High-precision automatic analysis method and system of coal structure based on full-diameter CT

Abstract

The present invention discloses a high-precision automatic analysis method and system for coal body structure based on full-diameter CT, and relates to the technical field of coal body structure analysis. The method comprises: performing full-diameter CT scanning on coal and rock in the entire well section to obtain multiple vertically continuous grayscale slice data bodies; performing coal rock skeleton particle segmentation on each grayscale slice data body to generate a coal rock skeleton particle structure data body; performing particle size calculation on the coal rock skeleton particle structure data body to obtain the coal rock particle size distribution; determining the classification boundaries of different coal body structures according to the coal rock coring diameter, and forming a coal body structure classification standard; calculating the proportion of each type of coal body structure according to the coal rock particle size distribution and coal body structure classification standard on each grayscale slice data body, and completing the coal body structure analysis of the current well section. The present invention realizes fully automatic high-precision analysis and evaluation of the continuous coal rock particle size distribution and coal body structure characterization of the entire well section, and provides strong technical support for coal rock exploration and development.

Description

Technical Field

[0001] The present invention relates to the technical field of coal body structure analysis, and in particular to a high-precision automatic analysis method and system for coal body structure based on full-diameter CT. Background Art

[0002] Coal body structure refers to the characteristics of the degree of damage and deformation of the coal body after the coal seam has been subjected to various geological actions during the geological history evolution. The degree of damage and deformation of the coal body directly affects the key geological characteristics of the coal seam, such as pore development, mechanical properties, and sensitivity. The study of coal body structure is of great significance to the evaluation of sweet spots and production capacity control analysis.

[0003] Traditional methods classify coal according to its macroscopic characteristics such as the degree of distinguishability of its macroscopic coal rock type, bedding integrity, coal body fragmentation, and hand test strength. Most of these characteristics are subjective qualitative characteristics, and only the degree of coal body fragmentation has corresponding quantitative standards. Standard GB / T 30050-2013 stipulates that primary structure coal is complete and has a hard hand test strength; fragmented structure coal is relatively complete or broken, with the particle size generally greater than 5mm, and the hand test strength is relatively hard; granular structure coal is broken, with a particle size mostly between 1mm and 5mm, and the hand test strength is relatively loose; mylonitic structure coal is mostly scaly and wrinkled.

[0004] Despite the above standards as a reference, it is difficult to measure and count coal rock particles one by one in actual operations. The judgment results are highly subjective and empirical, resulting in certain differences in the judgment results of different technicians. The evaluation of coal body structure remains at a qualitative level, which causes great difficulties in understanding coal seams and parallel comparisons.

[0005] In recent years, CT scanning has gradually been applied in the oil exploration industry. Traditional micron CT scanners usually only scan core plungers with a diameter of 1 inch or even smaller. Their scanning field of view is small, and the scanning results lack integrity relative to the entire wellbore formation. The applicant found that full-diameter spiral CT scanning has the advantage of a large field of view for the entire core, and is particularly suitable for the analysis of whole-barrel meter-level cores with a diameter of 8 to 12 cm. Based on this, the present invention proposes a high-precision automatic analysis method and system for coal body structure based on full-diameter CT. Summary of the invention

[0006] The present invention provides a high-precision automatic analysis method of coal body structure based on full-diameter CT, comprising:

[0007] Perform full-diameter CT scanning of the coal and rock in the entire well section to obtain multiple vertically continuous grayscale slice data volumes;

[0008] Segment the coal rock skeleton particles for each grayscale slice data volume to generate a coal rock skeleton particle structure data volume;

[0009] Calculate the particle size of the coal rock skeleton particle structure data volume of each gray slice data volume to obtain the coal rock particle size distribution;

[0010] According to the diameter of coal rock core sampling, the classification boundaries of different coal structures are determined, and the coal structure classification standards are formed;

[0011] According to the coal rock particle size distribution and coal body structure classification standards on each grayscale slice data volume, the proportion of each type of coal body structure is calculated to complete the coal body structure analysis of the current well section.

[0012] As described above, in the high-precision automatic analysis method of coal body structure based on full-diameter CT, the full-diameter CT scan is specifically set with a scanning lateral resolution of 146 μm, a longitudinal resolution of 800 μm, and a storage format of signed hexadecimal grayscale slice data.

[0013] As described above, in the high-precision automatic analysis method of coal body structure based on full-diameter CT, digital core threshold segmentation or watershed method is used to perform coal rock skeleton particle segmentation on the grayscale slice data body.

[0014] As described above, in the high-precision automatic analysis method of coal body structure based on full-diameter CT, a threshold range of >-200 is set as the coal rock skeleton threshold range, and segmentation is performed according to the threshold range to obtain the coal rock skeleton particle structure data body.

[0015] The high-precision automatic analysis method of coal body structure based on full-diameter CT as described above, wherein the particle size calculation of the coal rock skeleton particle structure data volume is performed, specifically includes the following sub-steps:

[0016] Performing a particle sorting operation on the coal rock skeleton particle structure data volume on each grayscale slice data volume to obtain a particle sorting data volume;

[0017] Calculate the particle diameter of the particle sorting data volume to obtain the particle diameter of each grayscale slice data volume and the average particle diameter of the slice;

[0018] The coal and rock particles in each grayscale slice data volume are counted to obtain a coal and rock particle statistics table.

[0019] As described above, in the high-precision automatic analysis method of coal body structure based on full-diameter CT, the particle sorting data body is input into the image processing software, the image processing software is used to count the size of coal rock particles in each slice, and the particle diameter of each grayscale slice data body and the average particle diameter of the slice are calculated.

[0020] The present invention also provides a high-precision automatic analysis system for coal body structure based on full-diameter CT, comprising: a full-diameter CT scanner and a coal body structure analysis device; the full-diameter CT scanner performs full-diameter CT scanning on coal and rock in the entire well section; the coal body structure analysis device specifically comprises:

[0021] A grayscale slice data volume acquisition module is used to acquire a plurality of longitudinally continuous grayscale slice data volumes from a full-diameter CT scanner;

[0022] The coal rock skeleton particle segmentation module is used to perform coal rock skeleton particle segmentation on each gray slice data volume to generate a coal rock skeleton particle structure data volume;

[0023] The coal rock particle size distribution acquisition module is used to calculate the particle size of the coal rock skeleton particle structure data volume of each gray slice data volume to obtain the coal rock particle size distribution;

[0024] A coal body structure classification standard forming module is used to determine the classification boundaries of different coal body structures according to the diameter of coal rock core sampling, and form a coal body structure classification standard;

[0025] The coal body structure analysis module is used to calculate the proportion of various types of coal body structures based on the coal rock particle size distribution and coal body structure classification standards on each grayscale slice data volume, and complete the coal body structure analysis of the current well section.

[0026] The present invention also provides a computer storage medium, characterized in that it comprises: at least one memory and at least one processor;

[0027] The memory is used to store one or more program instructions;

[0028] A processor is used to run one or more program instructions to execute any of the above-mentioned high-precision automatic analysis methods of coal body structure based on full-diameter CT.

[0029] The beneficial effects achieved by the present invention are as follows: The present invention applies full-diameter CT scanning digital core technology to the description and analysis of coal body structure, realizing fully automatic high-precision (up to micron level) analysis and evaluation of continuous coal rock particle size distribution and coal body structure characterization in the entire well section, and providing strong technical support for the exploration and development of clean energy such as coal-rock gas, especially deep coal-rock gas. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0031] Figure 1 This is a flow chart of a high-precision automatic analysis method of coal body structure based on full-diameter CT provided in Example 1 of the present application;

[0032] Figure 2It is the particle distribution diagram of different coal structures;

[0033] Figure 3 It is a schematic diagram of the coal rock skeleton particle structure data volume;

[0034] Figure 4 It is a coal rock particle sorting diagram;

[0035] Figure 5 It is the histogram of coal body structure distribution. DETAILED DESCRIPTION

[0036] The following is a clear and complete description of the technical solutions in the embodiments of the present invention in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0037] Embodiment 1

[0038] like Figure 1 As shown, the first embodiment of the present invention provides a high-precision automatic analysis method of coal body structure based on full-diameter CT, including:

[0039] Step 110, perform full-diameter CT scanning on the coal and rock of the entire well section to obtain multiple vertically continuous grayscale slice data volumes;

[0040] In the present embodiment, a Philips multi-spectral full-diameter spiral CT scanner (Philips IngenuityCore128) was selected, and the scanning lateral resolution was set to 146μm, the longitudinal resolution was set to 800μm, and the storage format was 16-bit signed grayscale slice data. A full-diameter CT scan was performed on a section of coal core in Well A of a coalbed methane exploration block. The core diameter was 70mm, the depth range was 2511.00~2512.29m, and the total scanning length was 1.29m. The plane distribution of coal particles was browsed by scanning the slices. The particle distribution of different coal structures is shown in Figure 1. Figure 2 shown.

[0041] Step 120, performing coal rock skeleton particle segmentation on each grayscale slice data volume to generate a coal rock skeleton particle structure data volume;

[0042] Specifically, digital core threshold segmentation or watershed methods are used to segment the coal rock skeleton particles on the gray slice data body. Usually, the threshold of skeleton particle segmentation is greater than -200, so the threshold range > -200 is set as the coal rock skeleton threshold range, and segmentation is performed according to the threshold range to obtain the coal rock skeleton particle structure data body as shown in the figure. Figure 3 shown.

[0043] Step 130, calculating the particle size of the coal rock skeleton particle structure data volume of each gray slice data volume to obtain the coal rock particle size distribution;

[0044] Specifically, the particle size calculation of the coal rock skeleton particle structure data volume includes the following sub-steps:

[0045] Step 131, performing a particle sorting operation on the coal rock skeleton particle structure data volume on each grayscale slice data volume to obtain a particle sorting data volume;

[0046] In an embodiment of the present application, a particle sorting operation is performed on the coal rock skeleton particle structure data body, specifically: first, the adjacency relationship between pixels is defined as 8-adjacency, and then the image is traversed using a depth-first search method, starting from a starting point and exploring in depth along each path until it can no longer be connected as the boundary of the particle. Through the above sorting operation, a particle sorting data body of each slice is obtained, and the particle sorting data body has distinguished the boundaries of different coal rock particles. Figure 4 This is a diagram of coal rock particle sorting.

[0047] Step 132, calculating the particle diameter of the particle sorting data volume to obtain the particle diameter of each grayscale slice data volume and the average particle diameter of the slice;

[0048] There are a number of coal rock particles distributed on each slice. The more broken the coal structure is, the more coal rock particles there are. For example, if there are 1250 slices per meter of core, then a 1.29-meter core consists of about 1608 slices.

[0049] The particle sorting data body is input into the image processing software, and the image processing software is used to count the size of the coal and rock particles in each slice, and the particle diameter of each grayscale slice data body and the average particle diameter of the slice are calculated.

[0050] Step 133, counting the coal and rock particles in each grayscale slice data volume to obtain a coal and rock particle statistics table;

[0051] Specifically, the coal rock particles in each grayscale slice data volume are counted, including particle sequence, slice sequence, particle diameter and slice average particle diameter. The statistical results are shown in Table 1 below:

[0052] Table 1 Coal rock particle statistics

[0053]

[0054] Step 140: Determine the classification boundaries of different coal structures according to the diameter of the coal rock core, and form a coal structure classification standard;

[0055] Specifically, assuming the diameter of the natural coal core is X mm, the average particle diameter range of the primary structure is X~(X - 20) mm, the average particle diameter range of the cataclastic structure is 5~(X - 20) mm, the average particle diameter range of the granular structure is 1~5 mm, and the average particle diameter range of the mylonitic structure is 0~1 mm. According to different coal rock drilling tools, the diameter of the natural coal rock core is a regular cylinder with diameters of 60 mm, 70 mm, 80 mm, 100 mm, and 120 mm. The diameter limit of the coal particles in the primary structure is set according to the original diameter width of the natural core, and the classification standard of the coal body structure formed is shown in Table 2 below:

[0056] Table 2 Classification Table of Particle Diameter Limits for Different Coal Body Structures

[0057]

[0058] Step 150: According to the particle size distribution of coal rock particles on each gray slice data volume and the classification standard of coal body structure, calculate the proportion of each type of coal body structure to complete the analysis of the coal body structure in the current well section;

[0059] In the embodiment of the present application, the specific formula for calculating the proportion of each type of coal body structure is as follows: Where F is the proportion of each type of coal body structure, pixel is the longitudinal resolution of the full-diameter CT scan, L is the total length of the coal core in the scanned section, count(i) represents the count of slices that meet the average particle size range, i represents the average particle diameter of the coal rock. When X - 20 < i ≤ X, the statistical result F is the proportion of the primary structure; when 5 < i ≤ X - 20, the statistical result F is the proportion of the cataclastic structure; when 1 < i ≤ 5, the statistical result F is the proportion of the granular structure; when 0 < i ≤ 1, the statistical result F is the proportion of the mylonitic structure.

[0060] According to the classification standard table of the coal body structure, the average particle diameter of each gray slice data volume calculated in the scanned section is evaluated correspondingly, and the evaluation result of the coal body structure in the full scanned section is shown in Table 3 below:

[0061] Table 3 Evaluation Table of Coal Body Structure in the Full Scanned Section

[0062]

[0063] Based on the full-diameter CT scan data volume, the present application can calculate the diameter of coal rock particles. On this basis, a classification standard for coal body structure is established, and the coal body structure in the full scanned section is quantitatively classified and evaluated according to the standard, realizing the accurate division of the coal body structure. For example, when analyzing a certain well section, it is found that the coal body structure of the 1.29-meter scanned well section is mainly composed of the primary structure and the cataclastic structure, as Figure 5As shown, primary structural coal accounts for 35.47%, crushed structural coal accounts for 58.99%, broken particle structural coal accounts for 5.48%, and mylonitic structural coal accounts for 0.06%.

[0064] Embodiment 2

[0065] A second embodiment of the present invention provides a high-precision automatic analysis system for coal structure based on full-diameter CT, comprising: a full-diameter CT scanner and a coal structure analysis device.

[0066] The full-diameter CT scanner performs full-diameter CT scanning on the coal and rock in the entire well section; the full-diameter CT scanning is specifically set with a scanning lateral resolution of 146 μm and a longitudinal resolution of 800 μm, and the storage format is signed hexadecimal grayscale slice data.

[0067] The coal structure analysis device specifically includes:

[0068] A grayscale slice data volume acquisition module is used to acquire a plurality of longitudinally continuous grayscale slice data volumes from a full-diameter CT scanner;

[0069] The coal rock skeleton particle segmentation module is used to perform coal rock skeleton particle segmentation on each grayscale slice data body respectively to generate a coal rock skeleton particle structure data body; specifically, the coal rock skeleton particle segmentation is performed on the grayscale slice data body using the digital core threshold segmentation or watershed method, and a threshold range of >-200 is set as the coal rock skeleton threshold range, and segmentation is performed according to the threshold range to obtain the coal rock skeleton particle structure data body.

[0070] The coal rock particle size distribution acquisition module is used to calculate the particle size of the coal rock skeleton particle structure data volume of each gray slice data volume to obtain the coal rock particle size distribution;

[0071] Among them, the particle size calculation of the coal rock skeleton particle structure data body specifically includes: performing particle sorting operation on the coal rock skeleton particle structure data body on each grayscale slice data body to obtain a particle sorting data body; calculating the particle diameter of the particle sorting data body to obtain the particle diameter of each grayscale slice data body and the average particle diameter of the slice; inputting the particle sorting data body into the image processing software, using the image processing software to count the size of the coal rock particles in each slice, and calculating the particle diameter of each grayscale slice data body and the average particle diameter of the slice; counting the coal rock particles in each grayscale slice data body to obtain a coal rock particle statistical table.

[0072] A coal body structure classification standard forming module is used to determine the classification boundaries of different coal body structures according to the diameter of coal rock core sampling, and form a coal body structure classification standard;

[0073] The coal body structure analysis module is used to calculate the proportion of various types of coal body structures based on the coal rock particle size distribution and coal body structure classification standards on each grayscale slice data volume, and complete the coal body structure analysis of the current well section.

[0074] Corresponding to the above-mentioned embodiment, an embodiment of the present invention provides a computer storage medium, including: at least one memory and at least one processor;

[0075] The memory is used to store one or more program instructions;

[0076] The processor is used to run one or more program instructions to execute a high-precision automatic analysis method of coal structure based on full-diameter CT.

[0077] Corresponding to the above embodiment, an embodiment of the present invention provides a computer-readable storage medium, which contains one or more program instructions, and the one or more program instructions are used by a processor to execute a high-precision automatic analysis method of coal structure based on full-diameter CT.

[0078] The embodiments disclosed in the present invention provide a computer-readable storage medium, in which computer program instructions are stored. When the computer program instructions are executed on a computer, the computer executes the above-mentioned high-precision automatic analysis method of coal structure based on full-diameter CT.

[0079] In the embodiment of the present invention, the processor may be an integrated circuit chip having the signal processing capability. The processor may be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0080] The methods, steps and logic block diagrams disclosed in the embodiments of the present invention can be implemented or executed. The general processor can be a microprocessor or the processor can also be any conventional processor, etc. The steps of the method disclosed in the embodiments of the present invention can be directly embodied as a hardware decoding processor for execution, or can be executed by a combination of hardware and software modules in the decoding processor. The software module can be located in a mature storage medium in the field such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory or an electrically erasable programmable memory, a register, etc. The processor reads the information in the storage medium and completes the steps of the above method in combination with its hardware.

[0081] The storage medium may be a memory, which may be, for example, a volatile memory or a nonvolatile memory, or may include both volatile and nonvolatile memory.

[0082] Among them, the non-volatile memory can be a read-only memory (ROM), a programmable ROM (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or a flash memory.

[0083] The volatile memory may be a random access memory (RAM) which is used as an external cache. By way of example and not limitation, many forms of RAM are available, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate synchronous DRAM (DDRSDRAM), enhanced synchronous DRAM (ESDRAM), synchronous link DRAM (SLDRAM), and direct RAM bus DRAM (DRRAM).

[0084] The storage media described in the embodiments of the present invention are intended to include, but are not limited to, these and any other suitable types of memory.

[0085] Those skilled in the art will appreciate that in one or more of the above examples, the functions described in the present invention can be implemented using a combination of hardware and software. When software is used, the corresponding functions can be stored in a computer-readable medium or transmitted as one or more instructions or codes on a computer-readable medium. Computer-readable media include computer storage media and communication media, wherein communication media include any media that facilitates the transmission of computer programs from one place to another. Storage media can be any available media that can be accessed by general or special-purpose computers.

[0086] The specific implementation methods described above further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific implementation method of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made on the basis of the technical solution of the present invention should be included in the scope of protection of the present invention.

Claims

1. A high-precision automatic analysis method of coal structure based on full-diameter CT, characterized in that: include: Perform full-diameter CT scanning of the coal and rock in the entire well section to obtain multiple vertically continuous grayscale slice data volumes; Segment the coal rock skeleton particles for each grayscale slice data volume to generate a coal rock skeleton particle structure data volume; Calculate the particle size of the coal rock skeleton particle structure data volume of each gray slice data volume to obtain the coal rock particle size distribution; According to the diameter of coal rock core sampling, the classification boundaries of different coal structures are determined, and the coal structure classification standards are formed; According to the coal rock particle size distribution and coal body structure classification standards on each grayscale slice data volume, calculate the proportion of each type of coal body structure and complete the coal body structure analysis of the current well section; The particle size calculation of the coal rock skeleton particle structure data volume includes the following sub-steps: The coal rock skeleton particle structure data volume on each grayscale slice data volume is subjected to a particle sorting operation to obtain a particle sorting data volume; the coal rock skeleton particle structure data volume is subjected to a particle sorting operation, specifically: first, the adjacency relationship between pixels is defined as 8-adjacency, and then the image is traversed using a depth-first search method, starting from a starting point and exploring in depth along each path until it is no longer possible to connect as the boundary of the particle, and the particle sorting data volume of each slice is obtained through the above sorting operation, and the particle sorting data volume has distinguished the boundaries of different coal rock particles; Calculate the particle diameter of the particle sorting data volume to obtain the particle diameter of each grayscale slice data volume and the average particle diameter of the slice; Count the coal and rock particles in each grayscale slice data volume to obtain a coal and rock particle statistics table; Count the coal and rock particles in each grayscale slice data volume, including particle sequence, slice sequence, particle diameter and slice average particle diameter; Calculate the proportion of various coal body structures, and the specific formula is as follows: Among them, F is the proportion of various coal body structures, pixel is the longitudinal resolution of the full-diameter CT scan, L is the total length of the coal core in the scanned section, count(i) represents the counting of slices that meet the average particle size range, i represents the average particle diameter of coal and rock. When X - 20 < i ≤ X, the statistical result F is the proportion of the primary structure; when 5 < i ≤ X - 20, the statistical result F is the proportion of the fragmented structure; when 1 < i ≤ 5, the statistical result F is the proportion of the granular structure; When 0<i≤1, the statistical result F is the proportion of mylonitic structure; according to the coal body structure classification standard table, the average particle diameter of each grayscale slice data volume calculated in the scanning section is evaluated accordingly to obtain the coal body structure evaluation result of the full scanning layer.

2. The high-precision automatic analysis method of coal structure based on full-diameter CT according to claim 1, characterized in that: The full-diameter CT scan was specifically set to have a transverse resolution of 146 μm and a longitudinal resolution of 800 μm, and the storage format was signed hexadecimal grayscale slice data.

3. The high-precision automatic analysis method of coal body structure based on full-diameter CT according to claim 2, characterized in that: The digital core threshold segmentation or watershed method is used to perform coal rock skeleton particle segmentation on the grayscale slice data volume.

4. The high-precision automatic analysis method of coal structure based on full-diameter CT according to claim 3 is characterized in that: The threshold range > -200 is set as the coal rock skeleton threshold range, and segmentation is performed according to the threshold range to obtain the coal rock skeleton particle structure data volume.

5. The high-precision automatic analysis method of coal structure based on full-diameter CT according to claim 1, characterized in that: The particle sorting data body is input into the image processing software, and the image processing software is used to count the size of the coal and rock particles in each slice, and the particle diameter of each grayscale slice data body and the average particle diameter of the slice are calculated.

6. A high-precision automatic analysis system for coal structure based on full-diameter CT, characterized in that: include: Full-diameter CT scanner and coal structure analysis device; The full-diameter CT scanner performs full-diameter CT scans of coal and rock in the entire well section; The coal structure analysis device specifically includes: A grayscale slice data volume acquisition module is used to acquire a plurality of longitudinally continuous grayscale slice data volumes from a full-diameter CT scanner; The coal rock skeleton particle segmentation module is used to perform coal rock skeleton particle segmentation on each gray slice data volume to generate a coal rock skeleton particle structure data volume; The coal rock particle size distribution acquisition module is used to calculate the particle size of the coal rock skeleton particle structure data volume of each gray slice data volume to obtain the coal rock particle size distribution; A coal body structure classification standard forming module is used to determine the classification boundaries of different coal body structures according to the diameter of coal rock core sampling, and form a coal body structure classification standard; The coal structure analysis module is used to calculate the proportion of various types of coal structures based on the coal rock particle size distribution and coal structure classification standards on each grayscale slice data volume, and complete the coal structure analysis of the current well section; The particle size calculation of the coal rock skeleton particle structure data volume includes: The coal rock skeleton particle structure data volume on each grayscale slice data volume is subjected to a particle sorting operation to obtain a particle sorting data volume; the coal rock skeleton particle structure data volume is subjected to a particle sorting operation, specifically: first, the adjacency relationship between pixels is defined as 8-adjacency, and then the image is traversed using a depth-first search method, starting from a starting point and exploring in depth along each path until it is no longer possible to connect as the boundary of the particle, and the particle sorting data volume of each slice is obtained through the above sorting operation, and the particle sorting data volume has distinguished the boundaries of different coal rock particles; Calculate the particle diameter of the particle sorting data volume to obtain the particle diameter of each grayscale slice data volume and the average particle diameter of the slice; Count the coal and rock particles in each grayscale slice data volume to obtain a coal and rock particle statistical table; count the coal and rock particles in each grayscale slice data volume, including particle sequence, slice sequence, particle diameter and slice average particle diameter; Calculate the proportion of various coal body structures, and the specific formula is as follows: Among them, F is the proportion of various coal body structures, pixel is the longitudinal resolution of the full-diameter CT scan, L is the total length of the coal core in the scanned section, count(i) represents the counting of slices that meet the average particle size range, i represents the average particle diameter of coal and rock. When X - 20 < i ≤ X, the statistical result F is the proportion of the primary structure; when 5 < i ≤ X - 20, the statistical result F is the proportion of the fragmented structure; when 1 < i ≤ 5, the statistical result F is the proportion of the granular structure; when 0 < i ≤ 1, the statistical result F is the proportion of the mylonite structure; according to the coal body structure classification standard table, the average particle diameter of each gray slice data body calculated in the scanned section is correspondingly evaluated to obtain the evaluation result of the coal body structure of the full scanned section.

7. A computer storage medium, characterized in that include: at least one memory and at least one processor; The memory is used to store one or more program instructions; A processor is used to run one or more program instructions to execute the high-precision automatic analysis method of coal body structure based on full-diameter CT as described in any one of claims 1-5.

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