Method, device, electronic device and storage medium for obtaining pore size distribution of rock images based on wire cutting technology

Abstract

The present application provides a method, device, electronic device and storage medium for obtaining the pore size distribution of rock images based on wire cutting technology. The method includes: obtaining an image of the rock and binarizing the image to obtain a binarized matrix, wherein the non-zero values in the binarized matrix represent the pore area; performing multi-directional wire cutting on the binarized matrix to obtain the number of pixels and single-pixel length of continuous pore segments in each direction, wherein the multi-direction includes at least the row direction and the column direction; and obtaining the pore size distribution of the rock in each direction based on the number of pixels and single-pixel length of continuous pore segments in each direction. In this way, by obtaining the pore size distribution through multi-directional wire cutting technology, the pore size distribution of the rock in each direction is accurately depicted, effectively solving the problem of inaccurate pore size distribution acquisition of irregular pore structures by traditional methods.

Description

Technical Field

[0001] The present application relates to the field of oil and gas exploration technology, and in particular to a method, device, electronic device and storage medium for obtaining pore size distribution of rock images based on wire cutting technology. Background Art

[0002] Accurately describing the microscopic pore structure of rock reservoirs is crucial in oil and gas geological exploration. Currently, methods for characterizing rock reservoir micropore structure primarily include fluid injection experiments and radiographic imaging. While these methods have achieved some success in pore identification and characterization, the challenge of analysing the diverse pore structures when using image processing techniques to determine rock pore size distribution remains.

[0003] To solve this problem, the existing technology has proposed equivalent circle processing technology and inscribed circle processing technology. The equivalent circle processing technology uses binarized electron microscope images to convert the pore area into a circle, and uses the radius of the circle to represent the pore size. However, this method may not accurately reflect the true characteristics of the pores when dealing with irregular pores, resulting in deviations in the description of the pore size distribution. The inscribed circle processing technology is a method based on morphological analysis, which characterizes the "bottleneck size" of the pore by calculating the maximum inscribed circle diameter that can be accommodated inside the pore. Although this method improves the accuracy of pore characterization to a certain extent, it also has limitations. For example, for pore structures with extremely complex morphology, the inscribed circle may not accurately reflect the anisotropy of the pores, resulting in inaccurate characterization of the pore size distribution. Therefore, how to provide a method that can accurately process irregular pores and accurately characterize the pore size distribution of rocks has become an urgent problem to be solved. Summary of the Invention

[0004] The embodiments of the present application provide a method, device, electronic device, and storage medium for obtaining the pore size distribution of rock images based on wire cutting technology.

[0005] According to a first aspect of the present application, a method for obtaining pore size distribution of rock images based on wire cutting technology is provided, the method comprising:

[0006] Acquire an image of the rock and perform binarization processing on the image to obtain a binarization matrix, wherein non-zero values in the binarization matrix represent pore areas;

[0007] Performing multi-directional line cutting on the binary matrix to obtain the number of pixels and single pixel length of the continuous pore segment in each direction, wherein the multi-directional directions include at least a row direction and a column direction;

[0008] The pore size distribution of the rock in each direction is obtained based on the number of pixels and single pixel length of the continuous pore segment in each direction.

[0009] According to one embodiment of the present application, the step of obtaining an image of a rock and performing binarization processing on the image includes:

[0010] Using imaging camera technology to obtain rock images;

[0011] Preprocessing the image, and performing binarization processing on the preprocessed image;

[0012] The preprocessing includes contrast enhancement and noise removal.

[0013] According to an embodiment of the present application, performing multi-directional line cutting on the binarized matrix to obtain the number of pixels and single-pixel length of continuous pore segments in each direction includes:

[0014] Scanning the binary matrix pixel by pixel along each direction, assigning independent increasing labels to continuous pore segments, and recording the number of pixels in each continuous pore segment;

[0015] Gets the single pixel length.

[0016] According to one embodiment of the present application, the binary matrix is scanned pixel by pixel along the row direction, independent and incremental labels are assigned to continuous pore segments, and the number of pixels of each continuous pore segment is recorded, including:

[0017] Scan each pixel in each row of the binary matrix from top to bottom. When encountering a non-zero pixel, check the label status of the left adjacent pixel in the same row. If the left pixel is already labeled, inherit the label; if the left pixel is a non-porous area or the current pixel is the beginning of the row, assign a new independent incremental label;

[0018] The number of pixels in each row with consecutive pore segments labeled with the same label is recorded; the labels differ between rows.

[0019] According to one embodiment of the present application, the binary matrix is scanned pixel by pixel along the column direction, independent and incremental labels are assigned to continuous pore segments, and the number of pixels of each continuous pore segment is recorded, including:

[0020] Scan each pixel in each column of the binary matrix from top to bottom. When a non-zero pixel is encountered, check the label status of the upper adjacent pixel in the same column. If the upper pixel is already labeled, inherit the label; if the upper pixel is a non-porous area or the current pixel is the first pixel in the column, assign a new independent incremental label.

[0021] The number of pixels in each column that are labeled with the same label for consecutive pore segments is recorded; where the labels differ between columns.

[0022] According to one embodiment of the present application, obtaining the pore size distribution of the rock in each direction based on the number of pixels and single pixel length of the continuous pore segment in each direction includes:

[0023] The pore size of each continuous pore segment is calculated based on the number of pixels and single pixel length of each continuous pore segment in each direction;

[0024] According to the total number of pixels and single pixel length of the continuous pore segment under each aperture, the surface rate component of the continuous pore segment under each aperture is calculated;

[0025] The pore size distribution of the rock in all directions is obtained by taking the pore size as the abscissa and the surface porosity component under the corresponding pore size as the ordinate.

[0026] According to one embodiment of the present application, the method further includes:

[0027] Anisotropy evaluation of the rock is performed according to the pore size distribution in each direction to obtain anisotropy evaluation results, wherein the anisotropy evaluation results include a fluctuation anisotropy factor, a position difference factor, and a comprehensive anisotropy factor;

[0028] Wherein, in the case where the multiple directions include row direction and column direction, the anisotropy evaluation of the rock is performed according to the pore size distribution in each direction to obtain the anisotropy evaluation result, including:

[0029] The number of pixels and single pixel length of continuous pore segments in the row and column directions were fitted with logarithmic Gaussian distribution functions to obtain the row mean, row standard deviation, column mean, and column standard deviation in the row and column directions respectively.

[0030] Calculate the wave anisotropy factor:

[0031]

[0032] in, is the row standard deviation, is the column standard deviation;

[0033] Calculate the position difference factor:

[0034]

[0035] in, is the row mean, is the column mean;

[0036] Calculate the integrated anisotropy factor:

[0037]

[0038] in, and is the weight coefficient.

[0039] According to a second aspect of the present application, a device for obtaining pore size distribution of rock images based on wire cutting technology is provided, the device comprising:

[0040] A processing module is used to obtain an image of the rock and perform binarization processing on the image to obtain a binarization matrix, wherein non-zero values in the binarization matrix represent pore areas;

[0041] a cutting module, configured to perform multi-directional line cutting on the binary matrix to obtain the number of pixels and single-pixel length of continuous pore segments in each direction, wherein the multi-directional directions include at least row and column directions;

[0042] The calculation module is used to obtain the pore size distribution of the rock in each direction based on the number of pixels and single pixel length of the continuous pore segment in each direction.

[0043] According to a third aspect of the present application, an electronic device is provided, including:

[0044] at least one processor; and

[0045] a memory communicatively connected to the at least one processor; wherein,

[0046] The memory stores instructions that can be executed by the at least one processor. The instructions are executed by the at least one processor to enable the at least one processor to perform the method described in this application.

[0047] According to a fourth aspect of the present application, a non-transitory computer-readable storage medium storing computer instructions is provided, wherein the computer instructions are used to enable the computer to execute the method described in the present application.

[0048] The method, device, electronic device and storage medium for obtaining the pore size distribution of rock images based on wire cutting technology in the embodiments of the present application obtain an image of the rock and perform binarization processing on the image to obtain a binarized matrix, wherein the non-zero values in the binarized matrix represent the pore area; the binarized matrix is subjected to multi-directional wire cutting to obtain the number of pixels and single pixel length of the continuous pore segment in each direction, wherein the multi-direction includes at least the row direction and the column direction; the pore size distribution in each direction is obtained based on the number of pixels and single pixel length of the continuous pore segment in each direction; the anisotropy of the rock is evaluated based on the pore size distribution in each direction to obtain an anisotropy evaluation result. The pore size distribution is obtained by multi-directional wire cutting technology, which achieves an accurate characterization of the pore size distribution in each direction of the rock, and effectively solves the problem of inaccurate characterization of irregular pore structure by traditional methods.

[0049] It should be understood that the teachings of this application do not necessarily achieve all of the beneficial effects described above, but that specific technical solutions can achieve specific technical effects, and other embodiments of this application can also achieve beneficial effects not mentioned above. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] The above and other objects, features and advantages of the exemplary embodiments of the present application will become readily understood by reading the detailed description below with reference to the accompanying drawings. In the accompanying drawings, several embodiments of the present application are shown in an illustrative and non-limiting manner, in which:

[0051] In the drawings, the same or corresponding reference numerals denote the same or corresponding parts.

[0052] Figure 1 A schematic diagram of the implementation process of the method for obtaining the pore size distribution of rock images based on the wire cutting technology provided in an embodiment of the present application is shown;

[0053] Figure 2 A schematic diagram of the wire cutting principle of a method for obtaining pore size distribution of rock images based on wire cutting technology provided in an embodiment of the present application is shown;

[0054] Figure 3 A schematic diagram of the implementation flow of the row-direction cutting operation of the method for obtaining the pore size distribution of rock images based on the wire cutting technology provided in an embodiment of the present application is shown;

[0055] Figure 4 A schematic diagram illustrating the implementation flow of the column-wise cutting operation of the method for obtaining the pore size distribution of rock images based on the wire cutting technology provided in an embodiment of the present application is shown;

[0056] Figure 5 A schematic diagram illustrating the implementation flow of the pore size distribution acquisition operation of the method for acquiring the pore size distribution of rock images based on the wire cutting technology provided in an embodiment of the present application is shown;

[0057] Figure 6 An example diagram of pore size distribution of a method for obtaining pore size distribution of rock images based on wire cutting technology provided in an embodiment of the present application is shown;

[0058] Figure 7 An example diagram of Gaussian fitting of the line-cut aperture distribution in the x-direction provided by an embodiment of the present application is shown;

[0059] Figure 8 An example diagram of Gaussian fitting of the y-direction line-cut aperture distribution provided by an embodiment of the present application is shown;

[0060] Figure 9 A schematic diagram of the structure of a device for obtaining pore size distribution of rock images based on wire cutting technology provided in an embodiment of the present application is shown;

[0061] Figure 10 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application is shown. DETAILED DESCRIPTION

[0062] In order to make the purpose, features, and advantages of this application more obvious and easy to understand, the technical solutions in the embodiments of this application will be clearly and completely described below in conjunction with the drawings in the embodiments of this application. Obviously, the described embodiments are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without making creative efforts shall fall within the scope of protection of this application.

[0063] Figure 1 A schematic diagram of the implementation flow of the method for obtaining the pore size distribution of rock images based on wire cutting technology provided in an embodiment of the present application is shown.

[0064] refer to Figure 1 The embodiment of the present application provides a method for obtaining pore size distribution of rock images based on wire cutting technology, the method comprising:

[0065] Operation 101 : Acquire an image of a rock and perform binarization processing on the image to obtain a binarization matrix. Non-zero values in the binarization matrix represent pore areas.

[0066] In one embodiment of the present application, an imaging image of a rock is obtained and the image is binarized, including: using imaging camera technology to obtain an imaging image of the rock; preprocessing the image and binarizing the preprocessed image; wherein the preprocessing includes contrast enhancement and noise removal.

[0067] First, the rock sample is photographed using high-resolution imaging technology to obtain a rock imaging image. Among them, photographing the rock sample using high-resolution imaging technology can be regarded as obtaining a rock imaging image using technical means such as light microscopy and electron microscopy.

[0068] After obtaining the image, in order to improve the image quality, the image is preprocessed to ensure that the image is clearer and richer in details. The preprocessing can include contrast enhancement and noise denoising.

[0069] In one embodiment of the present application, contrast enhancement is preferably performed using fused-constrained contrast histogram equalization (CLAHE). Specifically, CLAHE is first used to divide the image into multiple small regions, and histogram equalization is performed on each small region. Then, interpolation is performed to obtain the final enhanced image.

[0070] In one embodiment of the present application, noise removal is preferably performed using non-local means denoising (NL-means). Specifically, NL-means is used to calculate the weighted average of all pixels in the image to denoise the image, thereby reducing random noise in the image and improving the ability to identify pore boundaries.

[0071] After image preprocessing, the preprocessed image can be binarized using image processing algorithms, image processing software, or neural networks. For example, using threshold segmentation, each pixel in the pore region is converted to a non-zero value, while all pixels in the background region are converted to zero, resulting in a binary image. To facilitate the extraction of pore information from the image, a binarization matrix is extracted for the binary image. Each element in the binarization matrix corresponds to a pixel at a corresponding position in the binary image. The non-zero value can be pre-configured based on image analysis and can be considered a pre-configured threshold; for example, the non-zero value can be set to 1.

[0072] In operation 102 , multi-directional line cutting is performed on the binary matrix to obtain the number of pixels and single-pixel length of continuous pore segments in each direction, where the multi-directional directions include at least row and column directions.

[0073] In one embodiment of the present application, before performing multi-directional line cutting on the binary matrix, multi-directional settings are also performed so that cutting is performed according to the set multi-directional settings, wherein the multi-directional settings include at least row direction and column direction.

[0074] Preferably, to ensure that the cutting operation can fully and accurately capture the characteristics of the pore structure in different directions, an arbitrary angle θ is set for cutting in addition to the row and column directions, where 0°<θ<180°. The selection of angle θ can be determined based on actual needs. For example, if cracks or bedding in specific directions are known in the rock, the angle corresponding to these directions can be selected for cutting. This will not be repeated here.

[0075] After setting multiple directions, multi-directional line cutting is performed on the binary matrix based on the set multiple directions, wherein line cutting in one direction can be understood as traversing the binary matrix with a cutting line based on the current direction, for example, cutting each row or column of the binary matrix.

[0076] In the process of cutting the binary matrix, the number of pixels and the length of a single pixel of the continuous pore segments on the cutting line are recorded synchronously.

[0077] Operation 103 : Obtain the pore size distribution of the rock in each direction based on the number of pixels and single pixel length of the continuous pore segment in each direction.

[0078] After determining the number of pixels and single-pixel length of continuous pore segments in each direction, the equivalent pore size can be calculated based on a suitable equivalent pore size algorithm or formula. For example, the equivalent pore size can be calculated based on the number of pixels and single-pixel length of continuous pore segments and the pore size distribution in each direction can be statistically analyzed.

[0079] In this way, the embodiment of the present application determines the pore size distribution through multi-directional wire cutting technology, thereby achieving accurate characterization of the pore size distribution of the rock in all directions, and effectively solving the problem of inaccurate characterization of irregular pore structure by traditional methods.

[0080] In one embodiment of the present application, multi-directional line cutting is performed on the binary matrix to obtain the number of pixels and single-pixel length of the continuous pore segment in each direction, including: scanning the binary matrix pixel by pixel along each direction, assigning independent and incremental labels to the continuous pore segments, and recording the number of pixels of each continuous pore segment; obtaining the single-pixel length.

[0081] For each of the predefined multiple directions, a pixel-by-pixel scan is performed based on the cutting line. During the scanning process, each continuous pore segment is labeled by assigning a label, and the number of pixels in each continuous pore segment is recorded. The label is the same for each continuous pore segment, and different continuous pore segments have different labels. The labels are incremented based on the traversal order.

[0082] In one embodiment of the present application, during the line cutting process in each direction, an 8-neighborhood topological analysis method combined with a fast Union-Find algorithm can be used to mark continuous pore segments and assign labels to each continuous pore segment. Specifically, when traversing each pixel in each direction, an 8-neighborhood topological analysis is performed to examine the eight neighborhoods (up, down, left, right, and diagonal) to determine whether they belong to the same pore. The fast Union-Find algorithm is then used to assign labels to the pixels.

[0083] To further understand the cutting process of continuous pore segments, the following example is given. Figure 2 , Figure 2 A schematic diagram of the wire cutting principle of a method for obtaining pore size distribution of rock images based on wire cutting technology provided in an embodiment of the present application is shown. Figure 2 (a) shows an example of a binary image corresponding to a binary matrix. When a line cut is performed on the binary matrix, it can be regarded as cutting the binary image. Figure 2 Middle (b) is an example of the wire cutting result obtained after row-wise wire cutting, in which the white rectangle is the continuous pore segment obtained after wire cutting. Figure 2 (c) is an example of the wire cutting result obtained after the column direction wire cutting, and the white strips in it are the continuous pore segments obtained after wire cutting. Figure 2Each binary image in the figure is a simplified schematic diagram. To avoid the complexity of the graphics interfering with the understanding of the core principles, it is only used to intuitively demonstrate the physical segmentation effect of wire cutting and does not reflect the details of label assignment.

[0084] Figure 3 A schematic diagram of the implementation flow of the row-direction cutting operation of the method for obtaining the pore size distribution of rock images based on the wire cutting technology provided in an embodiment of the present application is shown.

[0085] In one embodiment of the present application, a process of performing pixel-by-pixel scanning on a binary matrix based on a row direction in multiple directions, that is, performing pixel-by-pixel scanning on the binary matrix along the row direction, assigning independent and incremental labels to continuous pore segments, and recording the number of pixels and single-pixel length of each continuous pore segment, includes:

[0086] Operation 201 scans each pixel in each row of the binary matrix from top to bottom. When a non-zero pixel is encountered, the label status of the adjacent pixel on the left in the same row is checked. If the pixel on the left is already marked, the label is inherited; if the pixel on the left is a non-porous area or the current pixel is at the beginning of the row, a new independent incremental label is assigned.

[0087] Traverse the binary matrix row by row in the x-direction (row direction), scanning each matrix element from left to right for each row, that is, each pixel of the image. If the current pixel is non-zero (valid pixel), check the label of the adjacent pixel to its left in the same row. If the pixel to the left is already labeled (such as label 2), it inherits that label; if the pixel to the left is background (label 0) or the current pixel is the first valid pixel in the row, assign a new label that increases independently starting from 1.

[0088] In the process of traversing pixels, each row is regarded as an independent space, and continuous valid pixels in the row are marked with the same label and regarded as a continuous pore segment.

[0089] In operation 202 , the number of pixels of consecutive pore segments marked with the same label in each row is recorded; wherein the labels are different between different rows.

[0090] During the pixel traversal process, the number of pixels of the marked continuous pore segments is obtained.

[0091] The label numbers of different rows are completely independent. In this way, even if there are horizontally aligned pixels in adjacent rows, their labels will not be merged, thus avoiding the problem of erroneous amplification of the equivalent aperture in the horizontal direction due to forced cross-column merging. It more realistically reflects the local pore size and avoids false connectivity of pores in the horizontal direction, thereby more accurately calculating the difference in pore size distribution between the horizontal and vertical directions and reducing anisotropic deviation.

[0092] Figure 4A schematic diagram of the implementation flow of the column-wise cutting operation of the method for obtaining the pore size distribution of rock images based on the wire cutting technology provided in an embodiment of the present application is shown.

[0093] In one embodiment of the present application, a process of performing pixel-by-pixel scanning on a binary matrix based on a column direction in multiple directions, that is, performing pixel-by-pixel scanning on the binary matrix along the column direction, assigning independent and incremental labels to continuous pore segments, and recording the number of pixels and single-pixel length of each continuous pore segment, includes:

[0094] Operation 301 scans each pixel in each column of the binary matrix from top to bottom. When a non-zero pixel is encountered, the label status of the upper adjacent pixel in the same column is checked. If the upper pixel is already labeled, the label is inherited. If the upper pixel is a non-porous area or the current pixel is the first pixel in the column, a new independent increasing label is assigned.

[0095] In operation 302 , the number of pixels of consecutive pore segments marked with the same label in each column is recorded; wherein the labels are different between different columns.

[0096] The line cutting method for the column direction is similar to that for the row direction. Specifically, the binary matrix is traversed column by column along the y direction (column direction). For each column, each pixel is scanned from top to bottom. If the current pixel is non-zero (valid pixel), the label of the adjacent pixel above it in the same column is checked. If the pixel above is already labeled (such as label 3), the label is inherited. If the pixel above is background (label 0) or the current pixel is the first valid pixel in the column, a new label is assigned, which is independently incremented starting from 1.

[0097] During the traversal process, each column is treated as an independent space, and consecutive valid pixel regions within the column are marked with the same label, resulting in continuous pore segments. The label numbers of different columns are completely independent, so even if there are vertically aligned pixels in adjacent columns, their labels will not be merged. This avoids the problem of forced cross-column merging that would lead to incorrect amplification of the equivalent pore size in the vertical direction. This more realistically reflects the local pore size and avoids false connectivity of pores in the vertical direction, thereby more accurately calculating the difference in pore size distribution between the horizontal and vertical directions and reducing anisotropic bias.

[0098] Figure 5 A schematic diagram of the implementation flow of the pore size distribution acquisition operation of the method for acquiring the pore size distribution of rock images based on the wire cutting technology provided in an embodiment of the present application is shown.

[0099] refer to Figure 5 In one embodiment of the present application, the operation 103, which obtains the pore size distribution of the rock in each direction based on the number of pixels and the length of a single pixel of the continuous pore segment in each direction, includes:

[0100] Operation 401 , calculating the aperture of each continuous pore segment according to the number of pixels and single pixel length of each continuous pore segment in each direction;

[0101] Operation 402 , calculating the surface rate component of the continuous pore segment under each aperture according to the total number of pixels and the single pixel length of the continuous pore segment under each aperture;

[0102] In operation 403 , the pore size is used as the abscissa and the surface porosity component corresponding to the pore size is used as the ordinate to obtain the pore size distribution of the rock in various directions.

[0103] The pore size distribution can be expressed in the form of a pore size distribution graph, with pore size representing the horizontal axis and surface area fraction representing the vertical axis. The pore size distribution in each direction is constructed within the pore size distribution graph. The pore size is the pore size, and the surface area fraction is the pore area.

[0104] Specifically, the aperture in each direction can be obtained based on the number of pixels and single-pixel length of the continuous aperture segment in each direction. Specifically, the aperture of each continuous aperture segment can be obtained based on the following formula:

[0105]

[0106] Where N is the number of pixels in the continuous pore segment, The actual length of a single pixel.

[0107] Furthermore, the surface rate component under each aperture can be obtained based on the total number of pixels and single pixel length of all continuous pore segments corresponding to the current aperture, that is, the product of the total number of pixels and single pixel length of the continuous pore segments.

[0108] In this way, after determining each pore size and the corresponding surface ratio component of the pore size, the pore size can be used as the horizontal coordinate and the surface ratio component under each pore size as the vertical coordinate to construct an pore size distribution diagram representing the pore size distribution. Figure 6 , Figure 6 An example diagram of pore size distribution of a method for obtaining pore size distribution of rock images based on wire cutting technology provided in an embodiment of the present application is shown. In the diagram, triangles and circles constitute the pore size distribution in the x-direction and the y-direction, respectively.

[0109] In one embodiment of the present application, in addition to evaluating the pore size distribution, an assessment of reservoir anisotropy is also performed, that is, an anisotropy assessment of the rock is performed through the pore size distribution in various directions to obtain an anisotropy assessment result.

[0110] Specifically, to achieve a more accurate characterization of pore structure, it is also necessary to understand the rock's physical properties, such as permeability and elastic modulus. Rock physical properties are typically characterized based on anisotropy. Therefore, to fully understand rock physical properties, after determining the pore size distribution, an anisotropy assessment of the rock is performed based on pore structure information to obtain the rock anisotropy assessment results.

[0111] In this embodiment of the present application, the anisotropy assessment results include multiple indices for evaluating anisotropy, including a wave anisotropy factor (WAF), a position difference factor (CAF), and a comprehensive anisotropy factor. Thus, when evaluating anisotropy, the wave anisotropy factor reflects the degree of dispersion of pore size, the position difference factor quantifies the relative differences in pore concentration locations in the X / Y directions, and the comprehensive anisotropy factor combines the WAF and CAF to overcome the limitations of a single indicator.

[0112] Accordingly, in the case of multiple directions including row direction and column direction, the anisotropy of the rock is evaluated according to the pore size distribution in each direction, and the anisotropy evaluation results are obtained, including:

[0113] The number of pixels and single pixel length of continuous pore segments in the row and column directions were fitted with logarithmic Gaussian distribution functions to obtain the row mean, row standard deviation, column mean, and column standard deviation in the row and column directions respectively.

[0114] Calculate the wave anisotropy factor:

[0115]

[0116] in, is the row standard deviation, is the column standard deviation, WAF≈0 means that the pore size distribution has a similar degree of dispersion in the X / Y direction (isotropy), and WAF→1 means that the pore size distribution has a large degree of dispersion in the X / Y direction (strong anisotropy);

[0117] Calculate the position difference factor:

[0118]

[0119] in, is the row mean, is the column mean, and the LAF value range is [0, 1);

[0120] Calculate the combined anisotropy factor:

[0121]

[0122] in, and is the weight coefficient, which can be adjusted based on reservoir type and engineering requirements.

[0123] Specifically, first, the pore size distribution in each direction is fitted based on the logarithmic Gaussian distribution function, and the expression of the logarithmic Gaussian distribution function is:

[0124]

[0125] Among them, x is the aperture distribution in each direction, and the mean of the Gaussian distribution , standard deviation , 、 、 It can be regarded as a fitting parameter and can be configured according to actual conditions.

[0126] The pore size distribution is fitted based on the above logarithmic Gaussian distribution function to obtain the standard deviation and mean corresponding to each direction, that is, the row mean and row standard deviation for the row direction and the column mean and column standard deviation for the column direction.

[0127] After determining the mean and standard deviation in each direction, the fluctuation anisotropy factor, position difference factor and comprehensive anisotropy factor are calculated according to their calculation formulas to obtain the final anisotropy assessment result.

[0128] In order to further illustrate the technical solution of the present application, a specific example is given below.

[0129] This specific application example of the embodiment of the present application may include:

[0130] S1. Rock sample preparation;

[0131] Rock sample source: Sandstone of the Shahezi Formation in the Songliao Basin, drilled from a 2.5 cm diameter standard plunger sample.

[0132] Pretreatment: Argon ion polishing to a surface roughness of <10 nm.

[0133] S2, rock imaging image acquisition;

[0134] Equipment: FEI Quanta 650 FEG field emission electron microscope.

[0135] Parameters: acceleration voltage 5 kV, resolution 100,000 × 100,000 pixels, pixel size 10 nm.

[0136] S3, multi-directional wire cutting;

[0137] 1) CLAHE algorithm is used to enhance image contrast and NL-means is used for denoising (filter kernel 7×7);

[0138] 2) Generate a binary image based on the U-Net network, with the pore area marked as 1 and the matrix marked as 0.

[0139] 3) Set the scanning direction to X / Y direction, perform line cutting on the binary image or matrix based on the scanning direction, count the length of continuous pore segments in each direction, calculate the equivalent pore size and surface porosity component, and obtain the pore size distribution in each direction.

[0140] 4) Perform Gaussian fitting on the pore size distribution and calculate the mean and standard deviation. For specific fitting methods, please refer to Figure 7 and Figure 8 , Figure 7 An example diagram of Gaussian fitting of the x-direction line-cut aperture distribution provided by an embodiment of the present application is shown. Figure 8 An example diagram of Gaussian fitting of the y-direction line-cut aperture distribution provided in an embodiment of the present application is shown.

[0141] S4. Anisotropy quantification analysis.

[0142] Calculate the fluctuation anisotropy factor, position difference factor and comprehensive anisotropy factor.

[0143] In this way, the specific application example of the embodiment of the present application abandons the traditional steps of distinguishing between connected pores and isolated pores through an innovative multi-directional wire cutting method, and directly uses the cutting line length to objectively characterize the pore size, which significantly simplifies the analysis process and improves the reliability of the results; it processes pores of different morphologies through statistical differentiation of line length, overcoming the scientific defect of the traditional equivalent circle method that causes loss of morphological information; based on directional wire cutting, it realizes the quantification of anisotropic pore size distribution, filling the gap that the existing technology cannot distinguish multi-directional pore characteristics.

[0144] Figure 9 A schematic diagram of the structure of a device for obtaining pore size distribution of rock images based on wire cutting technology provided in an embodiment of the present application is shown.

[0145] refer to Figure 9Based on the above-mentioned method for obtaining the pore size distribution of rock images based on wire cutting technology, an embodiment of the present application also provides a device for obtaining the pore size distribution of rock images based on wire cutting technology, and the device includes: a processing module 501, used to obtain an imaging image of the rock, and binarize the image to obtain a binarized matrix, and the non-zero values in the binarized matrix represent the pore area; a cutting module 502, used to perform multi-directional wire cutting on the binarized matrix to obtain the number of pixels and single-pixel length of continuous pore segments in each direction, and the multi-direction includes at least row direction and column direction; a calculation module 503, used to obtain the pore size distribution of the rock in each direction according to the number of pixels and single-pixel length of continuous pore segments in each direction.

[0146] It should be noted that the description of the device in the embodiment of the present application is similar to the description of the method embodiment above, and has similar beneficial effects as the method embodiment, so it will not be repeated here. Figures 1 to 8 The present invention shall be understood by reference to the description of any of the accompanying drawings.

[0147] According to an embodiment of the present application, the present application also provides an electronic device and a non-transitory computer-readable storage medium.

[0148] Figure 10 A schematic block diagram of an example electronic device 600 that can be used to implement an embodiment of the present application is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital assistants, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present application described and / or claimed herein.

[0149] like Figure 10 As shown, electronic device 600 includes a computing unit 601, which can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 602 or a computer program loaded from a storage unit 608 into a random access memory (RAM) 603. Various programs and data required for the operation of electronic device 600 may also be stored in RAM 603. Computing unit 601, ROM 602, and RAM 603 are interconnected via a bus 604. An input / output (I / O) interface 605 is also connected to bus 604.

[0150] Multiple components in the electronic device 600 are connected to the I / O interface 605, including an input unit 606, such as a keyboard, a mouse, etc.; an output unit 607, such as various types of displays, speakers, etc.; a storage unit 608, such as a magnetic disk, an optical disk, etc.; and a communication unit 609, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 609 allows the electronic device 600 to exchange information / data with other devices via a computer network such as the Internet and / or various telecommunication networks.

[0151] The computing unit 601 can be any general-purpose and / or specialized processing component with processing and computing capabilities. Some examples of the computing unit 601 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various specialized artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 601 performs the various methods and processes described above, such as the method for obtaining pore size distribution of rock images based on wire cutting technology. For example, in some embodiments, the method for obtaining pore size distribution of rock images based on wire cutting technology can be implemented as a computer software program tangibly embodied in a machine-readable medium, such as the storage unit 608. In some embodiments, part or all of the computer program can be loaded and / or installed on the electronic device 600 via the ROM 602 and / or the communication unit 609. When the computer program is loaded into the RAM 603 and executed by the computing unit 601, one or more steps of the method for obtaining pore size distribution of rock images based on wire cutting technology described above can be performed. Alternatively, in other embodiments, the computing unit 601 may be configured in any other appropriate manner (eg, by means of firmware) to execute the method for acquiring the pore size distribution of rock images based on the wire cutting technology.

[0152] Various embodiments of the systems and techniques described above can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), system-on-chip systems (SOCs), programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include being implemented in one or more computer programs that are executable and / or interpreted on a programmable system that includes at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0153] The program code for implementing the methods of the present application can be written in any combination of one or more programming languages. Such program code can be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the program code is executed by the processor or controller, the functions / operations specified in the flow charts and / or block diagrams are implemented. The program code can be executed entirely on the machine, partially on the machine, as a stand-alone software package, partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0154] In the context of this application, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or apparatus. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of machine-readable storage media may include an electrical connection based on one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), optical fibers, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0155] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the computer. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0156] The systems and techniques described herein can be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network (LAN), a wide area network (WAN), and the Internet.

[0157] A computer system may include a client and a server. The client and server are generally remote from each other and typically interact through a communication network. The client-server relationship arises through computer programs running on the respective computers and having a client-server relationship with each other. The server may be a cloud server, a server in a distributed system, or a server integrated with a blockchain.

[0158] It should be understood that the various forms of the processes shown above can be used to reorder, add, or delete steps. For example, the steps described in this application can be performed in parallel, sequentially, or in a different order, as long as the desired results of the technical solutions disclosed in this application can be achieved. This is not a limitation herein.

[0159] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of this application. Therefore, the scope of protection of this application should be based on the scope of protection of the claims.

Claims

1. A method for obtaining pore size distribution of rock images based on wire cutting technology, characterized in that: The method comprises: Acquire an image of the rock and perform binarization processing on the image to obtain a binarization matrix, wherein non-zero values in the binarization matrix represent pore areas; Performing multi-directional line cutting on the binary matrix to obtain the number of pixels and single pixel length of the continuous pore segment in each direction, wherein the multi-directional directions include at least a row direction and a column direction; According to the number of pixels and single pixel length of the continuous pore segment in each direction, the pore size distribution of the rock in each direction is obtained; The method of obtaining the pore size distribution of the rock in each direction according to the number of pixels and single pixel length of the continuous pore segment in each direction includes: The pore size of each continuous pore segment is calculated based on the number of pixels and single pixel length of each continuous pore segment in each direction; According to the total number of pixels and single pixel length of the continuous pore segment under each aperture, the surface rate component of the continuous pore segment under each aperture is calculated; The pore size distribution of the rock in each direction is obtained by taking the pore size as the abscissa and the surface porosity component under the corresponding pore size as the ordinate. Anisotropy evaluation of the rock is performed according to the pore size distribution in each direction to obtain anisotropy evaluation results, wherein the anisotropy evaluation results include a fluctuation anisotropy factor, a position difference factor, and a comprehensive anisotropy factor; Wherein, in the case where the multiple directions include row direction and column direction, the anisotropy evaluation of the rock is performed according to the pore size distribution in each direction to obtain the anisotropy evaluation result, including: The number of pixels and single pixel length of continuous pore segments in the row and column directions were fitted with logarithmic Gaussian distribution functions to obtain the row mean, row standard deviation, column mean, and column standard deviation in the row and column directions respectively. Calculate the wave anisotropy factor: in, is the row standard deviation, is the column standard deviation; Calculate the position difference factor: in, is the row mean, is the column mean; Calculate the integrated anisotropy factor: in, and is the weight coefficient.

2. The method according to claim 1, characterized in that The step of obtaining an image of the rock and performing binarization processing on the image includes: Using imaging camera technology to obtain rock images; Preprocessing the image, and performing binarization processing on the preprocessed image; The preprocessing includes contrast enhancement and noise removal.

3. The method according to claim 1, characterized in that The performing multi-directional line cutting on the binarized matrix to obtain the number of pixels and single pixel length of the continuous pore segment in each direction includes: Scanning the binary matrix pixel by pixel along each direction, assigning independent increasing labels to continuous pore segments, and recording the number of pixels in each continuous pore segment; Gets the single pixel length.

4. The method according to claim 3, characterized in that The binary matrix is scanned pixel by pixel along the row direction, independent and increasing labels are assigned to the continuous pore segments, and the number of pixels of each continuous pore segment is recorded, including: Scan each pixel in each row of the binary matrix from top to bottom. When encountering a non-zero pixel, check the label status of the left adjacent pixel in the same row. If the left pixel is already labeled, inherit the label; if the left pixel is a non-porous area or the current pixel is the beginning of the row, assign a new independent incremental label; The number of pixels in each row with consecutive pore segments labeled with the same label is recorded; the labels differ between rows.

5. The method according to claim 3, characterized in that Scan the binary matrix pixel by pixel along the column direction, assign independent and increasing labels to the continuous pore segments, and record the number of pixels of each continuous pore segment, including: Scan each pixel in each column of the binary matrix from top to bottom. When a non-zero pixel is encountered, check the label status of the upper adjacent pixel in the same column. If the upper pixel is already labeled, inherit the label; if the upper pixel is a non-porous area or the current pixel is the first pixel in the column, assign a new independent incremental label. The number of pixels in each column that are labeled with the same label for consecutive pore segments is recorded; where the labels differ between columns.

6. A device for obtaining pore size distribution of rock images based on wire cutting technology, characterized in that: The device comprises: A processing module is used to obtain an image of the rock and perform binarization processing on the image to obtain a binarization matrix, wherein non-zero values in the binarization matrix represent pore areas; a cutting module, configured to perform multi-directional line cutting on the binary matrix to obtain the number of pixels and single-pixel length of continuous pore segments in each direction, wherein the multi-directional directions include at least row and column directions; A calculation module is used to obtain the pore size distribution of the rock in each direction based on the number of pixels and single pixel length of the continuous pore segment in each direction; The method of obtaining the pore size distribution of the rock in each direction according to the number of pixels and single pixel length of the continuous pore segment in each direction includes: The pore size of each continuous pore segment is calculated based on the number of pixels and single pixel length of each continuous pore segment in each direction; According to the total number of pixels and single pixel length of the continuous pore segment under each aperture, the surface rate component of the continuous pore segment under each aperture is calculated; The pore size distribution of the rock in each direction is obtained by taking the pore size as the abscissa and the surface porosity component under the corresponding pore size as the ordinate. The device is also used to evaluate the anisotropy of the rock based on the pore size distribution in each direction, and obtain an anisotropy evaluation result, wherein the anisotropy evaluation result includes a fluctuation anisotropy factor, a position difference factor, and a comprehensive anisotropy factor; Wherein, in the case where the multiple directions include row direction and column direction, the anisotropy evaluation of the rock is performed according to the pore size distribution in each direction to obtain the anisotropy evaluation result, including: The number of pixels and single pixel length of continuous pore segments in the row and column directions were fitted with logarithmic Gaussian distribution functions to obtain the row mean, row standard deviation, column mean, and column standard deviation in the row and column directions respectively. Calculate the wave anisotropy factor: in, is the row standard deviation, is the column standard deviation; Calculate the position difference factor: in, is the row mean, is the column mean; Calculate the integrated anisotropy factor: in, and is the weight coefficient.

7. An electronic device, characterized in that: include: at least one processor; as well as a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method according to any one of claims 1 to 5.

8. A non-transitory computer-readable storage medium storing computer instructions, characterized in that: The computer instructions are used to enable a computer to execute the method according to any one of claims 1 to 5.

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