Carbonate rock pore aspect ratio extraction method, device, equipment and medium
By using an automated digital core analysis method, the porosity of carbonate rocks is separated and calculated, solving the accuracy problem of existing technologies that rely on rock physics models and achieving a more accurate characterization of porosity.
Patent Information
- Application Number
- CN202410819797.1
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-06-24
- Publication Date
- 2025-12-26
AI Technical Summary
Existing techniques for calculating the porosity of carbonate rocks rely on the input parameters of the rock physics model and the accuracy of the logging wave velocities, resulting in large errors in the calculation results and making it difficult to accurately characterize the porosity in practical applications.
The digital core automatic analysis method is adopted to obtain two-dimensional grayscale slices of carbonate rock cores, separate matrix, pores and fractures, and use the maximum Feret diameter method to calculate the equivalent horizontal axis and connected domain area of pores and fractures, and then calculate the porosity.
It enables a more accurate characterization of the aspect ratio of each pore and fracture in core CT images, provides a feasible verification and comparison method for pore aspect ratio inversion, and improves the accuracy and reliability of the calculation.
Smart Images
Figure CN121213634A_ABST
Abstract
Description
Technical Field
[0001] This disclosure relates to the fields of acoustic rock physics and digital core technology, and particularly to a method, apparatus, equipment and medium for extracting the aspect ratio of pores in carbonate rocks. Background Technology
[0002] Carbonate rocks possess complex pore and fracture structures that significantly influence their physical and elastic properties, especially deep, high-pressure, and dense carbonate rocks. Rock physicists idealize pores and fractures as ellipsoids, defining the ratio of the major axis (horizontal axis) to the minor axis (vertical axis) of the ellipse as the pore aspect ratio, which characterizes the complex pore structure. The smaller the pore aspect ratio, the narrower and longer the pores and fractures, resulting in greater deformation under axial pressure and stronger pressure on the fluid within the pores. When pores connect, jets form between pores with different aspect ratios, a phenomenon particularly common in dense rocks.
[0003] The existing techniques for calculating the porosity ratio face the following problems: (1) they are highly dependent on the input parameters of the rock physics model and the accuracy of the logging wave velocity; (2) if there is a large error in one of the parameters, the final calculated porosity ratio will have a large error. Summary of the Invention
[0004] This disclosure provides a method, apparatus, equipment, and medium for extracting the pore aspect ratio of carbonate rocks, which can more accurately and quantitatively characterize the pore aspect ratio based on automatic analysis of digital cores, accurately characterize the aspect ratio of each pore and fracture in the core CT image, and provide a feasible verification and comparison method for the pore aspect ratio inversion method.
[0005] In a first aspect, embodiments of this disclosure provide a method for extracting the aspect ratio of pores in carbonate rocks, including:
[0006] Obtain two-dimensional grayscale slices of carbonate rock cores;
[0007] Separate the matrix, pores, and fractures from the two-dimensional grayscale slice of the core;
[0008] The images of the separated holes and fractures were binarized to construct a first binarized 3D digital core containing only holes and a second binarized 3D digital core containing only fractures.
[0009] The holes in the first binarized 3D digital core and the cracks in the second binarized 3D digital core are marked.
[0010] The equivalent horizontal axis of the hole and the equivalent horizontal axis of the slot are calculated using the maximum Feret diameter method.
[0011] Calculate the area of the connected region of the hole and the area of the connected region of the slit;
[0012] The aspect ratio of a hole is calculated based on its equivalent horizontal axis and the area of its connected domain; the aspect ratio of a slit is calculated based on its equivalent horizontal axis and the area of its connected domain.
[0013] In some embodiments, obtaining a two-dimensional grayscale slice image of a carbonate rock core includes:
[0014] Two-dimensional grayscale slices of carbonate rock cores obtained from core CT scanning experiments were acquired.
[0015] Remove noise and errors from the two-dimensional grayscale slice image of the core.
[0016] In some embodiments, separating the matrix, pores, and fractures in the two-dimensional grayscale slice of the core includes:
[0017] Separate the holes in the two-dimensional grayscale slice of the core;
[0018] For crack regions with gray values similar to those of holes, the discontinuous cracks are connected, the unremoved holes are eliminated, a more accurate crack network is obtained, and the crack network structure is shaped by adjusting the brightness range.
[0019] In some embodiments, separating the matrix, pores, and fissures in the two-dimensional grayscale slice of the core further includes removing isolated areas that were not removed.
[0020] In some embodiments, when holes and seams are separated, holes or seams with similar gray levels that cannot be separated are cut off.
[0021] In some embodiments, the equivalent horizontal axis of the hole and the equivalent horizontal axis of the slit are calculated using the maximum Feret diameter method, including:
[0022] Obtain the minimum convex polygon containing the target hole and the minimum convex polygon containing the target slit;
[0023] Find the maximum Feret diameter between the vertices of the smallest convex polygon, and use this maximum Feret diameter as the equivalent horizontal axis of the target hole or the target seam.
[0024] Secondly, embodiments of this disclosure provide a carbonate rock pore aspect ratio extraction device, comprising:
[0025] The acquisition module is used to acquire two-dimensional grayscale slice images of carbonate rock cores;
[0026] The separation module is used to separate the matrix, pores, and fractures in the two-dimensional grayscale slice of the core.
[0027] The core construction module is used to binarize the images of the separated holes and fractures, and to construct a first binarized 3D digital core containing only holes and a second binarized 3D digital core containing only fractures, respectively.
[0028] The marking module is used to mark the holes in the first binarized 3D digital core and the cracks in the second binarized 3D digital core.
[0029] The first calculation module is used to calculate the equivalent horizontal axis of the hole and the equivalent horizontal axis of the slit using the maximum Feret diameter method;
[0030] The second calculation module is used to calculate the area of the connected domain of the hole and the area of the connected domain of the slit.
[0031] The third calculation module is used to calculate the aspect ratio of a hole based on its equivalent horizontal axis and the area of its connected domain, and to calculate the aspect ratio of a seam based on its equivalent horizontal axis and the area of its connected domain.
[0032] Thirdly, embodiments of this disclosure provide a computer device including a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the method described in the first aspect.
[0033] Fourthly, embodiments of this disclosure provide a computer-readable storage medium having a computer program stored thereon that, when executed by a processor, implements the steps of the method described in the first aspect.
[0034] Fifthly, embodiments of this disclosure provide a computer program product, including a computer program / instructions, which, when executed by a processor, implements the steps of the method described in the first aspect.
[0035] The method for extracting the aspect ratio of pores in carbonate rocks provided in this embodiment separates the matrix, pores, and fractures from a two-dimensional grayscale slice image of a carbonate rock core. The separated pore and fracture images are binarized to construct a first binarized three-dimensional digital core containing only pores and a second binarized three-dimensional digital core containing only fractures, respectively. The pores in the first binarized three-dimensional digital core and the fractures in the second binarized three-dimensional digital core are marked. The equivalent horizontal axis of the pores and the equivalent horizontal axis of the fractures are calculated using the maximum Feret diameter method, and the connected domain areas of the pores and the fractures are calculated. Then, the aspect ratio of the pores is calculated based on the equivalent horizontal axis of the pores and the connected domain area of the pores, and the aspect ratio of the fractures is calculated based on the equivalent horizontal axis of the fractures and the connected domain area of the fractures. The holes and seams separated by this method almost completely contain the original information of the holes and seams, and contain more information than related technologies, making the separation of holes and seams more accurate. In the calculation of the aspect ratio of holes and seams, the equivalent horizontal axis calculated using the maximum Feret diameter method is very close to the shape characteristics of holes and seams. By separating holes and seams and calculating them separately, the aspect ratio of the pores corresponding to the peak value in the probability distribution diagram of the pore aspect ratio is the number that best represents the equivalent aspect ratio of the holes or seams. Attached Figure Description
[0036] The present disclosure will be described in more detail below based on embodiments and with reference to the accompanying drawings:
[0037] Figure 1 This is a schematic flowchart of a method for extracting the aspect ratio of pores in carbonate rocks, provided in an embodiment of this disclosure.
[0038] Figure 2(a) is a schematic diagram of the principle of 8 connected regions provided in the embodiment of this disclosure, Figure 2(b) is a schematic diagram of the principle of the minimum convex polygon provided in the embodiment of this disclosure, and Figure 2(c) is a schematic diagram of the principle of the maximum Feret diameter method provided in the embodiment of this disclosure;
[0039] Figures 3(a), 3(b), and 3(c) are schematic diagrams of core 1, core 2, and core 3 provided in the embodiments of this disclosure, respectively.
[0040] Figures 4(a), 4(b), and 4(c) are respectively the pore and fracture binarized images of core 1, core 2, and core 3 provided in the embodiments of this disclosure, as well as the three-dimensional digital core images containing only pores and only fractures.
[0041] Figures 5(a), 5(b), and 5(c) are respectively the pore aspect ratio probability distribution diagrams of the three-dimensional cores of cores 1, core 2, and core 3 provided in the embodiments of this disclosure.
[0042] In the accompanying drawings, the same parts are referred to by the same reference numerals, and the drawings are not drawn to scale. Detailed Implementation
[0043] To enable those skilled in the art to better understand the technical solutions of this disclosure, and to fully understand and implement the process of how this disclosure applies technical means to solve technical problems and achieve corresponding technical effects, the technical solutions in the embodiments of this disclosure will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this disclosure, not all embodiments. The embodiments of this disclosure and the various features within them can be combined with each other without conflict, and the resulting technical solutions are all within the protection scope of this disclosure. All other embodiments obtained by those skilled in the art based on the embodiments of this disclosure without creative effort should fall within the protection scope of this disclosure.
[0044] Carbonate rocks have complex pore and fracture structures that significantly influence their physical and elastic properties, especially for deep, high-pressure, and dense carbonate rocks. Rock physicists idealize pores and fractures as ellipsoidal spheres, defining the ratio of the major axis (horizontal axis) to the minor axis (vertical axis) of the ellipse as the pore aspect ratio to characterize the complex pore structure.
[0045] The smaller the pore aspect ratio, the narrower and longer the pores and fissures, resulting in greater deformation under axial pressure and stronger pressure on the fluid within the pores. When pores connect, jets form between pores with different aspect ratios, a phenomenon particularly common in dense rocks. Boris Gurevich et al. (2010) proposed a method for calculating the elastic modulus related to pore aspect ratio—the jet model—based on the jet mechanism. Ouyang Fang and Zhao Jianguo et al. (2021) proposed a method for calculating the pore aspect ratio related to fracture density based on pressure-ultrasonic velocity measurement experiments, but this method relies on the accuracy of experimental data and cannot be used on a large scale in practical applications. Kuster and... (1974) et al., by considering the aspect ratio of pores and the elastic modulus of mineral particles, proposed The model calculates the equivalent elastic modulus. Based on... Previous researchers have proposed iterative methods for determining the porosity ratio, but due to the large number of intermediate parameters, significant parameter errors, and complex calculation processes, the obtained porosity ratios often contain substantial errors. Furthermore, rock physics models using porosity ratio as input include the Differential Equivalent Medium Model (DEM) (Norris, 1985) and the Self-Compatible Approximation Theory (SCA) (Berryman, 1980). These two models are commonly used to characterize the influence of porosity ratio on rock velocities in carbonate rocks. The linear simplification model of the Differential Equivalent Medium Model is frequently used to calculate the dry rock modulus considering the influence of pore and fracture structures with equal porosity ratio. Zhang Feng, Xu Xiaokai, Guo Zhiqi, and many others have calculated the formation equivalent porosity ratio by comparing and iteratively comparing the P-wave velocities calculated using different rock physics models with aspect ratio as input with the actual P-wave velocities measured in well logging. However, the existing techniques for calculating the porosity ratio face the following problems: (1) they are extremely dependent on the input parameters of the rock physics model and the accuracy of the logging wave velocity; (2) once one of the parameters has a large error, the final calculated porosity ratio will have a large error.
[0046] To more accurately and quantitatively characterize the aspect ratio of pores and accurately characterize the aspect ratio of each pore and fissure in a core CT image, this disclosure provides a method for characterizing the aspect ratio of pores and fissures in CT micron-scale images, providing a feasible verification and comparison method for pore aspect ratio inversion.
[0047] Example 1
[0048] Figure 1 This is a schematic flowchart illustrating a method for extracting the aspect ratio of pores in carbonate rocks, provided in an embodiment of this disclosure. Figure 1 As shown, this embodiment provides a method for extracting the aspect ratio of pores in carbonate rocks, including:
[0049] Step S11: Obtain a two-dimensional grayscale slice of the carbonate rock core.
[0050] Furthermore, obtaining two-dimensional grayscale slices of carbonate rock cores can include:
[0051] Step S11a: Obtain a two-dimensional grayscale slice of carbonate rock core obtained from the core CT scan experiment;
[0052] Step S11b: Remove noise errors from the two-dimensional grayscale slice image of the core.
[0053] In this step, edge information errors caused by CT scanning are removed by cropping, and as much representative portion of the complex pore and fracture structure of carbonate rocks as possible is selected. The built-in filtering algorithm of Avizo software can be used to remove noise errors from the core grayscale image. Median filtering can be used. Median filtering selects the pixel values of a pixel and its neighboring pixels (an odd number of pixels in total) from a digital image or sequence, sorts these pixel values, and then uses the pixel value in the middle position as the current pixel value, making the surrounding pixel values closer to the true value, thereby eliminating isolated noise points. The selected pixel value is y. i The expression is as follows:
[0054]
[0055] In the formula, v represents the number of neighboring pixels around the selected pixel, and f i-v , ..., f i ...f i+v This represents a one-dimensional sequence of pixel values of the selected pixel and its neighboring pixels, where m represents the window length and is an odd number.
[0056] This embodiment, by shearing the noise errors in the two-dimensional grayscale slice image of the core, can provide an accurate basis for subsequent separation of pores and fractures and quantitative characterization of the pore aspect ratio.
[0057] Step S12: Separate the matrix, pores, and fissures from the two-dimensional grayscale slice of the core.
[0058] Furthermore, separating the matrix, pores, and fractures in a two-dimensional grayscale slice of the core can include:
[0059] Step S12a: Separate the holes in the two-dimensional grayscale slice of the core.
[0060] Step S12b: For crack regions with gray values similar to those of holes, connect discontinuous cracks, eliminate unremoved holes, obtain a more accurate crack network, and adjust the brightness range to define the crack network structure.
[0061] In this embodiment, the core CT scan image can be processed into a grayscale image using Avizo software. Specifically, the built-in algorithm of Avizo software can be used: the cv2.imread() function reads the color image, the cv2.cvtColor() function converts the read color image into a grayscale image, the nump array obtains the grayscale value of each pixel, and the pixel grayscale value is identified. Thresholding is performed on the matrix composed of grayscale values (0~255), and the matrix, pores, and fractures are separated according to the grayscale values using the digital core automatic analysis algorithm.
[0062] In step S12, which separates the matrix, pores, and cracks, the interactive threshold segmentation method in Avizo software can be used to separate the pores. For crack regions with similar gray values to the pores, the membrane enhancement filter in Avizo software can be used to connect the cracks that are discontinuous due to similar gray values, and to eliminate some pores (also known as isolated regions) that are not removed due to similar gray values, thereby obtaining a more continuous mesh structure (crack network). Then, the brightness difference segmentation (Tophat) in Avizo software is used to adjust the brightness region range. By repeatedly clicking on the two-dimensional image to modify the chromatographic range and selecting a suitable region, the crack network structure is finalized.
[0063] In some cases, even after the fracture network structure has taken shape, there may still be a few isolated areas (i.e., a small number of micropores) that have not been removed due to over-segmentation. Therefore, separating the matrix, pores, and fractures in the two-dimensional grayscale slice of the core also includes removing these isolated areas. For the few isolated areas that have not been removed, the over-segmented small spots are removed to finally obtain an accurate fracture network.
[0064] In some cases, if holes and seams are separated, it is difficult to separate holes and seams with similar gray levels using the above methods. Therefore, in the case of hole and seam separation, holes or seams with similar gray levels that cannot be separated need to be cut off.
[0065] In this embodiment, when separating holes and seams, for holes and seams with similar gray levels that are difficult to separate using the above methods, the excess holes (or seams) can be cut off using the Volume Edit method with high segmentation intensity in Avizo software. Furthermore, the positional distribution of holes and seams in three dimensions can be displayed by removing the mask, according to actual needs.
[0066] Step S13: Binarize the images of the separated holes and fractures to construct a first binarized 3D digital core containing only holes and a second binarized 3D digital core containing only fractures.
[0067] In this embodiment, the matrix is set to 0 and the pores and fractures are set to 1 in the binarized image, resulting in binarized pore and fracture data. By sequentially overlaying 3D digital core models, binarized 3D digital cores containing only pores and only fractures are obtained. By analyzing such binarized 3D digital cores, the accurate porosity can be calculated.
[0068] Step S14: Mark the holes in the first binarized 3D digital core and the cracks in the second binarized 3D digital core.
[0069] In this embodiment, holes and seams are processed using the 8-connected-domain labeling method. Labeling holes and seams includes the following steps:
[0070] Step S14a: Prepare a labeled two-dimensional array with an initial value of 0 and the same row and column size as the binarized images of the holes and seams;
[0071] Step S14b: Starting from the top left corner of the binarized image of the hole and slit, scan the pixels. Starting with the first pixel with a value of 1, check whether there are pixels with a value of 1 in the surrounding area (up, top left, top right, bottom, top left, bottom left, left, and right directions). If there are, mark them as the same connected component and record the label number n (n = 1, 2, ..., N). Repeat the above process with these points as the new starting points. If there are no pixels, terminate the current loop.
[0072] Step S14c: Exclude the scanned region and the identified connected components, use a new label n+1, and repeat step S14b until connected component identification is complete. A schematic diagram of the connected component principle is shown in Figure 2(a).
[0073] Step S15: Calculate the equivalent horizontal axis of the hole and the equivalent horizontal axis of the slit using the maximum Feret diameter method.
[0074] Furthermore, the equivalent horizontal axis of the hole and the equivalent horizontal axis of the slit are calculated using the maximum Feret diameter method, including:
[0075] Step S15a: Obtain the smallest convex polygon containing the target hole and the smallest convex polygon containing the target slit.
[0076] In this embodiment, MATLAB software is used as the tool, and the `regionprops` function is used to enclose the target hole and target seam with a convex polygon. The specific calling format is: `STATS = regionprops(L, 'ConvexHull')`. `L` represents the binary array of the target hole and seam, and `'ConvexHull'` represents the minimum convex polygon that encloses the above region. The return value `STATS` is a p-row, 2-column matrix containing the x and y values of each vertex of the obtained convex polygon. A schematic diagram of the minimum convex polygon principle is shown in Figure 2(b).
[0077] Step S15b: Find the maximum Feret diameter between the vertices of the smallest convex polygon, and use this maximum Feret diameter as the equivalent horizontal axis of the target hole or the equivalent horizontal axis of the target seam.
[0078] Given the vertex coordinates of the smallest convex polygon, calculate the distance between any two parallel tangent lines that are tangent to the vertex. Arrange all distances in ascending order and select the largest distance, which is the maximum Feret diameter. A schematic diagram of the maximum Feret diameter method is shown in Figure 2(c). Using this maximum Feret diameter as the equivalent horizontal axis L of the hole or slit, the equivalent vertical axis can be further calculated.
[0079] Step S16: Calculate the area of the connected region of the hole and the area of the connected region of the slit.
[0080] In this embodiment, the Area function in the Regionprops function is used to calculate the area S of the connected region of the hole and the seam, and the equivalent vertical axis H = S / L of the hole and the seam is calculated according to the irregular shape area equivalent approximation method (area approximation method).
[0081] Step S17: Calculate the aspect ratio of the hole based on the equivalent horizontal axis of the hole and the area of the connected domain of the hole; calculate the aspect ratio of the seam based on the equivalent horizontal axis of the seam and the area of the connected domain of the seam.
[0082] α = H / L = S / L 2
[0083] In the formula, α represents the aspect ratio of the pores, including the aspect ratio of the pores and the aspect ratio of the slits.
[0084] The aspect ratio of pores and fractures characterizes their compressive and deformation resistance. For long, narrow, penny-shaped fractures, the stiffness is low, and the deformation is significant under pressure, exerting pressure on the pore fluid and greatly affecting its elastic properties. The aspect ratio is represented by approximating the pore or fracture as a flattened ellipse, using the ratio of its longitudinal and transverse axes. The magnitude of the aspect ratio is directly proportional to the compressive strength and inversely proportional to the degree of deformation, making it an important parameter characterizing the influence of pores and fractures on the elastic properties of fluid-saturated rocks.
[0085] In this embodiment, the two-dimensional slices obtained after core CT scans are filtered and denoised to obtain a two-dimensional grayscale image with significant differences in grayscale between pores, fractures, and matrix. The pores and fractures are separated using the digital core automatic analysis algorithm in Avizo software. Compared to existing methods that only equate pores and fractures to pinholes and near-circular holes, this method separates pores and fractures that almost completely contain the original information of the pores and fractures, providing more information and more accurate separation, thus laying a good foundation for subsequent calculations. For calculating the aspect ratio of the pores and fractures, the inventors of this application used the minimum rectangle long side method, the minimum convex polygon maximum distance between nodes method, and the maximum Feret diameter method to calculate the equivalent horizontal axis. Whether qualitatively comparing the principle diagrams of the three methods or quantitatively comparing the final calculated aspect ratios, the equivalent horizontal axis calculated by the maximum Feret diameter method best matches the shape characteristics of the pores and fractures. Finally, based on the irregular image area equivalence method and the formula α=H / L=S / L, the method is applied to the pores and fractures. 2 By qualitatively comparing the calculated pore aspect ratio probability distribution map with digital core data, the inventors found that the method calculates the pore aspect ratio separately for pores and fractures, resulting in a huge difference in the pore aspect ratio. The pore aspect ratio corresponding to the peak value in the obtained pore aspect ratio probability distribution map is the number that best represents the equivalent aspect ratio of pores or fractures.
[0086] Example 2
[0087] This embodiment provides a device for extracting the aspect ratio of pores in carbonate rocks, including:
[0088] The acquisition module is used to acquire two-dimensional grayscale slice images of carbonate rock cores;
[0089] The separation module is used to separate the matrix, pores, and fractures in a two-dimensional grayscale slice of the core.
[0090] The core construction module is used to binarize the images of the separated holes and fractures, and to construct a first binarized 3D digital core containing only holes and a second binarized 3D digital core containing only fractures, respectively.
[0091] The marking module is used to mark the holes in the first binarized 3D digital core and the cracks in the second binarized 3D digital core.
[0092] The first calculation module is used to calculate the equivalent horizontal axis of the hole and the equivalent horizontal axis of the slit using the maximum Feret diameter method;
[0093] The second calculation module is used to calculate the area of the connected domain of the hole and the area of the connected domain of the slit.
[0094] The third calculation module is used to calculate the aspect ratio of a hole based on its equivalent horizontal axis and the area of its connected domain, and to calculate the aspect ratio of a seam based on its equivalent horizontal axis and the area of its connected domain.
[0095] Furthermore, the acquisition module can be used to: acquire two-dimensional grayscale slices of carbonate rock cores obtained from core CT scanning experiments; and remove noise errors from the two-dimensional grayscale slices of the core.
[0096] By removing edge information errors caused by CT scans and selecting as many representative portions as possible of the complex pore and fracture structures of carbonate rocks, noise errors in the core grayscale image can be removed using the built-in filtering algorithm in Avizo software. A median filtering algorithm can be used. Median filtering selects the pixel values of a pixel and its neighboring pixels (an odd number of pixels in total) from a digital image or sequence, sorts these pixel values, and then uses the pixel value in the middle position as the current pixel value, making the surrounding pixel values closer to the true value, thereby eliminating isolated noise points. The selected pixel value is y. i The expression is as follows:
[0097]
[0098] In the formula, v represents the number of neighboring pixels around the selected pixel, and f i-v , ..., f i ...f i+v This represents a one-dimensional sequence of pixel values consisting of the selected pixel and its neighboring pixels, where m represents the window length and is an odd number. By trimming the noise errors in the two-dimensional grayscale slice of the core, an accurate basis can be provided for subsequent separation of pores and fractures and quantitative characterization of the pore aspect ratio.
[0099] Furthermore, the separation module can be specifically used to: separate the holes in the two-dimensional grayscale slice of the core; for the crack region with a grayscale value similar to that of the hole, connect the segmented discontinuous cracks, eliminate the unremoved holes, obtain a more complete crack network, and adjust the brightness range to shape the crack network structure.
[0100] In some cases, even after the crack network structure has taken shape, there may still be a few isolated regions (i.e., a small number of micropores) that have not been removed due to over-segmentation. Therefore, the separation module can also be used to: remove the isolated regions that have not been removed; and remove the over-segmented small spots for the few isolated regions that have not been removed, ultimately obtaining an accurate crack network.
[0101] In some cases, if holes and seams are separated, it is difficult to separate holes and seams with similar gray levels using the above method. Therefore, the separation module can also be used to: in the case of hole and seam separation, for holes or seams with similar gray levels that cannot be separated, it is necessary to cut them off.
[0102] In this embodiment, when separating holes and seams, for holes and seams with similar gray levels that are difficult to separate using the above methods, the separation module can also be used to: use the Volume Edit method with high segmentation intensity in Avizo software to cut and remove excess holes (or seams). Furthermore, according to actual needs, the positional distribution of holes and seams in three dimensions can be displayed by removing the mask.
[0103] The core construction module sets the matrix in the binarized image to 0 and the pores and fractures to 1, ultimately obtaining binarized pore and fracture data. By sequentially overlaying 3D digital core models, binarized 3D digital cores containing only pores and only fractures are obtained. By analyzing such binarized 3D digital cores, the accurate porosity can be calculated.
[0104] The labeling module processes holes and seams using the 8-connected-part labeling method. Labeling holes and seams includes: preparing a labeled two-dimensional array, initially set to 0, with row and column sizes identical to the binarized images of the holes and seams; scanning pixels starting from the top left corner of the binarized images of the holes and seams, starting with the first pixel with a value of 1, checking if there are pixels with a value of 1 in the surrounding area (top, top left, top right, bottom, top left, bottom left, left, right, etc.). If so, label them as the same connected component and record the label number n (n = 1, 2, ..., N). Repeat the above process using these points as new starting points; otherwise, terminate the current loop; exclude the scanned area and the identified connected components, use a new label n+1, and repeat step S14b until connected component identification is complete.
[0105] The first calculation module is specifically used to: obtain the smallest convex polygon containing the target hole and the smallest convex polygon containing the target slit; and find the maximum Feret diameter between the vertices of the smallest convex polygon, using the maximum Feret diameter as the equivalent horizontal axis of the target hole or the equivalent horizontal axis of the target slit.
[0106] Given the vertex coordinates of the smallest convex polygon, calculate the distance between any two parallel tangent lines that are tangent to the vertex. Arrange all distances in ascending order and select the largest distance, which is the maximum Feret diameter. Using this maximum Feret diameter as the equivalent horizontal axis L of the hole or slit, the equivalent vertical axis can be further calculated.
[0107] The second calculation module can use the Area function in the Regionprops function to calculate the area S of the connected region of the hole and the seam, and calculate the equivalent vertical axis H = S / L of the hole and the seam according to the area approximation method for irregular shapes (area approximation method).
[0108] For a detailed implementation of this embodiment, please refer to Embodiment 1, which will not be repeated here.
[0109] Example 3
[0110] This embodiment provides a computer device, including a memory, a processor, and a computer program stored in the memory. The processor executes the computer program to implement the steps of the method of Embodiment 1.
[0111] Example 4
[0112] This embodiment provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method of Embodiment 1.
[0113] Example 5
[0114] This embodiment provides a computer program product, including a computer program / instructions, which, when executed by a processor, implements the steps of the method of Embodiment 1.
[0115] The processor may include, but is not limited to, one or more processors or microprocessors. Each processor may be implemented as an Application Specific Integrated Circuit (ASIC), Digital Signal Processor (DSP), Digital Signal Processing Device (DSPD), Programmable Logic Device (PLD), Field Programmable Gate Array (FPGA), controller, microcontroller, microprocessor, or other electronic component, for executing the methods described in the above embodiments.
[0116] Computer-readable storage media can be implemented by any type of volatile or non-volatile storage device or a combination thereof. Computer-readable storage media may include, but are not limited to, random access memory (RAM), read-only memory (ROM), flash memory, EPROM memory, EEPROM memory, registers, and computer storage media (e.g., hard disks, floppy disks, solid-state drives, removable disks, CD-ROMs, DVD-ROMs, Blu-ray discs, etc.).
[0117] Computer-readable storage media may also store at least one computer-executable program / instruction, such as computer-readable instructions. Computer-readable storage media include, but are not limited to, volatile memory and / or non-volatile memory. Volatile memory may include, for example, random access memory (RAM) and / or cache memory. Computer-readable storage media may include, for example, read-only memory (ROM), hard disk, flash memory, etc. For example, a non-transitory computer-readable storage medium may be connected to a computing device such as a computer, and then, when the computing device executes the computer-readable instructions stored on the computer-readable storage medium, the various methods described above can be performed.
[0118] In addition, the computer device may include (but is not limited to) a data bus, an input / output (I / O) bus, a display, and input / output devices (e.g., keyboard, mouse, speakers, etc.).
[0119] The processor can communicate with external devices via the I / O bus through wired or wireless networks.
[0120] In one embodiment, the at least one computer-executable instruction may also be compiled into or comprise a software product / computer program product, wherein one or more computer-executable instructions are executed by a processor to perform the steps of the various functions and / or methods in the embodiments described herein.
[0121] Example 6
[0122] This embodiment provides an application example of implementing the methods described in the foregoing embodiments.
[0123] Cores 1, 2, and 3 from deep carbonate rocks in a certain oilfield were selected:
[0124] Step 1: CT scan experiments were conducted on three rock cores to obtain two-dimensional grayscale slice images of the rock cores; the left images in Figures 3(a), 3(b), and 3(c) are top-view cross-sectional views of the CT scan grayscale images of rock core 1, rock core 2, and rock core 3, respectively.
[0125] Step 2: Remove edge information errors caused by instrument scanning by cutting and selecting as many parts as possible that can represent the complex pore and fracture structure of carbonate rocks. Use Avizo's built-in median filtering algorithm (window length of 51) to remove noise errors in the core grayscale two-dimensional slice image.
[0126] Step 3: Using the Avizo thresholding algorithm, the matrix, pores, and cracks are separated based on their grayscale values. Specifically, interactive thresholding is used to separate the pores. For crack regions with similar grayscale values to the pores, a membrane enhancement filter is used to connect the discontinuous cracks caused by similar grayscale values. This process also eliminates some pores (also known as isolated regions) that were not removed due to similar grayscale values, resulting in a more continuous mesh structure (crack network). Then, brightness difference segmentation (Tophat) is used to adjust the brightness range. By repeatedly clicking on the 2D image and modifying the chromatographic range, suitable regions are selected, ultimately shaping the crack network structure. For a few isolated regions that were not removed (i.e., a small number of micropores), over-segmented small spots are removed, resulting in an accurate crack network. When separating holes and seams, if the gray levels are similar and the holes and seams are difficult to separate using the methods described above, the excess holes (or seams) can be removed by using the Volume Edit method with high segmentation intensity in Avizo. The middle image in Figures 3(a), 3(b), and 3(c) shows the preliminary threshold segmentation image. Furthermore, the positional distribution of holes and seams in three dimensions can be displayed using a mask, as shown in the right images of Figures 3(a), 3(b), and 3(c).
[0127] Step 4: Binarize the separated 2D images of pores and fractures, setting the matrix to 0 and the pores and fractures to 1. The pore and fracture binary images of the three cores are shown in the left image of Figures 4(a), 4(b), and 4(c). By sequentially overlaying the 3D digital core models, binarized 3D digital cores containing only pores and only fractures are obtained. The middle image in Figures 4(a), 4(b), and 4(c) shows the 3D digital core image containing only pores, while the right image in Figures 4(a), 4(b), and 4(c) shows the 3D digital core image containing only fractures.
[0128] Step 5: Process holes and seams using the 8-connected component labeling method, and label the holes and seams. a) Prepare a two-dimensional array of labels, with an initial value of 0, and the row and column size is the same as the binary image of the hole and seam; b) Starting from the upper left corner of the binary face image, scan the pixels. Starting with the first pixel with a value of 1, check whether there are pixels with a value of 1 in the surrounding (upper, upper left, upper right, lower, upper left, lower left, left, right, 8 directions). If there are, mark them as the same connected component and record the label number n (n = 1, 2, ..., N). Repeat the above process with these points as new starting points. If there are no such points, terminate the current loop; exclude the scanned area and the identified connected components, use a new label n+1, and repeat step b until the connected component identification is complete. The principle of this method is shown in Figure 2(a).
[0129] Step 6: Extract the maximum Feret diameter of the connected regions of the hole and seam using the maximum Feret diameter method as the equivalent horizontal axis L of the hole and seam. First, using MATLAB software, use the `regionprops` function to frame the target hole and seam with a convex polygon, as shown in Figure 2(b). The specific calling format is: `STATS = regionprops(L, 'ConvexHull')`. `L` represents the binary array of the target face, and `'ConvexHull'` represents the smallest convex polygon enclosing the above region. The return value `STATS` is a p-row, 2-column matrix containing the x and y values of each vertex of the obtained convex polygon. Next, find the maximum Feret diameter between the vertices of the convex polygon. Given the node coordinates of the smallest convex polygon, as shown in Figure 2(c), calculate the distance between every two parallel tangent lines tangent to the vertex. Arrange all distances in ascending order and take the largest distance, which is the maximum Feret diameter. Use this maximum Feret diameter as the equivalent horizontal axis L of the hole and seam.
[0130] Step 7: Calculate the area S of the connected region of the hole and seam using the Area function in the regionprops function, and calculate the equivalent vertical axis H = S / L of the hole and seam according to the area equivalent approximation method for irregular shapes.
[0131] Step 8: Calculate the aspect ratio α = H / L = S / L2 of the pores and fractures based on the longitudinal and transverse axis parameters calculated above. The probability distribution diagrams of the aspect ratio of the pores in core 1, core 2, and core 3 can be seen in Figures 5(a), 5(b), and 5(c). The left figure in Figures 5(a), 5(b), and 5(c) is the probability distribution diagram of the aspect ratio of the pores, and the right figure in Figures 5(a), 5(b), and 5(c) is the probability distribution diagram of the aspect ratio of the fractures.
[0132] This embodiment first performs threshold segmentation on the two-dimensional slices after filtering and denoising to separate the matrix, pores, and fractures. The image is then binarized to construct three-dimensional digital cores of the pores and fractures. The pores and fractures are labeled using an 8-connected domain labeling method, and the equivalent horizontal axis of the pores and fractures is obtained using the maximum Feret diameter method. The equivalent vertical axis H of the pores and fractures is then calculated, ultimately yielding the porosity aspect ratio of the three-dimensional digital core. A method for characterizing the porosity aspect ratio of rocks at the micrometer scale of digital cores is proposed. By separating the pores and fractures and extracting the probability distribution of the porosity aspect ratio of the core pores and fractures, accurate characterization of the porosity aspect ratio is achieved.
[0133] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this disclosure are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this disclosure described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.
[0134] It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases the steps shown or described may be executed in a different order than that shown here.
[0135] In the embodiments provided in this disclosure, it should be understood that the disclosed apparatus and methods can also be implemented in other ways. The apparatus embodiments described above are merely illustrative; for example, the flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods, and computer program products according to various embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than those marked in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram and / or flowchart, and combinations of blocks in block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.
[0136] It should be noted that, in this disclosure, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element limited by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.
[0137] While the embodiments disclosed herein are as described above, the foregoing content is merely for the purpose of facilitating understanding of this disclosure and is not intended to limit this disclosure. Any person skilled in the art to which this disclosure pertains may make any modifications and changes in form and detail of the implementation without departing from the spirit and scope of this disclosure; however, the scope of patent protection of this disclosure shall still be determined by the scope defined in the appended claims.
Claims
1. A method for extracting the aspect ratio of pores in carbonate rocks, characterized in that, include: Obtain two-dimensional grayscale slices of carbonate rock cores; Separate the matrix, pores, and fractures from the two-dimensional grayscale slice of the core; The images of the separated holes and fractures were binarized to construct a first binarized 3D digital core containing only holes and a second binarized 3D digital core containing only fractures. The holes in the first binarized 3D digital core and the cracks in the second binarized 3D digital core are marked. The equivalent horizontal axis of the hole and the equivalent horizontal axis of the slot are calculated using the maximum Feret diameter method. Calculate the area of the connected region of the hole and the area of the connected region of the slit; The aspect ratio of a hole is calculated based on its equivalent horizontal axis and the area of its connected domain; the aspect ratio of a slit is calculated based on its equivalent horizontal axis and the area of its connected domain.
2. The method according to claim 1, characterized in that, Obtain two-dimensional grayscale slices of carbonate rock cores, including: Two-dimensional grayscale slices of carbonate rock cores obtained from core CT scanning experiments were acquired. Remove noise and errors from the two-dimensional grayscale slice image of the core.
3. The method according to claim 1, characterized in that, Separating the matrix, pores, and fractures from the two-dimensional grayscale slice of the core, including: Separate the holes in the two-dimensional grayscale slice of the core; For crack regions with gray values similar to those of holes, the discontinuous cracks are connected, the unremoved holes are eliminated, a more accurate crack network is obtained, and the crack network structure is shaped by adjusting the brightness range.
4. The method according to claim 3, characterized in that, The separation of matrix, pores, and fissures in the two-dimensional grayscale slice of the core also includes: removing isolated areas that were not removed.
5. The method according to claim 4, characterized in that, In cases where holes and seams are separated, holes or seams with similar gray levels that cannot be separated are cut off.
6. The method according to claim 1, characterized in that, The equivalent horizontal axis of the hole and the equivalent horizontal axis of the slot are calculated using the maximum Feret diameter method, including: Obtain the minimum convex polygon containing the target hole and the minimum convex polygon containing the target slit; Find the maximum Feret diameter between the vertices of the smallest convex polygon, and use this maximum Feret diameter as the equivalent horizontal axis of the target hole or the target seam.
7. A device for extracting the aspect ratio of pores in carbonate rocks, characterized in that, include: The acquisition module is used to acquire two-dimensional grayscale slice images of carbonate rock cores; The separation module is used to separate the matrix, pores, and fractures in the two-dimensional grayscale slice of the core. The core construction module is used to binarize the images of the separated holes and fractures, and to construct a first binarized 3D digital core containing only holes and a second binarized 3D digital core containing only fractures, respectively. The marking module is used to mark the holes in the first binarized 3D digital core and the cracks in the second binarized 3D digital core. The first calculation module is used to calculate the equivalent horizontal axis of the hole and the equivalent horizontal axis of the slit using the maximum Feret diameter method; The second calculation module is used to calculate the area of the connected domain of the hole and the area of the connected domain of the slit. The third calculation module is used to calculate the aspect ratio of a hole based on its equivalent horizontal axis and the area of its connected domain, and to calculate the aspect ratio of a seam based on its equivalent horizontal axis and the area of its connected domain.
8. A computer device, comprising a memory, a processor, and a computer program stored in the memory, characterized in that, The processor executes the computer program to implement the steps of the method according to any one of claims 1 to 6.
9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the computer program implements the steps of the method according to any one of claims 1 to 6.
10. A computer program product comprising a computer program / instructions, characterized in that, When executed by a processor, the computer program implements the steps of the method according to any one of claims 1 to 6.