Shale multi-scale digital core reconstruction method and system, equipment and storage medium

Abstract

The invention relates to a shale multi-scale digital core reconstruction method and system, equipment and a storage medium, and belongs to the field of oil-gas exploration. The method comprises the following steps: based on a plurality of rock cores with different diameters, obtaining bedding seam characteristic parameters with different size distributions; based on the bedding seam characteristic parameters distributed in different sizes, constructing a bedding seam of the digital rock core; among bedding seams of the digital core, reconstructing matrix pores and throats according to shale matrix pore characteristic parameter probability distribution; and completing the digital core reconstruction based on the completion of the reconstruction of the matrix pores and throats. According to the method, diversity and multiple scales of pore structure types are fully considered, and the characteristics of low porosity, low permeability, poor pore connectivity and anisotropy of shale are simulated to a high degree; according to the sequence of bedding seam construction, matrix pore and throat reconstruction, the problems that in the reconstruction process of the multi-scale digital core considering the bedding seams and the matrix pores, the bedding seams and the matrix pores are disordered and troublesome to process when coupled are solved.

Description

Technical Field

[0001] This invention belongs to the field of oil and gas exploration, and specifically relates to a method, system, equipment, and storage medium for multi-scale digital core reconstruction of shale. Background Technology

[0002] With the improvement of computer computing power, computers can simulate increasingly complex object properties. Digital core technology has developed rapidly in recent years. Digital cores can provide an intuitive understanding of the physical properties of rocks. Shale has low porosity and pore size at the micro-nano level. Measuring the pore structure of cores is time-consuming and expensive. By establishing shale digital cores, research costs can be reduced and basic parameters can be provided for the construction of smart oilfields.

[0003] Current digital core reconstruction methods include direct testing reconstruction methods and numerical reconstruction methods. Direct simulation methods include CT scan reconstruction and FIB-SEM scan reconstruction. These methods reconstruct the actual pore structure, but are limited by the single measurement method, making it difficult to balance accuracy and measurement range. Numerical reconstruction methods do not directly rely on test results and can combine results from different testing methods for reconstruction, achieving a balance between accuracy and reconstruction range. Current digital core reconstruction methods include Gaussian method, Markov chain Monte Carlo method, simulated annealing method, and others. Shale is characterized by low porosity, low permeability, poor pore connectivity, and anisotropy. Existing digital core reconstruction technologies cannot reflect these pore structure characteristics when reconstructing shale pore structure. Summary of the Invention

[0004] To address the aforementioned problems, this invention provides a method, system, equipment, and storage medium for multi-scale digital core reconstruction of shale.

[0005] The first objective of this invention is to provide a method for multi-scale digital core reconstruction of shale, comprising:

[0006] Based on several rock cores of different diameters, characteristic parameters of bedding fractures with different size distributions were obtained;

[0007] Based on the characteristic parameters of bedding fractures with different size distributions, bedding fractures in digital cores are constructed.

[0008] Between the bedding fractures of digital cores, matrix pores and channels are reconstructed based on the probability distribution of characteristic parameters of shale matrix pores;

[0009] Based on the completion of the reconstruction of matrix pores and channels, digital core reconstruction is completed.

[0010] In a specific embodiment of the present invention, obtaining bedding fracture characteristic parameters with different size distributions based on several rock cores of different diameters includes:

[0011] Scan several rock cores of different diameters using different resolutions;

[0012] Based on the scanning results, a three-dimensional reconstruction is performed to obtain the three-dimensional morphology of the bedding joints;

[0013] Based on the three-dimensional morphology of the bedding seams, feature parameters of the bedding seams are extracted.

[0014] In a specific embodiment of the present invention, a CT scanning device is used when scanning at different resolutions.

[0015] In a specific embodiment of the present invention, when scanning several cores of different diameters with different resolutions, the scanning resolution is selected according to the diameter of the core based on the negative correlation between the direct scanning resolution and the diameter.

[0016] In a specific embodiment of the present invention, the characteristic parameters of the bedding joint include the bedding joint width, bedding joint porosity, and bedding joint spacing.

[0017] In a specific embodiment of the present invention, several cores of different diameters originate from the same full-diameter core.

[0018] In a specific embodiment of the present invention, when drilling several cores of different diameters from the same full-diameter core, drilling is performed along the direction parallel to the bedding plane.

[0019] In a specific embodiment of the present invention, the construction of bedding fractures in a digital core based on bedding fracture characteristic parameters with different size distributions includes:

[0020] Based on the characteristic parameters of bedding joints with different size distributions, the number of bedding joints of different sizes is determined;

[0021] Constructing a digital core coordinate system;

[0022] Based on the number of bedding joints, determine the number of arrays representing the direction of bedding joints in the constructed digital core coordinate system;

[0023] The initial values ​​of the group elements of the three-dimensional array are assigned to complete the construction of the bedding fractures of the digital core.

[0024] In a specific embodiment of the present invention, when determining the number of bedding joints of different sizes, the combination of bedding joints of different sizes is determined according to the limitation of the digital core size.

[0025] In a specific embodiment of the present invention, the number of arrays representing the direction of bedding fractures is calculated according to the following formula:

[0026] N=D1 / l1+D2 / l1+……+Dn / l1+L1 / l2+L2 / l2+……+Ln / l2

[0027] Where N is the number of arrays representing the direction of bedding seams, D1, D2, ..., Dn are the seam widths of bedding seams of different sizes, L1, L2, ..., Ln are the seam spacing between two adjacent bedding seams, l1 is the pixel length representing the direction of bedding seams, and l2 is the pixel length representing the matrix.

[0028] In a specific embodiment of the present invention, the probability distribution of the shale matrix pore characteristic parameters is obtained by scanning electron microscopy images of different core thin sections.

[0029] In a specific embodiment of the present invention, the different core sections include core sections parallel to the bedding direction of the same core sample and core sections perpendicular to the bedding direction of the same core sample.

[0030] In a specific embodiment of the present invention, the probability distribution of shale matrix pore characteristic parameters includes a set of image feature probability distributions of pore diameter probability distribution, pore shape factor probability distribution, throat diameter probability distribution, throat length probability distribution, tortuosity probability distribution, and pore throat coordination number probability distribution.

[0031] In a specific embodiment of the present invention, the reconstructing of matrix pores and throats between bedding fractures in the digital core based on the probability distribution of shale matrix pore characteristic parameters includes:

[0032] Between the bedding fractures in the digital core, a point is selected on the plane of the adjacent bedding fracture, and pore growth is carried out based on the probability distribution of matrix pore diameter and pore shape factor.

[0033] Throat growth is performed based on the probability distributions of throat diameter, throat length, tortuosity, and pore-throat coordination number.

[0034] Repeat the pore growth and throat growth steps until the functional location of the pores reaches the boundary of the three-dimensional array representing the direction of the bedding fracture;

[0035] Based on the completion of the pore and throat growth steps, a preliminary digital core model is obtained;

[0036] Compare the probability distribution of matrix pore characteristic parameters in the preliminary digital core model with the probability distribution of pore characteristic parameters measured in the core samples;

[0037] If the comparison result value exceeds the preset value, the matrix pores are reconstructed until the comparison result value is within the preset value range, thus completing the reconstruction of the matrix pores.

[0038] In a specific embodiment of the present invention, the step of pore growth based on the probability distribution of matrix pore diameter and the probability distribution of pore shape factor includes:

[0039] Reconstruct the porosity of the matrix adjacent to the bedding joint along the parallel bedding direction;

[0040] Pores are reconstructed into the matrix along the direction perpendicular to the stratification;

[0041] Based on the pore morphology determined by the pore diameter probability distribution and the shape factor probability distribution, the pore growth morphology is determined.

[0042] In a specific embodiment of the present invention, throat growth is performed based on the probability distributions of throat diameter, throat length, tortuosity, and pore-throat coordination number, including:

[0043] Based on the probability distribution of throat coordination number, the number and growth direction of throats in the direction parallel to and perpendicular to bedding are determined, and the initial growth of throats is carried out.

[0044] The morphological growth of the throat is carried out based on the throat morphology determined by the probability distribution of throat diameter, tortuosity, and throat length.

[0045] A second objective of this invention is to provide a multi-scale digital core reconstruction system for shale, comprising:

[0046] Module for characteristic parameters of bedding fractures: used to obtain characteristic parameters of bedding fractures with different size distributions based on several cores of different diameters;

[0047] Module for constructing bedding fractures: used to construct bedding fractures in digital cores based on bedding fracture feature parameters with different size distributions;

[0048] Reconstructing matrix pores and gills module: Used to reconstruct matrix pores and gills between bedding fractures in digital cores based on the probability distribution of shale matrix pore characteristics;

[0049] Completion Module: Used to complete the reconstruction based on matrix pores, and to complete the digital core reconstruction.

[0050] In a specific embodiment of the present invention, the reconstructed matrix pores and canals module includes a reconstructed matrix pores submodule, a reconstructed matrix canals submodule, a repetition submodule, and a comparison submodule;

[0051] The reconstructed matrix pore submodule is used to select a point on the plane of adjacent bedding fractures between bedding fractures in the digital core, and perform pore growth based on the probability distribution of matrix pore diameter and pore shape factor.

[0052] The reconstructed matrix throat submodule is used to grow the throat based on the probability distribution of throat diameter, throat length, tortuosity, and pore-throat coordination number.

[0053] The repeating submodule is used to repeat the pore growth and throat growth steps until the pore determination function position reaches the boundary of the three-dimensional array representing the bedding fracture direction; it is also used to obtain a preliminary digital core model based on the completion of the pore and throat growth steps.

[0054] The comparison submodule is used to compare the probability distribution of matrix pore characteristic parameters of the preliminary digital core model with the probability distribution of pore characteristic parameters of the core sample measured in actual samples; it is also used to reconstruct the matrix pores according to the comparison result value exceeding the preset value until the comparison result value is within the preset value range, that is, to complete the reconstruction of the matrix pores.

[0055] A third object of the present invention is to provide an electronic device comprising: a processor coupled to a memory;

[0056] The memory is used to store computer programs;

[0057] The processor is configured to execute the computer program stored in the memory, so that the electronic device performs the method described above.

[0058] A fourth object of the present invention is to provide a computer-readable storage medium storing a program or instructions that, when executed on a computer, cause the computer to perform the method described above.

[0059] The beneficial effects of this invention are:

[0060] The present invention relates to a shale multi-scale digital core reconstruction method, system, equipment, and storage medium. By coupling bedding fractures and matrix pores, it completes the reconstruction of multi-scale digital cores. On the one hand, it reflects the size of bedding fractures inside the shale, as well as the distribution of matrix pores between bedding fractures and the connectivity between them. It fully considers the diversity and multi-scale nature of pore structure types and simulates the characteristics of low porosity, low permeability, poor pore connectivity, and anisotropy of shale to a high degree. On the other hand, by following the order of bedding fracture construction, matrix pore, and channel reconstruction, it solves the problem of messy and troublesome processing when coupling bedding fractures and matrix pores in the reconstruction process of multi-scale digital cores that consider bedding fractures and matrix pores. This simplifies the coupling steps and improves the reconstruction efficiency of multi-scale digital cores while reflecting both the characteristics of bedding fractures and the characteristics of matrix pores and channels.

[0061] Secondly, when constructing bedding joints, this invention comprehensively considers the bedding joints with different size distributions and the size limitations of the digital core, avoiding the bedding joints occupying too many pixels in the width direction, which would result in an excessively large digital core size.

[0062] Other features and advantages of the invention will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures pointed out in the description, claims and drawings. Attached Figure Description

[0063] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0064] Figure 1 A flowchart of a shale multi-scale digital core reconstruction method according to an embodiment of the present invention is shown;

[0065] Figure 2 Schematic diagrams of rock cores of different diameters according to embodiments of the present invention are shown;

[0066] Figure 3 Three-dimensional morphology diagrams of bedding fractures of different diameters in rock cores according to embodiments of the present invention are shown.

[0067] Figure 4 A schematic diagram of a digital core containing bedding fractures according to an embodiment of the present invention is shown;

[0068] Figure 5 Original images of core thin sections obtained by scanning electron microscopy according to embodiments of the present invention are shown;

[0069] Figure 6 The image shown is a black-and-white binarized image obtained by image binarization processing according to an embodiment of the present invention;

[0070] Figure 7 The diagram shows the noise reduction and smoothing process obtained according to an embodiment of the present invention.

[0071] Figure 8 A schematic diagram of the pores obtained by the segmentation process according to an embodiment of the present invention is shown;

[0072] Figure 9 A schematic diagram of the throat obtained by the segmentation process according to an embodiment of the present invention is shown;

[0073] Figure 10 A schematic diagram of a digital core containing bedding fractures and matrix pores according to an embodiment of the present invention is shown;

[0074] Figure 11 A framework diagram of a shale multi-scale digital core reconstruction system according to an embodiment of the present invention is shown;

[0075] Figure 12 A frame diagram of an electronic device according to an embodiment of the present invention is shown;

[0076] In the figure: Module 1 for stratification fracture feature parameters; Module 2 for constructing stratification fractures; Module 3 for reconstructing matrix porosity; Module 4 for completion; Electronic device 300; Processor 301; Memory 302. Detailed Implementation

[0077] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0078] like Figure 1 As shown, the shale multi-scale digital core reconstruction method according to an embodiment of the present invention includes:

[0079] S1. Based on several rock cores of different diameters, characteristic parameters of bedding fractures with different size distributions were obtained;

[0080] S2. Based on the characteristic parameters of bedding fractures with different size distributions, construct the bedding fractures of the digital core;

[0081] S3. Reconstruct matrix porosity between the bedding fractures of the digital core based on the probability distribution of shale matrix porosity characteristics;

[0082] S4. The reconstruction based on matrix porosity is completed, thus completing the digital core reconstruction.

[0083] In some embodiments of the present invention, step S1 includes:

[0084] S11. Scan several core samples of different diameters using different resolutions:

[0085] When scanning at different resolutions, a CT scanning device is used.

[0086] When scanning several cores of different diameters with different resolutions, the scanning resolution is selected according to the diameter of the core based on the negative correlation between the scanning resolution and the diameter. That is, when scanning cores with smaller diameters, a larger scanning resolution is used.

[0087] S12. Based on the scanning results, perform three-dimensional reconstruction to obtain the three-dimensional morphology of the bedding joints;

[0088] S13. Based on the three-dimensional morphology of the bedding joints, extract the characteristic parameters of the bedding joints, including the bedding joint width, bedding joint porosity, and bedding joint spacing.

[0089] In step S11 of some embodiments of the present invention, in order to improve the accuracy of the characteristic parameter data of the bedding fractures, several cores of different diameters are derived from the same full-diameter core.

[0090] In step S11 of some embodiments of the present invention, when drilling several cores of different diameters from the same full-diameter core, drilling is performed along the direction parallel to the bedding plane.

[0091] In some embodiments of the present invention, step S2 includes:

[0092] S21. Based on the characteristic parameters of bedding fractures with different size distributions, determine the number of bedding fractures of different sizes, specifically:

[0093] When determining the number of bedding fractures of different sizes, the combination of bedding fractures of different sizes is determined according to the limitation of the digital core size. This is because the digital core reconstruction method of the present invention needs to consider multiple scales of bedding fractures and matrix pores. Among them, the size of bedding fractures varies. When determining the number of bedding fractures of different sizes, if the limitation of the digital core size is not considered and multiple bedding fractures with larger sizes (such as bedding fractures with a width greater than 13.6 μm) are selected, it will often result in the subsequent data core size being too large, leading to the complexity of data core application. Therefore, taking into account both the limitation of the digital core size and the multi-scale construction of the digital core, in the process of determining the number of bedding fractures of different sizes, a combination of a few bedding fractures with larger sizes and a majority of bedding fractures with smaller sizes is often selected.

[0094] S22. Construct a digital core coordinate system;

[0095] S23. Based on the number of bedding joints, determine the number of arrays representing the direction of bedding joints in the constructed digital core coordinate system. Specifically, the number of arrays representing the direction of bedding joints is calculated according to formula (1):

[0096] N = D1 / l1 + D2 / l1 + ... + D n / l1+L1 / l2+L2 / l2+……+L n / l2 (1)

[0097] In equation (1), N is the number of arrays representing the direction of bedding fractures, D1, D2, ..., D n L1, L2, ..., Ln are the widths of different sizes of bedding seams, L1, L2, ..., Ln are the seam spacings between two adjacent bedding seams, l1 is the pixel length representing the direction of the bedding seam, and l2 is the pixel length representing the matrix.

[0098] S24. Set the dimensions represented by different directions of the group elements of the three-dimensional array, that is, assign initial values ​​to the group elements, thus completing the construction of the bedding fractures of the digital core.

[0099] In some embodiments of the present invention, in step S3, the probability distribution of the shale matrix pore characteristic parameters is obtained by scanning electron microscope images of different core sections, wherein the different core sections include core sections parallel to the bedding direction of the same core sample and core sections perpendicular to the bedding direction of the same core sample.

[0100] The probability distribution of shale matrix pore characteristic parameters includes a set of image feature probability distributions of pore diameter probability distribution, pore shape factor probability distribution, throat diameter probability distribution, throat length probability distribution, tortuosity probability distribution, and pore throat coordination number probability distribution.

[0101] In some embodiments of the present invention, step S3 includes:

[0102] S31. Between the bedding fractures in the digital core, select a point on the plane of the adjacent bedding fractures, and perform pore growth based on the probability distribution of matrix pore diameter and pore shape factor.

[0103] S32. Based on the transformation rules, and the probability distributions of throat diameter, throat length, tortuosity, and pore-throat coordination number, throat growth is performed.

[0104] S33. Repeat the pore growth and throat growth steps until the functional location of the pores reaches the boundary of the three-dimensional array representing the direction of the bedding fracture.

[0105] S34. Based on the completion of the pore and throat growth steps, a preliminary digital core model is obtained;

[0106] S35. Compare the probability distribution of matrix pore characteristic parameters of the preliminary digital core model with the probability distribution of pore characteristic parameters of the core sample measured in actual samples.

[0107] S36. If the comparison result value exceeds the preset value, reconstruct the matrix pores until the comparison result value is within the preset value range, thus completing the reconstruction of the matrix pores.

[0108] In some embodiments of the present invention, the pore growth based on the probability distribution of rock matrix pore characteristics described in S31 includes:

[0109] i. Reconstruct the pores of adjacent pixels of the bedding plane along the parallel bedding plane, so that the pores are connected to the bedding plane;

[0110] ii. Reconstructing pores into the matrix along the direction perpendicular to the bedding planes;

[0111] iii. Based on the pore morphology determined by the pore diameter probability distribution and the shape factor probability distribution, determine the pore growth morphology.

[0112] In some embodiments of the present invention, S32 includes:

[0113] i. Based on the number and growth direction of throats in the direction parallel to and perpendicular to bedding, determined by the probability distribution of throat coordination number, preliminary growth of throats is carried out.

[0114] ii. Based on the throat morphology determined by the probability distribution of throat diameter, tortuosity, and throat length, perform throat morphological growth.

[0115] Hereinafter, by way of example, a detailed description of the implementation of steps S1-S4 of the present invention is provided:

[0116] Step S11: Drill shale cylindrical cores of different diameters along the direction parallel to the bedding in a full-diameter core, with diameters of 2.5cm and 2mm respectively;

[0117] CT scans were performed on core samples of different diameters. A 2.5cm diameter core had a scan resolution of 13.6μm, and a 2mm diameter core had a scan resolution of 1μm. Specifically, for example... Figure 2 As shown, Figure 2 In the diagram, a is a schematic diagram of a rock core with a diameter of 2.5 cm, and b is a schematic diagram of a rock core with a diameter of 2 mm.

[0118] Step S12: Perform three-dimensional reconstruction on the scanning results to obtain the three-dimensional morphology of the bedding joints, specifically, as follows: Figure 3 As shown, Figure 3 In Figure a, the three-dimensional morphology of a core bedding fracture with a diameter of 2.5 cm is shown, and in Figure b, the three-dimensional morphology of a core bedding fracture with a diameter of 2 mm is shown.

[0119] Step S13: Based on the three-dimensional morphology of bedding fractures in cores of different diameters, extract the characteristic parameters of different bedding fractures, namely:

[0120] Large-sized bedding joints (joint width greater than 13.6μm) have a joint width of 28μm and a crack spacing of 5.2mm. Small-sized bedding joints (1μm < joint width < 13.6μm) have a joint width of 5μm and a crack spacing of 100μm.

[0121] Step S21: Based on the large-sized bedding fracture with a width of 28 μm and a fracture spacing of 5.2 mm obtained in step S13, and the small-sized bedding fracture with a width of 5 μm and a fracture spacing of 100 μm, determine that the number of bedding fractures of different sizes includes at least two types of bedding fractures. Considering the size limitations of the digital core, in this embodiment of the invention, exemplarily, a combination of one large-sized bedding fracture with a width of 28 μm and a fracture spacing of 5.2 mm, and two small-sized bedding fractures with a width of 5 μm and a fracture spacing of 100 μm is selected. The layout of this bedding fracture combination on the digital core is as follows:

[0122] A large-size bedding joint is set in the middle of the digital core, and then two small-size bedding joints are set on both sides of the large-size bedding joint according to the spacing of the small-size bedding joints.

[0123] Step S22: Construct a coordinate system for digital core reconstruction. For example, the present invention uses a rectangular coordinate system for digital core reconstruction, and uses the Z direction as the direction of the bedding fractures in the core. Combined with the number of bedding fractures determined in step S21, the present invention constructs a 500×500×n (x, y, z directions) three-dimensional array (n is the number of arrays in the z direction, determined according to the number of fractures to be reconstructed).

[0124] Step S23: Determine the value of n. Specifically, in this embodiment of the invention, for example, each array element represents a pixel, and the side length of each pixel of the matrix pore is 12nm. Because the size of the lamination seam is much larger than the size of the pore, in order to better couple the lamination seam and the matrix pore in subsequent steps, the side length of each pixel at the lamination seam position represents 1μm in the z direction and 12nm in the x and y directions. Then, based on the calculation of 1 large-size lamination seam and 2 small-size lamination seams in S21, the formula for calculating the number of arrays in the z direction is transformed from formula (1) to formula (2):

[0125] n=D1 / l1+2×D2 / l1+2×L1 / l2 (2)

[0126] In equation (2), D1 is the width of the large-size bedding joint, D2 is the width of the small-size bedding joint, L1 is the spacing between the small-size bedding joints, l1 is the pixel-represented length of the crack in the z-direction, and l2 is the pixel-represented length of the pore in the z-direction.

[0127] Substituting D1, D2, L1, l1 and l2 into equation (2), we get: 28 / 1 + 2 × 5 / 1 + 2 × 100 / 0.012 = 16705. Therefore, the digital core size is 500 × 500 × 16705.

[0128] Step S24: In this embodiment of the invention, exemplarily, the initial value is assigned to 1 (representing the shale mineral skeleton), and the pixel value at the bedding fracture position is assigned to 0 (representing the flow channel), thus completing the construction of the bedding fracture of the digital core. A schematic diagram of the construction is shown below. Figure 4 As shown.

[0129] The probability distribution of shale matrix pore characteristics described in step S3 is obtained by scanning electron microscope images of different core sections. The different core sections include core sections parallel to the bedding direction and core sections perpendicular to the bedding direction of the same core sample.

[0130] Specifically, the process of obtaining the probability distribution of shale matrix pore features through scanning electron microscope images of different core thin sections involves processing the original scanned images and calculating the probability distribution of shale matrix pore features based on the data displayed in the images obtained from the processing steps.

[0131] The processing steps of the original scanned image include grayscale processing, image binarization processing, noise reduction, smoothing processing, and segmentation processing. Specifically, grayscale processing, image binarization processing, noise reduction, smoothing processing, and segmentation processing adopt techniques well known in the art, which will not be elaborated here.

[0132] The original scanned image in the embodiments of the present invention is as follows: Figure 5 As shown, the black and white binarized image obtained by image binarization is as follows: Figure 6 As shown, Figure 6 In the diagram, black represents pores and white represents the mineral skeleton;

[0133] The image obtained after noise reduction and smoothing is shown below. Figure 7 As shown;

[0134] The schematic diagrams of the pores and throats obtained from the segmentation process are shown below. Figure 8 and Figure 9 As shown;

[0135] The process of calculating the probability distribution of shale matrix pore features based on the image display data obtained from the processing steps includes the calculation of the probability distribution of pore diameter, shape factor, throat diameter, throat length, tortuosity, and pore throat coordination number from the image features.

[0136] In an embodiment of the present invention, by way of example:

[0137] The pore diameter probability distribution is the proportion of pores of different diameters to the total number of pores;

[0138] The shape factor probability distribution is the ratio of the cross-sectional area of ​​the pores and channels to the square of the perimeter.

[0139] The probability distribution of throat diameter is the proportion of throats of different diameters to the total number of pores;

[0140] The probability distribution of throat length is the proportion of throats of different lengths to the total number of pores.

[0141] The tortuosity probability distribution is the ratio of the actual length of the seepage channel to the apparent length through the seepage medium, which can be expressed as the ratio of the actual length of the throat to the straight lengths at both ends of the throat.

[0142] The pore-throat coordination number probability distribution is the number of throats that connect to a single pore.

[0143] The above calculation process involves formulas for calculating pore diameter, average pore diameter, pore shape factor, average shape factor, throat diameter, average throat diameter, throat length, average throat length, throat tortuosity, average tortuosity, and average coordination number. These formulas are well known in the technical field and will not be elaborated upon here.

[0144] S31: Select the midpoint of the xy plane between adjacent pixels of each bedding fracture as the starting point for pore growth. Pore growth is then performed based on the probability distribution of shale matrix pore characteristics. Specifically:

[0145] i. Reconstruct the adjacent pixel pores of the bedding seam along the parallel bedding direction, so that the pores are connected to the bedding seam;

[0146] ii. Reconstructing porosity into the matrix along the direction perpendicular to the stratification;

[0147] iii. Based on the pore morphology determined by the pore diameter probability distribution and the shape factor probability distribution, determine the pore growth morphology.

[0148] S32. Throat growth is performed between the bedding fractures of the digital core, based on the probability distribution of shale matrix porosity characteristics. Specifically:

[0149] i. Based on the number and growth direction of throats in the direction parallel to and perpendicular to bedding, determined by the probability distribution of throat coordination number, preliminary growth of throats is carried out.

[0150] ii. Based on the throat morphology determined by the probability distribution of throat diameter, tortuosity, and throat length, perform throat morphological growth.

[0151] S33. Repeat the pore growth and throat growth steps until the pore determination function position reaches the boundary of the three-dimensional array in the direction of the layering fracture.

[0152] S34. Based on the completion of the throat growth step, a preliminary digital core model and the probability distribution of matrix pore characteristic parameters are obtained.

[0153] S35. Compare the probability distribution of pore characteristic parameters between the preliminary digital core model and the core sample;

[0154] S36. If the comparison result value exceeds the preset value, reconstruct the matrix pores until the comparison result value is within the preset value range, that is, complete the reconstruction of the matrix pores. For example, the preset value is 5%.

[0155] Compare the probability distribution of matrix pore characteristic parameters of the preliminary digital core model with the probability distribution of pore characteristic parameters of the core sample. If the error is greater than 5%, reconstruct the matrix pores until the error between the probability distribution of pore characteristic parameters of the digital core model and the probability distribution of pore characteristic parameters of the core sample is less than 5%.

[0156] S4: Based on the completion of the reconstruction of matrix porosity and channels, the digital core reconstruction is completed, that is, the final digital core obtained is as follows: Figure 10 As shown.

[0157] like Figure 11 As shown, the shale multi-scale digital core reconstruction system according to an embodiment of the present invention includes:

[0158] Module 1 for bedding fracture characteristic parameters: used to obtain bedding fracture characteristic parameters with different size distributions based on several rock cores of different diameters;

[0159] Module 2 for constructing bedding joints: used to construct bedding joints in digital cores based on bedding joint feature parameters with different size distributions;

[0160] Module 3 for reconstructing matrix porosity: used to reconstruct matrix porosity between bedding fractures in digital cores based on the probability distribution of shale matrix porosity characteristics;

[0161] Module 4: Completes the reconstruction based on matrix pores, and completes the digital core reconstruction.

[0162] like Figure 12 As shown, in some embodiments of the present invention, an electronic device is provided, the electronic device 300 including: a processor 301 coupled to a memory 302;

[0163] The memory 302 is used to store computer programs;

[0164] The processor 301 is configured to execute the computer program stored in the memory 302, so that the electronic device performs the method described in the above embodiments.

[0165] In some embodiments of the present invention, a computer-readable storage medium is provided that stores a program or instructions that, when executed on a computer, cause the computer to perform the methods described in the above embodiments.

[0166] According to embodiments of the present invention, the computer-readable storage medium may be a non-volatile computer-readable storage medium, such as including, but not limited to: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In the present invention, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, electronic device, or apparatus.

[0167] Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A multi-scale digital core reconstruction method for shale, characterized in that, include: Based on several rock cores of different diameters, characteristic parameters of bedding fractures with different size distributions were obtained; Based on the characteristic parameters of bedding fractures with different size distributions, bedding fractures in digital cores are constructed. Between the bedding fractures of digital cores, matrix pores and channels are reconstructed based on the probability distribution of characteristic parameters of shale matrix pores; Based on the completion of the reconstruction of matrix pores and channels, digital core reconstruction is completed.

2. The shale multi-scale digital core reconstruction method according to claim 1, characterized in that, The bedding fracture characteristic parameters with different size distributions obtained based on several rock cores of different diameters include: Scan several rock cores of different diameters using different resolutions; Based on the scanning results, a three-dimensional reconstruction is performed to obtain the three-dimensional morphology of the bedding joints; Based on the three-dimensional morphology of the bedding seams, feature parameters of the bedding seams are extracted.

3. The shale multi-scale digital core reconstruction method according to claim 2, characterized in that, The scanning was performed using a CT scanning device when scanning several rock cores of different diameters at different resolutions.

4. The shale multi-scale digital core reconstruction method according to claim 2, characterized in that, When scanning several cores of different diameters using different resolutions, the scanning resolution is selected based on the diameter of the core, according to the negative correlation between the scanning resolution and the diameter.

5. The shale multi-scale digital core reconstruction method according to claim 2, characterized in that, The characteristic parameters of the bedding joints include the bedding joint width, bedding joint porosity, and bedding joint spacing.

6. The shale multi-scale digital core reconstruction method according to claim 2, characterized in that, Several cores of different diameters originated from the same full-diameter core.

7. The shale multi-scale digital core reconstruction method according to claim 5, characterized in that, When drilling several cores of different diameters from the same full-diameter core, drill along the direction parallel to the bedding plane.

8. The shale multi-scale digital core reconstruction method according to claim 1, characterized in that, The construction of bedding fractures in digital cores based on bedding fracture characteristic parameters with different size distributions includes: Based on the characteristic parameters of bedding joints with different size distributions, the number of bedding joints of different sizes is determined; Constructing a digital core coordinate system; Based on the number of bedding joints, determine the number of arrays representing the direction of bedding joints in the constructed digital core coordinate system; The initial values ​​of the group elements of the three-dimensional array are assigned to complete the construction of the bedding fractures of the digital core.

9. The shale multi-scale digital core reconstruction method according to claim 8, characterized in that, When determining the number of bedding joints of different sizes, the combination of bedding joints of different sizes is determined based on the limitation of the digital core size.

10. The shale multi-scale digital core reconstruction method according to claim 9, characterized in that, The number of arrays representing the direction of the bedding plane is calculated according to the following formula: N=D1 / l1+D2 / l1+……+Dn / l1+L1 / l2+L2 / l2+……+Ln / l2 Where N is the number of arrays representing the direction of bedding seams, D1, D2, ..., Dn are the seam widths of bedding seams of different sizes, L1, L2, ..., Ln are the seam spacing between two adjacent bedding seams, l1 is the pixel length representing the direction of bedding seams, and l2 is the pixel length representing the matrix.

11. The shale multi-scale digital core reconstruction method according to claim 1, characterized in that, The probability distribution of the shale matrix pore characteristic parameters was obtained by scanning electron microscopy images of different core thin sections.

12. The shale multi-scale digital core reconstruction method according to claim 11, characterized in that, Different core sections include core sections parallel to the bedding direction of the same core sample and core sections perpendicular to the bedding direction of the same core sample.

13. The shale multi-scale digital core reconstruction method according to any one of claims 1-11, characterized in that, The probability distribution of shale matrix pore characteristic parameters includes a set of image feature probability distributions of pore diameter probability distribution, pore shape factor probability distribution, throat diameter probability distribution, throat length probability distribution, tortuosity probability distribution, and pore throat coordination number probability distribution.

14. The shale multi-scale digital core reconstruction method according to claim 1, characterized in that, The process of reconstructing matrix pores and throats between bedding fractures in digital cores based on the probability distribution of shale matrix pore characteristic parameters includes: Between the bedding fractures in the digital core, a point is selected on the plane of the adjacent bedding fracture, and pore growth is carried out based on the probability distribution of matrix pore diameter and pore shape factor. Throat growth is performed based on the probability distributions of throat diameter, throat length, tortuosity, and pore-throat coordination number. Repeat the pore growth and throat growth steps until the functional location of the pores reaches the boundary of the three-dimensional array representing the direction of the bedding fracture; Based on the completion of the pore and throat growth steps, a preliminary digital core model is obtained; Compare the probability distribution of matrix pore characteristic parameters in the preliminary digital core model with the probability distribution of pore characteristic parameters measured in the core samples; If the comparison result value exceeds the preset value, the matrix pores are reconstructed until the comparison result value is within the preset value range, thus completing the reconstruction of the matrix pores.

15. The shale multi-scale digital core reconstruction method according to claim 14, characterized in that, The process of pore growth based on the probability distribution of matrix pore diameter and the probability distribution of pore shape factor includes: Reconstruct the porosity of the matrix adjacent to the bedding joint along the parallel bedding direction; Pores are reconstructed into the matrix along the direction perpendicular to the stratification; Based on the pore morphology determined by the pore diameter probability distribution and the shape factor probability distribution, the pore growth morphology is determined.

16. The shale multi-scale digital core reconstruction method according to claim 14, characterized in that, Throat growth is performed based on the probability distributions of throat diameter, throat length, tortuosity, and pore-throat coordination number, including: Based on the probability distribution of throat coordination number, the number and growth direction of throats in the direction parallel to and perpendicular to bedding are determined, and the initial growth of throats is carried out. The morphological growth of the throat is carried out based on the throat morphology determined by the probability distribution of throat diameter, tortuosity, and throat length.

17. A shale multi-scale digital core reconstruction system, characterized in that, include: Module for characteristic parameters of bedding fractures: used to obtain characteristic parameters of bedding fractures with different size distributions based on several cores of different diameters; Module for constructing bedding fractures: used to construct bedding fractures in digital cores based on bedding fracture feature parameters with different size distributions; Reconstructing matrix pores and gills module: Used to reconstruct matrix pores and gills between bedding fractures in digital cores based on the probability distribution of shale matrix pore characteristics; Completion Module: Used to complete the reconstruction based on matrix pores, and to complete the digital core reconstruction.

18. The shale multi-scale digital core reconstruction system according to claim 17, characterized in that, The reconstructed matrix pores and canals module includes a reconstructed matrix pores submodule, a reconstructed matrix canals submodule, a repetition submodule, and a comparison submodule; The reconstructed matrix pore submodule is used to select a point on the plane of adjacent bedding fractures between bedding fractures in the digital core, and perform pore growth based on the probability distribution of matrix pore diameter and pore shape factor. The reconstructed matrix throat submodule is used to grow the throat based on the probability distribution of throat diameter, throat length, tortuosity, and pore-throat coordination number. The repeating submodule is used to repeat the pore growth and throat growth steps until the pore determination function position reaches the boundary of the three-dimensional array representing the bedding fracture direction; it is also used to obtain a preliminary digital core model based on the completion of the pore and throat growth steps. The comparison submodule is used to compare the probability distribution of matrix pore characteristic parameters of the preliminary digital core model with the probability distribution of pore characteristic parameters of the core sample measured in actual samples; it is also used to reconstruct the matrix pores according to the comparison result value exceeding the preset value until the comparison result value is within the preset value range, that is, to complete the reconstruction of the matrix pores.

19. An electronic device, characterized in that, include: Processor, the processor being coupled to memory; The memory is used to store computer programs; The processor is configured to execute the computer program stored in the memory to cause the electronic device to perform the method as described in any one of claims 1 to 16.

20. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a program or instructions that, when executed on a computer, cause the computer to perform the method as described in any one of claims 1 to 16.

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