Digital core technology-based macroscopic coal rock type quantitative analysis method and system
By using CT scanning and digital core technology, the problem of the inability to quantitatively identify the macroscopic type of coal and rock in traditional methods has been solved, enabling rapid and accurate analysis of coal and rock types and supporting coalbed methane exploration and evaluation.
Patent Information
- Application Number
- CN202511089676.7
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-08-05
- Publication Date
- 2025-11-04
AI Technical Summary
Traditional methods for identifying the macroscopic types of coal and rock rely on human observation and description, which cannot observe the internal characteristics of the rock core. This leads to rough judgments and a lack of quantitative analysis, affecting the comprehensiveness and accuracy of the evaluation.
A CT-based imaging approach was adopted to obtain grayscale images of coal and rock segments through full-diameter spiral CT scanning. Grayscale calibration and threshold segmentation were performed, and the content of macroscopic coal and rock types was calculated. Digital core software was then used for modeling and analysis.
It enables rapid, intuitive, and quantitative identification of coal and rock types, improving identification efficiency and evaluation accuracy, and supporting coal and rock reservoir evaluation and coalbed methane resource calculation.
Smart Images
Figure CN120891017A_ABST
Abstract
Description
TECHNICAL FIELD
[0001] The present application relates to the technical field of coalbed methane exploration and development and CT digital core analysis, and particularly relates to a macro coal rock type quantitative analysis method and system based on digital core technology. BACKGROUND
[0002] The macro coal rock type refers to a coal rock type classified according to the total content of macro coal rock components in a coal seam, and is a type of coal facies composition, which reflects the combination of macro coal rock components to a certain extent. The basic components of coal rock are vitrite, clarite, durite and fusite, and the macro coal rock type is usually classified into bright coal, semi-bright coal, semi-dull coal and dull coal.
[0003] The bright coal is mainly composed of vitrite and clarite (80%), has very strong luster, and the composition is relatively uniform, and is often in a uniform or non-obvious line structure. Since the content of vitrite and clarite is the highest, the density is the lowest.
[0004] The semi-bright coal is mainly composed of vitrite and clarite (50% to 80%), and contains durite and fusite. The luster intensity is slightly weaker than that of the bright coal. The macro coal rock components can appear alternately, the content of vitrite and clarite is relatively high, and the density is relatively low.
[0005] The semi-dull coal has a small content of vitrite and clarite (50% to 20%), and a large content of durite and fusite. The luster is relatively dull. The hardness, toughness and specific gravity of the semi-dull coal are relatively large, and the density is relatively high.
[0006] The dull coal has a very small content of vitrite and clarite (<20%), and is mainly composed of durite. The luster is dull, the block structure is in a line structure or a lens structure, is dense and hard, has large toughness, has large specific gravity, and has the highest density.
[0007] The traditional method for identifying the macro type of coal rock mainly relies on human observation and description, which requires high core identification ability and experience of technical personnel, and is not conducive to comprehensive promotion and application. There are two major defects in human identification of the macro coal rock type. One is that the internal coal rock characteristics of the core cannot be observed. If the core segment is long, only the fresh cross sections at both ends of the core can be observed as the main description object, the description is relatively general, and the judgment of the macro type of the long coal rock can only be roughly estimated. The other is that all data obtained by the traditional method can only be estimated by human, and cannot be quantified, thereby affecting the comprehensiveness and accuracy of subsequent evaluation. Based on this, the present application provides a macro coal rock type quantitative analysis method based on CT scan imageology. SUMMARY
[0008] The present application provides a macro coal rock type quantitative analysis method based on digital core technology, which comprises the following steps.
[0009] Full-diameter spiral CT scans of coal and rock were performed to obtain multiple core scan grayscale images;
[0010] Different points in the core scanning grayscale image were selected to perform grayscale calibration on macroscopic coal and rock components, and the threshold range of each macroscopic coal and rock component was determined.
[0011] Based on the established threshold range of macroscopic coal and rock components, each core scan grayscale image is divided into macroscopic coal and rock components, macroscopic coal and rock type threshold segmentation is performed, and the content of macroscopic coal and rock type is calculated.
[0012] Coal and rock type analysis is conducted based on the content of macroscopic coal and rock types.
[0013] The above-mentioned method for quantitative analysis of macroscopic coal and rock types based on digital core technology involves performing full-diameter spiral CT continuous scanning on typical coal and rock cores to obtain grayscale slice images of coal and rock segments. The grayscale slices are then modeled using digital core software to obtain the core scanning grayscale image and the grayscale data values of sample points within the coal and rock segments.
[0014] The quantitative analysis method for macroscopic coal and rock types based on digital core technology, as described above, includes macroscopic coal and rock components such as vitreous coal, bright coal, dark coal, fibrous coal, and inorganic minerals. In the threshold segmentation process, vitreous coal and bright coal are segmented together, dark coal and fibrous coal are segmented together, and inorganic minerals are segmented separately.
[0015] The quantitative analysis method for macroscopic coal and rock types based on digital core technology, as described above, includes the following sub-steps for determining the threshold range of each macroscopic coal and rock component:
[0016] The scanned grayscale image is processed pixel by pixel based on the coal and rock composition.
[0017] In the pixel-processed image, the coal and rock composition of the sample points is identified;
[0018] Based on the calibrated coal and petrographic components, the grayscale threshold range of the coal and petrographic components is determined.
[0019] The quantitative analysis method for macroscopic coal and rock types based on digital core technology, as described above, involves threshold segmentation of all scanned core grayscale images according to the threshold range of macroscopic coal and rock components. Taking each scanned core grayscale cross-section as the object, the grayscale threshold segmentation on each cross-section divides the composition into three major categories: vitreous coal + bright coal, dark coal + fibrous coal, and inorganic minerals.
[0020] The quantitative analysis method for macroscopic coal and rock types based on digital core technology, as described above, involves calculating the content of macroscopic coal and rock types by: calculating the grayscale image of each core scan, calculating the area of vitreous coal + bright coal, the area of dark coal + fibrous coal, and the mineral area on the cross section, and then calculating the area ratio of vitreous coal + bright coal and the area ratio of dark coal + fibrous coal on each core scan grayscale image.
[0021] The quantitative analysis method for macroscopic coal and rock types based on digital core technology, as described above, involves calculating the content of macroscopic coal and rock types and then classifying each scanned single-layer slice according to the macroscopic coal and rock type classification standard.
[0022] The quantitative analysis method for macroscopic coal and rock types based on digital core technology, as described above, involves analyzing coal and rock types based on the content of macroscopic coal and rock types. Specifically, based on the results of the macroscopic coal and rock type classification of single-layer slices, a macroscopic coal and rock type evaluation map is drawn vertically from shallow to deep, and the content ratio of each macroscopic coal and rock type is calculated.
[0023] This invention also provides a macroscopic coal and rock type quantitative analysis system based on digital core technology, including: a CT scanning device and a coal and rock component analysis device;
[0024] CT scanning equipment is used to perform full-diameter spiral CT scans of coal and rock to obtain multiple core scan grayscale images.
[0025] The coal and rock composition analysis device is used to select different points in the core scanning grayscale image, perform grayscale calibration on the macroscopic coal and rock composition, and determine the threshold range of each macroscopic coal and rock composition; based on the determined threshold range of the macroscopic coal and rock composition, the device divides each core scanning grayscale image into macroscopic coal and rock composition, performs macroscopic coal and rock type threshold segmentation, and calculates the content of macroscopic coal and rock type; and performs coal and rock type analysis based on the content of macroscopic coal and rock type.
[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 for running one or more program instructions to execute the macroscopic coal and rock type quantitative analysis method based on digital core technology described above.
[0029] The beneficial effects achieved by this invention are as follows:
[0030] (1) This invention applies CT digital core scanning analysis technology to the classification and evaluation of macroscopic coal and rock types. Full-diameter CT scanning can intuitively reflect the relative density of the scanned material, so bright coal, semi-bright coal, semi-dark coal and dark coal can be distinguished by threshold segmentation of the scanned gray scale slices.
[0031] (2) By using digital core full-diameter spiral CT scanning technology, the threshold division boundary of coal and rock macro types is clarified, and a gray threshold model of coal and rock macro types is established to realize the evaluation of the vertical macro types of coal and rock strata in the whole well, effectively supporting the evaluation of coal and rock reservoirs and the calculation of coalbed methane resources.
[0032] (3) Identifying the macroscopic types of coal and rock through full-diameter spiral CT scanning has the advantages of being fast, intuitive, and quantitative. It is necessary to promote this technology in the industry to improve the efficiency of technical personnel and promote productivity. Attached Figure Description
[0033] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For those skilled in the art, other drawings can be obtained based on these drawings.
[0034] Figure 1 This is a flowchart of the method for quantitative analysis of macroscopic coal and rock types based on digital core technology provided in Embodiment 1 of this application;
[0035] Figure 2 It is a grayscale image of the core scan;
[0036] Figure 3 This is a schematic diagram comparing the image before and after pixel processing;
[0037] Figure 4 This is a schematic diagram of the macroscopic coal and petrographic component grayscale slice calibration;
[0038] Figure 5 It is a macroscopic coal and rock composition scanning threshold segmentation map;
[0039] Figure 6 This is a schematic diagram of the evaluation results of the macroscopic type of coal and rock in the scanned section. Detailed Implementation
[0040] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.
[0041] Example 1
[0042] like Figure 1 As shown, Embodiment 1 of this application provides a method for quantitative analysis of macroscopic coal and rock types based on digital core technology, including:
[0043] Step 110: Conduct a full-diameter spiral CT scan of the coal and rock to obtain multiple core scan grayscale images;
[0044] Specifically, taking a Paleozoic coal-rock well in a certain coalbed methane block in China as an example, the core of the coal-rock section that has been obtained was subjected to continuous full-diameter spiral CT scanning. The scanning equipment was the Sinowon InsitumCT338 spiral CT scanner, which obtained grayscale slices. The horizontal resolution of the scan was 146μm and the vertical resolution was 600μm.
[0045] Full-diameter spiral CT continuous scanning was performed on typical coal core samples to obtain grayscale slices of the coal sections. These grayscale slices were then modeled using specialized digital core software to obtain the desired results. Figure 2 The image shows a grayscale image of the core scan, and the grayscale data values of the sample points inside the coal and rock section are obtained.
[0046] Step 120: Select different points in the core scan grayscale image, perform grayscale calibration on the macroscopic coal and rock components, and determine the threshold range of each macroscopic coal and rock component;
[0047] In this embodiment, the grayscale image of the core scan is compared with the actual core sample, and different sampling points are selected to perform grayscale calibration on the macroscopic coal and petrographic components of the well. During actual observation and threshold segmentation, the grayscale values of vitreous coal and bright coal are both low, making them difficult to distinguish. Therefore, vitreous coal and bright coal are segmented together during threshold segmentation. The grayscale values of dark coal and fusiform coal are slightly higher than those of vitreous coal + bright coal, but they are still difficult to distinguish, so they are also combined during threshold segmentation. Inorganic minerals have the highest grayscale values and can be thresholded separately.
[0048] This application processes scanned grayscale images, selects different reference points to perform grayscale calibration on coal and petrographic components, and determines the grayscale threshold range for three major categories: vitreous coal + bright coal, dark coal + fibrous coal, and inorganic minerals.
[0049] Specifically, determining the threshold ranges for each macroscopic coal and petrographic component includes the following sub-steps:
[0050] Step 121: Perform pixel processing on the scanned grayscale image based on the coal and rock composition.
[0051] Because the scanned images contain noise due to resolution issues, which is detrimental to subsequent threshold segmentation and does not reflect the actual development of macroscopic coal and rock types, which are actually characterized by banded and sheet-like formations, the noise, appearing as dots, can easily mislead segmentation. Therefore, pixel processing of the scanned images is performed first based on the coal and rock composition. The pixel-processed image is shown below. Figure 3 As shown.
[0052] The formula for pixel processing calculation is as follows:
[0053]
[0054] Wherein, the original image grayscale value is f(x,y), the processed image grayscale value is g(x,y), the pixel processor window size is m×n, and (x+i,y+j) represents the pixel coordinates within the window centered at (x,y).
[0055] Step 122: In the image after pixel processing, label the coal and rock components of the sample points;
[0056] On the scanned image after pixel processing, sampling points with different grayscale values were selected based on the differences in the grayscale images of the core scan. Coal and petrographic components were identified at each sampling point to determine the coal and petrographic component type (including vitreous coal, bright coal, dark coal, and fibrous coal). If a sampling point was not coal or petrographic, it was labeled as inorganic matter. The grayscale values of each sampling point and their corresponding coal and petrographic component types were listed and statistically analyzed, and a scatter plot was generated.
[0057] Different points were selected on the pixel-processed image based on grayscale differences for microscopic identification of coal and petrographic components. The results are shown in Table 1 below.
[0058] Table 1. Results of Coal and Rock Component Identification
[0059]
[0060]
[0061] Step 123: Determine the gray threshold range of coal and rock components based on the calibrated sample coal and rock components;
[0062] Based on the statistical analysis of sample component calibration, the grayscale thresholds of each component were classified. Since vitreous coal and bright coal have low densities, their scanned grayscale values are also low, resulting in high repetition within the grayscale value range of the scatter plot, making differentiation difficult. Therefore, the threshold ranges of vitreous coal and bright coal were combined for classification. Dark coal and fibrous charcoal have higher densities, and their grayscale values are higher than those of vitreous coal + bright coal, but they are still difficult to distinguish. Therefore, their threshold ranges were also combined for classification. Inorganic minerals have the highest grayscale values, making classification relatively easy.
[0063] Determining the grayscale threshold range of coal and petrographic components specifically includes:
[0064] Through sample point calibration, the maximum gray value of vitreous coal + bright coal sample points was Jmax, and the minimum gray value was Jmin; the maximum gray value of dark coal + fibrous charcoal sample points was Amax, and the minimum gray value was Amin; the maximum gray value of inorganic minerals was Wmax, and the minimum gray value was Wmin.
[0065] The gray threshold range for vitreous coal and bright coal is: 0~(Jmax+Amin) / 2
[0066] The ash threshold range for dark coal + charcoal is: (Jmax + Amin) / 2 ~ (Amax + Wmin) / 2
[0067] The grayscale threshold range for inorganic minerals is: (Amax + Wmin) / 2 ~ ∞
[0068] As shown in Table 1, the maximum gray value of vitreous coal + bright coal is Jmax = 398 and the minimum gray value is Jmin = 42; the maximum gray value of dark coal + charcoal is Amax = 562 and the minimum gray value is Amin = 362; and the maximum gray value of inorganic minerals is Wmax = 538 and the minimum gray value is Wmin = 1150.
[0069] Based on the calculation method, the threshold ranges for each component are determined as follows:
[0070] The gray threshold range for vitreous coal + bright coal is 0~(Jmax+Amin) / 2, and the calculated result is 0~380;
[0071] The ash threshold range for dark coal + charcoal is (Jmax+Amin) / 2 to (Amax+Wmin) / 2, with a calculated value of 380 to 550.
[0072] The gray threshold range for inorganic minerals is (Amax+Wmin)~∞, and the calculated result is 550~∞.
[0073] Figure 4 This is a schematic diagram of the macroscopic coal and petrographic component grayscale slice calibration. The grayscale threshold range for vitreous coal + bright coal in this well is determined to be 0–380 mm, the grayscale threshold range for dark coal + fibrous char is 380 mm–500 mm, and the grayscale threshold range for inorganic minerals is greater than 500 mm. Then, the grayscale threshold ranges for vitreous coal + bright coal, dark coal + fibrous char, and inorganic minerals are delineated, resulting in the following: Figure 5 The image shows a macroscopic coal and rock composition scanning threshold segmentation diagram.
[0074] Step 130: Based on the determined threshold range of macroscopic coal and rock components, divide each core scan grayscale image into macroscopic coal and rock components, perform macroscopic coal and rock type threshold segmentation, and calculate the content of macroscopic coal and rock types.
[0075] Specifically, all scanned core grayscale images are segmented according to the threshold range of macroscopic coal and petrographic components. Taking each scanned core grayscale cross-section as the object, the grayscale threshold segmentation on each cross-section divides the composition into three major categories: vitreous coal + bright coal, dark coal + fibrous charcoal, and inorganic minerals. The grayscale images of each core are calculated, and the areas of vitreous coal + bright coal (Sj), dark coal + fibrous charcoal (Sa), and minerals (Sm) on the cross-section are calculated respectively. Then, the area ratio of vitreous coal + bright coal (Cj) and the area ratio of dark coal + fibrous charcoal (Ca) on each core grayscale image are calculated.
[0076] Let the cross-sectional area of a single sheet be SD, then:
[0077] The content of vitreous coal and bright coal in a single-layer slice is:
[0078] Cj = Sj / SD * 100%
[0079] The content of dark coal + charcoal in a single-layer slice is:
[0080] Ca = Sa / SD * 100%
[0081] Based on the coal and rock slice information and the above-mentioned data on macroscopic coal and rock types, the numerical table shown in Table 1 below is obtained:
[0082] Table 1. Numerical Table of Slicing Results
[0083]
[0084] Based on the above calculation results, and according to the macroscopic coal and rock type classification standard, each scanned single-layer slice is classified into macroscopic coal and rock types. The classification standard is shown in Table 2 below:
[0085] Table 2. Standards for Classifying Macroscopic Types of Coal and Rock
[0086]
[0087]
[0088] Step 140: Perform coal and petrographic type analysis based on the macroscopic coal and petrographic type content;
[0089] Based on the results of the single-layer slice coal and rock macro-type classification in step 130, a coal and rock macro-type evaluation map is drawn vertically from shallow to deep, and the content ratio of each macro-coal and rock type is calculated. Let the scanned coal and rock length be L, the cumulative length of bright coal be Lg, the cumulative length of semi-bright coal be Ll, the cumulative length of semi-dark coal be La, and the cumulative length of dark coal be Ld.
[0090] The proportion of bright coal content in the scanned section is: Pg = Lg / L
[0091] The proportion of semi-bright coal in the scanned segment is: Pl = Ll / L
[0092] The semi-dark coal content ratio in the scanned segment is: Pa = La / L
[0093] The proportion of dark coal content in the scanned segment is: Pd = Ld / L.
[0094] In this application example, the proportion of bright coal (Pg) in the coal-rock section of this well is calculated to be 66.5%, the proportion of semi-bright coal (Pl) is 14.6%, the proportion of semi-dark coal (Pa) is 2.9%, and the proportion of dark coal (Pd) is 16.0%.
[0095] By calculating the content of each type vertically, the macroscopic type of coal and rock in the scanned section is evaluated as a whole, such as... Figure 6 As shown, the evaluation of the technical solution in this application shows that the proportion of bright coal in the macroscopic coal and rock type of this well is high, indicating that the coal quality of the coal and rock section of this well is good and the degree of coalification is high. It is speculated that the content of vitrinite is high, which is an important basis for judging the advantageous sweet spot in the early stage of coalbed methane exploration, and it is also an important favorable factor for coalbed methane exploration in this well, especially for evaluating the gas generation capacity.
[0096] Example 2
[0097] Embodiment 2 of the present invention provides a macroscopic coal and rock type quantitative analysis system based on digital core technology, including: a CT scanning device and a coal and rock component analysis device;
[0098] CT scanning equipment is used to perform full-diameter spiral CT scans of coal and rock to obtain multiple core scan grayscale images.
[0099] The coal and rock composition analysis device is used to select different points in the core scanning grayscale image, perform grayscale calibration on the macroscopic coal and rock composition, and determine the threshold range of each macroscopic coal and rock composition; based on the determined threshold range of the macroscopic coal and rock composition, the device divides each core scanning grayscale image into macroscopic coal and rock composition, performs macroscopic coal and rock type threshold segmentation, and calculates the content of macroscopic coal and rock type; and performs coal and rock type analysis based on the content of macroscopic coal and rock type.
[0100] Specifically, the CT scanning equipment performs full-diameter spiral CT continuous scanning on typical coal cores to obtain grayscale slice images of the coal section, which are then sent to the coal component analysis device. The coal component analysis device uses digital core software to model the grayscale slices, obtain the core scanning grayscale image, and obtain the grayscale data values of the sample points inside the coal section.
[0101] The coal and petrographic composition analysis device performs threshold segmentation on all scanned core grayscale images according to the macroscopic coal and petrographic composition threshold range. Taking each scanned core grayscale cross-section as the object, the grayscale threshold segmentation on each cross-section divides it into three major categories: vitreous coal + bright coal, dark coal + fibrous coal, and inorganic minerals.
[0102] The coal petrographic component analysis device calculates the macroscopic coal petrographic type content, specifically by: calculating the grayscale image of each core scan, and calculating the area of vitreous coal + bright coal, dark coal + fibrous coal, and mineral area on the cross-section; then calculating the area ratio of vitreous coal + bright coal and the area ratio of dark coal + fibrous coal on each core scan grayscale image. After calculating the macroscopic coal petrographic type content, the macroscopic coal petrographic type is classified for each scanned single-layer slice according to the macroscopic coal petrographic type classification standard.
[0103] The coal and rock composition analysis device performs coal and rock type analysis based on the content of macroscopic coal and rock types. Specifically, based on the results of the macroscopic coal and rock type classification of single-layer slices, a coal and rock macroscopic type evaluation map is drawn vertically from shallow to deep, and the content ratio of each macroscopic coal and rock type is calculated.
[0104] Corresponding to the above embodiments, the present invention provides a computer storage medium, including: at least one memory and at least one processor;
[0105] The memory is used to store one or more program instructions;
[0106] A processor is used to run one or more program instructions to execute a quantitative analysis method for macroscopic coal and rock types based on digital core technology.
[0107] Corresponding to the above embodiments, this embodiment of the invention provides a computer-readable storage medium containing one or more program instructions, which are executed by a processor to provide a method for quantitative analysis of macroscopic coal and rock types based on digital core technology.
[0108] The embodiments disclosed in this invention provide a computer-readable storage medium storing computer program instructions. When the computer program instructions are executed on a computer, the computer performs the aforementioned method for quantitative analysis of macroscopic coal and rock types based on digital core technology.
[0109] In this embodiment of the invention, the processor can be an integrated circuit chip with signal processing capabilities. The processor can 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.
[0110] The various methods, steps, and logic diagrams disclosed in the embodiments of this invention can be implemented or executed. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of this invention can be directly implemented by a hardware decoding processor, or implemented by a combination of hardware and software modules in the decoding processor. The software modules can reside in random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, or other mature storage media in the art. The processor reads information from the storage medium and, in conjunction with its hardware, completes the steps of the above methods.
[0111] The storage medium can be memory, such as volatile memory or non-volatile memory, or may include both volatile and non-volatile memory.
[0112] Among them, non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory.
[0113] Volatile memory can be random access memory (RAM), which is used as an external cache. By way of example, but not limitation, many forms of RAM are available, such as static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDRSDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous linked dynamic random access memory (Synchlink DRAM, SLDRAM), and direct memory bus RAM (DRRAM).
[0114] 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.
[0115] Those skilled in the art will recognize that, in one or more of the examples above, the functions described in this invention can be implemented using a combination of hardware and software. When applied as software, the corresponding functions can be stored in a computer-readable medium or transmitted as one or more instructions or code on a computer-readable medium. Computer-readable media include computer storage media and communication media, wherein communication media include any medium that facilitates the transmission of computer programs from one place to another. Storage media can be any available medium accessible to general-purpose or special-purpose computers.
[0116] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above description is only a specific embodiment 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 within the scope of protection of the present invention.
Claims
1. A method for quantitative analysis of macroscopic coal and rock types based on digital core technology, characterized in that, include: Full-diameter spiral CT scans of coal and rock were performed to obtain multiple core scan grayscale images; Different points in the core scanning grayscale image were selected to perform grayscale calibration on macroscopic coal and rock components, and the threshold range of each macroscopic coal and rock component was determined. Based on the established threshold range of macroscopic coal and rock components, each core scan grayscale image is divided into macroscopic coal and rock components, macroscopic coal and rock type threshold segmentation is performed, and the content of macroscopic coal and rock type is calculated. Coal and rock type analysis is conducted based on the content of macroscopic coal and rock types.
2. The method for quantitative analysis of macroscopic coal and rock types based on digital core technology as described in claim 1, characterized in that, A full-diameter spiral CT continuous scan was performed on a typical coal core to obtain a grayscale slice image of the coal section. The grayscale slice was then modeled using digital core software to obtain a core scan grayscale image and grayscale data values of sample points inside the coal section.
3. The method for quantitative analysis of macroscopic coal and rock types based on digital core technology as described in claim 2, characterized in that, Macroscopic coal petrographic components include vitreous coal, bright coal, dark coal, fibrous coal, and inorganic minerals. During threshold segmentation, vitreous coal and bright coal are segmented together, dark coal and fibrous coal are segmented together, and inorganic minerals are segmented separately.
4. The method for quantitative analysis of macroscopic coal and rock types based on digital core technology as described in claim 3, characterized in that, Determining the threshold ranges for each macroscopic coal and petrographic component involves the following sub-steps: The scanned grayscale image is processed pixel by pixel based on the coal and rock composition. In the pixel-processed image, the coal and rock composition of the sample points is identified; Based on the calibrated coal and petrographic components, the grayscale threshold range of the coal and petrographic components is determined.
5. The method for quantitative analysis of macroscopic coal and rock types based on digital core technology as described in claim 1, characterized in that, All scanned core grayscale images were segmented according to the threshold range of macroscopic coal and petrographic components. Taking each scanned core grayscale cross section as the object, each cross section was divided into three major categories of composition: vitreous coal + bright coal, dark coal + fibrous coal, and inorganic minerals through grayscale threshold segmentation.
6. The method for quantitative analysis of macroscopic coal and rock types based on digital core technology as described in claim 5, characterized in that, The calculation of macroscopic coal and rock type content is specifically as follows: calculate the grayscale image of each core scan, and calculate the area of vitreous coal + bright coal, dark coal + fibrous coal, and mineral area on the cross section, and then calculate the area ratio of vitreous coal + bright coal and the area ratio of dark coal + fibrous coal on each core scan grayscale image.
7. The method for quantitative analysis of macroscopic coal and rock types based on digital core technology as described in claim 6, characterized in that, After calculating the content of macroscopic coal and rock types, the macroscopic coal and rock types are classified for each scanned single-layer slice according to the classification standard for macroscopic coal and rock types.
8. The method for quantitative analysis of macroscopic coal and rock types based on digital core technology as described in claim 7, characterized in that, Coal and rock type analysis is conducted based on the content of macroscopic coal and rock types. Specifically, based on the results of the macroscopic coal and rock type classification of single-layer slices, a macroscopic coal and rock type evaluation map is drawn vertically from shallow to deep, and the content ratio of each macroscopic coal and rock type is calculated.
9. A quantitative analysis system for macroscopic coal and rock types based on digital core technology, characterized in that, include: CT scanning equipment and coal and rock composition analysis device; CT scanning equipment is used to perform full-diameter spiral CT scans of coal and rock to obtain multiple core scan grayscale images. The coal and rock composition analysis device is used to select different points in the core scanning grayscale image, perform grayscale calibration on the macroscopic coal and rock composition, and determine the threshold range of each macroscopic coal and rock composition; based on the determined threshold range of the macroscopic coal and rock composition, the device divides each core scanning grayscale image into macroscopic coal and rock composition, performs macroscopic coal and rock type threshold segmentation, and calculates the content of macroscopic coal and rock type; and performs coal and rock type analysis based on the content of macroscopic coal and rock type.
10. 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 for running one or more program instructions to execute the macroscopic coal and rock type quantitative analysis method based on digital core technology as described in any one of claims 1-8.