the mineralization probability level of the target area; All are positive integers.

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