Shale pore and organic matter identification method, device, computer equipment and storage medium

Abstract

The present invention provides a shale pore and organic matter identification method, device, computer equipment and storage medium. The method comprehensively applies image processing algorithms such as image segmentation, local cropping, image expansion, boundary extraction, intersection and union operations, and solves the problem that the transition zone between inorganic pores and inorganic matter affects the identification of organic matter, and then affects the identification of organic pores and inorganic pores. The method can quickly and accurately identify shale organic pores, inorganic pores and organic matter, and supports parallel computing, with the characteristics of high accuracy, fast speed and low memory usage. The present application lays a foundation for calculating and characterizing shale pore parameters, and is of great significance for shale oil and gas resource evaluation and development method optimization.

Description

Technical Field

[0001] The present invention relates to the technical field of shale oil and gas exploration, and in particular to a shale pore and organic matter identification method, device, computer equipment and storage medium. Background Art

[0002] Shale reservoirs contain organic matter and pores. The pores are mainly nanoscale pores and contain organic matter. Pores are divided into organic pores and inorganic pores [1]. The storage and development methods of oil and gas in different types of pores are different. Studying the size and distribution of shale organic matter, organic pores and inorganic pores is of great significance for the evaluation and development of shale resources.

[0003] At present, there are two main methods for studying shale pore structure[2]. One method is the direct method, which uses electron microscopy, CT and other imaging methods to obtain shale images, observe and mark the shale organic pores, inorganic pores, organic matter and other minerals on the images. In order to improve the resolution of the image, some scholars have invented a method of injecting molten alloy into the core to increase the accuracy of pore identification[3]. The second method is the indirect method, which uses mercury injection, nuclear magnetic resonance, gas adsorption and other methods to obtain core test data, and then obtains shale pore parameters through mathematical inversion[4].

[0004] The existing direct method is based on image observation and manual annotation, which cannot be automated and quantified. Therefore, the workload is large and the reliability is low. It can only be limited to individual pores and cannot expand the scope of view to form statistical results. The indirect method is based on an ideal mathematical model. For complex shale pores, the model accuracy is poor. The results obtained by various indirect methods are different and the reliability of the results is low. The automatic identification method of organic pores and inorganic pores in mudstone invented by Xue Haitao, Tian Shansi et al. [5] can automatically identify organic pores and inorganic pores in shale, but it does not consider the problem that the pixel value of the edge of inorganic pores in shale images is approximately equal to the pixel value of organic matter. It cannot accurately distinguish the edges of organic and inorganic pores. Therefore, the identification result has a large error.

[0005] References:

[0006] [1] Sun Chao, Yao Suping. Pore development characteristics and characterization methods of shale oil reservoirs[J]. Petroleum Geology and Recovery, 2019, 26(01): 153-164.

[0007] [2] Jiang Tao, Jin Zhijun, Liu Guangxiang, Hu Zongquan, Liu Quanyou, Liu Zhongbao, Wang Pengwei, Wang Ruyue, Yang Tao, Wang Guanping. Pore structure characteristics of shale reservoirs in the Ziliujing Formation in Yuanba area, Sichuan Basin [J / OL]. Petroleum & Natural Gas Geology: 1-18 [2020-05-13]. http: / / kns.cnki.net / kcms / detail / 11.4820.TE.20191218.1425.002.html.

[0008] [3] Yu Lingjie, Bao Fang, Liu Youxiang, Rui Xiaoqing, Chen Hongyu, Fan Ming. A device and method for injecting molten alloy into rock pores[P]. CN110672388A, 2020-01-10.

[0009] [4] Li Jun, Jin Wujun, Wang Liang, Wu Qingzhao, Lu Jing, Hao Shibo. Determination of pore size distribution of organic and inorganic pores using nuclear magnetic resonance technology: A case study of shale gas reservoirs in the Silurian Longmaxi Formation in Fuling, Sichuan Basin [J]. Petroleum & Natural Gas Geology, 2016, 37(01): 129-134.

[0010] [5] Xue Haitao, Tian Shansi, Zeng Fang, Lu Shuangfang, Zhao Rixin, Xiao Dianshi, Li Junqian, Huang Wenbiao. Automatic identification method and system for organic pores and inorganic pores in shale[P]. CN110223282A, 2019-09-10. Summary of the invention

[0011] Based on this, it is necessary to provide a shale pore and organic matter identification method, device, computer equipment and storage medium to address the above technical problems.

[0012] A method for identifying shale pores and organic matter, comprising:

[0013] Acquire shale core images;

[0014] Performing a primary segmentation on the shale core image using a threshold segmentation algorithm to obtain a segmented pore image containing pores, an organic transition image containing organic matter and a transition zone, and an inorganic image containing inorganic matter;

[0015] Cutting the pores in the pore image based on the minimum circumscribed cube to obtain a local pore image;

[0016] Based on the cutting cube, the organic transition image and the inorganic image are cut respectively to obtain an organic transition partial image and an inorganic partial image;

[0017] Performing expansion processing on the local pore image to obtain an expanded boundary image of the local pore image;

[0018] Performing an intersection operation on the expansion boundary image and the organic transition local image to obtain a first intersection, and performing an intersection operation on the expansion boundary image and the inorganic local image to obtain a second intersection;

[0019] comparing the number of pixels in the first intersection with the number of pixels in the second intersection;

[0020] When the number of pixels in the first intersection is greater than the number of pixels in the second intersection, the corresponding pores are determined to be organic pores, and when the number of pixels in the first intersection is less than the number of pixels in the second intersection, the corresponding pores are determined to be inorganic pores.

[0021] A shale pore and organic matter identification device, comprising:

[0022] A shale core image acquisition module, used for acquiring shale core images;

[0023] A segmentation module, used for performing initial segmentation on the shale core image by using a threshold segmentation algorithm to obtain a segmented pore image containing pores, an organic transition image containing organic matter and a transition zone, and an inorganic image containing inorganic matter;

[0024] A first cropping module, used for cropping the pores in the pore image based on a minimum circumscribed cube to obtain a local pore image;

[0025] A second cutting module, used for cutting the organic transition image and the inorganic image respectively based on a cutting cube to obtain an organic transition partial image and an inorganic partial image;

[0026] An expansion module, used for performing expansion processing on the local pore image to obtain an expanded boundary image of the local pore image;

[0027] An intersection operation module, used for performing an intersection operation on the expansion boundary image and the organic transition local image to obtain a first intersection, and performing an intersection operation on the expansion boundary image and the inorganic local image to obtain a second intersection;

[0028] A pixel comparison module, used to compare the number of pixels in the first intersection with the number of pixels in the second intersection;

[0029] A determination module is used to determine that the corresponding pores are organic pores when the number of pixels in the first intersection is greater than the number of pixels in the second intersection, and to determine that the corresponding pores are inorganic pores when the number of pixels in the first intersection is less than the number of pixels in the second intersection.

[0030] A computer device comprises a memory and a processor, wherein the memory stores a computer program, and wherein the processor implements the following steps when executing the computer program:

[0031] Acquire shale core images;

[0032] Performing a primary segmentation on the shale core image using a threshold segmentation algorithm to obtain a segmented pore image containing pores, an organic transition image containing organic matter and a transition zone, and an inorganic image containing inorganic matter;

[0033] Cutting the pores in the pore image based on the minimum circumscribed cube to obtain a local pore image;

[0034] Based on the cutting cube, the organic transition image and the inorganic image are cut respectively to obtain an organic transition partial image and an inorganic partial image;

[0035] Performing expansion processing on the local pore image to obtain an expanded boundary image of the local pore image;

[0036] Performing an intersection operation on the expansion boundary image and the organic transition local image to obtain a first intersection, and performing an intersection operation on the expansion boundary image and the inorganic local image to obtain a second intersection;

[0037] comparing the number of pixels in the first intersection with the number of pixels in the second intersection;

[0038] When the number of pixels in the first intersection is greater than the number of pixels in the second intersection, the corresponding pores are determined to be organic pores, and when the number of pixels in the first intersection is less than the number of pixels in the second intersection, the corresponding pores are determined to be inorganic pores.

[0039] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the following steps:

[0040] Acquire shale core images;

[0041] Performing a primary segmentation on the shale core image using a threshold segmentation algorithm to obtain a segmented pore image containing pores, an organic transition image containing organic matter and a transition zone, and an inorganic image containing inorganic matter;

[0042] Cutting the pores in the pore image based on the minimum circumscribed cube to obtain a local pore image;

[0043] Based on the cutting cube, the organic transition image and the inorganic image are cut respectively to obtain an organic transition partial image and an inorganic partial image;

[0044] Performing expansion processing on the local pore image to obtain an expanded boundary image of the local pore image;

[0045] Performing an intersection operation on the expansion boundary image and the organic transition local image to obtain a first intersection, and performing an intersection operation on the expansion boundary image and the inorganic local image to obtain a second intersection;

[0046] comparing the number of pixels in the first intersection with the number of pixels in the second intersection;

[0047] When the number of pixels in the first intersection is greater than the number of pixels in the second intersection, the corresponding pores are determined to be organic pores, and when the number of pixels in the first intersection is less than the number of pixels in the second intersection, the corresponding pores are determined to be inorganic pores.

[0048] The above-mentioned shale pore and organic matter identification method, device, computer equipment and storage medium comprehensively apply image processing algorithms such as image segmentation, local cropping, image expansion, boundary extraction, intersection and union operations, which solves the problem that the transition zone between inorganic pores and inorganic matter affects the identification of organic matter, and then affects the identification of organic pores and inorganic pores. It can quickly and accurately identify shale organic pores, inorganic pores and organic matter, and supports parallel computing, with the characteristics of high accuracy, fast speed and low memory usage. This application lays the foundation for the calculation and characterization of shale pore parameters, and is of great significance for the resource evaluation and development method optimization of shale oil and gas. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 A schematic diagram of a process for identifying shale pores and organic matter in one embodiment;

[0050] Figure 2 is a structural block diagram of a shale pore and organic matter identification device in one embodiment;

[0051] Figure 3 is an internal structure diagram of a computer device in one embodiment;

[0052] Figure 4 A shale core image obtained by scanning with a scanning electron microscope in one embodiment;

[0053] Figure 5 is a shale core image after noise reduction processing in an embodiment;

[0054] Figure 6a is a segmented pore image in one embodiment;

[0055] Figure 6b An organic transition image including organic matter and transition zone after segmentation in one embodiment;

[0056] Figure 6c is an inorganic image containing inorganic matter after segmentation in one embodiment;

[0057] Figure 7a is an image of a pore interconnector in one embodiment;

[0058] Figure 7b An image of a connected body of organic matter (or transition zone) in one embodiment;

[0059] Figure 8ais a schematic diagram of the position of the cuboid Ωi in the pore interconnected body in one embodiment;

[0060] Figure 8b Schematic diagram of the position of the rectangular parallelepiped Ωi' in the organic matter (or transition zone) interconnected body in one embodiment;

[0061] Figure 8c is a schematic diagram of the position of a rectangular parallelepiped Ω_i' in an inorganic substance in one embodiment;

[0062] Figure 9a is a pore expansion boundary extraction process of the first pore in one embodiment;

[0063] Figure 9b is a pore expansion boundary extraction process of the second pore in one embodiment;

[0064] Fig.10a A local image of organic matter (or transition zone) in one embodiment;

[0065] Fig.10b is a partial image of an inorganic substance in one embodiment;

[0066] Fig.11a An intersection operation is performed between the expanded pore boundary of the expanded boundary image of the first pore and the corresponding organic matter (or transition zone) in one embodiment;

[0067] Fig.11b An intersection operation is performed between the expanded pore boundary of the expanded boundary image of the second pore in one embodiment and the corresponding organic matter (or transition zone);

[0068] Fig.12a An intersection operation between the expanded pore boundary of the expanded boundary image of the first pore and the corresponding inorganic matter in one embodiment;

[0069] Figure 12b An intersection operation between the expanded pore boundary of the expanded boundary image of the second pore and the corresponding inorganic matter in one embodiment;

[0070] Fig.13 A schematic diagram of the intersection of organic matter or transition zone and pores in one embodiment;

[0071] Fig.14a is a schematic diagram of an extracted organic pore in an embodiment;

[0072] Fig.14b is a schematic diagram of extracted inorganic pores in one embodiment;

[0073] Fig.14c is a schematic diagram of the extracted organic matter in one embodiment;

[0074] Fig.15 is a rectangular parallelepiped position and orientation diagram in one embodiment;

[0075] Fig.16a is a disk structure element with a radius of 1 in one embodiment

[0076] Fig.16b is a disk structure element with a radius of 4 in one embodiment;

[0077] Fig.17 This is an actual SEM scanning image of shale in an embodiment.

[0078] Fig.18 is an actual denoised image in an embodiment;

[0079] Fig.19a is an actual segmented pore image in an embodiment;

[0080] Fig.19b is an actual segmented organic matter and transition zone image in one embodiment;

[0081] Fig.19c is an actual segmented inorganic image in an embodiment;

[0082] Fig.20a is an image of an actual identified organic hole in one embodiment;

[0083] Fig.20b An image of an actual identified inorganic hole in an embodiment

[0084] Fig.20c FIG. 4 is an image of organic matter actually identified in one embodiment. DETAILED DESCRIPTION

[0085] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0086] Embodiment 1

[0087] In this embodiment, Figure 1 As shown, a method for identifying shale pores and organic matter is provided, which includes:

[0088] Step 110: Acquire a shale core image.

[0089] Specifically, the shale core image is obtained by scanning with a scanning electron microscope, and the scanned shale core image is a grayscale image, such as Figure 4As shown, the origin of the image is the upper left corner, the vertical direction is the x-axis, and the horizontal direction is the y-axis. The area with the lowest brightness in the figure is the pore, the next brightest is the organic matter, and the highest brightness is the inorganic matter. The pores developed in the inorganic matter are called inorganic pores, and the pores developed in the organic matter are called organic pores. Since the image brightness changes continuously in space, there is a transition zone from inorganic pores to inorganic matter. The brightness value of this transition zone is similar to that of organic matter, resulting in the same result as that of the edge pixel value of the inorganic pore and the organic matter, which brings difficulties to the distinction between inorganic pores and organic pores. The present invention uses a comprehensive image processing method to successfully solve this problem.

[0090] In this step, a shale core image A is obtained by using a SEM (scanning electron microscope).

[0091] Step 120, using a threshold segmentation algorithm to perform initial segmentation on the shale core image to obtain a segmented pore image containing pores, an organic transition image containing organic matter and a transition zone, and an inorganic image containing inorganic matter.

[0092] In one embodiment, before the step of performing initial segmentation on the shale core image using a threshold segmentation algorithm, the step also includes: performing noise reduction processing on the shale core image to obtain the shale core image after noise reduction; the step of performing initial segmentation on the shale core image using a threshold segmentation algorithm includes: performing initial segmentation on the shale core image after noise using a threshold segmentation algorithm.

[0093] In this embodiment, before the shale core image is segmented for the first time, the shale core image is first subjected to noise reduction processing. Specifically, a bilateral noise reduction algorithm is used to reduce the noise of the scanned image to obtain a noise-reduced image B, such as Figure 5 shown.

[0094] After denoising, according to the brightness of the denoised shale core image, the threshold segmentation algorithm is used to perform the initial segmentation on the denoised shale core image to form the initial segmentation results of pore image C1, organic transition image C2 and inorganic image C3, where C1 is pore (including organic pores and inorganic pores), C2 is organic matter (or transition zone) and C3 is inorganic matter. The segmentation results are shown in Figure 2. Figures 6a to 6c As shown, the white area represents the segmentation target, which is represented by 1 in value, and the black area represents the background, which is represented by 0.

[0095] Step 130 : cropping the pores in the pore image based on the minimum circumscribed cube to obtain a local pore image.

[0096] In one embodiment, the step of clipping the pores in the pore image based on the minimum circumscribed cube to obtain the local pore image includes: finding a connected body for the pore image to obtain a pore connected image; and clipping the pores in the pore connected image based on the minimum circumscribed cube to obtain the local pore image.

[0097] In this embodiment, the pore image is firstly connected to obtain a pore connection image, and then the pore connection image is cropped to obtain the pore local image.

[0098] Specifically, the pore connectivity graph D is obtained by finding the connected body of pore C1, and the set of independent pore connected bodies {Di} is obtained, such as Figure 7a As shown; the connected body of organic matter (or transition zone) C2 is obtained to obtain the connected graph E, and the independent organic matter (or transition zone) set {Ei} is obtained, as shown Figure 7b As shown; the i-th connected body is represented by the number i, and the black background number is 0.

[0099] Take the minimum circumscribed cube Ω of each pore Di parallel to the XYZ axis i , according to the minimum circumscribed cube Ω i The pore connectivity map D is cropped according to the position and size to obtain the pore local image Di.

[0100] Step 140 , cutting the organic transition image and the inorganic image respectively based on the cutting cube to obtain an organic transition partial image and an inorganic partial image.

[0101] In this step, according to the cutting cube Ω i The position and size of ′ are cut in the organic matter (or transition zone) C2 and the inorganic matter C3 to obtain the local image Ji of the organic matter (or transition zone) and the local image Ki of the inorganic matter, as shown in Fig.10a and Fig.10b shown.

[0102] Step 150: dilate the local pore image to obtain a dilated boundary image of the local pore image.

[0103] In this step, the pore local image Di is expanded to obtain an expanded image, and the boundaries of the pores in the expanded image are extracted to obtain an expanded boundary image Ii.

[0104] Step 160 , performing an intersection operation on the dilated boundary image and the organic transition local image to obtain a first intersection, and performing an intersection operation on the dilated boundary image and the inorganic local image to obtain a second intersection.

[0105] In this step, the expanded pore boundary map Ii and the organic matter (or transition zone) local map Ji are intersected to obtain a map Mi. The expanded pore boundary map Ii and the inorganic matter local map Ki are intersected to obtain a map Ni. The process of taking the intersection is as follows: Fig.12a and Figure 12b shown.

[0106] Step 170: Compare the number of pixels in the first intersection with the number of pixels in the second intersection.

[0107] Step 180: When the number of pixels in the first intersection is greater than the number of pixels in the second intersection, the corresponding pores are determined to be organic pores; when the number of pixels in the first intersection is less than the number of pixels in the second intersection, the corresponding pores are determined to be inorganic pores.

[0108] The number of pixels of the target object in the statistical graph Mi and graph Ni are recorded as and judge and If the size relationship Then the pore Di is an organic pore, if The pore Di is determined to be an inorganic pore; i Indicates whether the pore Di is an organic pore.

[0109]

[0110] In the above embodiments, image processing algorithms such as image segmentation, local cropping, image expansion, boundary extraction, and intersection operations are comprehensively applied to solve the problem that the transition zone between inorganic pores and inorganic matter affects the identification of organic matter, and then affects the identification of organic pores and inorganic pores. It can quickly and accurately identify shale organic pores, inorganic pores and organic matter, and supports parallel computing, with the characteristics of high accuracy, fast speed and low memory usage. This application lays the foundation for calculating and characterizing shale pore parameters, and is of great significance for shale oil and gas resource evaluation and development method optimization.

[0111] In one embodiment, the step of performing expansion processing on the local pore image to obtain an expanded boundary image of the local pore image includes: on the basis of keeping the pore size of the local pore image unchanged, respectively adding preset layers of pixels on six faces of the minimum circumscribed cube of the local pore image to obtain a first expanded image; in the first expanded image, performing expansion processing on the pores based on a disk structure element with a first preset radius to obtain a second expanded image; in the second expanded image, performing expansion processing on the pores based on a disk structure element with a second preset radius to obtain a third expanded image; and extracting the boundary of the third expanded image, and obtaining the expanded boundary image based on the boundary of the third expanded image.

[0112] Specifically, according to the cuboid Ω i The pore connectivity graph D is cropped according to the position and size of the pore, and the pore local image Di is obtained. The pore size is kept unchanged, and m layers of pixels are added to the upper, lower, left, right, front, and back six surface boundaries of the image Di to enlarge it, and obtain Fi; in the Fi image, the pores are represented by a disk structure element with a radius of 1 (such as Fig.16a As shown in the figure, the expansion operation is performed to obtain the graph Gi; the graph Gi is treated with a disk structure element with a radius of m-1 (as shown in the figure Fig.16b As shown in FIG. 1 , an expansion operation is performed to obtain FIG. Hi; the boundary of FIG. Hi is extracted to obtain FIG. Ii, which is the boundary of pore Di after expansion; the process is as shown in FIG. Figure 9a and Figure 9b shown.

[0113] In one embodiment, when the number of pixels in the first intersection is less than the number of pixels in the second intersection, the step of determining that the corresponding pores are inorganic pores also includes: obtaining a transition connection image of the organic transition image and the first expansion image; performing an intersection operation on the transition connection image and the first expansion image to obtain a third intersection; detecting the value of the third intersection, and when the value of the third intersection is 1, determining that the corresponding transition zone is organic matter, and when the value of the third intersection is 0, determining that the corresponding transition zone is an inorganic transition zone.

[0114] In this embodiment, if D i is the inorganic hole, Γ i =1, then further judge D i The corresponding organic matter (or transition zone) is whether it is organic matter; otherwise, continue to judge the next pore.

[0115] Specifically, if D i When it is an inorganic pore, the intersection operation is performed on the local connectivity graph Ji of organic matter (or transition zone) and the corresponding pore expansion graph Fi. The intersection operation rule is specified as follows:

[0116]

[0117] The calculation results in Figure L i ,like Fig.13 shown.

[0118] Extract the specific value of Li, denoted as set Φ i , for the set Φ i Remove duplicate elements and remove elements that are 0 to obtain the set Φ i A subset of i .

[0119] Repeat steps 110 to 180 to complete the traversal identification of all pores. In particular, this process can be accelerated in parallel.

[0120] For the set Ψ i Taking the union operation, we get

[0121]

[0122] Use Θ i Indicates whether the jth organic matter (or transition zone) Ej is organic matter. If Θ i =1, indicating that Ej is organic matter, if Θ i =0, indicating that Ej is a transition zone.

[0123]

[0124] According to Γ and Θ, the identification results of organic pores, inorganic pores and organic matter are extracted from the pore connectivity map D and the organic matter (transition zone) connectivity map E, respectively, as shown in Figures 14a to 14c shown.

[0125] In one embodiment, the step of cropping the pore connectivity image based on the minimum circumscribed cube to obtain a pore local image includes: respectively obtaining the minimum circumscribed square of each pore of the pore connectivity image in the directions parallel to the three coordinate axes of the coordinate system; cropping the pores of the pore connectivity image based on the minimum circumscribed cube determined by the minimum circumscribed square to obtain a pore local image.

[0126] Specifically, the three coordinate axes of the coordinate system are the X axis, the Y axis and the Z axis. In this embodiment, the minimum circumscribed square Ω of each pore Di parallel to the XYZ axis is taken as i , the method of taking the smallest circumscribed square is as follows, and combined with Fig.15 ,Ω i Vertex P in the NWD direction i The coordinates are (x i ,y i , z i ), the length of the cuboid is l i , width w i , high h i , where the length, width, and height correspond to the three directions of X, Y, and Z respectively; the minimum circumscribed square Ω i The location of Figure 8a shown.

[0127] In one embodiment, the steps of respectively cutting the organic transition image and the inorganic image based on the cutting cube to obtain the organic transition local image and the inorganic local image include: obtaining the center position of the minimum circumscribed cube; constructing the cutting cube based on the center position of the minimum circumscribed cube and the size of the transition zone between the inorganic pores and the inorganic substance; and respectively cutting the organic transition image and the inorganic image based on the cutting cube to obtain the organic transition local image and the inorganic local image.

[0128] In this embodiment, keep Ω i The center position remains unchanged, and a new cuboid Ω is constructed i ′,Ω′ i The upper left vertex P′ i The coordinates are (x′ i , y′ i , z′ i ), length l′ i , width w′ i , high h′ i ; Take x′ i =x i -m,y′ i =y i -m,z′ i =z i -m, l′ i = l i +2m,w′ i =w i +2m,h′ i =h i +2m; m is between 5 and 10, and the specific value depends on the size of the transition zone between inorganic pores and inorganic matter. i The position of ′ is Figure 8b to Figure 8c shown.

[0129] It should be understood that although Figure 1 The steps in the flowchart are shown in sequence as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified in this document, there is no strict order restriction for the execution of these steps, and these steps can be executed in other orders. Moreover, Figure 1 At least part of the steps may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily executed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least part of the sub-steps or stages of other steps.

[0130] Embodiment 2

[0131] The shale scanned image is a grayscale image, such as Figure 4 As shown, the origin of the image in this article is the upper left corner, the vertical direction is the x-axis, and the horizontal direction is the y-axis. The area with the lowest brightness in the figure is the pores, the next brightest is the organic matter, and the highest brightness is the inorganic matter. The pores developed in the inorganic matter are called inorganic pores, and the pores developed in the organic matter are called organic pores. Since the image brightness changes continuously in space, there is a transition zone from inorganic pores to inorganic matter. The brightness value of this transition zone is similar to that of organic matter, resulting in the same result as that of the edge pixel value of the inorganic pore and the organic matter, which brings difficulties to the distinction between inorganic pores and organic pores. The present invention uses a comprehensive image processing method to successfully solve this problem.

[0132] ② Obtain shale core image A through SEM scanning electron microscope, such as Figure 4 shown.

[0133] ② Use the bilateral denoising algorithm to denoise the scanned image and obtain the denoised image B, as shown in Figure 5 shown.

[0134] ③ According to the image brightness, the threshold segmentation algorithm is used to perform the initial segmentation of the image to form the initial segmentation results C1, C2, C3, C1 is pores (including organic pores and inorganic pores), C2 is organic matter (or transition zone), C3 is inorganic matter, such as Figures 6a to 6c As shown, the white area represents the segmentation target, which is represented by 1 in value, and the black area represents the background, which is represented by 0.

[0135] ④ Find the connected body of pore C1 to obtain the pore connected graph D, and obtain the independent pore connected body set {Di}, such as Figure 7a As shown; the connected body of organic matter (or transition zone) C2 is obtained to obtain the connected graph E, and the independent organic matter (or transition zone) set {Ei} is obtained, as shown Figure 7b As shown; the i-th connected body is represented by the number i, and the black background number is 0.

[0136] ⑤ Take the minimum circumscribed square Ω of each pore Di parallel to the XYZ axis i (like Fig.15 As shown), Ω i Vertex P in the NWD direction i The coordinates are (x i ,y i , z i ), the length of the cuboid is l i , width w i , high h i , where the length, width, and height correspond to the X, Y, and Z directions respectively; keep Ω i The center position remains unchanged, and a new cuboid Ω is constructed i ′,Ω′i The upper left vertex P′ i The coordinates are (x′ i , y′ i , z′ i ), length l′ i , width w′ i , high h′ i ; Take x′ i =x i -m,y′ i =y i -m,z′ i =z i -m, l′ i = l i +2m,w′ i =w i +2m,h′ i =h i +2m; m is between 5 and 10, and the specific value depends on the size of the transition zone between inorganic pores and inorganic matter. Ω i and Ω i The position of ′ is Figures 8a to 8c shown.

[0137] ⑥According to the rectangular block Ω i The pore connectivity graph D is cropped according to the position and size of the pore, and the pore local image Di is obtained. The pore size is kept unchanged, and m layers of pixels are added to the upper, lower, left, right, front, and back six surface boundaries of the image Di to enlarge it, and obtain Fi; in the Fi image, the pores are represented by a disk structure element with a radius of 1 (such as Fig.16a As shown in the figure, the expansion operation is performed to obtain the graph Gi; the graph Gi is treated with a disk structure element with a radius of m-1 (as shown in the figure Fig.16b As shown in FIG. 1 , an expansion operation is performed to obtain FIG. Hi; the boundary of FIG. Hi is extracted to obtain FIG. Ii, which is the boundary of pore Di after expansion; the process is as shown in FIG. Figure 9a and Figure 9b shown.

[0138] ⑦According to the rectangular block Ω i The position and size of ′ are cut in the organic matter (or transition zone) C2 and the inorganic matter C3 to obtain the local image Ji of the organic matter (or transition zone) and the local image Ki of the inorganic matter, as shown in Fig.10a and Fig.10b shown.

[0139] ⑧ Take the intersection operation of the expanded pore boundary map Ii and the local map of organic matter (or transition zone) Ji to obtain the map Mi.

[0140] M i =I i ∩J i

[0141] M i =I i ∩J i

[0142] The intersection operation rule here is

[0143]

[0144] The intersection obtained is Fig.11a and Fig.11b shown.

[0145] ⑨ Take the intersection operation on the expanded pore boundary map Ii and the inorganic local map Ki to obtain the map Ni. Fig.12a and Figure 12b As shown.

[0146] N i =I i ∩K i

[0147] ⑩ The number of pixels of the target object in the statistical graph Mi and graph Ni is recorded as and judge and If the size relationship Then the pore Di is an organic pore, if The pore Di is determined to be an inorganic pore; i Indicates whether the pore Di is an organic pore.

[0148]

[0149] If Di is an inorganic hole, Γ i =1, then further judge D i The corresponding organic matter (or transition zone) is whether it is organic matter; otherwise, continue to judge the next pore. Perform an intersection operation on the local connectivity graph Ji of the organic matter (or transition zone) and the corresponding pore expansion graph Fi, and specify the intersection operation rule as follows:

[0150]

[0151] The calculation results in Figure L i ,like Fig.13 shown.

[0152] Extract the specific value of Li, denoted as set Φ i , for the set Φ i Remove duplicate elements and remove elements that are 0 to obtain the set Φ i A subset of i .

[0153] Repeat step ⑤~ Complete the traversal and identification of all pores. In particular, this process can be accelerated in parallel.

[0154] For the set Ψ i Taking the union operation, we get

[0155]

[0156] Use Θ i Indicates whether the jth organic matter (or transition zone) Ej is organic matter. If Θ i =1, indicating that Ej is organic matter, if Θ i =0, indicating that Ej is a transition zone.

[0157]

[0158] According to Γ and Θ, the identification results of organic pores, inorganic pores and organic matter are extracted from the pore connectivity map D and the organic matter (transition zone) connectivity map E, respectively, as shown in Figures 14a to 14c shown.

[0159] The application of the above method can eliminate the interference of the transition zone between pores and inorganic matter, and can accurately identify shale organic pores, inorganic pores and organic matter; the present invention performs calculations after trimming each pore, which greatly reduces the amount of calculation. At the same time, the method supports parallelism and has the characteristics of high efficiency and small storage space.

[0160] In one embodiment, the direction coordinates of the cuboid are XYZ, see Fig.15 , the directions of the faces of the cuboid are N, E, S, W, U, D, and the point P_ i Located in the NWD direction. During the expansion process, the disk structure element with radius 1 is Fig.16a As shown, the disk structure element with a radius of 4 is Fig.16b shown.

[0161] Embodiment 3

[0162] Embodiment 3 is described by taking the schematic diagram in the content of the invention as an example.

[0163] ① The pixel size of the scanned image A is 300 in the x direction, 200 in the y direction, and 1 in the z direction;

[0164] ② The coordinates of the rectangular parallelepiped Ω1 are P1(60, 60, 1), length l1=70, width w1=70, height h1=1; the coordinates of the rectangular parallelepiped Ω2 are P2(220, 70, 1), length l2=55, width w2=55, height h1=1; m=5; the coordinates of the rectangular parallelepiped Ω′1 are P1(55, 55, 1), length l′1=80, width w′1=80, height h′1=11; the coordinates of the rectangular parallelepiped Ω′2 are P2(215, 65, 1), length l′2=65, width w′2=65, height h′2=11;

[0165] ③Implementation D i →F i →G i →H i →I i ;

[0166] ⑤Figure M i and Figure N i The number of pixels of the target object in is:

[0167] Therefore, D1 is an organic pore and D2 is an inorganic pore;

[0168] ⑥ The numerical set Φ2 of Figure O2 = {2, 2, 2, 2...0, 0, 0, 0, ...}, its subset Ψ2 = {2}, and the set Ώ = {2}, therefore, Θ1 = 1, Θ2 = 0, Θ3 = 1, identifying E1 and E3 as organic holes.

[0169] Embodiment 4

[0170] Example 4 takes a real scanned image as an example to illustrate the recognition process and results.

[0171] ①SEM scanning images of shale cores are shown in Fig.17 As shown, the image is an 8-bit grayscale image with a resolution of x:

[0172] 1456, y:1051, z:1;

[0173] ② After applying bilateral noise reduction to the scanned image, Fig.18 As shown;

[0174] ③According to the gray value interval, Fig.18 Perform the initial segmentation, 0-60 is segmented as pores, 61-120 is segmented as organic matter (or transition zone), and 121-255 is segmented as inorganic matter; the segmentation results are as follows Figures 19a to 19c As shown;

[0175] ④ By applying the method of this invention, further identification is obtained Figures 20a to 20c Identification results of organic pores, inorganic pores and organic matter.

[0176] Embodiment 5

[0177] In this embodiment, Figure 2 As shown, a shale pore and organic matter identification device is provided, comprising:

[0178] A shale core image acquisition module 210, used to acquire a shale core image;

[0179] The segmentation module 220 is used to perform initial segmentation on the shale core image using a threshold segmentation algorithm to obtain a segmented pore image containing pores, an organic transition image containing organic matter and a transition zone, and an inorganic image containing inorganic matter;

[0180] A first cropping module 230 is used to crop the pores in the pore image based on the minimum circumscribed cube to obtain a local pore image;

[0181] A second cutting module 240 is used to cut the organic transition image and the inorganic image based on a cutting cube to obtain an organic transition partial image and an inorganic partial image;

[0182] An expansion module 250 is used to perform expansion processing on the local pore image to obtain an expanded boundary image of the local pore image;

[0183] An intersection operation module 260 is used to perform an intersection operation on the expansion boundary image and the organic transition local image to obtain a first intersection, and perform an intersection operation on the expansion boundary image and the inorganic local image to obtain a second intersection;

[0184] A pixel comparison module 270, configured to compare the number of pixels in the first intersection with the number of pixels in the second intersection;

[0185] The determination module 280 is used to determine that the corresponding pores are organic pores when the number of pixels in the first intersection is greater than the number of pixels in the second intersection, and to determine that the corresponding pores are inorganic pores when the number of pixels in the first intersection is less than the number of pixels in the second intersection.

[0186] In one embodiment, the expansion module comprises:

[0187] A first expansion unit is used to add preset layers of pixels to six faces of a minimum circumscribed cube of the local pore image on the basis of keeping the pore size of the local pore image unchanged, so as to obtain a first expansion image;

[0188] A second expansion unit is used to expand the pores in the first expansion image based on a disk structure element of a first preset radius to obtain a second expansion image;

[0189] a third expansion unit, configured to expand the pores in the second expansion image based on a disk structure element of a second preset radius to obtain a third expansion image;

[0190] The boundary extraction unit is used to extract the boundary of the third dilated image, and obtain the dilated boundary image based on the boundary of the third dilated image.

[0191] In one embodiment, the shale pore and organic matter identification device further comprises:

[0192] An image obtaining module, used for obtaining a transition connected image of the machine transition image and the first dilation image;

[0193] A second intersection operation module, used for performing an intersection operation on the transition connected image and the first dilated image to obtain a third intersection;

[0194] The second determination module is used to detect the value of the third intersection. When the value of the third intersection is 1, the corresponding transition zone is determined to be organic matter. When the value of the third intersection is 0, the corresponding transition zone is determined to be an inorganic transition zone.

[0195] In one embodiment, the first cutting module includes:

[0196] A connected body obtaining unit, used for obtaining a connected body for the pore image to obtain a pore connected image;

[0197] The first cutting unit is used to cut the pores in the pore connection image based on the minimum circumscribed cube to obtain the pore local image.

[0198] In one embodiment, the first cutting module includes:

[0199] A minimum circumscribed square unit is used to respectively obtain the minimum circumscribed square of each pore of the pore connectivity image in directions parallel to the three coordinate axes of the coordinate system;

[0200] The second cropping unit is used to crop the pores of the pore connection image based on the minimum circumscribed cube determined by the minimum circumscribed square to obtain a pore local image.

[0201] In one embodiment, the second cutting module includes:

[0202] A center position acquisition unit, used to acquire the center position of the minimum circumscribed cube;

[0203] A cut cube construction unit, used to construct the cut cube based on the center position of the minimum circumscribed cube and the size of the transition zone between the inorganic hole and the inorganic substance;

[0204] The third cutting unit is used to cut the organic transition image and the inorganic image respectively based on the cutting cube to obtain an organic transition partial image and an inorganic partial image.

[0205] In one embodiment, the shale pore and organic matter identification device further comprises:

[0206] A noise reduction processing module, used for performing noise reduction processing on the shale core image to obtain the noise-reduced shale core image;

[0207] The segmentation module is also used to perform initial segmentation on the noisy shale core image using a threshold segmentation algorithm.

[0208] For the specific definition of the shale pore and organic matter identification device, please refer to the definition of the shale pore and organic matter identification method above, which will not be repeated here. Each unit in the above-mentioned shale pore and organic matter identification device can be implemented in whole or in part by software, hardware and their combination. The above-mentioned units can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above-mentioned units.

[0209] Embodiment 6

[0210] In this embodiment, a computer device is provided. Its internal structure diagram can be shown as follows: Figure 3 As shown. The computer device includes a processor, a memory, a network interface, a display screen and an input device connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program, and the non-volatile storage medium is deployed with a database, which is used to store shale core images and images obtained after processing in each step. The internal memory provides an environment for the operation of the operating system and computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with other external computer devices. When the computer program is executed by the processor, a method for identifying shale pores and organic matter is implemented. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covered on the display screen, or a key, trackball or touchpad set on the computer device shell, or an external keyboard, touchpad or mouse.

[0211] Those skilled in the art will understand that Figure 3The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0212] In one embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor implements the shale pore and organic matter identification method described in any of the above embodiments when executing the computer program.

[0213] Embodiment 7

[0214] In this embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the shale pore and organic matter identification method described in any of the above embodiments is implemented.

[0215] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0216] The above-mentioned embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent of the present application shall be subject to the attached claims.

Claims

1. A method for identifying shale pores and organic matter, characterized in that: include: Acquire shale core images; Performing a primary segmentation on the shale core image using a threshold segmentation algorithm to obtain a segmented pore image containing pores, an organic transition image containing organic matter and a transition zone, and an inorganic image containing inorganic matter; The pores in the pore image are cropped based on the minimum circumscribed cube to obtain a local pore image; Based on the cutting cube, the organic transition image and the inorganic image are cut respectively to obtain an organic transition partial image and an inorganic partial image; Performing expansion processing on the local pore image to obtain an expanded boundary image of the local pore image; Performing an intersection operation on the expansion boundary image and the organic transition local image to obtain a first intersection, and performing an intersection operation on the expansion boundary image and the inorganic local image to obtain a second intersection; comparing the number of pixels in the first intersection with the number of pixels in the second intersection; When the number of pixels in the first intersection is greater than the number of pixels in the second intersection, the corresponding pore is determined to be an organic pore; when the number of pixels in the first intersection is less than the number of pixels in the second intersection, the corresponding pore is determined to be an inorganic pore; The step of performing expansion processing on the local pore image to obtain the expanded boundary image of the local pore image comprises: On the basis that the pore size of the local pore image remains unchanged, a preset layer of pixels is added to six faces of the minimum circumscribed cube of the local pore image to obtain a first dilated image; In the first expansion image, the pores are expanded based on a disk structure element of a first preset radius to obtain a second expansion image; In the second expansion image, the pores are expanded based on a disk structure element of a second preset radius to obtain a third expansion image; extracting a boundary of the third dilated image, and obtaining the dilated boundary image based on the boundary of the third dilated image; When the number of pixels in the first intersection is less than the number of pixels in the second intersection, the step of determining that the corresponding pore is an inorganic pore further includes: Obtaining a transition connected image of the machine transition image and the first dilated image; performing an intersection operation on the transition connected image and the first dilated image to obtain a third intersection; The value of the third intersection is detected. When the value of the third intersection is 1, the corresponding transition zone is determined to be organic matter. When the value of the third intersection is 0, the corresponding transition zone is determined to be an inorganic matter transition zone.

2. The method according to claim 1, characterized in that The step of clipping the pores in the pore image based on the minimum circumscribed cube to obtain a local pore image comprises: Finding a connected body for the pore image to obtain a pore connected image; The pores in the pore connectivity image are cropped based on the minimum circumscribed cube to obtain the pore local image.

3. The method according to claim 2, characterized in that The step of clipping the pore connectivity image based on the minimum circumscribed cube to obtain a pore local image comprises: respectively obtaining the minimum circumscribed square of each pore of the pore connection image in directions parallel to the three coordinate axes of the coordinate system; The pores of the pore connection image are cropped by the minimum circumscribed cube determined based on the minimum circumscribed square to obtain a pore local image.

4. The method according to claim 3, characterized in that The step of cutting the organic transition image and the inorganic image based on the cutting cube to obtain the organic transition partial image and the inorganic partial image comprises: Obtaining the center position of the minimum circumscribed cube; Constructing the cut cube based on the center position of the minimum circumscribed cube and the size of the transition zone between the inorganic hole and the inorganic substance; The organic transition image and the inorganic image are cut respectively based on the cutting cube to obtain an organic transition partial image and an inorganic partial image.

5. The method according to any one of claims 1 to 4, characterized in that: Before the step of performing initial segmentation on the shale core image using a threshold segmentation algorithm, the method further includes: Performing noise reduction processing on the shale core image to obtain the noise-reduced shale core image; The step of performing initial segmentation on the shale core image using a threshold segmentation algorithm comprises: A threshold segmentation algorithm is used to perform initial segmentation on the noisy shale core image.

6. A shale pore and organic matter identification device, characterized in that: include: A shale core image acquisition module, used for acquiring shale core images; A segmentation module, used for performing initial segmentation on the shale core image by using a threshold segmentation algorithm to obtain a segmented pore image containing pores, an organic transition image containing organic matter and a transition zone, and an inorganic image containing inorganic matter; A first cropping module, used for cropping the pores in the pore image based on a minimum circumscribed cube to obtain a local pore image; A second cutting module, used for cutting the organic transition image and the inorganic image respectively based on a cutting cube to obtain an organic transition partial image and an inorganic partial image; An expansion module, used for performing expansion processing on the local pore image to obtain an expanded boundary image of the local pore image; An intersection operation module, used for performing an intersection operation on the expansion boundary image and the organic transition local image to obtain a first intersection, and performing an intersection operation on the expansion boundary image and the inorganic local image to obtain a second intersection; A pixel comparison module, used to compare the number of pixels in the first intersection with the number of pixels in the second intersection; A determination module, configured to determine that the corresponding pore is an organic pore when the number of pixels in the first intersection is greater than the number of pixels in the second intersection, and to determine that the corresponding pore is an inorganic pore when the number of pixels in the first intersection is less than the number of pixels in the second intersection; The expansion module comprises: A first expansion unit is used to add preset layers of pixels to six faces of a minimum circumscribed cube of the local pore image on the basis of keeping the pore size of the local pore image unchanged, so as to obtain a first expansion image; A second expansion unit is used to expand the pores in the first expansion image based on a disk structure element of a first preset radius to obtain a second expansion image; a third expansion unit, configured to expand the pores in the second expansion image based on a disk structure element of a second preset radius to obtain a third expansion image; a boundary extraction unit, configured to extract a boundary of the third dilated image, and obtain the dilated boundary image based on the boundary of the third dilated image; The shale pore and organic matter identification device also includes: An image obtaining module, used for obtaining a transition connected image of the machine transition image and the first dilation image; A second intersection operation module, used for performing an intersection operation on the transition connected image and the first dilated image to obtain a third intersection; The second determination module is used to detect the value of the third intersection. When the value of the third intersection is 1, the corresponding transition zone is determined to be organic matter. When the value of the third intersection is 0, the corresponding transition zone is determined to be an inorganic transition zone.

7. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 5 are implemented.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 5 are implemented.

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