Regional geochemical data processing method, system, storage medium and terminal

Abstract

The present invention discloses a method, system, storage medium, and terminal for processing regional geochemical data, belonging to the field of electronic digital data processing. The method comprises: S1, for regional geochemical concentration data of a specific element, traversing and calculating the curvature at all sampling points to obtain the local concavity and convexity of the concentration data; S2, traversing the element concentration data at all sampling points and modifying the curvature to maintain the local element concentration extreme value; S3, traversing the element concentration data at all sampling points and replacing the element concentration data with adjacent values according to the curvature sign; S4, iteratively repeating steps S1-S3 until the element concentration data converges to a trapezoidal shape. The present invention proposes a new trapezoidalization operator that automatically grades element concentrations through curvature-driven nonlinear iteration and identifies element concentration centers and abrupt change boundaries, solving the problems of fuzzy boundaries and strong subjectivity in traditional methods.

Description

Technical Field

[0001] The present invention relates to the field of electronic digital data processing, and in particular to a regional geochemical data processing method, system, storage medium and terminal, which are used to perform abnormal classification of geochemical element concentrations in a given region and identify element concentration centers and abrupt change boundaries. The method can be widely used in environmental geochemical surveys, solid mineral exploration and geological science research. Background Art

[0002] Regional geochemical anomalies reveal how the concentrations of specific elements vary with sampling location, providing valuable insights and evidence for environmental surveys, mineral exploration, and scientific research. The processing and analysis of regional geochemical data has traditionally relied on methods such as contour mapping, statistical classification, and manual interpretation. However, these methods exhibit significant limitations in practical application.

[0003] In contour maps, geochemical data are interpolated to produce smooth contour maps. While these maps can accurately reflect the spatial distribution trends of element concentrations, the inherent characteristics of the interpolation algorithm can oversmooth abrupt changes in features such as mineralization boundaries and lithologic contacts. This leads to a lack of hierarchy in anomaly classification and insufficient identification of anomaly boundaries. For example, in magmatic and hydrothermal deposits, element concentrations often exhibit sharp changes near rock-mass contacts, and traditional contour maps are unable to effectively preserve this abrupt change, resulting in significant errors in the positioning of exploration targets. While statistical analysis methods (such as mean ± 2 standard deviations) can identify anomalous areas based on data distribution characteristics, they assume a normal distribution. Actual geochemical data are often influenced by multiple geological processes, exhibiting multimodal or skewed distributions. This can cause the statistical anomaly range to deviate from the true mineralized area. For example, in areas of intense weathering, surface processes may enrich certain elements (such as Au and As) at the surface, masking some mineralization at depth. In such cases, anomaly delineation methods based on global statistics may overestimate or underestimate the mineralization potential. In addition, abnormal thresholds (such as 85% or 90% quantiles) are usually set based on manual experience and lack objective standards. Different interpreters may come to different conclusions, affecting the repeatability and comparability of the data.

[0004] In summary, the core problems of existing regional geochemical data processing methods are: (1) lack of hierarchical anomaly classification, making it difficult to automatically distinguish anomalies of different intensities; (2) insufficient boundary recognition ability, which cannot effectively capture the sudden change characteristics of element concentrations; and (3) excessive reliance on manual experience, resulting in highly subjective interpretation results. These shortcomings seriously restrict the accurate application of geochemical data, and a new method that can automatically classify anomalies and identify abrupt change boundaries is urgently needed. Summary of the Invention

[0005] The purpose of the present invention is to overcome the technical problems existing in the prior art and provide a regional geochemical data processing method, system, storage medium and terminal. Based on a curvature-driven trapezoidal operator, the geochemical data is converted into a stepped distribution through nonlinear iteration, thereby generating a graded concentration domain and highlighting the abrupt boundary and concentration center.

[0006] The object of the present invention is achieved through the following technical solutions:

[0007] In a first aspect, a method for processing regional geochemical data is provided, comprising:

[0008] S1. For the regional geochemical concentration data of a specific element, the curvature at all sampling points is calculated to obtain the local concavity and convexity of the concentration data;

[0009] S2, traverse the element concentration data at all sampling points and modify the curvature so that the local element concentration extreme value remains unchanged;

[0010] S3, traverse the element concentration data at all sampling points, and replace the adjacent values of the element concentration data according to the curvature sign;

[0011] S4. Iteratively repeat steps S1-S3 until the element concentration data converges into a trapezoid.

[0012] In some embodiments, the traversal calculates the curvature at all sampling points, including:

[0013] For one-dimensional equally spaced geochemical data, the curvature is calculated according to the following formula:

[0014] ;

[0015] in, Indicates the cross-sectional coordinates of a chemical element x The concentration at represents the sampling interval, The cross-sectional coordinates of a chemical element x The element concentration curvature at ;

[0016] For two-dimensional gridded geochemical data, the curvature is calculated according to the following formula:

[0017] ;

[0018] in, Represents a chemical element in a plane coordinate x , y The concentration at and Respectively indicate along x He Yan y The sampling spacing in the direction, For a chemical element in the plane coordinate x , y The element concentration curvature at , the subscripts i-1, i, i+1 represent the numbers of three adjacent measuring points in the x direction, and the subscripts j-1, j, j+1 represent the numbers of three adjacent measuring points in the y direction.

[0019] In some embodiments, obtaining local concavity and convexity of concentration data includes:

[0020] like or , indicating that the current element concentration anomaly is in a local depression;

[0021] like or , indicating that the current element concentration anomaly is in a local bulge (i.e., near the local peak);

[0022] like or , indicating that the current data is in a flat area.

[0023] In some embodiments, step S2 specifically includes:

[0024] For one-dimensional equally spaced geochemical data, if satisfy:

[0025] ;

[0026] Then order ;

[0027] For two-dimensional gridded geochemical data, if At the same time:

[0028] ;

[0029] Then order .

[0030] In some embodiments, step S3 specifically includes:

[0031] If the curvature is positive, the center point value is replaced by the minimum value in the neighborhood; if the curvature is negative, the center point value is replaced by the maximum value in the neighborhood; if the curvature is zero, the center point value remains unchanged.

[0032] In some embodiments, step S4 specifically includes:

[0033] For one-dimensional equally spaced geochemical data, the iteration termination condition is:

[0034] ;

[0035] in, N Represents the number of observation points, superscript k and k -1 represents the kth iteration and k -Result of 1 iteration;

[0036] For 2D gridded geochemical data, the iteration termination condition is:

[0037] ;

[0038] in, N and M Respectively represent the x Direction and y The number of observation points in the direction, superscript k and k -1 represents the kth iteration and k -Results of 1 iteration.

[0039] In a second aspect, a regional geochemical data processing system is provided, comprising:

[0040] The curvature calculation module is used to traverse and calculate the curvature of all sampling points in the regional geochemical concentration data of a specific element to obtain the local concavity and convexity of the concentration data;

[0041] The local extreme value protection module is used to traverse the element concentration data at all sampling points and modify the curvature to keep the local element concentration extreme value unchanged;

[0042] The adjacent value replacement module is used to traverse the element concentration data at all sampling points and replace the adjacent values of the element concentration data according to the curvature sign;

[0043] The iterative update module is used to iteratively and repeatedly execute the curvature calculation module, the local extreme value protection module, and the adjacent value replacement module in sequence until the element concentration data converges to a trapezoid.

[0044] In a third aspect, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the regional geochemical data processing method described in the first aspect is implemented.

[0045] In a fourth aspect, a terminal is provided, comprising a memory and a processor, wherein the memory stores computer instructions that can be executed on the processor, and when the processor executes the computer instructions, the regional geochemical data processing method described in the first aspect is executed.

[0046] It should be further explained that the technical features corresponding to the above embodiments can be combined or replaced with each other to form a new technical solution if there is no conflict.

[0047] Compared with the prior art, the present invention has the following beneficial effects:

[0048] The present invention provides a trapezoidalization operator that uses curvature analysis to identify the convex and concave characteristics of element concentrations at the current sampling point, and then replaces them with the minimum or maximum values of the element concentrations at adjacent sampling points, while preserving the local extremes of element concentration. By repeatedly performing this operation, geochemical data can be transformed into an anomalous form resembling a stepped distribution. This form naturally reflects the hierarchical characteristics of element concentrations, automatically grading element concentrations and identifying element concentration centers and abrupt transition boundaries. A significant advantage of the present iterative process is that it does not rely on human intervention or require the data to meet the prerequisite of a normal distribution, thus addressing the fuzzy boundaries and strong subjectivity of traditional methods. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 A flow chart of a method for processing regional geochemical data according to an embodiment of the present invention;

[0050] Figure 2 The original observed anomaly of arsenic (As) on the exploration line profile of a low-temperature hydrothermal deposit in Guizhou and the result after trapezoidal processing are shown in an embodiment of the present invention;

[0051] Figure 3 This is an original abnormal plan view of lithium (Li) elements in a pegmatite-type lithium mining area according to an embodiment of the present invention ( Figure 3 a) and the result after trapezoidal processing ( Figure 3 b). DETAILED DESCRIPTION

[0052] The technical solutions of the present invention are described clearly and completely below in conjunction with the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all of the embodiments. The components of the embodiments of the present application generally described and shown in the drawings herein can be arranged and designed in various different configurations. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0053] It should be noted that the defects existing in the solutions in the above-mentioned prior art are the results obtained by the inventor after practice and careful research. Therefore, the discovery process of the above-mentioned problems and the solutions proposed in the embodiments of this application below for the above-mentioned problems should be the contributions made by the inventor to this application in the process of invention and creation, and should not be understood as technical contents known to technical personnel in this field.

[0054] In response to the technical problems pointed out in the background technology, the embodiments provided by the present invention are as follows:

[0055] Reference Figure 1 In an exemplary embodiment, a method for processing regional geochemical data is provided, comprising:

[0056] S1. For the regional geochemical concentration data of a specific element, the curvature at all sampling points is calculated to obtain the local concavity and convexity of the concentration data;

[0057] S2, traverse the element concentration data at all sampling points and modify the curvature so that the local element concentration extreme value remains unchanged;

[0058] S3, traverse the element concentration data at all sampling points, and replace the adjacent values of the element concentration data according to the curvature sign;

[0059] S4. Iteratively repeat steps S1-S3 until the element concentration data converges into a trapezoid.

[0060] The present invention proposes a new trapezoidalization operator that converts element concentration anomaly data into a stepped distribution through curvature-driven nonlinear iteration, thereby generating a graded concentration domain that highlights the abrupt change boundary and the concentration center. The core concept of this trapezoidalization operator is to use curvature analysis to identify the convex and concave characteristics of the element concentration at the current sampling point, and then replace it with the minimum or maximum value of the element concentration at the adjacent sampling points. In this process, the local element concentration extreme value remains unchanged. By repeatedly performing this operation, a step-like anomaly morphology can be generated, which naturally reflects the graded characteristics of the element concentration. A significant advantage of this process is that it does not rely on human intervention and does not require the data to meet the prerequisite of normal distribution.

[0061] Specifically, step S1 performs curvature calculation, including:

[0062] For regional geochemical concentration data of a specific element, the Laplace curvature at all sampling points is calculated to obtain the local concavity and convexity of the concentration data. For one-dimensional equally spaced geochemical data, the curvature is calculated according to the following formula:

[0063] (1);

[0064] in, Indicates the cross-sectional coordinates of a chemical element x The concentration at represents the sampling interval, The cross-sectional coordinates of a chemical element x The element concentration curvature at ;

[0065] For two-dimensional gridded geochemical data, the curvature is calculated according to the following formula:

[0066] (2);

[0067] in, Represents a chemical element in a plane coordinate x , y The concentration at and Respectively indicate along x He Yan y The sampling spacing in the direction, For a chemical element in the plane coordinate x , y The element concentration curvature at , the subscripts i-1, i, i+1 represent the numbers of three adjacent measuring points in the x direction, and the subscripts j-1, j, j+1 represent the numbers of three adjacent measuring points in the y direction.

[0068] The element concentration curvature defined above reflects the local situation of element concentration anomaly, that is, the local concavity and convexity of concentration data are obtained according to the element concentration curvature:

[0069] ① If or , indicating that the current element concentration anomaly is in a local depression (i.e., near the local value valley);

[0070] ②If or , indicating that the current element concentration anomaly is in a local bulge (i.e., near the local peak);

[0071] ③If or , indicating that the current data is in a flat area.

[0072] Step S2 performs local extreme value protection, including:

[0073] In order to keep the local extreme value unchanged, that is, the local extreme value should be located in the flat area, the element concentration data at all sampling points are traversed and the curvature is modified according to the following formula.

[0074] For one-dimensional equally spaced geochemical data, if satisfy:

[0075] (3)

[0076] Then order .

[0077] For two-dimensional gridded geochemical data, if At the same time:

[0078] (4)

[0079] Then order .

[0080] Step S3 performs adjacent value replacement, including:

[0081] Traverse all sampling points and update the element concentration data according to the curvature sign. If the curvature is positive, the center point value is replaced by the minimum value in the neighborhood; if the curvature is negative, it is replaced by the maximum value in the neighborhood; if the curvature is zero, it remains unchanged.

[0082] For one-dimensional equally spaced geochemical data:

[0083] ① If ,but ;

[0084] ②If ,but ;

[0085] ③If ,but Remain unchanged.

[0086] For 2D gridded geochemical data

[0087] ① If ,but ;

[0088] ②If ,but ;

[0089] ③If ,but Remain unchanged.

[0090] Step S4 performs iterative updating, including:

[0091] Repeat steps S1-S3 until the data converges to a trapezoidal shape. Whether the iteration termination condition is met can be determined by whether equation (5) or (6) holds. If so, the iteration is terminated.

[0092] For one-dimensional equally spaced geochemical data:

[0093] (5)

[0094] Where N represents the number of observation points, and the superscripts k and k-1 represent the results of the kth iteration and k-1th iteration, respectively.

[0095] For 2D gridded geochemical data:

[0096] (6)

[0097] Where N and M represent the number of observation points along the x-direction and y-direction, respectively, and the superscripts k and k-1 represent the results of the kth iteration and k-1th iteration, respectively.

[0098] In order to verify the advantages of the trapezoidalization operator proposed in this invention in processing regional geochemical data, we applied it to actual mineral exploration practice.

[0099] Figure 2 This figure shows the original observed anomalies of arsenic (As) along a profile of an exploration line at a low-temperature hydrothermal deposit in Guizhou, along with the results after trapezoidal processing. The figure clearly shows that the original observed data appears as a smooth curve, lacking a clear concentration anomaly classification, and the element's concentration centers and their sharp transition boundaries are blurred. The trapezoidal processing, however, clearly demonstrates the anomaly classification at different concentrations, including the concentration centers and the boundaries of sharp concentration transitions, making data interpretation more intuitive and accurate.

[0100] Figure 3 The original anomaly plane map of lithium (Li) elements in a pegmatite-type lithium mining area in western my country is shown. Figure 3 a) and the result after trapezoidal processing ( Figure 3 b). Despite significant Li anomalies in this mining area, the original plan view of the anomaly made it difficult to accurately delineate its boundaries and stratify them. However, after trapezoidal processing, the results clearly revealed multi-level Li anomaly regions, with Li concentration centers and their boundaries becoming more distinct. This result is highly consistent with geological observations and the actual distribution of mineralization (mineralization), further demonstrating the practicality and reliability of the proposed trapezoidal operator for processing regional geochemical data.

[0101] In another exemplary embodiment, based on the same inventive concept as the method embodiment, a regional geochemical data processing system is provided, comprising:

[0102] The curvature calculation module is used to traverse and calculate the curvature of all sampling points in the regional geochemical concentration data of a specific element to obtain the local concavity and convexity of the concentration data;

[0103] The local extreme value protection module is used to traverse the element concentration data at all sampling points and modify the curvature to keep the local element concentration extreme value unchanged;

[0104] The adjacent value replacement module is used to traverse the element concentration data at all sampling points and replace the adjacent values of the element concentration data according to the curvature sign;

[0105] The iterative update module is used to iteratively and repeatedly execute the curvature calculation module, the local extreme value protection module, and the adjacent value replacement module in sequence until the element concentration data converges to a trapezoid.

[0106] In another exemplary embodiment, based on the same inventive concept as the method embodiment, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the regional geochemical data processing method provided by the embodiment of the present invention is implemented. Based on this understanding, the technical solution of this embodiment, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods of each embodiment of the present invention. The aforementioned storage medium includes various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0107] In another exemplary embodiment, based on the same inventive concept as the method embodiment, a terminal is provided, including a memory and a processor, wherein the memory stores computer instructions that can be executed on the processor, and when the processor executes the computer instructions, it executes the regional geochemical data processing method provided by the embodiment of the present invention.

[0108] The processor may be a single-core or multi-core central processing unit or a specific integrated circuit, or one or more integrated circuits configured to implement the present invention.

[0109] Embodiments of the subject matter and functional operations described in this specification may be implemented in: tangibly embodied computer software or firmware, computer hardware including the structures disclosed in this specification and their structural equivalents, or a combination of one or more thereof. Embodiments of the subject matter described in this specification may be implemented as one or more computer programs, i.e., one or more modules of computer program instructions encoded on a tangible, non-transitory program carrier for execution by a data processing apparatus or to control the operation of the data processing apparatus. Alternatively or in addition, the program instructions may be encoded on an artificially generated propagated signal, such as a machine-generated electrical, optical, or electromagnetic signal, that is generated to encode and transmit information to a suitable receiver apparatus for execution by the data processing apparatus.

[0110] The processes and logic flows described in this specification can be performed by one or more programmable computers executing one or more computer programs to perform the corresponding functions by operating on input data and generating output. The processes and logic flows can also be performed by, and apparatus can be implemented as, special purpose logic circuitry, such as an FPGA (field programmable gate array) or an ASIC (application-specific integrated circuit).

[0111] Processors suitable for executing computer programs include, for example, general-purpose and / or special-purpose microprocessors, or any other type of central processing unit. Typically, a central processing unit will receive instructions and data from a read-only memory and / or random access memory. The basic components of a computer include a central processing unit for implementing or executing instructions and one or more memory devices for storing instructions and data. Typically, a computer will also include one or more mass storage devices for storing data, such as magnetic disks, magneto-optical disks, or optical disks, or the computer will be operably coupled to such a mass storage device to receive data from it or to transmit data to it, or both. However, a computer does not necessarily have such a device. In addition, a computer can be embedded in another device, such as a mobile phone, a personal digital assistant (PDA), a mobile audio or video player, a game console, a global positioning system (GPS) receiver, or a portable storage device such as a universal serial bus (USB) flash drive, to name a few.

[0112] It should be understood that each box in the flow chart or block diagram can represent a module, program segment or a part of code, and the part of the module, program segment or code comprises one or more executable instructions for realizing the logical function of the provision. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a sequence different from that marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flow chart, and the combination of the boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs the function or action of the provision, or can be implemented with a combination of dedicated hardware and computer instructions.

[0113] The above specific implementation methods are detailed descriptions of the present invention. It cannot be considered that the specific implementation methods of the present invention are limited to these descriptions. For ordinary technicians in the technical field to which the present invention belongs, they can make several simple deductions and substitutions without departing from the concept of the present invention, which should be regarded as falling within the scope of protection of the present invention.

Claims

1. A method for processing regional geochemical data, characterized in that: include: S1. For the regional geochemical concentration data of elements, traverse and calculate the curvature at all sampling points to obtain the local concavity and convexity of the concentration data; The obtaining of local concavity and convexity of concentration data includes: like or , indicating that the current element concentration anomaly is in a local depression; like or , indicating that the current element concentration anomaly is in a local bulge; like or , indicating that the current data is in a flat area; S2, traverse the element concentration data at all sampling points and modify the curvature so that the local element concentration extreme value remains unchanged; S3, traverse the element concentration data at all sampling points, and replace the adjacent values of the element concentration data according to the curvature sign; S4. Iteratively repeat steps S1-S3 until the element concentration data converges into a trapezoid.

2. A regional geochemical data processing method according to claim 1, characterized in that: The traversal calculates the curvature at all sampling points, including: For one-dimensional equally spaced geochemical data, the curvature is calculated according to the following formula: ； in, Indicates the cross-sectional coordinates of a chemical element x The concentration at represents the sampling interval, The cross-sectional coordinates of a chemical element x The element concentration curvature at ; For two-dimensional gridded geochemical data, the curvature is calculated according to the following formula: ； in, Represents a chemical element in a plane coordinate x , y The concentration at and Respectively indicate along x He Yan y The sampling spacing in the direction, For a chemical element in the plane coordinate x , y The element concentration curvature at , the subscripts i-1, i, i+1 represent the numbers of three adjacent measuring points in the x direction, and the subscripts j-1, j, j+1 represent the numbers of three adjacent measuring points in the y direction.

3. A regional geochemical data processing method according to claim 2, characterized in that: The step S2 specifically includes: For one-dimensional equally spaced geochemical data, if satisfy: ； Then order ; For two-dimensional gridded geochemical data, if At the same time: ； Then order .

4. A regional geochemical data processing method according to claim 2, characterized in that: The step S3 specifically includes: If the curvature is positive, the center point value is replaced by the minimum value in the neighborhood; if the curvature is negative, the center point value is replaced by the maximum value in the neighborhood; if the curvature is zero, the center point value remains unchanged.

5. A regional geochemical data processing method according to claim 2, characterized in that: The step S4 specifically includes: For one-dimensional equally spaced geochemical data, the iteration termination condition is: ； in, N Represents the number of observation points, superscript k and k -1 represents the kth iteration and k -Result of 1 iteration; For 2D gridded geochemical data, the iteration termination condition is: ； in, N and M Respectively represent the x Direction and y The number of observation points in the direction, superscript k and k -1 represents the kth iteration and k -Results of 1 iteration.

6. A regional geochemical data processing system, characterized in that: include: The curvature calculation module is used to traverse and calculate the curvature of all sampling points in the regional geochemical concentration data of elements to obtain the local concavity and convexity of the concentration data; The obtaining of local concavity and convexity of concentration data includes: like or , indicating that the current element concentration anomaly is in a local depression; like or , indicating that the current element concentration anomaly is in a local bulge; like or , indicating that the current data is in a flat area; The local extreme value protection module is used to traverse the element concentration data at all sampling points and modify the curvature to keep the local element concentration extreme value unchanged; The adjacent value replacement module is used to traverse the element concentration data at all sampling points and replace the adjacent values of the element concentration data according to the curvature sign; The iterative update module is used to iteratively and repeatedly execute the curvature calculation module, the local extreme value protection module, and the adjacent value replacement module in sequence until the element concentration data converges to a trapezoid.

7. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the regional geochemical data processing method according to any one of claims 1 to 5 is implemented.

8. A terminal comprising a memory and a processor, wherein the memory stores computer instructions that can be executed on the processor, characterized in that: When the processor runs the computer instructions, it executes the regional geochemical data processing method described in any one of claims 1 to 5.

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