A multi-scale stitching method and system for micro-aperture data based on digital core

Abstract

The present invention discloses a multi-scale stitching method and system for micro-pore data based on digital cores. The method comprises: performing dual-resolution multi-scale CT scanning experiments on core samples to obtain a CT core scanning data body at dual resolution; selecting typical regions for the CT core scanning data body at dual resolution, and performing pore data analysis; calculating the volume ratio coefficients of different pore data structures according to the selected typical regions; stitching the pore data obtained under different scans according to the volume ratio coefficients, thereby obtaining full-scale pore size distribution data. The present invention aims to solve the problem of stitching multi-scale CT scanning data, thereby obtaining a comprehensive characterization of the pore structure of dense cores; the invention provides a strong theoretical and technical support for the detailed and comprehensive evaluation of dense core reservoirs, especially unconventional reservoirs with dual media of pores and fractures, and provides a strong driving force for the efficient and accurate exploration and development of unconventional oil and gas.

Description

Technical Field

[0001] The invention relates to the field of digital core microscopic pore structure scanning analysis, and in particular to a multi-scale splicing method of micro-pore diameter data based on digital cores. Background Art

[0002] Digital core is the image of the core after X-ray scanning. The simulated core is obtained through computer inversion, modeling, and reconstruction. Its core modeling methods can be divided into two categories: physical experimental methods and numerical reconstruction methods. Physical experimental methods use high-precision instruments such as high-power optical microscopes, scanning electron microscopes, or CT imagers to obtain the plane image of the core, and then the plane image is reconstructed in three dimensions to obtain the digital core.

[0003] CT stands for Computed Tomography, which is a computer tomography technology. CT digital core applications play an increasingly important role in the analysis of geological reservoir cores in oil exploration and development. Its physical principle is based on the interaction between rays and matter. Different densities inside the core have different responses to X-rays. The high density of the rock skeleton has low X-ray transmittance, and the small pore density of the core has high X-ray transmittance. By performing a 360° full-scale scan of the sample, a series of two-dimensional projection images are obtained and three-dimensional reconstruction is performed to obtain a three-dimensional model of the rock sample and construct a digital core. In the process of reconstructing the digital core, the physical property characterization information of the core pores and pore throat network topology will be obtained, usually including parameters such as core pore radius, throat radius, pore throat connectivity, porosity, surface ratio, fracture porosity / width, open porosity and closed porosity. These parameters are used to evaluate the microscopic pore structure characteristics of the core, and the evaluation and characterization of the reservoir quality can be achieved more finely.

[0004] The existing digital core CT scanning and analysis technology only performs single data characterization. For example, a 1-micron resolution CT scan can only characterize the distribution of micropores (1 to 10 μm), and a 13-micron resolution CT scan can only characterize the distribution of macropores (larger than 10 μm). Therefore, the existing single-scale resolution data pore structure characterization has the defect of being incomplete.

[0005] However, dense cores such as coal rock, shale, mudstone, and volcanic rock usually have multi-scale pore-fracture dual medium characteristics. In this type of core reservoir, pores and fractures of multiple scales are developed at the same time. The pore radius is mostly distributed in the range of 1 to 10 microns, and the width of microfractures can reach tens or even hundreds of microns. However, the resolution of CT scanning is inversely proportional to the slice field of view. The field of view of the slice at a high-precision scanning resolution of 1 micron is only about 1mm, and it is impossible to effectively collect the structural information of macropores and microfractures; the field of view of the slice at a low-precision 13 micron resolution scanning can reach about 13mm, but pore data with a pore size less than 13μm cannot be obtained. If two different resolutions are used to scan dense cores, for example, a rock sample is scanned twice at a resolution of 1 micron and 13 microns respectively, and then two sets of quantitative data of pore and fracture structures at different scales are calculated respectively. Since the two sets of data independently represent the pore and fracture sizes at different scales, the same sample will obtain two very different pore and fracture data conclusions. Such results can only characterize the distribution characteristics of the pore size at each scale, and cannot obtain the distribution law of the pore size at all scales. This leads to the inability to achieve unified conclusions when interpreting and applying data and comparing different samples, which brings great difficulties to the promotion and application of digital core technology in unconventional reservoirs. The problem of splicing multi-scale data needs to be solved urgently. Summary of the invention

[0006] The present invention provides a multi-scale stitching method of micro-aperture data based on digital cores, comprising:

[0007] Double-resolution multi-scale CT scanning experiments were performed on the core samples to obtain the CT core scanning data volume at double resolution.

[0008] Select typical areas from the dual-resolution CT core scan data volume and perform pore data analysis;

[0009] Calculate the volume ratio coefficient of different pore data structures according to the selected typical area;

[0010] The pore data obtained under different scans are spliced ​​according to the volume scale coefficient to obtain the full-scale pore size distribution data.

[0011] As described above, a multi-scale stitching method of micropore data based on digital cores is described, wherein, when evaluating the multi-scale pore structure of a sample, a professional CT scanning instrument is used to perform multi-scale CT scanning experiments on the sample with a resolution of 1 micron and 13 microns to obtain a 1 micron CT core scanning data volume and a 13 micron CT core scanning data volume.

[0012] As described above, a multi-scale stitching method of micropore data based on digital cores is described, wherein a 1-micron CT core scan data volume is used to identify pore structures with a radius of 1 to 10 microns, and a 13-micron CT core scan data volume is used to identify pore structures with a radius of >10 microns.

[0013] As described above, a multi-scale stitching method of micropore data based on digital core is used, wherein the maximum sphere method is used for pore calculation, wherein the maximum sphere method is to fill a series of spheres of different sizes into the core pore space, and there is a connection relationship between the filling spheres of each size according to the radius from large to small. The pore structure inside the entire core will be characterized by overlapping and containing sphere strings, and the establishment of "pores" and "throats" in the pore network structure is completed by finding the local maximum sphere and the minimum sphere between the two maximum spheres in the sphere string, thereby forming a "pore-throat-pore" pairing relationship; finally, the entire sphere string structure is simplified into a pore network structure model with "pores" and "throats" as units, and the corresponding pore throat quantitative data are obtained through the ball-and-stick model.

[0014] A multi-scale stitching method for micropore data based on digital cores as described above, wherein the volume ratio coefficient is obtained by dividing the volumes of typical areas of two resolutions.

[0015] As described above, a multi-scale stitching method for micropore data based on digital cores is used, wherein the frequency, volume and surface area ratio of pores in the pore size range of (i to i+1) μm are calculated according to the volume proportion coefficient, the number, volume and surface area of ​​pores in the pore size range of (i to i+1) μm, the total number, total volume and total surface area of ​​pores in the pore size range of 1 to 10 μm, and the total number, total volume and total surface area of ​​pores with a pore size greater than 10 μm, wherein i=0, 1, 2, 3, 4, 5, 6, 7, 8, 9.

[0016] As described above, a multi-scale stitching method for micropore data based on digital cores is used, wherein the frequency, volume and surface area ratio of pores in the pore size range of (m-10~m)μm are calculated according to the volume proportion coefficient, the number, volume and surface area values ​​of pores with a pore size of (m-10~m)μm, the total number, total volume and total surface area values ​​of pores with a pore size of 1~10μm, and the total number, total volume and total surface area values ​​of pores with a pore size greater than 10μm, wherein m=20, 30, 40, 50, 60, 70, 80, 90, 100.

[0017] The present invention also provides a multi-scale stitching system for micro-aperture data based on digital cores, the system comprising a CT scanning device and a data processing device, the CT scanning device performs dual-resolution multi-scale CT scanning experiments on core samples respectively, and the data processing device executes any one of the multi-scale stitching methods for micro-aperture data based on digital cores described above.

[0018] The present invention also provides a computer storage medium, characterized in that it comprises: at least one memory and at least one processor;

[0019] The memory is used to store one or more program instructions;

[0020] A processor is used to run one or more program instructions to execute any of the above-mentioned methods for multi-scale stitching of micro-aperture data based on digital cores.

[0021] The beneficial effects achieved by the present invention are as follows: The present invention aims to solve the problem of splicing multi-scale CT scanning data, thereby obtaining a comprehensive characterization of the pore structure of dense cores. The invention provides a strong theoretical and technical support for the detailed and comprehensive evaluation of dense core reservoirs, especially unconventional reservoirs with dual media of pores and fractures, and provides a strong impetus for the efficient and accurate exploration and development of unconventional oil and gas. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0023] Figure 1 This is a flow chart of a multi-scale stitching method of micro-aperture data based on digital cores provided in the first embodiment of the present invention;

[0024] Figure 2 It is the 1-10 micron pore size distribution map obtained by 1 micron resolution CT scan;

[0025] Figure 3 It is the distribution map of pore sizes >10 μm obtained by CT scanning with a resolution of 13 μm;

[0026] Figure 4 It is the multi-scale splicing feature map of aperture distribution;

[0027] Figure 5 It is the grayscale image of microcrack development characteristics of different coal samples obtained by CT scanning of samples A and B with different resolutions;

[0028] Figure 6 and Figure 7This is a typical distribution spectrum of samples A and B before and after splicing. DETAILED DESCRIPTION

[0029] The following is a clear and complete description of the technical solutions in the embodiments of the present invention in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are 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 those skilled in the art without creative work are within the scope of protection of the present invention.

[0030] Embodiment 1

[0031] like Figure 1 As shown, the first embodiment of the present invention provides a multi-scale stitching method of micro-aperture data based on digital cores, comprising:

[0032] Step 110, performing dual-resolution multi-scale CT scanning experiments on the core samples respectively to obtain a dual-resolution CT core scanning data volume;

[0033] When evaluating the multi-scale pore structure of a sample, first use a professional CT scanning instrument to perform multi-scale CT scanning experiments on the sample (it is recommended to use a standard core plunger with a diameter of one inch) at 1 micron and 13 micron resolutions. The 1 micron resolution CT scan obtains a core three-dimensional structure with a field of view size of 1mm*1mm*1mm, which can mainly identify pore structures with a radius of 1 to 10 microns, and obtains a CT core scanning data volume at a resolution of 1 micron; the 13 micron resolution CT scan obtains a core three-dimensional structure with a field of view size of 13mm*13mm*13mm, which can mainly identify pore structures with a radius of >10 microns, and obtains a CT core scanning data volume at a resolution of 13 microns, for example, the CT core scanning data volume is a core projection image; the two sets of structural data can achieve complementarity in scale, which is the scanning resolution preferably adopted by the method of the present application.

[0034] Step 120, selecting typical regions from the CT core scan data volume at dual resolutions, and performing pore data analysis;

[0035] Specifically, the sizes of the regions selected for cores with different heterogeneity characteristics are different. To ensure typical representativeness: for core slices with strong heterogeneity, a larger region should be selected to ensure representativeness; for core slices with relatively uniform pore distribution, a smaller region can be appropriately selected to improve analysis efficiency.

[0036] In the embodiment of the present application, typical region selection is performed on the CT core scan data volume at dual resolution, specifically including the following sub-steps:

[0037] Step 121, reconstructing the CT core scan projection at dual resolution by slicing to obtain two-dimensional grayscale slices;

[0038] Preferably, professional projection data volume reconstruction software is used to perform three-dimensional reconstruction of the scanning projection using the Feldkamp algorithm. This algorithm regards cone beam rays as a stack of fan beam rays with different inclination angles along the Z-axis direction. The data reconstruction on the central plane belongs to the precise reconstruction of fan beam scanning. For the reconstruction of non-central planes, the fan beam reconstruction is corrected and then the precise reconstruction is completed.

[0039] Step 122, using a median filtering method to perform noise reduction processing on the two-dimensional grayscale slice;

[0040] Median filtering is a nonlinear smoothing filtering technique that can overcome the blurring problem caused by linear filtering under certain conditions. A two-dimensional grayscale slice can be viewed as a set of two-dimensional grayscale value matrices, such as the following two-dimensional grayscale value matrix:

[0041]

[0042] The grayscale values ​​of this group are sorted from small to large as 12, 14, 14, 15, 16, 17, 18, 19, 20, where 16 is the median value, and the grayscale values ​​in this area are replaced by 16. This method can make each pixel value in each grayscale slice very close to the surrounding (neighborhood) pixel value, so that those isolated abnormal grayscale noise points can achieve a good denoising effect.

[0043] Step 123, selecting a typical area of ​​the slice after the noise reduction process;

[0044] Set the typical area volume size of the grayscale slice scanned with a resolution of 1 micron to V1, the pixel size is X1*Y1*Z1, and the typical area volume size of the grayscale slice scanned with a resolution of 13 microns is V 13 , pixels are X 13 *Y 13 *Z 13 , where V1=1 3 ×(number of pixels in the X direction X1*number of pixels in the Y direction Y1*number of pixels in the Z direction Z1), V 13 =13 3 ×(Number of pixels in X direction X 13 * Number of pixels in Y direction Y 13 * Number of pixels in Z direction Z 13 ).

[0045] Specifically, the maximum sphere method is used to analyze pore data. The "maximum sphere method" is to fill a series of spheres of different sizes into the pore space of the three-dimensional core image. The filling spheres of each size are connected according to the radius from large to small. The pore structure inside the entire core will be characterized by overlapping and containing sphere strings. The "pores" and "throats" in the pore network structure are established by finding the local maximum sphere and the minimum sphere between the two largest spheres in the sphere string, thereby forming a "pore-throat-pore" pairing relationship. Finally, the entire ball string structure is simplified into a pore network structure model with "pores" and "throats" as units, and the corresponding pore throat quantitative data are obtained through the ball-and-stick model;

[0046] For example, the calculated results of two sets of pore size distribution data are shown in Tables 1 and 2 below:

[0047] Table 1 1 micron resolution scanning pore size distribution data table

[0048]

[0049]

[0050] Table 2 13 micron resolution scanning pore size distribution data table

[0051] Pore ​​size range μm Quantity / pcs Volume / μm3 Surface area / μm2 10～20 23547 394897518 52725153.25 20～30 17897 1039839956 115026790.7 30～40 4709 756541241.4 69016332.53 40～50 763 269211554.7 21268330.53 50～60 253 174186922.9 11995063.24 60～70 183 207502227.9 12946409.47 70～80 172 305400533 17590958.81 80～90 144 372962666 20040843.95 90～100 111 391979896.5 20047704.88 100+ 172 1251446171 55666337.05 total 47951 5163968687 396323924.4

[0052] Figure 2 It is the 1-10 micron pore size distribution map obtained by 1 micron resolution CT scan; Figure 3 This is a pore size distribution map of >10 μm obtained by 13 μm resolution CT scan.

[0053] Return to see Figure 1 , step 130, calculating the volume ratio coefficients of different pore data structures according to the selected typical areas;

[0054] Specifically, the volume ratio coefficient K is obtained by dividing the typical area volumes of the two resolutions, that is, K = V 13 / V1, where V 13 =13 3 ×(number of pixels in the X direction X1*number of pixels in the Y direction Y1*number of pixels in the Z direction Z1), V1=1 3 ×(X direction pixel number X1*Y direction pixel number Y1*Z direction pixel number Z1). For example, the pixels of the typical area of ​​the selected 13 micron resolution scan grayscale slice are 658*684*671, and the pixels of the typical area of ​​the selected 1 micron resolution scan grayscale slice are 481*519*460, that is,

[0055] Step 140, splicing the pore data obtained under different scans according to the volume scale coefficient, so as to obtain full-scale pore size distribution data;

[0056] Among them, the core pore distribution data information of more than 10 microns can be obtained through 13 micron resolution CT scanning, and the pore distribution of 1 to 10 microns can be obtained through 1 micron resolution CT scanning. The data results of the two can be connected to characterize the distribution characteristics of the sample within the micron-level full pore size range. Compared with conventional methods such as mercury injection and nuclear magnetic resonance, multi-scale digital core technology reduces the artificial destruction of multiple pores during the experiment, and the pore data obtained are more direct and objective, and more realistically reflect the distribution of coal rock pores in the original state.

[0057] In the embodiment of the present application, the pore data obtained under dual-resolution scanning is spliced. The data splicing process needs to normalize the fields of view under two different resolutions to the same field of view size. The specific calculation method is as follows:

[0058]

[0059]

[0060]

[0061] Among them, f i 、v i and i Respectively represent the pore frequency, volume and surface area ratio in the pore size range of (i~i+1)μm, i=0,1,2,3,4,5,6,7,8,9, n i～i+1 、v i～i+1 、s i～i+1 They represent the number, volume and surface area of ​​pores in the range of (i~i+1)μm, respectively. K represents the volume ratio coefficient of the two scale data bodies. N 1总 、V 1总 , S 1总 Respectively represent the total number, total volume and total surface area of ​​pores with a pore size of 1 to 10 μm, N 13总 、V 13总 , S 13总 They represent the total number, total volume and total surface area of ​​pores with a pore size greater than 10 μm, respectively.

[0062]

[0063]

[0064]

[0065] Among them, F m 、Vm and S m Indicates the frequency, volume and surface area ratio of pores with a pore size in the range of (m-10~m)μm, m=20,30,40,50,60,70,80,90,100, N m-10～m 、V m-10～m , S m-10～m Respectively represent the number, volume and surface area of ​​pores with a pore size of (m-10~m) μm.

[0066] If the 1 micron scan data contains data larger than 10 microns, then this part of the data is added to N m-10～m 、V m-10～m and S m-10～m The specific formula is as follows:

[0067]

[0068]

[0069]

[0070] According to the above formulas (1) to (9), the number of pores, volume and surface area ratio of each interval can be calculated, that is:

[0071]

[0072]

[0073] …

[0074]

[0075]

[0076]

[0077] …

[0078]

[0079] Similarly, the data concatenation results of volume V and surface area S can be obtained, as shown in Table 3 below:

[0080] Table 3 Multi-scale splicing data results

[0081]

[0082]

[0083] Figure 4 This is a multi-scale stitching feature map of aperture distribution drawn based on the multi-scale stitching data results.

[0084] The present invention was applied to two coal rock samples of different types. After CT scanning experiments, it was found that sample A had obvious pore-crack dual medium, while the other sample B did not have a microcrack structure. Figure 5 As shown, the white and gray parts are the rock skeleton, and the black parts are the rock pores and cracks: It can be seen from the figure that sample A not only develops microcracks, but also develops microcracks at two scales. The cracks have multi-scale characteristics, with both micron cracks and hundred-micron cracks. Sample B does not develop microcracks at both scanning scales. The two have obvious differences in pore-crack structure.

[0085] Figure 6 and Figure 7 The typical distribution spectrum of sample A and sample B before and after splicing using the technical solution of the present invention. The two sets of data of two samples were spliced ​​using the present invention, and it was found that after splicing, not only the pore radius distribution characteristics of the full micron scale were obtained, but also the pore size distribution had the typical characteristics of multiple peaks. Analysis shows that the first peak of sample A after splicing mainly represents pores with a radius of 1 to 10 microns; the second peak represents microcracks with a radius of 10 to 30 microns; and the third peak represents hundred-micron cracks with a radius greater than 100 microns. After splicing, the first peak of sample B mainly represents pores with a radius of 1 to 10 microns, the second peak represents a peak without micron cracks, and the third peak represents a peak without hundred-micron cracks. This shows that the multi-scale joint map obtained by the method of the present invention can well reflect the characteristics of multi-scale pore = fracture development in coal rock samples, and the characteristic pore size map is more conducive to the comprehensive evaluation and classification of complex and multi-scale unconventional oil and gas reservoirs. This greatly improves the application effect of digital core technology in the field of geological exploration, especially in the exploration and development of unconventional oil and gas, and provides strong theoretical support for the efficient exploration and exploitation of clean energy such as coalbed methane and shale gas in the country.

[0086] Corresponding to the above embodiment, an embodiment of the present invention provides a computer-readable storage medium, which contains one or more program instructions, and the one or more program instructions are used by a processor to execute a multi-scale stitching method of micropore data based on digital cores.

[0087] The embodiment disclosed in the present invention provides a computer-readable storage medium, in which computer program instructions are stored. When the computer program instructions are executed on a computer, the computer executes a multi-scale stitching method of micro-aperture data based on digital cores.

[0088] In the embodiment of the present invention, the processor may be an integrated circuit chip having the ability to process signals. The processor may be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0089] The methods, steps and logic block diagrams disclosed in the embodiments of the present invention can be implemented or executed. The general processor can be a microprocessor or the processor can also be any conventional processor, etc. The steps of the method disclosed in the embodiments of the present invention can be directly embodied as a hardware decoding processor for execution, or can be executed by a combination of hardware and software modules in the decoding processor. The software module can be located in a mature storage medium in the field such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory or an electrically erasable programmable memory, a register, etc. The processor reads the information in the storage medium and completes the steps of the above method in combination with its hardware.

[0090] The storage medium may be a memory, which may be, for example, a volatile memory or a nonvolatile memory, or may include both volatile and nonvolatile memory.

[0091] Among them, the non-volatile memory can be a read-only memory (ROM), a programmable ROM (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or a flash memory.

[0092] The volatile memory may be a random access memory (RAM) which is used as an external cache. By way of example and not limitation, many forms of RAM are available, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate synchronous DRAM (DDRSDRAM), enhanced synchronous DRAM (ESDRAM), synchronous link DRAM (SLDRAM), and direct RAM bus DRAM (DRRAM).

[0093] The storage media described in the embodiments of the present invention are intended to include, but are not limited to, these and any other suitable types of memory.

[0094] Those skilled in the art will appreciate that in one or more of the above examples, the functions described in the present invention can be implemented using a combination of hardware and software. When software is used, the corresponding functions can be stored in a computer-readable medium or transmitted as one or more instructions or codes on a computer-readable medium. Computer-readable media include computer storage media and communication media, wherein communication media include any media that facilitates the transmission of computer programs from one place to another. Storage media can be any available media that can be accessed by general or special-purpose computers.

[0095] The specific implementation methods described above further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific implementation method of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made on the basis of the technical solution of the present invention should be included in the scope of protection of the present invention.

Claims

1. A multi-scale stitching method for micro-aperture data based on digital core, characterized in that: include: Double-resolution multi-scale CT scanning experiments were performed on the core samples to obtain the CT core scanning data volume at double resolution. Select typical areas from the dual-resolution CT core scan data volume and perform pore data analysis; Calculate the volume ratio coefficient of different pore data structures according to the selected typical area; The pore data obtained under different scans are spliced ​​according to the volume scale coefficient to obtain the full-scale pore size distribution data; According to the volume proportion coefficient, the number, volume and surface area of ​​pores in the range of i~i+1μm, the total number, total volume and total surface area of ​​pores in the range of 1~10μm, and the total number, total volume and total surface area of ​​pores with a pore size greater than 10μm, the frequency, volume and surface area of ​​pores in the range of i~i+1μm are calculated, where i=0,1,2,3,4,5,6,7,8,9; According to the volume proportion coefficient, the number, volume and surface area of ​​pores with a pore size of m-10~mμm, the total number, total volume and total surface area of ​​pores with a pore size of 1~10μm, and the total number, total volume and total surface area of ​​pores with a pore size greater than 10μm, the frequency, volume and surface area ratio of pores with a pore size in the range of m-10~mμm are calculated, where m=20, 30, 40, 50, 60, 70, 80, 90, 100.

2. A multi-scale stitching method for micropore data based on digital core according to claim 1, characterized in that: When evaluating the multi-scale pore structure of a sample, a professional CT scanning instrument is used to perform multi-scale CT scanning experiments on the sample at 1 micron and 13 micron resolutions to obtain 1 micron CT core scanning data volumes and 13 micron CT core scanning data volumes.

3. A multi-scale stitching method for micropore data based on digital core according to claim 2, characterized in that: The 1-micron CT core scan data volume is used to identify pore structures with a radius of 1 to 10 microns, and the 13-micron CT core scan data volume is used to identify pore structures with a radius of >10 microns.

4. The multi-scale stitching method of micropore data based on digital core according to claim 1, characterized in that: The maximum sphere method is used for pore calculation, in which a series of spheres of different sizes are filled into the core pore space. The filling spheres of different sizes are connected according to the radius from large to small. The pore structure inside the entire core will be characterized by overlapping and contained sphere strings. The pores and throats in the pore network structure are established by finding the local maximum sphere and the minimum sphere between the two largest spheres in the sphere string, thereby forming a pore-throat-pore pairing relationship; finally, the entire sphere string structure is simplified into a pore network structure model with pores and throats as units, and the corresponding pore throat quantitative data are obtained through the ball-and-stick model.

5. The multi-scale stitching method of micro-aperture data based on digital core according to claim 1, characterized in that: The volume scaling factor is obtained by dividing the typical area volumes of the two resolutions.

6. A multi-scale stitching system for micro-aperture data based on digital core, characterized in that: The system includes a CT scanning device and a data processing device. The CT scanning device performs dual-resolution multi-scale CT scanning experiments on core samples respectively, and the data processing device executes a multi-scale stitching method of micro-aperture data based on digital cores as described in any one of claims 1 to 5.

7. A computer storage medium, characterized in that: include: at least one memory and at least one processor; The memory is used to store one or more program instructions; A processor, used to run one or more program instructions to execute a multi-scale stitching method of micro-aperture data based on digital cores as described in any one of claims 1 to 5.

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