A method for calculating absolute permeability of porous media based on image layering processing technology

Abstract

The present invention discloses a method for calculating the absolute permeability of porous media based on image layering processing technology, and the method comprises the following steps: S1, firstly, using microscopic imaging technology such as SEM, CT, FIB, etc. to shoot the porous medium material to obtain its two-dimensional microstructure digital image, S2, using the digital image segmentation threshold algorithm of rock and soil material, performing image segmentation processing on its two-dimensional digital image to obtain the binary image of the rock and soil material, S3, inputting the binary image of the material obtained in S2 into the two-dimensional digital image permeability algorithm model to obtain the permeability of the corresponding image. The method of the present invention has a fast test and analysis speed of core technology, and the permeability of a single sample can be measured within half an hour. At the same time, the labor cost is low, and the rock cuttings brought to the ground by the drilling platform can also be analyzed and calculated to obtain relevant technical indicators. The test sample selection is convenient, and the core is non-destructively photographed using microscopic imaging technology, and the image is directly analyzed and calculated without testing the damaged sample.

Description

Technical Field

[0001] The invention relates to the technical field of digital image imaging, in particular to a method for calculating the absolute permeability of a porous medium based on an image layering processing technology. Background Art

[0002] Porous media materials are widely present in nature. Permeability is one of the important indicators for evaluating the properties of porous media. How to effectively obtain permeability has become a hot topic in many engineering practices.

[0003] In the fields of environmental earth science and new energy development, such as deep geological storage of carbon dioxide, multiphase and multi-field coupling mechanism and disaster prediction research, unconventional oil and gas resource exploitation, etc., the permeability of porous media materials in rock and soil bodies is involved. This physical indicator is of great significance in guiding engineering practice.

[0004] In addition, the permeability of related porous media materials plays an important role in engineering construction projects such as ship terminals, cargo ports, offshore launch platforms, as well as extraterrestrial planet exploration and planetary evolution analysis.

[0005] The equipment is expensive, the test cycle is long, and a certain confining pressure needs to be applied to the core during the test. For some sensitive and fragile samples, it is easy to permanently damage their original internal pore structure, and subsequent analysis and testing work cannot be carried out after damage. For some samples that are difficult to obtain, and the core sampling is difficult and costly, this method should not be used for testing. Summary of the invention

[0006] The purpose of the present invention is to provide a method for calculating the absolute permeability of porous media based on image layering processing technology, so as to solve the problems of high cost of testing equipment, long testing cycle and great difficulty in coring during the testing process in the prior art.

[0007] The purpose of the present invention can be achieved through the following technical solutions:

[0008] A method for calculating absolute permeability of porous media based on image layering processing technology, the method comprising the following steps:

[0009] S1. First, use microscopic imaging techniques such as SEM, CT, and FIB to photograph the porous medium material to obtain its two-dimensional microstructure digital image.

[0010] S2. Use the rock and soil material digital image segmentation threshold algorithm to perform image segmentation processing on its two-dimensional digital image to obtain the rock and soil material binary image segmentation.

[0011] S3. Input the binary material image obtained in S2 into a two-dimensional digital image permeability algorithm model to obtain the permeability of the corresponding image.

[0012] Furthermore, the S2 includes image segmentation, which refers to the process of dividing an image into regions with specific features and extracting a target image. In general, the captured digital image cannot be directly used for quantitative research on rock and soil materials. A series of post-processing is required for the image, the most important of which is to accurately binarize the image. The pore-crack structure in the digital image of rock and soil materials is extracted by binarization, and the key to binarization lies in the setting of the segmentation threshold. The gray value of each pixel in the image is compared with the numerical value of the given segmentation threshold to divide the pixel points in the image into the pore-crack structure and the rock and soil matrix, which is defined as:

[0013]

[0014] Where: T is the given segmentation threshold, f(x, y) is the grayscale value of the pixel at (x, y) in the original image, g(x, y) is the grayscale value of the pixel at (x, y) after the image is binarized, 1 and 0 are the labels of the pixel classification in the image. In the digital image of rock and soil materials, 1 represents the soil matrix and 0 represents the soil pore-crack structure.

[0015] Furthermore, the S3 includes the following algorithm model principles:

[0016] For a two-dimensional microscopic digital image of rock and soil material, its fluid flow path is mainly divided into three directions XYZ, where the Z direction is perpendicular to the image, and the XY direction is in the same plane as the image, which is suitable for the permeability calculation in the XY direction of the two-dimensional image.

[0017] In the XY direction, the fluid penetrates and flows along the pores and cracks of the black pixel structure in the binary image, which is an irregular shape. The permeability calculation model is mainly based on the Hagen-Poiseuille law, and the expression is:

[0018]

[0019] In the above formula, ΔP is the pressure loss, l is the length of the capillary, μ is the dynamic viscosity, Q is the volume flow rate, and R is the radius of the capillary;

[0020] Due to the differentiation method of "turning curves into straight lines" in calculus, a new and effective permeability calculation model was constructed. For the pixel-scale binary image, the pore structure composed of black pixels as a whole is curved and irregular. However, when the whole is differentiated into multiple layers according to the pixels, the pore structure pipes composed of black pixels in each layer are regular straight pipes. This idea is extended to the entire binary image. At this time, the Hagen-Poiseuille law is used for calculation and permeability model construction.

[0021] Furthermore, S3 includes the construction of a permeability calculation model. Since the size of a single pixel is in the micron level, the original square straight tube can be approximated as a circular straight tube. Combining Darcy's law and Hagen-Poiseuille's law, the permeability expression of a single-layer pixel image can be derived as follows:

[0022]

[0023] In the above formula, k i is the permeability of the pixel image in the i-th layer, R e is the image resolution, N 0 is the number of black pixels representing the pore structure in the i-th layer pixel image, and N is the total number of pixels in a single layer;

[0024] The permeability of the single-layer pixel image and the entire image is combined through Darcy's law, and the expression is:

[0025]

[0026]

[0027] In the above formula, ΔP is the pressure difference of the whole image, Q is the flow rate of the whole image, K is the permeability of the whole image, L is the length of the image in the direction of fluid flow, A is the cross-sectional area, and ΔP is i is the pressure difference of the pixel image in the i-th layer, Q i is the flow of the pixel image of the i-th layer, L i is the length of the fluid flow direction of the i-th layer pixel image, where ΔP = ∑ΔP i and Q = Q i ;

[0028] The permeability of the entire two-dimensional image is obtained, and its expression is:

[0029]

[0030] In the above formula, K is the permeability of the entire image, and M is the number of pixel layers of the image in the direction of fluid flow.

[0031] Further, S3 includes performing three-dimensional reconstruction using imaging technology such as CT to obtain the flow path in the Z direction and perform permeability calculation of the three-dimensional reconstruction;

[0032] Using imaging technologies such as CT and FIB, more than 500 two-dimensional images of porous media can be obtained, and three-dimensional visualization images can be obtained through three-dimensional reconstruction technology.

[0033] Furthermore, S3 includes the fluid seepage in the X direction through the interconnected pore structure. Each layer is a two-dimensional image. The permeability K of a single two-dimensional image is calculated using the two-dimensional image permeability calculation method described in the previous section. i ;

[0034] The permeability of a single 2D image and a 3D reconstructed image is combined through Darcy's law, and the expression is:

[0035]

[0036]

[0037] Where ΔP is the pressure difference in the X direction of the entire 3D reconstructed image, Q is the flow rate in the X direction of the entire 3D reconstructed image, and K 3D is the permeability of the entire 3D reconstructed image in the X direction, l is the length of the fluid flow, A is the cross-sectional area of ​​the entire 3D reconstructed image, ΔP i is the pressure difference of the i-th layer image, Q i is the flow of the i-th layer image, l i is the length of the fluid flow in the i-th layer image, A i is the cross-sectional area of ​​the i-th layer image;

[0038] Where ΔP = ΔP i , Q=∑Q i , l=l i

[0039] So we have:

[0040] Finally, the permeability of the entire 3D reconstructed image in the X direction is obtained, and its expression is:

[0041]

[0042] Where M is the number of 2D images required to reconstruct the 3D image;

[0043] The above calculation method takes the X direction as an example, and the Y direction also has the same calculation method and formula.

[0044] Furthermore, the S3 includes a method for calculating the permeability in the Z direction as follows:

[0045] In the Z direction, the pore structure distribution inside the porous medium is directly observed through three-dimensional reconstruction, which is composed of tortuous pore pipes. The interval between two adjacent CT images is one pixel (micrometer level), so the differential idea is used to "turn the curve into a straight line", and the pore pipe between two adjacent images is approximated as a straight pipe. The pore size distribution of each CT image is obtained by the PSD algorithm, and then the permeability K of each image is calculated. i ;

[0046] Finally, the permeability of the single-layer pixel image and the entire image is combined through Darcy's law (similar to the previous derivation method), and the permeability expression of the 3D reconstructed image in the Z direction is obtained:

[0047]

[0048] In the above formula, M is the number of two-dimensional images required for three-dimensional reconstruction.

[0049] Beneficial effects of the present invention:

[0050] 1. The method of the present invention uses a fast core technology test and analysis speed, and the permeability of a single sample can be measured within half an hour. At the same time, the labor cost is low, and the rock cuttings brought to the ground by the drilling platform can also be analyzed and calculated to obtain relevant technical indicators, making it easy to select test samples;

[0051] 2. The method of the present invention uses microscopic imaging technology to carry out non-destructive photography of the core, and then directly analyzes and calculates the image without any damage to the sample. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] The present invention will be further described below in conjunction with the accompanying drawings.

[0053] Figure 1 It is a binary image of different rock and soil materials after pretreatment in the present invention;

[0054] Figure 2 It is a schematic diagram of the fluid seepage in the Z direction of the present invention;

[0055] Figure 3 It is a schematic diagram of the fluid seepage in the XY direction of the present invention;

[0056] Figure 4 It is a schematic diagram of pixel scale of binary image of rock and soil mass of the present invention;

[0057] Figure 5 It is a differential schematic diagram of a binary graph of a rock and soil mass according to the present invention;

[0058] Figure 6 It is a schematic diagram of a permeability calculation model based on two-dimensional digital image pixels of the present invention;

[0059] Figure 7 It is a schematic diagram of three-dimensional reconstruction of porous media according to the present invention. DETAILED DESCRIPTION

[0060] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0061] A method for calculating absolute permeability of porous media based on image layering processing technology, the method comprising the following steps:

[0062] S1. Obtaining a two-dimensional microstructure digital image

[0063] First, use microscopic imaging techniques such as SEM, CT, and FIB to photograph porous media materials and obtain their two-dimensional microstructure digital images;

[0064] S2. Analysis to obtain binary image

[0065] Taking geotechnical materials as an example, Figure 1 As shown, the rock and soil material digital image segmentation threshold algorithm is used to perform image segmentation processing on the two-dimensional digital image to obtain a rock and soil material binary image;

[0066] The digital image segmentation threshold algorithm for rock and soil materials is disclosed in Patent No. CN110021030A.

[0067] Image segmentation refers to the process of dividing an image into regions with specific features and extracting the target image. In general, the digital images obtained by shooting cannot be directly used for quantitative research on rock and soil materials. A series of post-processing is required for the images, the most important of which is to accurately binarize the images. The pore-crack structure in the digital image of rock and soil materials is extracted through binarization, and the key to binarization lies in the setting of the segmentation threshold. The gray value of each pixel in the image is compared with the numerical value of the given segmentation threshold to divide the pixels in the image into pore-crack structures and rock and soil matrix, which is defined as:

[0068]

[0069] Where: T is the given segmentation threshold, f(x,y) is the grayscale value of the pixel at (x,y) in the original image, g(x,y) is the grayscale value of the pixel at (x,y) after the image is binarized, 1 and 0 are the labels of the pixel classification in the image, in the digital image of rock and soil materials, 1 represents the soil matrix, and 0 represents the soil pore-crack structure. Intuitively speaking in the binary image, that is: black pixels are soil pore-crack structures, and white pixels are soil matrix.

[0070] S3. Calculate the permeability

[0071] The material binary image obtained in S2 is input into the two-dimensional digital image permeability algorithm model to obtain the permeability of the corresponding image.

[0072] The algorithm model works as follows:

[0073] like Figure 2 , Figure 3 As shown in the figure, for a two-dimensional microscopic digital image of rock and soil material, its fluid flow path is mainly divided into three directions XYZ, where the Z direction is perpendicular to the image, and the XY direction is in the same plane as the image, which is suitable for the permeability calculation in the XY direction of the two-dimensional image.

[0074] In the XY direction, the fluid penetrates and flows along the holes and cracks of the black pixel structure in the binary image, which is an irregular shape. The permeability calculation model is mainly based on the Hagen-Poiseuille law. The Hagen-Poiseuille law describes the pressure loss caused by the fluid flowing through a capillary tube. The pressure loss is proportional to the product of the volume flow rate, dynamic viscosity and tube length, and inversely proportional to the fourth power of the tube diameter. This law is applicable to Newtonian fluids that are incompressible, have no acceleration, are laminar and stable, and are longer than the tube diameter. Its expression is:

[0075]

[0076] In the above formula, ΔP is the pressure loss, l is the length of the capillary, μ is the dynamic viscosity, Q is the volume flow rate, and R is the radius of the capillary.

[0077] like Figure 4 As shown in the figure, since the above law is only applicable to regular long straight pipes, it cannot be directly applied to the two-dimensional irregular pore-crack structure of rock and soil materials. By drawing on the differential method of "turning curves into straight lines" in calculus, a new and effective permeability calculation model is constructed. Figure 3 Taking as an example, the details are magnified to obtain a schematic diagram of the pixel scale (each pixel is 5.345um×5.345um).

[0078] like Figure 5 As shown in the figure, for the pixel-scale binary image, the pore structure composed of the black pixels as a whole is a curved irregular shape, but when the whole is differentiated into multiple layers according to the pixel points, the pore structure pipeline composed of the black pixels in each layer is a regular straight tube. Figure 5 There are 10 layers in total. This idea is extended to the entire binary graph. At this time, the Hagen-Poiseuille law is used for calculation and permeability model construction.

[0079] Permeability calculation model construction:

[0080] like Figure 6As shown in the figure, since the size of a single pixel is micron-level, the original square straight tube can be approximated as a circular straight tube. Combining Darcy's law and Hagen-Poiseuille's law, the permeability expression of a single-layer pixel image can be derived as follows:

[0081]

[0082] In the above formula, k i is the permeability of the pixel image in the i-th layer, R e is the image resolution, N 0 is the number of black pixels representing the pore structure of the i-th layer pixel image, and N is the total number of pixels in a single layer.

[0083] The permeability of the single-layer pixel image and the entire image is combined through Darcy's law, and the expression is:

[0084]

[0085]

[0086] Where ΔP is the pressure difference of the entire image, Q is the flow rate of the entire image, K is the permeability of the entire image, L is the length of the image in the direction of fluid flow, A is the cross-sectional area, and ΔP is i is the pressure difference of the pixel image in the i-th layer, Q i is the flow of the pixel image of the i-th layer, L i is the length of the fluid flow direction of the i-th layer pixel image. Where ΔP = ∑ΔP i and Q = Q i .

[0087] Finally, the permeability of the entire two-dimensional image is obtained, and its expression is:

[0088]

[0089] Where K is the permeability of the entire image, and M is the number of pixel layers in the image in the direction of fluid flow.

[0090] 1. In the above formula, N 0 is not equal to 0, otherwise K is equal to 0, which is not realistic. 0 If it is equal to 0, then the layer K is not i Taken into account.

[0091] 2. The black pixels in the binary image represent the pore structure, but it does not mean that the fluid only passes through it. Due to the imaging resolution, the smaller pore structure is not captured, and the fluid also passes through it. Therefore, the discontinuous pore channels shown in the binary image do not affect the actual seepage.

[0092] In the Z direction, since a two-dimensional image of the rock and soil material is obtained, the flow path in the Z direction cannot be known, and it is necessary to use imaging technology such as CT for three-dimensional reconstruction. The permeability calculation method for three-dimensional reconstruction is as follows.

[0093] Although the microstructure of porous media materials can be obtained through two-dimensional digital images, the real porous media contains an intricate network of voids. The two-dimensional image can only observe the void structure on the surface of the sample, which is one-sided and the internal complex pore structure cannot be considered in the calculation. Using CT, FIB and other technical means, a large number of two-dimensional images of the porous media can be obtained. Through three-dimensional reconstruction by related algorithms, the entire internal pore structure can be intuitively seen. The permeability of the porous media can be obtained by calculating the three-dimensional reconstructed image.

[0094] like Figure 7 As shown, using imaging technologies such as CT and FIB, more than 500 two-dimensional images of porous media can be obtained, and three-dimensional visualization images can be obtained through three-dimensional reconstruction technology.

[0095] Taking the X direction as an example, the fluid seeps in the X direction through the interconnected pore structure. Each layer is a two-dimensional image. The permeability K of a single two-dimensional image is calculated using the two-dimensional image permeability calculation method described in the previous section. i .

[0096] The permeability of a single 2D image and a 3D reconstructed image is combined through Darcy's law, and the expression is:

[0097]

[0098]

[0099] Where ΔP is the pressure difference in the X direction of the entire 3D reconstructed image, Q is the flow rate in the X direction of the entire 3D reconstructed image, and K 3D is the permeability of the entire 3D reconstructed image in the X direction, l is the length of the fluid flow, A is the cross-sectional area of ​​the entire 3D reconstructed image, ΔP i is the pressure difference of the i-th layer image, Q i is the flow of the i-th layer image, l i is the length of the fluid flow in the i-th layer image, A i is the cross-sectional area of ​​the i-th layer image.

[0100] Where ΔP = ΔP i , Q=∑Q i , l=l i

[0101] So we have:

[0102] Finally, the permeability of the entire 3D reconstructed image in the X direction is obtained, and its expression is:

[0103]

[0104] Where M is the number of 2D images required to reconstruct a 3D image.

[0105] The above calculation method takes the X direction as an example, and the Y direction also has the same calculation method and formula.

[0106] The permeability in the Z direction is calculated as follows:

[0107] In the Z direction, the pore structure distribution inside the porous medium is directly observed through three-dimensional reconstruction, which is composed of tortuous pore pipes. The interval between two adjacent CT images is one pixel (micrometer level), so the differential idea is used to "turn the curve into a straight line", and the pore pipe between two adjacent images is approximated as a straight pipe. Then the pore size distribution of each CT image is obtained through the PSD algorithm, and then the permeability K of each image is calculated. i .

[0108] The PSD algorithm is disclosed in patent number ZL201810047752.1.

[0109] Finally, the permeability of the single-layer pixel image and the entire image is combined through Darcy's law (similar to the previous derivation method), and the permeability expression of the 3D reconstructed image in the Z direction is obtained:

[0110]

[0111] In the above formula, M is the number of two-dimensional images required for three-dimensional reconstruction.

[0112] According to the above-derived models (including the two-dimensional image XYZ direction permeability calculation model and the three-dimensional reconstructed image XYZ direction permeability calculation model), a related image permeability calculation system is developed. The error between the calculated permeability and its accurate value does not exceed one order of magnitude, and it has good accuracy and application value.

[0113] In the description of this specification, the description with reference to the terms "one embodiment", "example", "specific example", etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0114] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments, and the above embodiments and descriptions are only for explaining the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, and these changes and improvements all fall within the scope of the present invention to be protected.

Claims

1. A method for calculating absolute permeability of porous media based on image layering processing technology, characterized in that: The method comprises the following steps: S1. First, use SEM, CT, and FIB microscopic imaging technology to photograph the porous medium material to obtain its two-dimensional microstructure digital image; S2. Using a digital image segmentation threshold algorithm for rock and soil materials, perform image segmentation processing on the two-dimensional microstructure digital image to obtain a binary image of the rock and soil materials; S3, inputting the binary material image obtained in S2 into the two-dimensional digital image permeability algorithm model to obtain the permeability of the corresponding image; The S3 algorithm model principle is as follows: For a two-dimensional microscopic digital image of rock and soil material, its fluid flow path is mainly divided into three directions XYZ, where the Z direction is perpendicular to the image, and the XY direction is in the same plane as the image, which is suitable for the permeability calculation in the XY direction of the two-dimensional image; In the XY direction, the fluid penetrates and flows along the pores and cracks of the black pixel structure in the binary image, which is an irregular shape. The permeability calculation model is mainly based on the Hagen-Poiseuille law, and the expression is: In the above formula, is the pressure loss, l is the length of the capillary tube, µ is the kinematic viscosity, Q is the volume flow rate, and R is the radius of the capillary tube; A new and effective permeability calculation model was constructed by using the differential method of "turning curves into straight lines" in calculus. For the pixel-scale binary image, the pore structure composed of the black pixels as a whole is curved and irregular. However, when the whole is differentiated into multiple layers according to the pixels, the pore structure pipeline composed of the black pixels in each layer is a regular straight pipe. At this time, the Hagen-Poiseuille law is used for calculation and permeability model construction. The S3 includes the fluid seepage in the X direction through the interconnected pore structure. Each layer is a two-dimensional image. According to the two-dimensional image permeability calculation method, the permeability of a single two-dimensional image is calculated. ; The permeability of a single 2D image and a 3D reconstructed image is combined through Darcy's law, and the expression is: In the formula, is the pressure difference in the X direction of the entire 3D reconstructed image, Q is the flow rate in the X direction of the entire 3D reconstructed image, and K 3D is the permeability of the entire 3D reconstructed image in the X direction, l is the length of the fluid flow, A is the cross-sectional area of ​​the entire 3D reconstructed image, is the pressure difference of the i-th layer image, Q i is the flow of the i-th layer image, l i is the length of the fluid flow in the i-th layer image, A i is the cross-sectional area of ​​the i-th layer image; in, , , ; So we have: ; Finally, the permeability of the entire 3D reconstructed image in the X direction is obtained, and its expression is: Where M is the number of 2D images required to reconstruct the 3D image; The above calculation method takes the X direction as an example, and the Y direction also has the same calculation method and formula; The calculation method of S3 including the permeability in the Z direction is as follows: In the Z direction, the pore structure distribution inside the porous medium is directly observed through three-dimensional reconstruction, which is composed of tortuous pore pipes. Since the interval between two adjacent CT images is one pixel, the differential idea is used to "turn the curve into a straight line", and the pore pipe between two adjacent images is approximately a straight pipe. The pore size distribution of each CT image is obtained through the PSD algorithm, and then the permeability of each image is calculated. ; Finally, the permeability of the single-layer pixel image and the entire image is combined through Darcy's law to obtain the permeability expression of the 3D reconstructed image in the Z direction: In the above formula, M is the number of two-dimensional images required for three-dimensional reconstruction.

2. The method for calculating absolute permeability of porous media based on image layered processing technology according to claim 1, characterized in that: The S2 includes image segmentation, which refers to the process of dividing an image into regions with specific features and extracting a target image. The captured digital image cannot be directly used for quantitative research on rock and soil materials. A series of post-processing is required for the image, the most important of which is to accurately binarize the image. The pore-crack structure in the digital image of rock and soil materials is extracted by binarization, and the key to binarization lies in the setting of the segmentation threshold. The gray value of each pixel in the image is compared with the numerical value of the given segmentation threshold to divide the pixels in the image into pore-crack structures and rock and soil matrix. It is defined as: Where: T is the given segmentation threshold, For the original image The gray value of the pixel at After the image is binarized The grayscale value of the pixel at , 1 and 0 are the labels for the classification of pixels in the image. In the digital image of rock and soil materials, 1 represents the soil matrix and 0 represents the soil pore-crack structure.

3. The method for calculating absolute permeability of porous media based on image layered processing technology according to claim 1, characterized in that: S3 includes the construction of a permeability calculation model. Since the size of a single pixel is micrometer-level, the original square straight tube can be approximated as a circular straight tube. Combining Darcy's law and Hagen-Poiseuille law, the permeability expression of a single-layer pixel image is derived as follows: In the above formula, k i is the permeability of the pixel image in the i-th layer, R e is the image resolution, N0 is the number of black pixels representing the pore structure in the i-th layer pixel image, and N is the total number of pixels in a single layer; The permeability of the single-layer pixel image and the entire image is combined through Darcy's law, and the expression is: In the above formula, is the pressure difference of the whole image, Q is the flow rate of the whole image, K is the permeability of the whole image, L is the length of the image in the direction of fluid flow, A is the cross-sectional area, is the pressure difference of the pixel image in the i-th layer, Q i is the flow of the pixel image of the i-th layer, L i is the length of the fluid flow direction of the i-th layer pixel image, where and ; The permeability of the entire two-dimensional image is obtained, and its expression is: In the above formula, K is the permeability of the entire image, and M is the number of pixel layers of the image in the direction of fluid flow.

4. The method for calculating absolute permeability of porous media based on image layered processing technology according to claim 3, characterized in that: S3 includes using CT imaging technology to perform three-dimensional reconstruction, obtain the flow path in the Z direction, and perform permeability calculation of the three-dimensional reconstruction; Using CT and FIB imaging techniques, more than 500 two-dimensional images of porous media can be obtained, and three-dimensional visualization images can be obtained through three-dimensional reconstruction technology.

Images