Deep coal rock cleat development degree evaluation method based on full-diameter rock core end face image

Abstract

The invention discloses a deep coal rock cleat development degree evaluation method based on a full-diameter rock core end face image, and the method comprises the steps: firstly obtaining the full-diameter rock core end face image, and carrying out the illumination balance processing of the rock core end face image, including image brightness calculation and brightness balance; setting a core end face image threshold value, and converting the gray level image into a binary image according to the threshold value; calculating a coal rock cleat pixel proportion by using the binary image, and further calculating a coal rock end face cleat porosity and a coal rock end face fractal dimension; and finally, establishing a cross plot of the fractal dimension and the cleat porosity. And according to the intersection relationship between the fractal dimension and the cleat porosity, finding out division boundaries of relatively developed, developed and extremely developed, and further carrying out classification evaluation on the cleat development degree of the end face of the coal rock core. The original data required by the method is the coal rock core end face image, and the method is suitable for analysis and calculation of the coal rock surface image under most conditions, so that the working efficiency is remarkably improved, and the time and the economic cost are saved.

Description

Technical Field

[0001] The invention relates to the technical field of coalbed methane exploration and development, and in particular to a method for evaluating the development degree of deep coal cleats based on full-diameter core end face images. Background Art

[0002] The cleats in deep coal rock are mainly cracks caused by changes in the structure and texture of coal materials during the coalification process, also known as endogenous cracks. The cleats are mainly divided into face cleats and end cleats. Face cleats are generally more continuous and approximately parallel to the layer, while end cleats are generally less continuous and approximately vertical to the layer. The degree of development of cleats will affect the storage and seepage capacity of coal rock. At present, the evaluation of the degree of development of cleats can only be qualitatively evaluated with reference to relevant national standards. The evaluation results are mainly divided into several development degree categories such as relatively developed, developed, and extremely developed.

[0003] The methods commonly used to evaluate the development degree of coal cleats are mainly CT scanning and core surface observation. The CT scanning method forms a grayscale image after CT scanning, so as to further identify, judge and describe the development of cleats. This method can accurately reconstruct and model the core in three dimensions, but the economic cost of CT scanning is high, and it only shows good results when scanning plunger-like cores or small-diameter cores, while the scanning effect of full-diameter cores is relatively poor. In addition, plunger-like cores or small-diameter cores are difficult to fully and accurately represent the overall development degree of deep coal cleats. In contrast, the core surface observation method is cheaper, easier to obtain, and can be based on full-diameter cores, which is more representative. This method can be evaluated by manual identification and statistics or by machine identification and calculation of cleat porosity for evaluation, but the manual identification and evaluation method may have different observation and description locations and measurement points for different description personnel, resulting in different measured and recorded data, and even due to the discontinuity and scattered distribution of end cleats, it is impossible to count them, and the workload is high, the efficiency is low, and the time cost is high. Although the machine recognition and evaluation method saves a certain amount of time and improves efficiency, it is easy to ignore factors such as the complexity of the cleat, resulting in those cleats with high porosity but low actual development level being mistakenly judged as having high development level, making the evaluation effect worse. Therefore, the existing technology still lacks a simple, efficient, and accurate method for evaluating the development level of deep coal cleats. Summary of the invention

[0004] In view of the above-mentioned shortcomings of the existing coal rock cleat development degree evaluation method, the present invention provides an efficient deep coal rock cleat development degree evaluation method based on the full-diameter core end face image. The method uses a machine to identify the full-diameter core end face image of deep coal rock, and adopts a method combining cleat porosity and fractal dimension to achieve accurate evaluation of deep coal rock cleat development degree, while also significantly improving work efficiency and saving time and economic costs.

[0005] The method for evaluating the degree of development of deep coal cleats based on full-diameter core end face images provided by the present invention comprises the following specific steps:

[0006] S1. Obtain the full-diameter core end face image and perform light balance processing on the core end face image, including image brightness calculation and brightness balance. A photo of the core end face is taken with a camera at the core sampling site, which is the core end face image.

[0007] The method for calculating image brightness is as follows:

[0008] The input coal rock color image is converted into a grayscale image; the maximum value of the three components in the color image is used as the grayscale value of the grayscale image, and the pixel brightness calculation formula is:

[0009] Gray(x,y)=max{R(x,y),G(x,y),B(x,y)}

[0010] Where Gray(x,y) is the gray value of the pixel at position (x,y) of the grayscale image, and R(x,y), G(x,y), and B(x,y) are the red, green, and blue components of the pixel at position (x,y) of the RGB image, respectively.

[0011] Image brightness equalization method: take the brightness of the local area with small brightness difference as the background brightness, calculate the background brightness value, and then subtract the background brightness value from the image brightness value to obtain the brightness difference image, which is the image after brightness equalization.

[0012] After brightness equalization, the relevant parameters of the new image are recalculated to obtain a brightness-equalized RGB image.

[0013] S2. Setting the core end face image threshold; the method is as follows:

[0014] Automatically obtain the initial segmentation threshold T based on the maximum inter-class variance method 0 , then at T 0 The surroundings are respectively greater than T 0 The sum of at least three values ​​is less than T 0At least three values ​​are taken, and the cleat pixel area corresponding to each value is calculated. The threshold is taken as the horizontal coordinate and the cleat pixel area is taken as the vertical coordinate. A curve graph between the cleat pixel area and the threshold is established. Then, the starting segment and the end segment of the curve are fitted, and the intersection of the two fitting straight lines is taken as the threshold T.

[0015] In order to simplify calculation in subsequent steps, the threshold value may be further simplified to be an integer closest to the threshold value T.

[0016] S3, binary segmentation of core end face image;

[0017] The grayscale image is converted into a binary image according to the threshold determined in step S2, and all pixels with grayscale greater than or equal to the threshold T are judged as coal rock skeletons, and their grayscale values ​​are set to 255 (white); otherwise, they are judged as coal rock cleats, and their grayscale values ​​are set to 0 (black).

[0018] S4. Calculation of coal rock face cleat porosity;

[0019] The binary image is used to calculate the percentage of coal rock cleat pixels. The formula is as follows:

[0020]

[0021] In the formula, S is the proportion of pixels where cleats are located on the coal rock end surface, A is the number of pixels occupied by cleats on the coal rock end surface, and B is the total number of pixels on the coal rock end surface;

[0022] The coal rock cleat pixel ratio is converted into cleat porosity using the following formula:

[0023]

[0024] Where X is the cleat porosity calculated by calibration, S is the cleat pixel ratio before calibration, d and c are the maximum and minimum cleat porosity in the study area, b and a are the maximum and minimum cleat pixel ratios of the target coal rock, respectively.

[0025] S5. Calculation of fractal dimension of coal rock end surface, the formula is as follows:

[0026]

[0027] Where ε is the length of one side of the small cube, and N(ε) is the number of small cubes covering the cleavage being measured.

[0028] S6. Evaluate the degree of cleat development on the end face of coal core;

[0029] Through steps S1-S5, the processing of all deep coal core end face images, the identification of cleats, the calculation of cleat porosity and fractal dimension are completed; then, the fractal dimension is used as the horizontal coordinate and the cleat porosity is used as the vertical coordinate to establish an intersection diagram of fractal dimension and cleat porosity; based on the intersection relationship between fractal dimension and cleat porosity, the dividing line between relatively developed, developed and extremely developed is found, and then the degree of cleat development on the coal core end face is classified and evaluated.

[0030] Compared with the prior art, the present invention is beneficial in that:

[0031] (1) The method of the present invention is more accurate in evaluating the cleat development of coal and rock surfaces. The method of the present invention is compared with the conventional method. The average accuracy of the method is 85.03%, while the average accuracy of the conventional method is 67.86%. The method significantly improves the accuracy of the evaluation of the cleat development degree of deep coal and rock end faces.

[0032] (2) Wide application scope. The original data required by the method of the present invention is the end face image of the coal rock core, and it is applicable to the analysis and calculation of coal rock surface images in most cases, especially the end face image of the full-diameter core. Regardless of how the shooting direction angle of the image is changed, the illumination can be uniformed. The defect of the existing CT scanning method that the scanning effect of the full-diameter core is poor is overcome.

[0033] (3) The method of the present invention rationally utilizes machines to identify the full-diameter core end face images of deep coal and rock, thereby improving the efficiency of description and evaluation and saving a lot of time and economic costs of manual identification and evaluation.

[0034] Other advantages, objectives and features of the present invention will be embodied in part through the following description, and in part will be understood by those skilled in the art through study and practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 The brightness balance comparison diagram of the core image. (a) is the image of the coal rock end surface before brightness balance, and (b) is the image of the coal rock end surface after brightness balance.

[0036] Figure 2 Select a map for Threshold.

[0037] Figure 3 This is a comparison chart of the core binary image.

[0038] Figure 4 Calculate the fractal dimension of an image.

[0039] Figure 5 This is a graph showing the evaluation results of the degree of development of cleats on the coal rock face using the method of the present invention.

[0040] Figure 6This is the evaluation result of the development degree of cleat on the coal rock face using method 1.

[0041] Figure 7 This is the evaluation result of the development degree of cleat on the coal rock face using method 2.

[0042] Figure 8 This is a comparison chart before and after the coal rock end face is evenly illuminated. DETAILED DESCRIPTION

[0043] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0044] like Figure 1-8 As shown, the method for evaluating the development degree of deep coal cleats based on the full-diameter core end face image provided by the present invention comprises the following specific steps:

[0045] (1) Core end face image illumination balance

[0046] Image brightness equalization is an important image processing technology that aims to solve the problem of uneven brightness in images and improve the quality and visibility of images. In images with uneven brightness, the brightness distribution of the image will directly affect the extraction of cleat features, resulting in differences in the cleat features extracted from different areas of the image. This technology can make the cleats in the image clearer and easier to distinguish, and improve the accuracy and efficiency of image processing and analysis. Therefore, when extracting the cleat features on the core end face, appropriate preprocessing techniques are needed to balance the brightness distribution of the image. It mainly includes image brightness calculation and brightness equalization processing.

[0047] Image brightness calculation: The input coal rock color image needs to be converted into a grayscale image. Grayscale processing is the process of converting a color image into a black and white image. In the RGB color model, each pixel is represented by three components: red (R), green (G), and blue (B). The maximum value of the three components in the color image is used as the grayscale value of the grayscale image. The size of the grayscale value determines the brightness of the pixel, thereby affecting the brightness of the entire image. The formula for calculating pixel brightness is:

[0048] Gray(x,y)=max{R(x,y),G(x,y),B(x,y)}

[0049] Where Gray(x,y) is the gray value of the pixel at position (x,y) of the grayscale image, and R(x,y), G(x,y), and B(x,y) are the red, green, and blue components of the pixel at position (x,y) of the RGB image, respectively.

[0050] Brightness balance processing: The specific calculation formula is:

[0051] I(x,y)=f(x,y)–0.5*bg(x,y)

[0052] Where I(x, y) is the brightness value of the image after brightness equalization, f(x, y) is the brightness value of the image before brightness equalization, and bg(x, y) is the background brightness value. In practical applications, the background brightness ratio needs to be reasonably adjusted to avoid excessive equalization. In this embodiment, the ratio is 0.5. After brightness equalization, the relevant parameters of the new image are recalculated to obtain the RGB image after brightness equalization. The result is as follows: Figure 1 As shown in the figure, (a) is the image of the coal rock end face before brightness equalization, and (b) is the image of the coal rock end face after brightness equalization.

[0053] (2) Core end face image threshold setting

[0054] Automatically obtain the initial segmentation threshold T based on the maximum inter-class variance method 0 In this embodiment, T 0 =40.8, then, within the range of plus or minus 30, the threshold is increased in steps of 10, multiple numerical points (10, 20, 30, 40, 50, 60, 70, 80) are set, and the cleat pixel area corresponding to each numerical point is calculated; Figure 2 As shown, a curve diagram between the cleat pixel area and the threshold is established, and then the starting segment and the ending segment are fitted, and the intersection of the two fitting lines is used as the threshold T, T=47.6.

[0055] (3) Binary segmentation of core end surface image

[0056] Image binary segmentation is an important image processing technology. It sets the grayscale value of the image pixels to 0 or 255, so that the image presents an obvious black and white effect. This technology can significantly reduce the amount of data in the image and highlight the outline of the cleat, which facilitates subsequent analysis and processing. The specific steps are: based on the threshold value 47.6 determined in step (2), for the convenience of calculation, this embodiment takes the integer 50 closest to 47.6 as the final threshold, that is, T=50. The grayscale image is converted into a binary image. Usually, all pixels with a grayscale greater than or equal to the threshold are judged to belong to the coal rock skeleton, and their grayscale value is set to 255 (white); otherwise, they are judged to be coal rock cleats, and their grayscale value is set to 0 (black). The calculation formula is as follows:

[0057]

[0058] Where B(x,y) is the pixel value of the binarized image at position (x,y), I(x,y) is the pixel value of the original grayscale image at position (x,y), and T is the set threshold, T=50.

[0059] Figure 3 The comparison between the results obtained when selecting multiple different thresholds (30, 40, 50, 60) and the original image is given. It can be seen that the effect of binarization is better when the threshold T=50 is used.

[0060] (4) Calculate the cleat porosity of coal rock end faces;

[0061] After the coal rock end face image is binarized, the binary image is used to calculate the proportion of cleat pixels, and the number of pixels occupied by cleats and the total pixels of the coal rock end face image are obtained to obtain the coal rock end face cleat rate. The formula is as follows:

[0062]

[0063] Where S is the proportion of pixels where cleats are located on the coal rock end face, A is the number of pixels occupied by cleats on the coal rock end face, and B is the total number of pixels on the coal rock end face.

[0064] Then, according to the characteristics of cleat porosity in the study area, the coal rock cleat pixel ratio scale is converted into cleat porosity, and the formula is as follows:

[0065]

[0066] Where X is the cleat porosity calculated by calibration, s is the proportion of cleat pixels before calibration, d and c are the maximum and minimum cleat porosity in the study area, respectively, and b and a are the maximum and minimum cleat pixel proportions of the target coal rock, respectively.

[0067] (5) Coal rock end face fractal;

[0068] Image fractal is a geometric shape that contains detailed structures of any small scale, that is, it can be described as a rough or fragmented geometric shape that can be divided into multiple parts, each part (at least approximately) is a reduced copy of the whole. Image fractal dimension is a quantitative description of image complexity and irregularity. A higher fractal dimension usually means that the surface of the coal rock end face image contains more detailed information and a higher degree of complexity, while a lower fractal dimension means that the surface of the coal rock end face image is smoother and flatter, contains less detailed information, and has a lower degree of complexity. The calculation formula of fractal dimension is as follows;

[0069]

[0070] Where ε is the length of one side of a small cube, N(ε) is the number of small cubes covering the cleat being measured, and the dimension formula means that the dimension of the cleat being measured is determined by covering the cleat being measured with small cubes with a side length of ε. Figure 4 These are the calculation results of the fractal dimensions of the two images in this embodiment.

[0071] (6) Through the above five steps, all deep coal core end face images are processed, cleats are identified, and cleat porosity and fractal dimension are calculated; then, the fractal dimension is used as the horizontal coordinate and the cleat porosity is used as the vertical coordinate to establish an intersection diagram of fractal dimension and cleat porosity; based on the intersection relationship between fractal dimension and cleat porosity, the dividing line between relatively developed, developed, and extremely developed is found, and then the degree of cleat development on the coal core end face is classified and evaluated.

[0072] Figure 5 is the intersection diagram of the fractal dimension and cleat porosity obtained in this embodiment. The figure is divided into relatively developed, developed, and extremely developed areas from the lower left to the upper right by the dotted line as the dividing line. The area where each coal core sample is located represents its development degree. In order to verify the accuracy of the method of the present invention, the existing artificial surface observation method is used to evaluate the cleat development degree of each coal core, and the evaluation results are marked on Figure 5 For details, see Figure 5 The scattered points shown in the figure each represent the degree of cleat development of a coal core. As can be seen from the figure, the evaluation results of the evaluation method of the present invention are roughly similar to those of the manual observation method, with only a small number of individual samples having different evaluation results, such as those that are manually judged to be extremely developed, while the method of the present invention judges them to be developed. This is because the features of some core end faces are not particularly obvious and can be identified manually, but the method of this patent may not be able to identify them well, resulting in different evaluation results. It can be concluded that the average accuracy of the evaluation method of the present invention is 85.03%.

[0073] The method of the present invention is compared with other methods (method 1 and method 2). Method 1 refers to using cleat porosity alone for judgment. The results are shown in FIG. Figure 6 ; Method 2 is to use fractal dimension alone to make judgments, and the results are shown in Figure 7 . Method 1 and method 2 are evaluated from left to right as relatively developed, developed, and extremely developed, respectively, with the dotted line as the dividing line. It can be concluded that the average accuracy of the evaluation of the method of the present invention is 85.03%, while the average accuracy of the evaluation of method 1 is 67.86%, and the average accuracy of the evaluation of method 2 is 81.9%. The method of the present invention significantly improves the accuracy of the evaluation of the development degree of deep coal rock end face cleats.

[0074] The original data required by the method of the present invention is the end face image of the coal rock core, and it is applicable to the analysis and calculation of coal rock surface images in most cases. No matter how the shooting direction and angle of the image are changed, the illumination can be uniformed. For example Figure 8 From the case shown, it can be seen that after uniform illumination, the problem of missing or over-identification before uniform illumination can be optimized, so that the calculated fractal dimension and cleat porosity are closer to the actual situation.

[0075] The above description is only a preferred embodiment of the present invention and does not constitute any form of limitation to the present invention. Although the present invention has been disclosed as a preferred embodiment as above, it is not intended to limit the present invention. Any technician familiar with the profession can make some changes or modifications to equivalent embodiments of equivalent changes using the technical contents disclosed above without departing from the scope of the technical solution of the present invention. However, any simple modification, equivalent change and modification made to the above embodiments based on the technical essence of the present invention without departing from the content of the technical solution of the present invention still falls within the scope of the technical solution of the present invention.

Claims

1. A method for evaluating the degree of cleat development in deep coal and rock based on full-diameter core end face images, characterized in that: The following steps are involved: S1. Obtain a full-diameter core end face image, and perform light balance processing on the core end face image, including image brightness calculation and brightness balance; S2, core end face image threshold setting; S3, binary segmentation of core end face image; The grayscale image is converted into a binary image according to the threshold value determined in step S2, and all pixels with grayscale greater than or equal to the threshold value T are determined to be coal-rock skeletons, and their grayscale values ​​are set to 255; otherwise, they are determined to be coal-rock cleats, and their grayscale values ​​are set to 0; S4. Calculation of coal rock end face cleat porosity; The binary image is used to calculate the percentage of coal rock cleat pixels. The formula is as follows: In the formula, S is the proportion of pixels where cleats are located on the coal rock end surface, A is the number of pixels occupied by cleats on the coal rock end surface, and B is the total number of pixels on the coal rock end surface; The coal rock cleat pixel ratio is converted into cleat porosity using the following formula: Where X is the cleat porosity calculated by calibration, S is the cleat pixel ratio before calibration, d and c are the maximum and minimum cleat porosity in the study area, b and a are the maximum and minimum cleat pixel ratios of the target coal rock, respectively. S5. Calculation of fractal dimension of coal rock end surface; S6. Evaluate the degree of cleat development on the end face of coal core; Through steps S1-S5, the processing of all deep coal core end face images, the identification of cleats, the calculation of cleat porosity and fractal dimension are completed; then, the fractal dimension is used as the horizontal coordinate and the cleat porosity is used as the vertical coordinate to establish an intersection diagram of fractal dimension and cleat porosity; based on the intersection relationship between fractal dimension and cleat porosity, the dividing line between relatively developed, developed and extremely developed is found, and then the degree of cleat development on the coal core end face is classified and evaluated.

2. The method for evaluating the development degree of deep coal cleats based on full-diameter core end face images according to claim 1, characterized in that: The method for setting the core end face image threshold in step S2 is as follows: Based on the maximum inter-class variance method, the initial segmentation threshold T0 is automatically obtained, and then at least three values ​​greater than T0 and at least three values ​​less than T0 are taken around T0, and the cleat pixel area corresponding to each value is calculated. The threshold is used as the horizontal coordinate and the cleat pixel area is used as the vertical coordinate. A curve graph between the cleat pixel area and the threshold is established, and then the starting segment and the end segment of the curve are fitted, and the intersection of the two fitting straight lines is used as the threshold T.

3. The method for evaluating the development degree of deep coal cleats based on full-diameter core end face images according to claim 1, characterized in that: In step S1, the method for calculating the image brightness is as follows: The input coal rock color image is converted into a grayscale image; the maximum value of the three components in the color image is used as the grayscale value of the grayscale image, and the pixel brightness calculation formula is: Gray(x,y)=max{R(x,y),G(x,y),B(x,y)} Where Gray(x, y) is the gray value of the pixel at position (x, y) of the grayscale image, R(x, y), G(x, y), and B(x, y) are the red, green, and blue components of the pixel at position (x, y) of the RGB image, respectively.

4. The method for evaluating the development degree of deep coal cleats based on full-diameter core end face images according to claim 3, characterized in that: In step S1, the brightness equalization method is as follows: the brightness of the local area with small brightness difference is taken as the background brightness, the background brightness value is calculated, and then the background brightness value is subtracted from the brightness value of the image to obtain a brightness difference image, that is, an image after brightness equalization.

5. The method for evaluating the development degree of deep coal cleats based on full-diameter core end face images according to claim 1, characterized in that: In step S5, the formula for calculating the fractal dimension is as follows: Where ε is the length of one side of the small cube, and N(ε) is the number of small cubes covering the cleavage being measured.

6. The method for evaluating the development degree of deep coal cleats based on full-diameter core end face images according to claim 1, characterized in that: The core end face image is a photo of the core end face taken by a camera at the sampling site.

Images