A method for simulating gas-water two-phase percolation of multiple media digital cores under high pressure conditions

Abstract

The application discloses a kind of high-pressure conditions under multiple medium digital core gas-water two-phase percolation simulation method, and the gray scale image of fracture-pore type piston rock sample is obtained by CT scanning, the fracture-pore network model of the rock sample is constructed, then the experimental results of gas-water relative permeability under normal temperature and pressure are used to correct the model, carry out permeability stress sensitivity experiment under high temperature and high pressure, obtain the relationship curve of permeability with confining pressure, the fracture opening in the corrected fracture-pore network model is used to simulate the fracture closure under high temperature and high pressure, and the experimental results of permeability under high temperature and high pressure are used to correct, obtain the relationship of fracture opening with confining pressure, further predict the gas-water two-phase relative permeability curve under different pressures, provide theoretical support for efficient development of high-pressure gas reservoir.

Description

Technical Field

[0001] This invention relates to a method for simulating gas-water two-phase flow in multi-medium digital cores under high pressure conditions. Specifically, it relates to a method for predicting the gas-water two-phase flow characteristics of high-pressure gas reservoirs in multi-medium (including pores, cavities, and fractures) carbonate reservoirs based on digital core simulation, belonging to the field of oil and gas field development technology. Background Technology

[0002] The deep carbonate gas reservoirs in the Sichuan Basin have enormous potential and have become a key focus of conventional gas exploration and development in recent years. However, these reservoirs generally exhibit characteristics such as high temperature and pressure, low porosity and permeability, diverse reservoir and permeability types, and strong heterogeneity, posing significant challenges to the scientific and efficient development of these reservoirs. Taking the Shuangyushi Qixia Formation in northern Sichuan as an example, this gas reservoir is buried at a depth of over 7000m, with an original formation pressure as high as 96MPa, a formation temperature of 158℃, an average porosity of 3.09%, and an average matrix permeability of 0.12mD. Furthermore, the reservoir rocks exhibit diverse relationships between pores, fractures, and caverns, resulting in complex seepage patterns and significant differences in well productivity and production stability.

[0003] Indoor core physics experiments are a primary technical means for studying the seepage mechanism of gas reservoirs. However, conducting high-temperature and high-pressure core seepage experiments still faces certain limitations: on the one hand, the extremely high temperature and pressure conditions place high demands on experimental instruments, resulting in significant safety risks, long experimental cycles, and low success rates; on the other hand, the experiments are destructive to the cores, making repeated experiments impractical, and the limited experimental results make it difficult to obtain systematic insights. In recent years, digital core analysis and micro-flow simulation, as emerging technologies, have become an important supplement to indoor core experiments. They are widely used in reservoirs such as medium-to-high permeability sandstone, shale, and low-permeability tight sandstone, enabling quantitative and refined characterization of rock micropore structure, analysis of rock electrical properties, and description of micro-seepage characteristics.

[0004] For example, the study "Simulating High-Temperature and High-Pressure Gas-Water Seepage Using Digital Core Technology" describes the use of CT scans of rock samples for three-dimensional reconstruction to calculate rock porosity, permeability, permeability tensor, and other physical property parameters. Finally, it describes manually correcting poorly distributed meshes and deriving a partial differential matrix equation for gas-water phase seepage using the gas-water two-phase mass equation, applicable to multiphysics finite element coupling software. However, in practical applications, actual seepage conditions are often more complex. Using the matrix equations constructed from digital cores for analysis not only makes simulation difficult but also results in poor accuracy. Summary of the Invention

[0005] To address the issue that existing digital core models cannot guarantee the feasibility of simulation results under high-pressure conditions during gas-water two-phase flow simulation, this invention provides a multi-medium digital core gas-water two-phase flow simulation method under high-pressure conditions. This method is used to obtain the gas-water two-phase flow curves and their variation laws in high-pressure gas reservoirs, providing theoretical support for the efficient development of high-pressure gas reservoirs.

[0006] This invention is achieved through the following technical solution: a method for simulating two-phase gas-water flow in digital cores under high pressure conditions, comprising the following steps:

[0007] S1. Obtain grayscale images of fracture-pore type plunger rock samples by CT scanning, and construct a fracture-pore network model of the rock samples;

[0008] S2. Conduct core displacement experiments on the rock sample to obtain the relative permeability curves of gas and water under normal temperature and pressure conditions;

[0009] S3. Based on the fracture-pore network model, the gas-water two-phase interpenetration curve is obtained, and the experimental results from step S2 are used to correct it to obtain the corrected fracture-pore network model.

[0010] S4. Conduct a permeability stress sensitivity experiment on the rock sample under high temperature and high pressure conditions to obtain the relationship curve of permeability with confining pressure;

[0011] S5. Using the crack aperture in the modified crack-void network model, the crack closure under high temperature and high pressure conditions is simulated. Combined with the experimental results of step S4, the relationship between crack aperture and confining pressure is obtained.

[0012] S6. Based on the modified crack-pore network model and the relationship between crack aperture and confining pressure, the gas-water two-phase interpenetration curves under different pressures are predicted.

[0013] In step S1, grayscale images of fracture-pore type plunger rock samples are obtained by CT scanning. The grayscale images are then processed by noise reduction, filtering, and image segmentation to establish a digital core of the rock sample containing pore and fracture spaces. Finally, the maximum sphere method is used to construct a fracture-pore network model that takes into account both the topological structure of the storage space and the computational complexity of the simulation.

[0014] In step S2, a core displacement experiment is conducted on the rock sample using the unsteady-state method.

[0015] In step S3, based on the crack-pore network model, the "intrusion-percolation" theory is used to conduct a pore-scale simulation of gas-water two-phase flow and calculate the gas-water two-phase percolation curve.

[0016] In step S3, during the pore-scale simulation of the gas-water two-phase flow, for the gas-driven water process, it is first necessary to determine the single-phase flow rate of the fluid passing through the fracture-pore network model under a given pressure difference. q t and the flow rates of the gas and water phases respectively q pg and q pw Then, the pressure distribution of each pore node under a given pressure difference is calculated according to formulas (1) and (2), and the flow rate of each phase fluid through the pore network is calculated. Then, the absolute permeability and relative permeability of gas and water in the fracture-pore network model are obtained according to Darcy's law, thus obtaining the gas-water two-phase inter-permeability curve.

[0017] (1)

[0018] (2)

[0019] in, q p,ij for p Phase fluid from pores j Inflow into pores i Traffic, n To be with pores i The number of connected larynxes g p,ij To connect pores i , j Fluid in the throat p conductivity; L ij Indicates the length of the larynx; P pi , P pj Pores i , j The pressure.

[0020] In step S3, during the pore-scale simulation of gas-water two-phase flow, the conductivity coefficient of the fluid located in the middle of the pore throat in both single-phase and multiphase flows is... g p The result is obtained by formula (3):

[0021] (3)

[0022] in, C The correction factors are set to 0.5, 0.5623, and 0.6, respectively. A The cross-sectional area of ​​the throat; G for p The shape factor of the pore throat occupied by the phase fluid; μ p for pViscosity of the phase fluid.

[0023] In step S4, the experimental process includes: using the same core from the core displacement experiment described in step 2, washing and drying the core, placing the core in a core holder, and venting the core outlet to the atmosphere. During the experiment, the core inlet pressure is kept constant, and the net stress borne by the core is changed by altering the confining pressure. The confining pressure is increased sequentially in increments of 10 MPa. A stable flow rate is measured and the time is recorded at each pressure point, and the gas permeability is calculated to obtain the permeability-confining pressure relationship curve.

[0024] In step S5, the crack aperture b under different confining pressures is calculated according to formula (4):

[0025] b = b 0e -aσ (4)

[0026] in: b 0 represents the initial crack aperture, in μm; b The crack aperture, in μm, is the crack opening after deformation under confining pressure. σ The confining pressure is in MPa. a The deformation coefficient is denoted by MPa. -1 ,

[0027] Then, in the crack-hole network model modified in step S3, all pixels representing crack information are multiplied by e. -aσ Then, Darcy's law is used to calculate the model permeability, making it consistent with the experimental results in step S4, and the deformation coefficient is determined. a .

[0028] Based on the crack-pore network model obtained in step S3, considering the relationship between crack aperture and confining pressure determined in step S5, as well as the changes in fluid physical parameters under different confining pressures, the gas-water two-phase permeation curve under high pressure conditions is predicted.

[0029] The fluid properties include, but are not limited to: water phase density, water phase viscosity, gas phase density, gas phase viscosity, and gas-water interfacial tension.

[0030] Compared with the prior art, the present invention has the following advantages and beneficial effects:

[0031] This invention, for the first time, establishes a method for predicting gas-water two-phase flow under high pressure based on multi-media digital core construction and multiphase flow simulation. This method compares and verifies the results of gas-water two-phase flow simulation at the pore scale with phase permeation experiments under normal temperature and pressure conditions. Furthermore, it combines stress-sensitive experiments to obtain the relationship between permeability and fracture aperture, and considers the changes in permeability and fluid properties under different formation pressures. This method can predict the gas-water two-phase flow mechanism in high-pressure gas reservoirs and provide theoretical support for the efficient development of high-pressure gas reservoirs. Attached Figure Description

[0032] Figure 1 This is a flowchart illustrating the model construction process of the present invention.

[0033] Figure 2 This is the result of a CT scan of a plunger core.

[0034] Figure 3 A binarized image is created by overlaying the void space and the crack space.

[0035] Figure 4 This is a three-dimensional digital core of a rock sample.

[0036] Figure 5 This is a model of the crack-pore network in rock samples.

[0037] Figure 6 This is a frequency distribution diagram of crack aperture in a crack-void network model.

[0038] Figure 7 This is a comparison chart of simulation and experimental results of gas-water phase permeation in rock samples.

[0039] Figure 8 This is a graph showing the relationship between rock sample permeability and confining pressure.

[0040] Figure 9 The effect of crack closure on the gas-water two-phase interpenetration curve under different pressures. Detailed Implementation

[0041] The present invention will be further described in detail below with reference to embodiments, but the implementation of the present invention is not limited thereto.

[0042] Example 1:

[0043] This embodiment relates to a method for simulating gas-water two-phase flow in digital cores under high pressure conditions. (See also...) Figure 1 The flowchart shown below illustrates the specific steps:

[0044] Step S1: Select carbonate rock plunger samples with developed pores, cavities, and fissures, and perform CT scans to obtain grayscale images of the rock samples. Use the Mask method to mark the entire plunger sample, and apply nonlocal mean filtering to remove noise from the image. Then, use the watershed algorithm to segment the image, separating the pore space and framework of the rock sample, resulting in a binarized image containing pore space and some obvious fissure information. On the other hand, use the ant colony algorithm to extract fissures. For the tracked fissure framework, match it with the pore space image extracted using the watershed algorithm, mark the pixels of the overlapping parts, and calculate the width of the fissure in that part. Separate this fissure information from all the pore spaces extracted by the watershed algorithm to obtain a binarized image of the pore space. Simultaneously, overlay this fissure image with the fissure framework tracked by the ant colony algorithm to obtain a binarized image containing complete fissure information.

[0045] The extracted pore space and the binarized image of the complete fracture space are overlaid to obtain a binary image containing both pore and fracture spaces. By sequentially overlaying individual images and then reconstructing the overlaid image in 3D, a 3D digital core containing both pore and fracture spaces can be obtained. Alternatively, the binarized images of pore and fracture spaces can be reconstructed in 3D separately to obtain the corresponding 3D digital core.

[0046] For the constructed digital core of the pore space, the maximum sphere algorithm is used to model it, and the connectivity of the pore space is determined by the relationship between the maximum spheres, the pores and throats are divided, and the pore throat parameters are calculated. For the constructed digital core of the fracture space, the fracture network model is established by combining centerline extraction and maximum sphere filling. The two are integrated to obtain the fracture-pore network model.

[0047] Step S2: For the same rock sample mentioned above, a core displacement experiment is carried out according to the unsteady-state method in GB / T28912-2012 "Method for Determination of Relative Permeability of Two-Phase Fluids in Rocks" to obtain the gas-water relative permeability curve under normal temperature and pressure conditions.

[0048] Step S3: Based on the fracture-pore network model, a pore-scale simulation is performed using the "intrusion-percolation" theory to calculate the gas-water two-phase interpercolation curve, as follows:

[0049] The "intrusion-percolation" theory is used to conduct pore-scale simulations of gas-water two-phase flow. For gas-driven water processes, it is first necessary to determine the single-phase flow rate of the fluid passing through the pore network model under a given pressure difference. q t and the flow rates of the gas and water phases respectively q pg and q pwSince it is assumed that the fluid is incompressible, for any phase fluid flowing through any pore node... i The flow rate follows the law of conservation of mass:

[0050] (1)

[0051] In formula (1), n ​​is the number of throats connected to pore i; q p,ij Let be the flow rate of p-phase fluid flowing from pore j into pore i.

[0052] The flow rate between adjacent pores i and j is calculated using the following formula:

[0053] (2)

[0054] In formula (2), q p,ij for p Phase fluid from pores j Inflow into pores i Traffic, n To be with pores i The number of connected larynxes g p,ij To connect pores i , j Fluid in the throat p conductivity; L ij Indicates the length of the larynx; P pi , P pj Pores i , j The pressure.

[0055] For single-phase and multiphase flows, the conductivity of the fluid located in the middle of the pore throat (non-wetting phase) is... g p This can be obtained through the Hagen-Poiseuille law:

[0056] (3)

[0057] In formula (3), C is a correction coefficient. For elements with circular, square and triangular cross sections, the corresponding C values ​​are 0.5, 0.5623 and 0.6, respectively. A The cross-sectional area of ​​the throat; G for p The shape factor of the pore throat occupied by the phase fluid; μ p for p Viscosity of the phase fluid.

[0058] By combining formulas (1) and (2), the pressure distribution of each pore node under a given pressure difference can be obtained, and then the flow rate of each phase fluid through the pore network can be calculated. Then, the absolute permeability and relative permeability of air and water of the fracture-pore network model can be obtained according to Darcy's law.

[0059] Furthermore, by comparing the results with the experimental results from step S2, a modified crack-pore network model is obtained, which makes the simulation calculations and experimental results highly consistent.

[0060] Step S4: For the same rock sample mentioned above, the core is washed and dried. A permeability stress sensitivity experiment under high temperature and high pressure conditions is conducted according to the "SY / T 5358-2010 Reservoir Sensitivity Flow Test Evaluation Method". The experimental instruments are connected as required, and the core is placed in the core holder. The core outlet is vented to the atmosphere. During the experiment, the core inlet pressure is kept constant. The net stress borne by the core is changed by altering the confining pressure. The confining pressure is increased sequentially in increments of 5 MPa (specific pressures depend on requirements). A stable flow rate is measured and the time is recorded at each pressure point. The gas permeability is calculated, and the relationship curve between permeability and confining pressure is obtained, providing a basis for correcting the subsequent pore network model.

[0061] Step S5: In the modified crack-pore network model obtained in step S3, the variation of pore structure with confining pressure is ignored, and it is assumed that the initial crack aperture under normal pressure is... b 0, under confining pressure σ Crack aperture under action b for:

[0062] b = b 0e -aσ (4)

[0063] In the formula: b 0 represents the initial crack aperture, in μm; b The crack aperture, in μm, is the crack opening after deformation under confining pressure. σ The confining pressure is in MPa. a The deformation coefficient is denoted by MPa. -1 .

[0064] By adjusting formula (4) a The magnitude of the value is used to calculate the crack aperture under different confining pressures. Then, in the crack-pore network model modified in step S3, each pixel representing crack information is multiplied by e. -aσ Then, Darcy's law is used to calculate the model permeability, making it consistent with the experimental results in step S4, and the deformation coefficient is determined. a .

[0065] Step S6: Based on the crack-pore network model obtained in step S3, consider the relationship between crack aperture and confining pressure determined in step S5, as well as the changes in fluid physical properties (such as water phase density, water phase viscosity, gas phase density, gas phase viscosity and gas-water interfacial tension) under different confining pressures, and predict the gas-water two-phase interpenetration curve under high pressure conditions.

[0066] Example 2:

[0067] A fracture-cavity plunger rock sample from a carbonate gas reservoir, measuring 2.5 cm (diameter) × 4.2 cm (height), was selected. The sample exhibited a gas porosity of 6.74% and a permeability of 3.37 mD. Microfractures, cracks, and cavities were clearly visible on the surface. The sample was scanned using a scanning system, and a three-dimensional structural image was obtained by reconstructing 1340 16-bit grayscale slices from CT images (e.g., [image of CT image]). Figure 2 As shown, the image size is 1530×1530×1340 pixels, and the resolution is 7.83μm.

[0068] Step 1: Establishment of multi-medium digital core and fracture-pore network model.

[0069] The obtained 3D CT image data volume was imported into the image 3D reconstruction software. The entire plunger rock sample was marked using the Mask method, and nonlocal mean filtering was applied to remove noise. The filtered image was then segmented using the watershed algorithm and ant colony tracking algorithm to separate the rock sample's pores, fracture spaces, and skeleton, resulting in a binarized image containing pore and fracture information, as shown below. Figure 3 As shown, the binarized image is reconstructed in three dimensions to obtain a digital core containing information on pores and fractures, as shown. Figure 4 As shown. To perform simulation calculations, the maximum sphere algorithm was used to model the digital core, resulting in a fracture-pore network model with the same topological structure as the real core, as shown. Figure 5 As shown in Table 1 below, the digital core porosity and permeability parameters and the internal structural parameters of the rock sample are shown in Table 1. The fracture aperture distribution diagram is shown in the figure below. Figure 6 As shown.

[0070] Table 1. Simulation input parameters for gas-water two-phase flow under different pressures

[0071]

[0072] Step two: For the above rock samples, core displacement experiments were conducted using the unsteady-state method in GB / T28912-2012 "Method for Determination of Relative Permeability of Two-Phase Fluids in Rocks". The obtained relative permeability curves are shown below. Figure 7 As shown.

[0073] The experimental procedure is as follows:

[0074] (1) After the core is washed and dried, weigh the dry weight of the core.

[0075] (2) Prepare simulated formation water with distilled water according to the mineralization of formation water. Let the prepared formation water stand for 1 day before the experiment, filter it with filter paper to remove impurities, and then vacuum it.

[0076] (3) After measuring the gas permeability, put the core into a vacuum dryer and evacuate it for about 8 hours using a vacuum pump.

[0077] (4) Introduce the prepared simulated formation water into the vacuum dryer, continue to evacuate for 2 hours, and then soak it under normal pressure for more than 4 hours.

[0078] (5) Quickly wipe off the liquid from the surface of the rock sample and weigh it. The difference between the weight of the rock sample after it is saturated with liquid and the dry weight of the rock sample, divided by the density of the simulated formation water, is the porosity of the rock sample.

[0079] (6) Measure the dead volume of the core holder and pipeline.

[0080] (7) Water permeability of the sample. Under a certain pressure difference, simulated formation water passes through the rock sample, the flow rate at steady state is measured, and the water permeability is calculated.

[0081] (8) The initial pressure difference is calculated using the constant pressure method to determine the relative permeability of air and water according to the following formula:

[0082] (5)

[0083] Where: σ—interfacial tension between air and water, mN / m.

[0084] (9) Conduct the gas-driven water experiment under the pressure determined in (8); accurately record the time of gas emergence, the cumulative gas production, and the cumulative water production at the time of gas emergence. In the early stage of gas emergence, increase the recording frequency, and gradually increase the recording time interval as the gas production decreases.

[0085] (10) Measure the gas phase permeability when the gas-driven water reaches the bound water state, and end the experiment.

[0086] Step 3: Conduct pore-scale simulation based on the crack-pore network model.

[0087] Based on the fracture-pore network model established in step one, pore scale simulation was carried out. The gas-water phase permeability curves were calculated using formulas (1) to (3) and Darcy's law, and compared with the experimental results in step two. The fracture-pore network model was then modified to ensure a better match between the simulation calculations and experimental results. Figure 7 As shown.

[0088] Step four: Conduct core permeability stress-sensitive experiments to obtain the relationship between permeability and confining pressure.

[0089] For the same core sample mentioned above, the core was washed and dried, connected to the experimental apparatus as required, and placed in the core holder. The core outlet was vented to the atmosphere. During the experiment, the core inlet pressure was kept constant. The net stress on the core was varied by changing the confining pressure, with the confining pressure increased in increments of 10 MPa. Stable flow rates were measured and recorded at each pressure point, and the gas permeability was calculated. The relationship curve between permeability and confining pressure was obtained, as shown in the figure. Figure 8 As shown.

[0090] Step 5: Obtain the permeability variation curve with confining pressure based on the crack-pore network model.

[0091] In the fracture-pore network model modified in step three, the fracture aperture under different confining pressures (10~90MPa) is characterized based on formula (4), the permeability of the fracture-pore network model is calculated, and the theoretical value is compared with the permeability experimental results in step four (e.g., Figure 8 Adjusting the deformation coefficient yields the deformation coefficient. a =0.0226MPa -1 ,Right now:

[0092] b = b 0e -0.0226σ (6).

[0093] Step 6: Prediction of the relative permeability curves of the gas-water two-phase system under high pressure conditions

[0094] Based on the fracture-void network model, considering the influence of different confining pressures on fracture aperture and the changes in gas-water two-phase fluid properties under different confining pressures (as shown in Table 1), the gas-water two-phase permeability curves under high pressure (10MPa, 30MPa, 50MPa, 70MPa, 90MPa) are predicted. Figure 9 As shown in Table 2, the characteristic parameters of the relative permeability curve are statistically analyzed.

[0095] Table 2. Statistical analysis of gas-water two-phase permeation curves under different pressures.

[0096]

[0097] Based on simulation results (such as) Figure 9 As shown in Table 2, at a certain temperature, as the confining pressure increases, the cracks gradually close, the connectivity of the rock sample deteriorates, the saturation of bound water gradually increases, the co-permeability zone of the two phases narrows, the isopermeability point shifts to the right, and the relative permeability of the water phase decreases faster.

[0098] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Any simple modifications or equivalent changes made to the above embodiments based on the technical essence of the present invention shall fall within the protection scope of the present invention.

Claims

1. A method for simulating gas-water two-phase flow in digital core samples under high pressure conditions, characterized in that: Includes the following steps: S1. Obtain grayscale images of fracture-pore type plunger rock samples by CT scanning, and construct a fracture-pore network model of the rock samples; S2. Conduct core displacement experiments on the rock sample to obtain the relative permeability curves of gas and water under normal temperature and pressure conditions; S3. Based on the fracture-pore network model, the gas-water two-phase interpenetration curve is obtained, and the experimental results from step S2 are used to correct it to obtain the corrected fracture-pore network model. S4. Conduct a permeability stress sensitivity experiment on the rock sample under high temperature and high pressure conditions to obtain the relationship curve of permeability with confining pressure; S5. Using the crack aperture in the modified crack-void network model, the crack closure under high temperature and high pressure conditions is simulated. Combined with the experimental results of step S4, the relationship between crack aperture and confining pressure is obtained. S6. Based on the modified crack-pore network model and the relationship between crack aperture and confining pressure, the gas-water two-phase interpenetration curves under different pressures are predicted.

2. The method for simulating two-phase gas-water flow in digital cores under high pressure conditions according to claim 1, characterized in that: In step S1, grayscale images of fracture-pore type plunger rock samples are obtained by CT scanning. The grayscale images are then processed by noise reduction, filtering, and image segmentation to establish a digital core of the rock sample containing pore and fracture spaces. Finally, the maximum sphere method is used to construct a fracture-pore network model that takes into account both the topological structure of the storage space and the computational complexity of the simulation.

3. The method for simulating two-phase gas-water flow in digital cores under high pressure conditions according to claim 1, characterized in that: In step S2, a core displacement experiment is conducted on the rock sample using the unsteady-state method.

4. The method for simulating two-phase gas-water flow in digital cores under high pressure conditions according to claim 1, characterized in that: In step S3, based on the crack-pore network model, the "intrusion-percolation" theory is used to conduct a pore-scale simulation of gas-water two-phase flow and calculate the gas-water two-phase percolation curve.

5. The method for simulating two-phase gas-water flow in digital cores under high pressure conditions according to claim 4, characterized in that: In step S3, during the pore-scale simulation of the gas-water two-phase flow, for the gas-driven water process, it is first necessary to determine the single-phase flow rate of the fluid passing through the fracture-pore network model under a given pressure difference. q t and the flow rates of the gas and water phases respectively q pg and q pw Then, the pressure distribution of each pore node under a given pressure difference is calculated according to formulas (1) and (2), and the flow rate of each phase fluid through the pore network is calculated. Then, the absolute permeability and relative permeability of gas and water in the fracture-pore network model are obtained according to Darcy's law, thus obtaining the gas-water two-phase inter-permeability curve. （1） （2） in, q p,ij for p Phase fluid from pores j Inflow into pores i Traffic, n To be with pores i The number of connected larynxes g p,ij To connect pores i , j Fluid in the throat p conductivity; L ij Indicates the length of the larynx; P pi , P pj Pores i , j The pressure.

6. The method for simulating gas-water two-phase flow in digital cores under high pressure conditions according to claim 5, characterized in that: In step S3, during the pore-scale simulation of gas-water two-phase flow, the conductivity coefficient of the fluid located in the middle of the pore throat in both single-phase and multiphase flows is... g p The result is obtained by formula (3): （3） in, C The correction factors are set to 0.5, 0.5623, and 0.6, respectively. A The cross-sectional area of ​​the throat; G for p The shape factor of the pore throat occupied by the phase fluid; μ p for p Viscosity of the phase fluid.

7. The method for simulating two-phase gas-water flow in digital cores under high pressure conditions according to claim 1, characterized in that: In step S4, the experimental process includes: using the same core from the core displacement experiment described in step 2, washing and drying the core, placing the core in a core holder, and venting the core outlet to the atmosphere. During the experiment, the core inlet pressure is kept constant, and the net stress borne by the core is changed by altering the confining pressure. The confining pressure is increased sequentially in increments of 10 MPa. A stable flow rate is measured and the time is recorded at each pressure point, and the gas permeability is calculated to obtain the permeability-confining pressure relationship curve.

8. The method for simulating gas-water two-phase flow in digital cores under high pressure conditions according to claim 1, characterized in that: In step S5, the crack aperture b under different confining pressures is calculated according to formula (4): b = b 0e -aσ （4） in: b 0 represents the initial crack aperture, in μm; b The crack aperture, in μm, is the crack opening after deformation under confining pressure. σ The confining pressure is in MPa. a The deformation coefficient is denoted by MPa. -1 , Then, in the crack-hole network model modified in step S3, all pixels representing crack information are multiplied by e. -aσ Then, Darcy's law is used to calculate the model permeability, making it consistent with the experimental results in step S4, and the deformation coefficient is determined. a .

9. The method for simulating gas-water two-phase flow in digital cores under high pressure conditions according to claim 1, characterized in that: Based on the crack-pore network model obtained in step S3, considering the relationship between crack aperture and confining pressure determined in step S5, as well as the changes in fluid physical parameters under different confining pressures, the gas-water two-phase permeation curve under high pressure conditions is predicted.

10. The method for simulating two-phase gas-water flow in digital cores under high pressure conditions according to claim 9, characterized in that: The fluid properties include: aqueous phase density, aqueous phase viscosity, gas phase density, gas phase viscosity, and gas-water interfacial tension.

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