Multi-scale digital core construction method, device, equipment and medium

Abstract

The invention discloses a multi-scale digital core construction method, device and equipment and a medium, and relates to the technical field of reservoir logging identification. Digital cores of carbonate reservoirs are constructed on different scales through a Markov chain Monte Carlo method and mercury injection curve data; the carbonate rock digital cores are scaled through expansion and corrosion algorithms, so that Boolean superposition can be carried out after the scale phases of the digital cores are unified, and finally, proper multi-scale digital cores are obtained; in the process, by adjusting the growth rate and path optimization of a pore skeleton, pore size distribution gradually approaches mercury injection curve target distribution, and in the reconstruction process, the range of the pore size of the node is limited, so that the integrity and connectivity of the pore structure are ensured, the microscopic pore structures of hole type, crack type and hole type in the rock are accurately displayed, and the rock quality is improved. And generating a multi-scale digital core with complete mineral distribution and pore structure through scale adjustment and Boolean superposition.

Description

Technical Field

[0001] The present invention relates to the technical field of reservoir logging identification, and in particular to a multi-scale digital core construction method, device, equipment and medium. Background Art

[0002] The gas production capacity and recovery rate of reservoirs with different pore types vary greatly, and the extent to which seepage characteristics affect gas reservoir development is unclear. Therefore, targeted research on the influence of seepage characteristics and depletion development characteristics in different types of reservoirs can provide a theoretical basis for well deployment, capacity analysis and production plan adjustment. Regarding the pore structure, seepage characteristics and depletion development characteristics of gas reservoirs, relevant research by domestic and foreign scholars is mostly focused on low-permeability-tight gas, shale gas reservoirs, or carbonate gas reservoirs of a single pore type, and the pertinence and completeness still need to be improved. Affected by multiple pore structures and high temperature and high pressure formation conditions, the seepage characteristics and depletion development laws of deep carbonate gas reservoirs have certain particularities, and conventional knowledge and empirical conclusions are not fully applicable.

[0003] Therefore, it is of great significance to conduct in-depth research on the relevant seepage mechanism based on the pore structure characteristics of carbonate reservoir gas. Carbonate reservoir gas refers to natural gas stored in carbonate rocks. Carbonate rocks are sedimentary rocks composed of carbonate minerals (mainly calcite and dolomite). Carbonate reservoirs are the main reservoirs of oil and gas reservoirs, with large reserves, high production, and easy formation of large oil and gas fields. At the same time, they have strong heterogeneity in reservoir properties and diverse reservoir types. The reservoir pore structure types include primary pores, dissolution pores, fractures, caves, etc.

[0004] At present, the research on the reserves of carbonate reservoir gas fields is mainly carried out by studying the pore structure characteristics and related seepage mechanisms of carbonate rocks to characterize the oil and gas volume of carbonate reservoirs; at present, numerical reconstruction method and physical experimental scanning method are usually used to study the pore structure characteristics of carbonate rocks. The physical experimental scanning method usually includes CT scanning method, sequential imaging method, focused scanning method, scanning electron microscope and other methods, but this type of method is subject to the limitation of instrument resolution and it is difficult to identify complex small pore structures.

[0005] The emergence of numerical reconstruction method has solved the problems existing in physical experimental scanning method to a certain extent. The numerical reconstruction method is based on the two-dimensional image of core slices to identify the pore or particle information therein, and then construct a digital core through simulation method. However, due to the development of carbonate reservoirs with complex pore-type, fracture-type, and vug-type pore structures, and the pore-type, fracture-type, and vug-type pores show typical heterogeneous characteristics, making it difficult to reconstruct the true microstructure inside the rock by this method. Summary of the invention

[0006] The embodiments of the present invention provide a multi-scale digital core construction method, device, equipment and medium, which can solve the problem in the prior art that the current methods are difficult to reconstruct the real microstructure inside the rock.

[0007] The embodiment of the present invention provides a multi-scale digital core construction method, comprising the following steps: Obtain CT scan images of different scales of each reservoir in carbonate oil and gas reservoirs and the corresponding mercury injection curve experimental data of each reservoir; Based on CT scan images of different scales, the Markov Chain Monte Carlo method (MCMC) is used to construct pore frameworks of different scales, and the mercury injection curve experimental data of each reservoir is used to physically constrain the constructed pore framework to limit the pore growth rate and growth path, and obtain digital cores of micropores, fracture-cavity and fracture-pore carbonate rocks of different scales that conform to the pore size distribution in the mercury injection curve experiment; The microporous, fracture-cavity and fracture-pore carbonate digital cores are expanded and eroded to unify their scales; the unified-scaled microporous, fracture-cavity and fracture-pore carbonate digital cores are Boolean superimposed to obtain multi-scale carbonate digital cores.

[0008] Preferably, the step of obtaining CT scan images of different scales of each reservoir in the carbonate oil and gas reservoir and mercury injection curve experimental data corresponding to each reservoir includes: Obtaining a core sample from the target reservoir, cleaning the core sample to remove contaminants in the pores, and placing the sample in a vacuum drying oven for drying; The dried sample is placed in a mercury injection chamber, and mercury is gradually injected under low pressure. As the pressure increases, the amount of mercury intrusion and the corresponding capillary pressure are recorded to obtain small-scale mercury injection curve experimental data. A CT scanning device is used to scan and output two-dimensional tomographic images of multiple core samples to obtain reservoir CT scanning images of different scales of each reservoir in the carbonate oil and gas reservoir.

[0009] Preferably, the limiting pore growth rate and growth path comprises: Extracting capillary pressure from mercury injection curve experimental data P and the corresponding cumulative mercury volume V Hg According to the Washburn equation, the capillary pressure P Convert to aperture r , the transformation equation is: ; in: r represents the pore throat radius; γ represents the surface tension of mercury; θrepresents the contact angle of mercury; P Indicates capillary pressure; Divide the pore size range into multiple intervals, count the pore ratio in each interval, and obtain the pore size distribution histogram D MIP , the pore size distribution histogram D MIP Normalize to a probability distribution P MIP ( r ), as the target constraint condition for the growth of the pore skeleton; the probability distribution is expressed as: ; By adjusting the growth process of the pore framework, the pore size distribution gradually approaches the target distribution of the mercury injection curve. P MIP ( r ) ; Define the growth rate of the pore skeleton nodes according to the pore size ratio in the target distribution g ( r ), the growth equation is: ; in: g ( r ) represents a node r Growth rate; During the growth process, the maximum aperture r of the node is limited max , ensuring that it does not exceed the upper limit of the target distribution; on the pore skeleton network, the pore growth path is optimized by the Markov Chain Monte Carlo method MCMC: each node of the pore skeleton network constitutes a state, and the node includes the pore size and position x, y, z; according to the Metropolis criterion, the candidate growth path is accepted or rejected, and the equation is expressed as: .

[0010] Preferably, the method of unifying the scales of micropore, fracture-cavity type and fracture-pore type carbonate digital cores includes: Each digital core is represented by a 2D slice or a 3D volume image, where pixels 2D or voxels 3D correspond to a region in physical space; Assuming that 1 represents the pore or crack area and 0 represents the matrix area, each layer image in the depth direction is extracted as a two-dimensional binary image; according to the unified standard, the target pixel scale is determined S target , extract the corresponding original pixel scale from the input digital core data S original , get the zoom ratio R : ; like R >1, perform expansion operation; if R<1, perform corrosion operation; if R >1, the pore or fracture area of ​​the digital core is expanded using the morphological dilation operator, and the expansion equation is: ; in: A represents the binary image of the input digital core; B Represents the structural element SE; D ( A ) represents the expanded image; specifically, the pore area of ​​the digital core is operated pixel by pixel, and all adjacent pixels are marked as pores; if R <1, the pore or fracture area of ​​the digital core is filtered out using the morphological corrosion operator, and the filtering equation is: ; in: A represents the binary image of the input digital core; B Represents the structural element SE; E ( A ) represents the image after corrosion; the pore area of ​​the digital core is operated pixel by pixel, the edge pixels are removed, and the area completely contained by the structural element is retained.

[0011] Preferably, the Boolean superposition of the micropore, fracture-cavity and fracture-pore carbonate digital cores after unifying the scale includes: The digital cores of microporous carbonate rocks and fracture-cavity carbonate rocks are Boolean superimposed, and the matrix part of the fracture-cavity core is filled with micropores to retain the connectivity between mesoscale pores and fractures. The superposition equation is expressed as: ; in: A Represents the binary volume data of microporous core, B Represents the binary volume data of fracture-cavity core, C Represents the binary volume data of fracture-pore core; In the results R ( x , y , z ), if any input is 1, the output is 1, which is a pore; otherwise, it is 0, which is a matrix; The results of Boolean superposition of the digital core of fracture-pore carbonate rock, the digital core of microporous carbonate rock and the digital core of fracture-cavity carbonate rock are superimposed, and the large-scale fractures of fracture-cavity type cover the overall pore structure of the former two. The superposition equation is: ; In the results R (x , y , z ), if any input is 1, the output is 1, which is a pore; otherwise, it is 0, which is a matrix; the final R multi—scale It is a multi-scale carbonate digital core.

[0012] The embodiment of the present invention further provides a multi-scale digital core construction device, comprising: Data module, used to obtain CT scan images of different scales of each reservoir of carbonate oil and gas reservoirs and experimental data of mercury injection curves corresponding to each reservoir; The processing module is used to construct pore skeletons of different scales based on CT scan images of different scales using the Markov Chain Monte Carlo method MCMC, and to physically constrain the constructed pore skeletons using the mercury injection curve experimental data corresponding to each reservoir to limit the pore growth rate and growth path, and obtain digital cores of micropores, fracture-cavity type and fracture-pore type carbonate rocks of different scales that conform to the pore size distribution in the mercury injection curve experiment; The unified module is used to perform expansion and corrosion operations on the digital cores of microporous, fracture-cavity and fracture-pore carbonate rocks to unify the scales of the digital cores of microporous, fracture-cavity and fracture-pore carbonate rocks; the unified-scale digital cores of microporous, fracture-cavity and fracture-pore carbonate rocks are Boolean superimposed to obtain multi-scale digital cores of carbonate rocks.

[0013] An embodiment of the present invention further provides an electronic device, including a memory and a processor; The memory is used to store computer programs; The processor is used to implement the steps of the multi-scale digital core construction method as described above when executing the computer program stored in the memory.

[0014] An embodiment of the present invention further provides a computer-readable storage medium for storing a computer program, which, when executed by a processor, implements the steps of the multi-scale digital core construction method as described above.

[0015] The embodiments of the present invention provide a multi-scale digital core construction method, device, equipment and medium. Compared with the prior art, the beneficial effects thereof are as follows: The present invention uses the Markov chain Monte Carlo method MCMC and mercury injection curve data to construct digital cores of microporous, fracture-cave and fracture-pore carbonate reservoirs at different scales, and on this basis, the digital cores of carbonate rocks of various scales are scaled by expansion and corrosion algorithms, so that the scales of each digital core can be unified and Boolean superposition can be performed, and finally a suitable multi-scale digital core is obtained. In this process, the Markov chain Monte Carlo method MCMC simulates the random reconstruction generation process of the digital core, and in the simulation and reconstruction generation, the mercury injection curve experimental data is used to limit the growth rate and growth path of the pore skeleton, so that the simulated and reconstructed pore skeleton conforms to the pore size distribution in the mercury injection curve experiment, so as to obtain real microporous, fracture-cave and fracture-pore carbonate digital cores of different scales, accurately showing the microscopic pore structure of the pore type, fracture type and pore type inside the rock, thereby reconstructing a multi-scale digital core reflecting the real structure inside the rock.

[0016] Moreover, after obtaining digital cores of microporous, fracture-cavity and fracture-pore carbonate rocks of different scales, the present invention unifies the scales of the digital cores of microporous, fracture-cavity and fracture-pore carbonate rocks of different scales through corrosion and expansion, and solves the problem of inconsistent pixel scales in different digital cores by morphological means, and finally performs Boolean superposition to generate multi-scale digital cores with complete mineral distribution and pore structure, which has the advantages of high timeliness, low cost and multi-scale, and can further provide reference significance for the formulation of oil and gas reservoir development plans. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 A schematic diagram of the overall process of a multi-scale digital core construction method provided by an embodiment of the present invention; Figure 2 A schematic diagram of CT scanning results of a Sinian gas reservoir according to a multi-scale digital core construction method provided in an embodiment of the present invention; Figure 3 A schematic diagram of mercury injection curve data of a Sinian gas reservoir in a multi-scale digital core construction method provided in an embodiment of the present invention; (a) is mercury injection curve data; (b) is the pore size distribution structure of the mercury injection curve; Figure 4 A schematic diagram of carbonate pore-type digital core reconstruction results of a multi-scale digital core construction method provided in an embodiment of the present invention; Figure 5 A schematic diagram of a fracture-cavity type digital core reconstruction result of a multi-scale digital core construction method provided in an embodiment of the present invention; (a) is a fracture-cavity type pore result reconstruction result; (b) is a fracture-cavity type reconstruction result after corrosion and expansion operations; Figure 6A schematic diagram of a fracture-pore type digital core reconstruction result of a multi-scale digital core construction method provided in an embodiment of the present invention; (a) is a CT scan image of a fracture-pore type reservoir; (b) is a result after corrosion and expansion operations; Figure 7 A schematic diagram of a multi-scale digital core of a Sinian carbonate oil and gas reservoir according to a multi-scale digital core construction method provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0018] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific embodiments of the present invention are described in detail below in conjunction with the accompanying drawings. In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention can be implemented in many other ways different from those described herein, and those skilled in the art can make similar improvements without violating the connotation of the present invention, so the present invention is not limited by the specific embodiments disclosed below.

[0019] See also Figure 1 The embodiment of the present invention provides a multi-scale digital core construction method, specifically a multi-scale digital core construction method based on Markov chain Monte Carlo method and mercury injection curve, which uses Markov chain Monte Carlo method and mercury injection curve data to construct digital cores of carbonate reservoirs at different scales, and on this basis, the digital cores of carbonate rocks at various scales are scaled by expansion and corrosion algorithms, so that the scales of various digital cores can be unified and Boolean superposition can be performed, and finally a suitable multi-scale digital core is obtained. It includes the following steps:

[0020] Step 1: Collect and obtain reservoir CT scan images of different scales of each reservoir in carbonate oil and gas reservoirs and the corresponding small-scale mercury injection curve experimental data. Specifically:

[0021] A representative core sample (columnar core) is obtained from the target reservoir, and the sample is cleaned to remove contaminants in the pores (such as clay particles or oil and gas residues). After the sample is dried (such as placed in a vacuum drying oven), it is subsequently processed using a mercury injection device; the sample is placed in a mercury injection chamber, and mercury is gradually injected under low pressure; as the pressure increases, the amount of mercury intrusion and the corresponding capillary pressure are recorded to obtain small-scale mercury injection curve experimental data; an industrial CT scanning device is used to scan and output a series of two-dimensional tomographic images (DICOM format) of the core sample to obtain reservoir CT scanning images of different scales for each reservoir in the carbonate oil and gas reservoir.

[0022] Step 2: Reconstruct the pore structure of micropores and microcracks through mercury injection curve experimental data and CT scan images, construct the pore skeleton based on the CT scan images through Markov chain Monte Carlo method MCMC, and use mercury injection curve experimental data to impose physical constraints and limit pore growth, thereby constructing a microporous carbonate digital core that meets the pore size distribution of the mercury injection curve experiment.

[0023] Among them, the capillary pressure is extracted from the mercury injection experimental curve ( P ) and the corresponding cumulative mercury volume (VHg), according to the Washburn equation, the capillary pressure P Convert to aperture r , the formula is: .

[0024] in: r represents the pore throat radius; γ represents the surface tension of mercury; θ represents the contact angle of mercury; P Represents capillary pressure. The pore size range is divided into several size intervals (such as r ∈[0.01 μm,10 μm]), count the pore proportion in each interval and get the pore size distribution histogram D MIP .

[0025] The pore size distribution histogram D MIP Normalize to a probability distribution P MIP ( r ), as the target constraint condition for the growth of the pore skeleton: .

[0026] By adjusting the growth process of the pore framework, the pore size distribution gradually approaches the target distribution of the mercury injection curve. P MIP ( r ). The following are the specific steps: Define the growth rate of the pore skeleton nodes g ( r ), so that the pore growth occurs preferentially in the range with a higher pore size ratio in the target distribution, and the formula is:

[0027] .

[0028] in: g ( r ) represents a node r growth rate.

[0029] In addition, during the growth process, the maximum aperture r of the node is limited max, ensuring that it does not exceed the upper limit of the target distribution. On the pore skeleton network, the pore growth path is optimized by the Markov Chain Monte Carlo method (MCMC): each node (aperture and position x, y, z) of the pore skeleton network constitutes a state. The candidate growth path is accepted or rejected according to the Metropolis criterion, which is formulated as:

[0030] .

[0031] Step 3: Based on the CT scan images of carbonate fracture-cavity and fracture-pore reservoirs, the digital cores of carbonate fracture-cavity and fracture-pore are constructed by using the Markov Chain Monte Carlo method MCMC. Specifically:

[0032] According to the method of step 2, the CT scanning images and mercury injection data of the fracture-cavity type and fracture-pore type reservoirs of carbonate rocks are obtained through step 1, and then step 2 is performed respectively using the above formula to perform physical constraints to obtain the fracture-cavity type and fracture-pore type digital cores of carbonate rocks corresponding to the fracture-cavity type and fracture-pore type reservoirs of carbonate rocks.

[0033] Step 4: Through expansion and corrosion operations, the micropore, fracture-cavity, and fracture-hole digital cores are scaled to unify them at the pixel scale. The micropore, fracture-cavity, and fracture-hole digital cores are scaled through expansion and corrosion operations to adjust the digital cores of different pixel scales to a unified physical scale. This process mainly solves the problem that each pixel represents a different physical size, thereby completing the standardization and size adjustment of the digital core at the pixel level. Specifically:

[0034] Each digital core is represented by a two-dimensional slice or a three-dimensional volume image, and a pixel (2D) or voxel (3D) corresponds to a certain area in the physical space. The input digital core is binary point cloud data, where 1 represents the pore or fracture area and 0 represents the matrix area. Each layer image in the depth direction is extracted as a two-dimensional binary image. According to the unified standard, the target pixel scale is determined S target Extract the original pixel scale from the input digital core data S original . Calculate the scaling factor R , the formula is:

[0035] .

[0036] Among them: R >1, expansion operation is required. R <1, corrosion operation is required. R >1, the pore or fracture area of ​​the digital core is expanded using the morphological dilation operator, and the expansion formula is:

[0037] .

[0038] in: A represents the binary image of the input digital core; B Represents the structural element SE; D ( A ) represents the image after expansion. The specific implementation is to select the radius of the structural element as r = R − 1. The pore area of ​​the digital core is operated pixel by pixel, and all adjacent pixels (determined by the structural element) are marked as pores.

[0039] if R <1, the pore or fracture area of ​​the digital core is filtered out using the morphological corrosion operator, and the filtering formula is: .

[0040] in: A represents the binary image of the input digital core; B Represents the structural element SE; E ( A ) represents the image after corrosion. The specific implementation is to select the radius of the structural element as r = R − 1. The pore area of ​​the digital core is operated pixel by pixel, the edge pixels are removed, and the area completely contained by the structural element is retained.

[0041] The dilation operation expands the object area by increasing the boundaries of the objects in the image; the erosion operation reduces the boundaries of the objects in the image, removes small details or connects small channels between objects.

[0042] Step 5: Perform Boolean superposition operations on micropore, fracture-cavity, and fracture-pore digital cores to obtain multi-scale carbonate digital cores. Specifically:

[0043] First, the micropores are superimposed on the fracture-cavity type, and the matrix part of the fracture-cavity type core is filled with micropores to retain the connectivity between the mesoscale pores and fractures. The formula is: .

[0044] in: A Represents the binary volume data of microporous core, B Represents the binary volume data of fracture-cavity core, C Represents the binary volume data of fracture-pore core.

[0045] result R ( x , y , z), if any input is 1, the output is 1 (pore); otherwise, it is 0 (matrix). Secondly, the fracture-pore type is superimposed on the micropore + fracture-hole type, and the large-scale cracks of the fracture-hole type cover the overall pore structure of the first two. The formula is:

[0046] .

[0047] Among them: Results R ( x , y , z ), if any input is 1, then the output is 1 (pore); otherwise it is 0 (matrix). R multi—scale It is a multi-scale carbonate digital core.

[0048] Among them, the construction of multi-scale digital cores based on Markov chain Monte Carlo method and mercury injection curve is a combination of point cloud processing technology and digital core technology. In view of the complex pore structure of carbonate reservoirs, the coexistence of pores, holes (pore diameter>2mm), and cracks, some pore structures are filled with asphaltene, and the heterogeneity within the layer (transverse) and between layers (vertical) is strong. Based on CT scanning data and mercury injection curve experimental data, the digital core technology superposition technology is used to first construct micropore type, fracture pore type, and fracture cave type digital cores, and finally a multi-scale carbonate digital core is constructed through Boolean superposition.

[0049] The present invention can construct a multi-scale digital core of carbonate reservoirs only by collecting mercury injection curve data, corrosion and expansion operations, Boolean superposition operations, and Markov chain Monte Carlo algorithms. Compared with conventional digital core construction methods, the present invention has the advantages of high timeliness, low cost, and multi-scale, and can further provide reference significance for the formulation of oil and gas reservoir development plans.

[0050] The present invention is a combination of point cloud processing technology and digital core technology. Aiming at the complex pore structure of carbonate reservoirs, the coexistence of pores, holes (pore diameter>2mm), and cracks, some pore structures are filled with asphaltene, and the heterogeneity within the layer (transverse) and between the layers (vertical) is strong. Based on CT scanning data and mercury injection curve experimental data, the digital core technology superposition technology is used to first construct micropore type, fracture pore type, and fracture cave type digital cores, and finally a multi-scale carbonate digital core is constructed through Boolean superposition.

[0051] In the method of the present invention, the study on the development characteristics of pores, caves and fractures in carbonate rocks and the complex seepage laws of gas and water can not only provide important theoretical support for the exploration and development of oil and gas reservoirs, but also provide important technical support for the deep development of oil and gas reservoirs, thereby improving the development efficiency of oil and gas reservoirs, which is of great significance for in-depth understanding of the physical properties and development effects of fracture-cavity type carbonate reservoirs.

[0052] Specific experiments: Select representative samples from the Sinian carbonate reservoir to ensure that the micropore, fracture-cavity, and fracture-pore reservoir characteristics are covered. Remove the surface clay particles and oil and gas residues, use a vacuum drying oven to treat for 24 hours, and then use an industrial CT scanner to scan the core layer by layer. The resolution is set to 0.5um and 20um. The output results are as follows: Figure 2 As shown. Among them, Figure 2 In order to obtain reservoir CT scanning images of different scales for each reservoir of the Sinian carbonate oil and gas reservoir and the corresponding small-scale mercury injection curve experimental data.

[0053] Using a mercury intrusion instrument, gradually apply pressure in the mercury intrusion instrument and record the cumulative mercury intrusion and corresponding capillary pressure at different pressures, such as Figure 3 As shown. The capillary pressure is converted to pore size using the Washburn equation to generate a pore size distribution plot. Figure 3 (a) is the obtained core mercury injection curve data of carbonate rock. Figure 3 (b) is the core pore size distribution diagram obtained from the core mercury injection curve data.

[0054] like Figure 4 As shown in the figure, based on the CT scan images of the pore-type reservoirs of each reservoir in the Sinian carbonate oil and gas reservoir, the pore-type pore result reconstruction is constructed by the Markov chain Monte Carlo method, and the results after corrosion and expansion operations are performed. Among them, the pore area is extracted using the CT image segmentation method, the initial pore skeleton is generated and the initial pore size distribution is statistically calculated, the pore size distribution generated by the mercury injection curve is normalized to the target probability distribution, and the pore skeleton nodes (position x, y, z and pore size r) are initialized. The node growth rate is determined by the formula g ( r ), giving priority to expanding the pore size range with a higher proportion in the target distribution. Subsequently, the pore growth path is optimized according to the Metropolis criterion and the pore size distribution is updated. Finally, the reconstructed microporous digital core pore structure is shown in Figure 4 shown.

[0055] Similarly, based on the CT scan images of fracture-cavity reservoirs in the Sinian carbonate oil and gas reservoirs, the Markov chain Monte Carlo method was used to construct the fracture-cavity pore reconstruction results, and the results after corrosion and expansion operations are shown in the figure below. Figure 5 shown; Figure 5 (a) is the reconstruction result of the fracture-cavity pore result; Figure 5 (b) The reconstruction result of the hole type after corrosion and dilation operations.

[0056] Similarly, based on the CT scan images of the fracture-pore type reservoirs of the Sinian carbonate oil and gas reservoirs, the fracture-pore type pore results were reconstructed by the Markov chain Monte Carlo method, and the results after corrosion and expansion operations are shown in the figure below. Figure 6 shown; Figure 6 (a) is a CT scan image of a fracture-pore reservoir; Figure 6 (b) is the result after erosion and dilation operations.

[0057] According to the pixel scale of each digital core S original and the target pixel scale S target , calculate the scaling ratio according to the formula R . According to the formula, the Boolean superposition operation is performed on the micropore and fracture-cavity type digital cores to fill the matrix part of the fracture-cavity type core. According to the formula, the fracture-pore type core is superimposed with the former to merge the fracture and pore structure. Finally, the multi-scale digital core of the Sinian carbonate oil and gas reservoir is obtained as follows Figure 7 shown.

[0058] The above-mentioned embodiments only express several implementation methods of the present invention, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for ordinary technicians in this field, several variations and improvements can be made without departing from the concept of the present invention, and these all belong to the protection scope of the present invention. Therefore, the protection scope of the patent of the present invention shall be subject to the attached claims.

Claims

1. A multi-scale digital core construction method, characterized in that: The following steps are involved: Obtain CT scan images of different scales of each reservoir in carbonate oil and gas reservoirs and the corresponding mercury injection curve experimental data of each reservoir; Based on CT scan images of different scales, the Markov Chain Monte Carlo method (MCMC) is used to construct pore frameworks of different scales, and the mercury injection curve experimental data of each reservoir is used to physically constrain the constructed pore framework to limit the pore growth rate and growth path, and obtain digital cores of micropores, fracture-cavity and fracture-pore carbonate rocks of different scales that conform to the pore size distribution in the mercury injection curve experiment; The microporous, fracture-cavity and fracture-pore carbonate digital cores are expanded and eroded to unify their scales; the unified-scaled microporous, fracture-cavity and fracture-pore carbonate digital cores are Boolean superimposed to obtain multi-scale carbonate digital cores.

2. A multi-scale digital core construction method according to claim 1, characterized in that: The method of obtaining CT scanning images of different scales of each reservoir of carbonate oil and gas reservoir and mercury injection curve experimental data corresponding to each reservoir includes: Obtaining a core sample from the target reservoir, cleaning the core sample to remove contaminants in the pores, and placing the sample in a vacuum drying oven for drying; The dried sample is placed in a mercury injection chamber, and mercury is gradually injected under low pressure. As the pressure increases, the amount of mercury intrusion and the corresponding capillary pressure are recorded to obtain small-scale mercury injection curve experimental data. A CT scanning device is used to scan and output two-dimensional tomographic images of multiple core samples to obtain reservoir CT scanning images of different scales of each reservoir in the carbonate oil and gas reservoir.

3. A multi-scale digital core construction method according to claim 1, characterized in that: The limiting pore growth rate and growth path includes: Extracting capillary pressure from mercury injection curve experimental data P and the corresponding cumulative mercury volume V Hg According to the Washburn equation, the capillary pressure P Convert to aperture r , the transformation equation is: ； in: r represents the pore throat radius; γ represents the surface tension of mercury; θ represents the contact angle of mercury; P Indicates capillary pressure; Divide the pore size range into multiple intervals, count the pore ratio in each interval, and obtain the pore size distribution histogram D MIP , the pore size distribution histogram D MIP Normalize to a probability distribution P MIP ( r ), as the target constraint condition for the growth of the pore skeleton; the probability distribution is expressed as: ； By adjusting the growth process of the pore framework, the pore size distribution gradually approaches the target distribution of the mercury injection curve. P MIP ( r ) ; Define the growth rate of the pore skeleton nodes according to the pore size ratio in the target distribution g ( r ), the growth equation is: ； in: g ( r ) represents a node r Growth rate; During the growth process, the maximum aperture r of the node is limited max , ensuring that it does not exceed the upper limit of the target distribution; on the pore skeleton network, the pore growth path is optimized by the Markov Chain Monte Carlo method MCMC: each node of the pore skeleton network constitutes a state, and the node includes the pore size and position x, y, z; according to the Metropolis criterion, the candidate growth path is accepted or rejected, and the equation is expressed as: 。 4. A multi-scale digital core construction method according to claim 1, characterized in that: The method of unifying the scales of micropore, fracture-cavity type and fracture-pore type carbonate digital cores includes: Each digital core is represented by a 2D slice or a 3D volume image, where pixels 2D or voxels 3D correspond to a region in physical space; Assuming that 1 represents the pore or crack area and 0 represents the matrix area, each layer image in the depth direction is extracted as a two-dimensional binary image; according to the unified standard, the target pixel scale is determined S target , extract the corresponding original pixel scale from the input digital core data S original , get the zoom ratio R : ； like R >1, perform expansion operation; if R <1, perform corrosion operation; if R >1, the pore or fracture area of ​​the digital core is expanded using the morphological dilation operator, and the expansion equation is: ； in: A represents the binary image of the input digital core; B represents the structural element SE; D ( A ) represents the expanded image; specifically, the pore area of ​​the digital core is operated pixel by pixel, and all adjacent pixels are marked as pores; if R <1, the pore or fracture area of ​​the digital core is filtered out using the morphological corrosion operator, and the filtering equation is: ； in: A represents the binary image of the input digital core; B represents the structural element SE; E ( A ) represents the image after corrosion; the pore area of ​​the digital core is operated pixel by pixel, the edge pixels are removed, and the area completely contained by the structural element is retained.

5. A multi-scale digital core construction method according to claim 1, characterized in that: The Boolean superposition of the micropores, fracture-cavity type and fracture-pore type carbonate digital cores after unified scale includes: The digital cores of microporous carbonate rocks and fracture-cavity carbonate rocks are Boolean superimposed, and the matrix part of the fracture-cavity core is filled with micropores to retain the connectivity between mesoscale pores and fractures. The superposition equation is expressed as: ； in: A Represents the binary volume data of microporous core, B Represents the binary volume data of fracture-cavity core, C Represents the binary volume data of fracture-pore core; In the results R ( x , y , z ), if any input is 1, the output is 1, which is a pore; otherwise, it is 0, which is a matrix; The results of Boolean superposition of the digital core of fracture-pore carbonate rock, the digital core of microporous carbonate rock and the digital core of fracture-cavity carbonate rock are superimposed, and the large-scale fractures of fracture-cavity type cover the overall pore structure of the former two. The superposition equation is: ； In the results R ( x , y , z ), if any input is 1, the output is 1, which is a pore; otherwise, it is 0, which is a matrix; the final R multi—scale It is a multi-scale carbonate digital core.

6. A multi-scale digital core construction device, characterized in that: include: Data module, used to obtain CT scan images of different scales of each reservoir of carbonate oil and gas reservoirs and experimental data of mercury injection curves corresponding to each reservoir; The processing module is used to construct pore skeletons of different scales based on CT scan images of different scales using the Markov Chain Monte Carlo method MCMC, and to physically constrain the constructed pore skeletons using the mercury injection curve experimental data corresponding to each reservoir to limit the pore growth rate and growth path, and obtain digital cores of micropores, fracture-cavity type and fracture-pore type carbonate rocks of different scales that conform to the pore size distribution in the mercury injection curve experiment; The unified module is used to perform expansion and corrosion operations on the digital cores of microporous, fracture-cavity and fracture-pore carbonate rocks to unify the scales of the digital cores of microporous, fracture-cavity and fracture-pore carbonate rocks; the unified-scale digital cores of microporous, fracture-cavity and fracture-pore carbonate rocks are Boolean superimposed to obtain multi-scale digital cores of carbonate rocks.

7. An electronic device, characterized in that: include: Memory and processor; The memory is used to store computer programs; The processor is used to implement the steps of a multi-scale digital core construction method as described in any one of claims 1 to 5 when executing the computer program stored in the memory.

8. A computer-readable storage medium, characterized in that: Used to store a computer program, which, when executed by a processor, implements the steps of a multi-scale digital core construction method as described in any one of claims 1 to 5.

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