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

Abstract

The invention discloses a regional geochemical data processing method and system, a storage medium and a terminal, and belongs to the field of electrical digital data processing.The method comprises the steps that S1, for regional geochemical concentration data of specific elements, curvatures of all sampling points are traversed and calculated, and local concavity and convexity of the concentration data are obtained; s2, element concentration data at all sampling points are traversed to modify the curvature, so that the local element concentration extreme value is not changed; s3, traversing element concentration data at all sampling points, and carrying out adjacent value replacement on the element concentration data according to curvature symbols; and S4, iteratively repeating the steps S1-S3 until the element concentration data converges into a trapezoid. According to the method, a new trapezoid operator is provided, element concentration is automatically graded through curvature-driven nonlinear iteration, the element concentration center and the abrupt change boundary are identified, and the problems that a traditional method is fuzzy in boundary and high in subjectivity are solved.

Description

Technical Field

[0001] The present invention relates to the field of electronic digital data processing, and particularly to a method, system, storage medium and terminal for processing regional geochemical data, which are used for performing anomaly grading on given regional geochemical element concentrations, identifying element concentration centers and abrupt change boundaries, and can be widely applied to environmental geochemical surveys, solid mineral exploration and geological scientific research. Background Art

[0002] Regional geochemical anomalies reveal the law of the change of the concentration of specific elements with the sampling point position, and provide valuable clues and basis for fields such as environmental surveys, prospecting exploration and scientific research. For the processing and analysis of regional geochemical data, traditionally, methods mainly rely on drawing isograms, statistical classification, manual interpretation, etc. However, these methods have shown obvious limitations in the actual application process.

[0003] In the isogram, geochemical data generates a smooth isogram through interpolation. Although it can reflect the spatial distribution trend of element concentrations, due to the inherent characteristics of the interpolation algorithm, abrupt change features such as mineralization boundaries and lithological contact zones are over-smoothed, resulting in a lack of hierarchical anomaly grading and insufficient ability to identify anomaly boundaries. For example, in magmatic hydrothermal deposits, the element concentration often shows a sharp change near the rock mass contact zone, while the traditional isogram cannot effectively retain this mutation information, which leads to a large deviation in the positioning of the exploration target area. Statistical analysis methods (such as mean ± 2 times standard deviation) can delimit anomaly areas based on data distribution characteristics, but their assumption is that the data conforms to a normal distribution, while actual geochemical data is often affected by multi-stage geological processes and shows multi-modal or skewed distribution, which results in the statistical anomaly range may deviate from the true mineralization area. For example, in areas with strong weathering, supergene processes may enrich some elements (such as Au, As) in the surface layer, covering up some deep mineralization information. At this time, the anomaly delimitation method based on global statistics may overestimate or underestimate the mineralization potential. In addition, anomaly thresholds (such as the 85% or 90% quantile) usually rely on manual experience to set, lacking objective criteria, and different interpreters may draw different conclusions, affecting the repeatability and comparability of the data.

[0004] Generally speaking, the core problems of the existing regional geochemical data processing methods are: (1) lack of hierarchical anomaly grading, making it difficult to automatically distinguish anomalies of different intensities; (2) insufficient boundary recognition ability, unable to effectively capture the mutation characteristics of element concentrations; (3) over-reliance on manual experience, and the interpretation results are highly subjective. These defects seriously restrict the accurate application of geochemical data, and there is an urgent need for a new method that can automatically divide anomaly levels and identify abrupt change boundaries. Summary of the Invention

[0005] The object of the present invention is to overcome the technical problems existing in the prior art, and provides a method, a system, a storage medium and a terminal for processing regional geochemical data. Based on a curvature-driven trapezoidal operator, geochemical data is converted into a stepped distribution through non-linear iteration, so as to generate a hierarchical concentration domain and highlight abrupt change boundaries and concentration centers.

[0006] The object of the present invention is achieved by the following technical solutions: In a first aspect, a method for processing regional geochemical data is provided, including: S1. For the regional geochemical concentration data of a specific element, traverse and calculate the curvature at all sampling points to obtain the local concavity and convexity of the concentration data; S2. Traverse the element concentration data at all sampling points to modify the curvature so that the local element concentration extreme values remain unchanged; S3. Traverse the element concentration data at all sampling points, and perform adjacent value replacement on the element concentration data according to the curvature sign; S4. Iteratively repeat steps S1 - S3 until the element concentration data converges to a trapezoid.

[0007] In some embodiments, the traversing and calculating the curvature at all sampling points includes: For one-dimensional equally spaced geochemical data, calculate the curvature according to the following formula: ; where, represents the concentration of a certain chemical element at the profile coordinate x , represents the sampling interval, is the element concentration curvature of a certain chemical element at the profile coordinate x ; For two-dimensional gridded geochemical data, calculate the curvature according to the following formula: ; where, represents the concentration of a certain chemical element at the plane coordinate x , y and and respectively represent the sampling intervals along x and along y directions, is the element concentration curvature of a certain chemical element at the plane coordinate x , y ; 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.

[0008] In some embodiments, obtaining the local concavity and convexity of the concentration data includes: If or , it indicates that the current element concentration anomaly is in a local depression; If or , it indicates that the current element concentration anomaly is in a local protrusion (i.e., near the local peak); If or , it indicates that the current data is in a flat area.

[0009] In some embodiments, step S2 specifically includes: For one-dimensional equally spaced geochemical data, if satisfies: ; Then let ; For two-dimensional gridded geochemical data, if simultaneously satisfies: ; Then let .

[0010] In some embodiments, step S3 specifically includes: If the curvature is positive, the center point value is replaced with the minimum value in the neighborhood; if the curvature is negative, the center point value is replaced with the maximum value in the neighborhood; if the curvature is zero, the center point value remains unchanged.

[0011] In some embodiments, step S4 specifically includes: For one-dimensional equally spaced geochemical data, the iteration termination condition: ; Wherein, N represents the number of observation points, and the superscript k and k -1 represent the results of the k-th iteration and k -1-th iteration respectively; For two-dimensional gridded geochemical data, the iteration termination condition: ; Wherein, N and M respectively represent the number of observation points along the x direction and y direction, and the superscripts k and k -1 represent the results of the k-th iteration and k -1-th iteration respectively.

[0012] In a second aspect, a regional geochemical data processing system is provided, including: A curvature calculation module for traversing and calculating the curvature at all sampling points in the regional geochemical concentration data of a specific element to obtain the local concavity and convexity of the concentration data; A local extreme value protection module for traversing the element concentration data at all sampling points to modify the curvature so that the local element concentration extreme values remain unchanged; A neighboring value replacement module for traversing the element concentration data at all sampling points and performing neighboring value replacement on the element concentration data according to the curvature sign; An iterative update module for iteratively and repeatedly executing the curvature calculation module, the local extreme value protection module, and the neighboring value replacement module until the element concentration data converges to a trapezoid.

[0013] In a third aspect, a computer-readable storage medium is provided. 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.

[0014] In a fourth aspect, a terminal is provided, including a memory and a processor. A computer instruction that can run on the processor is stored on the memory, and when the processor runs the computer instruction, the regional geochemical data processing method described in the first aspect is executed.

[0015] It should be further noted that the technical features corresponding to the above embodiments can be combined or replaced with each other without conflict to form a new technical solution.

[0016] Compared with the prior art, the beneficial effects of the present invention are: The present invention provides a trapezoid operator, which uses curvature analysis to identify the convex and concave characteristics of the element concentration at the current sampling point, and then replaces it with the minimum or maximum value of the element concentration at the neighboring sampling points. During this process, the local element concentration extreme values remain unchanged. By repeatedly performing this operation, the geochemical data can be converted into an abnormal form similar to a stepped distribution, which naturally reflects the hierarchical characteristics of the element concentration, automatically classifies the element concentration, and identifies the element concentration center and the steep change boundary. At the same time, a significant advantage of the iterative process of the present invention is that it neither depends on human intervention nor requires the data to meet the prerequisite of normal distribution, solving the problems of fuzzy boundaries and strong subjectivity of traditional methods. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 It is a flowchart of a regional geochemical data processing method shown in an embodiment of the present invention; Figure 2This is the original observed anomaly of arsenic (As) element on the exploration line section of a low-temperature hydrothermal deposit in Guizhou shown in the embodiments of the present invention and the result after trapezoid processing; Figure 3 This is the original anomaly plan of lithium (Li) element in a pegmatite-type lithium mining area shown in the embodiments of the present invention ( Figure 3 a) and the result after its trapezoid processing ( Figure 3 b). Detailed implementation manners

[0018] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. Usually, the components of the embodiments of the present application described and shown in the drawings here can be arranged and designed in various different configurations. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0019] It should be noted that all the defects existing in the above prior art solutions are the results obtained by the inventor after practice and careful research. Therefore, the discovery process of the above problems and the solutions proposed by the embodiments of the present application below for the above problems should be the contributions made by the inventor to the present application during the invention creation process, rather than being understood as the technical content known to those skilled in the art.

[0020] In response to the technical problems pointed out in the background art, the embodiments provided by the present invention are as follows: Referring to Figure 1 , in an exemplary embodiment, a method for processing regional geochemical data is provided, including: S1. For the regional geochemical concentration data of a specific element, traverse and calculate the curvature at all sampling points to obtain the local concavity and convexity of the concentration data; S2. Traverse the element concentration data at all sampling points to modify the curvature so that the local element concentration extreme values remain unchanged; S3. Traverse the element concentration data at all sampling points and perform adjacent value replacement on the element concentration data according to the curvature sign; S4. Iteratively repeat steps S1 - S3 until the element concentration data converges to a trapezoid.

[0021] The present invention proposes a new trapezoidal operator. Through curvature-driven non-linear iteration, it converts element concentration anomaly data into a stepped distribution, thereby generating a hierarchical concentration domain and highlighting the abrupt change boundaries and concentration centers. The core concept of this trapezoidal 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 adjacent sampling points. During this process, the local element concentration extreme values remain unchanged. By repeatedly performing this operation, a stepped anomaly pattern can be generated, which naturally reflects the hierarchical characteristics of the element concentration. A significant advantage of this process is that it neither depends on human intervention nor requires the data to meet the prerequisite of normal distribution.

[0022] Specifically, step S1 performs curvature calculation, including: For the regional geochemical concentration data of a specific element, traverse and calculate the Laplace curvature at all sampling points to obtain the local convexity and concavity of the concentration data. Among them, for one-dimensional equally spaced geochemical data, the curvature is calculated according to the following formula: (1); Where, represents the concentration of a certain chemical element at the profile coordinate x , represents the sampling interval, is the element concentration curvature of a certain chemical element at the profile coordinate x ; For two-dimensional gridded geochemical data, the curvature is calculated according to the following formula: (2); Where, represents the concentration of a certain chemical element at the plane coordinate x , y , and respectively represent the sampling intervals along x and along y directions, is the element concentration curvature of a certain chemical element at the plane coordinate x , y . The subscripts i - 1, i, i + 1 represent the numbers of three adjacent measurement points in the x direction, and the subscripts j - 1, j, j + 1 represent the numbers of three adjacent measurement points in the y direction.

[0023] The element concentration curvature defined above reflects the local situation of the element concentration anomaly, that is, the local convexity and concavity of the concentration data are obtained according to the element concentration curvature: ① If or , indicating that the abnormal concentration of the current element is in a local depression (i.e., near the local value trough); ② If or , indicating that the abnormal concentration of the current element is in a local protrusion (i.e., near the local peak); ③ If or , indicating that the current data is in a flat area.

[0024] Step S2 performs local extreme value protection, including: To keep the local extreme values unchanged, that is, the local extreme values should be in the flat area, traverse the element concentration data at all sampling points and modify the curvature according to the following formula.

[0025] For one-dimensional equally spaced geochemical data, if satisfies: (3) Then let .

[0026] For two-dimensional gridded geochemical data, if simultaneously satisfies: (4) Then let .

[0027] Step S3 performs adjacent value replacement, including: 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.

[0028] For one-dimensional equally spaced geochemical data: ① If , then ; ② If , then ; ③ If , then Remain unchanged.

[0029] For two-dimensional gridded geochemical data ① If , then ; ② If , then ; ③ If , then Remain unchanged.

[0030] Step S4 is iteratively updated, including: Repeat the process of steps S1 - S3 until the data converges to a trapezoid. For whether the iteration termination condition is reached, it can be judged according to whether equation (5) or (6) holds. If it holds, terminate the iteration.

[0031] For one - dimensional equally - spaced geochemical data: (5) where N represents the number of observation points, and the superscripts k and k - 1 represent the results of the k - th iteration and the (k - 1) - th iteration respectively.

[0032] For two - dimensional gridded geochemical data: (6) 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 k - th iteration and the (k - 1) - th iteration respectively.

[0033] To verify the advantages of the trapezoid operator proposed in the present invention in processing regional geochemical data, we apply it to the actual prospecting exploration practice.

[0034] Figure 2 It shows the original observed anomaly of arsenic (As) element and its result after trapezoid processing on the exploration line section of a low - temperature hydrothermal deposit in Guizhou. It can be clearly seen from the figure that the original observed data presents as a smooth curve, lacking clear concentration anomaly grading, and the element concentration center and its steep change boundary are both blurred. However, the result after trapezoid processing clearly shows different concentration anomaly gradings, including the concentration center and the boundary of concentration steep change, which makes the data interpretation more intuitive and accurate.

[0035] Figure 3 It shows the original anomaly plan map of lithium (Li) element ( Figure 3 a) and its result after trapezoid processing ( Figure 3 b) in a pegmatite - type lithium ore district in the western part of China. Although there are significant Li element anomalies in this ore district, it is difficult to accurately divide the anomaly boundary and further classify the anomalies through the original anomaly plan map. However, after trapezoid processing, the result clearly reveals multiple - level Li element anomaly regions, and the concentration center and its boundary of Li element also become clearer. This processing result is highly consistent with the geological observation results and the actual distribution area of the ore (mineralized) body, further proving the practicality and reliability of the trapezoid operator proposed in the present invention in processing regional geochemical data.

[0036] In another exemplary embodiment, based on the same inventive concept as the method embodiment, a regional geochemical data processing system is provided, including: A curvature calculation module for traversing and calculating the curvature at all sampling points in the regional geochemical concentration data of a specific element to obtain the local concavity and convexity of the concentration data; A local extreme value protection module for traversing the element concentration data at all sampling points to modify the curvature so that the local element concentration extreme values remain unchanged; A neighboring value replacement module for traversing the element concentration data at all sampling points and performing neighboring value replacement on the element concentration data according to the curvature sign; An iterative update module for iteratively and repeatedly executing the curvature calculation module, the local extreme value protection module, and the neighboring value replacement module in sequence until the element concentration data converges to a trapezoid.

[0037] In another exemplary embodiment, based on the same inventive concept as the method embodiment, a computer-readable storage medium is provided. The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, it implements the regional geochemical data processing method provided by the embodiments of the present invention. Based on such an understanding, the technical solution of this embodiment, in essence, or the part that contributes to the prior art, or a part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods of the various embodiments of the present invention. The foregoing 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 disc.

[0038] In another exemplary embodiment, based on the same inventive concept as the method embodiment, a terminal is provided, including a memory and a processor. The memory stores computer instructions that can run on the processor, and when the processor runs the computer instructions, it executes the regional geochemical data processing method provided by the embodiments of the present invention.

[0039] The processor can be a single-core or multi-core central processing unit or a specific integrated circuit, or an integrated circuit configured to implement one or more of the present invention.

[0040] Embodiments of the subject matter and the functional operations described in this specification can be implemented in one of the following: 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 of them. Embodiments of the subject matter described in this specification can 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 to be executed by, or to control the operation of, a data processing apparatus. Alternatively or additionally, the program instructions can be encoded on an artificially generated propagated signal, such as a machine-generated electrical, optical, or electromagnetic signal, which is generated to encode and transmit information to a suitable receiving apparatus for execution by the data processing apparatus.

[0041] The processes and logical 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 logical flows can also be performed by, for example, FPGA (Field Programmable Gate Array) or ASIC (Application Specific Integrated Circuit), which are special logic circuits, and the apparatus can also be implemented as special logic circuits.

[0042] Processors suitable for executing computer programs include, for example, general and / or special purpose microprocessors, or any other type of central processing unit. Generally, a central processing unit will receive instructions and data from a read-only memory and / or a random access memory. 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. Generally, a computer will also include one or more mass storage devices for storing data, such as magnetic disks, magneto-optical disks, or optical disks, etc., or the computer will be operatively coupled to such mass storage devices to receive data from them or to transfer data to them, or both. However, a computer is not necessarily required to have such devices. 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 just a few.

[0043] It should be understood that each block in the flowchart or block diagram may represent a module, a program segment, or a part of code, and the module, the program segment, or the part of code contains one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order from that marked in the accompanying drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in the reverse order, depending on the functions involved. It should also be noted that each block in the block diagram and / or flowchart, as well as the combination of blocks in the block diagram and / or flowchart, may be implemented by a dedicated hardware-based system that performs the specified functions or actions, or may be implemented by a combination of dedicated hardware and computer instructions.

[0044] The above specific implementation manners are detailed descriptions of the present invention. It cannot be determined that the specific implementation manners of the present invention are only limited to these descriptions. For those of ordinary skill in the technical field to which the present invention pertains, without departing from the concept of the present invention, several simple deductions and substitutions can still be made, and all should be regarded as belonging to the protection scope of the present invention.

Claims

1. A method for processing regional geochemical data, characterized in that, Including: S1. For the regional geochemical concentration data of specific elements, traverse and calculate the curvature at all sampling points to obtain the local concavity and convexity of the concentration data; S2. Traverse the element concentration data at all sampling points to modify the curvature so that the local element concentration extreme values remain unchanged; S3. Traverse the element concentration data at all sampling points and perform adjacent value replacement on the element concentration data according to the curvature sign; S4. Iteratively repeat steps S1 - S3 until the element concentration data converges to a trapezoid.

2. The regional geochemical data processing method according to claim 1, characterized in that The traversing and calculating the curvature at all sampling points includes: For one-dimensional equally spaced geochemical data, calculate the curvature according to the following formula: ； Among them, represents the concentration of a certain chemical element at the profile coordinate x . represents the sampling interval, is the curvature of the element concentration of a certain chemical element at the profile coordinate x . For two-dimensional gridded geochemical data, calculate the curvature according to the following formula: ； Among them, represents the concentration of a certain chemical element at a planar coordinate x , y at the place, and respectively represent the sampling intervals along x and along y the directions, is the curvature of the element concentration of a certain chemical element at the planar coordinate x , y at the place. 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 method for processing regional geochemical data according to claim 2, characterized in that, The obtaining the local concavity and convexity of the concentration data includes: If or , it indicates that the abnormal current element concentration is in a local depression; If or , it indicates that the abnormal concentration of the current element is in a local bulge (i.e., near the local peak); If or , it means that the current data is located in a flat area.

4. The regional geochemical data processing method according to claim 2, wherein The specific steps of S2 include: For one-dimensional equally spaced geochemical data, if Satisfy: ； Then let ; For two-dimensional gridded geochemical data, if Simultaneously satisfy: ； Then make .

5. A method for processing regional geochemical data according to claim 2, characterized in that The specific steps of S3 include: If the curvature is positive, the central point value is replaced with the minimum value in the neighborhood; if the curvature is negative, the central point value is replaced with the maximum value in the neighborhood; if the curvature is zero, the central point value remains unchanged.

6. A method for processing regional geochemical data according to claim 2, wherein The specific steps of S4 include: For one-dimensional equally spaced geochemical data, the iteration termination condition: ； Among them, N represents the number of observation points, and the superscript k and k -1 represent the results of the k-th iteration and k the (-1)-th iteration, respectively; For two-dimensional gridded geochemical data, the iteration termination condition: ； Among them, N and M represent the number of observation points along the x direction and the y direction respectively. The superscripts k and k -1 represent the results of the k-th iteration and the k (-1)-th iteration respectively.

7. A regional geochemical data processing system, characterized in that, Including: A curvature calculation module for traversing and calculating the curvature at all sampling points in the regional geochemical concentration data of specific elements to obtain the local concavity and convexity of the concentration data; A local extreme value protection module for traversing the element concentration data at all sampling points to modify the curvature so that the local element concentration extreme values remain unchanged; An adjacent value replacement module for traversing the element concentration data at all sampling points and performing adjacent value replacement on the element concentration data according to the curvature sign; An iterative update module for iteratively repeating the execution of 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.

8. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the regional geochemical data processing method described in any one of claims 1 - 6.

9. A terminal, comprising a memory and a processor, wherein the memory stores computer instructions that can be run 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 - 6.

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