Discrete element method-based compact layer CO2 fracturing numerical simulation method and system

Abstract

The invention relates to a compact layer CO2 fracturing numerical simulation method and system based on a discrete element method, and belongs to the technical field of rock mass fracturing in the petroleum engineering technology. The method comprises the following steps: performing CT scanning based on a glutenite core to obtain particle size sorting parameter distribution of the glutenite core; establishing a compact layer discrete element model based on particle size sorting parameter distribution; and obtaining a compact layer CO2 fracturing result based on the compact layer discrete element model and a fracturing simulation test. On the basis of distinguishing gravel particle distribution in different compact layers through CT scanning of compact layer rock cores, a dimensionless particle size sorting index is introduced, then compact layer discrete element models of different sorting indexes are established according to the particle size sorting index, and the obtained compact layer discrete element models can accurately feed back compact layer rock core real objects; a fracture condition and a fluid-solid coupling algorithm are embedded in the compact layer discrete element model, and the precision of a fracture simulation result is further improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of rock mass fracturing in petroleum engineering, and particularly relates to a numerical simulation method and system for CO2 fracturing of tight formations based on the discrete element method. Background Art

[0002] Unconventional oil and gas reservoirs such as tight oil and gas and shale oil and gas have characteristics such as large storage capacity and wide distribution, and have currently become the main battlefield for oil and gas resource exploration and development. However, unconventional oil and gas reservoirs have many unfavorable mining conditions, such as: large changes in reservoir physical properties, obvious sorting characteristics of dense rock particle sizes, obvious low porosity-low permeability characteristics, oil and gas resources are mainly concentrated in micro-nano pores, migration is difficult, there are surface adsorption and pore migration sites, and conventional mining processes cannot achieve large-scale commercial mining. Fracturing, as a technical means widely used in reservoir stimulation, realizes "fracture creation" in unconventional oil and gas reservoirs, and can greatly improve reservoir permeability. Field tests of CO2 dry fracturing and pre-injection energy-increasing fracturing technologies have been widely carried out in unconventional oil and gas reservoirs, and simulation methods suitable for CO2 fracturing have been developed for tight formations. Summary of the Invention

[0003] In view of the above problems, the present invention provides a numerical simulation method and system for CO2 fracturing of tight formations based on the discrete element method to improve the numerical simulation accuracy of CO2 fracturing and make the simulation results more in line with the actual situation.

[0004] The first object of the present invention is to provide a numerical simulation method for CO2 fracturing of tight formations based on the discrete element method, including:

[0005] Based on the CT scan of the sandstone core, obtain the particle size sorting parameter distribution of the sandstone core;

[0006] Based on the particle size sorting parameter distribution, establish a discrete element model of the tight formation;

[0007] Based on the discrete element model of the tight formation and the fracturing simulation test, obtain the CO2 fracturing result of the tight formation.

[0008] In a specific embodiment of the present invention, the particle size sorting parameter H is calculated according to the following formula:

[0009]

[0010] Wherein,

[0011] S a is the average area of gravel particles, m is the number of gravel particles, r i is the radius of the gravel particle;

[0012] S i is the area of the i-th gravel particle;

[0013] The higher the particle size sorting index, the poorer the non-uniformity of the gravel particle distribution.

[0014] In a specific embodiment of the present invention, based on the discrete element model of the tight layer and the fracturing simulation test, the numerical simulation results of CO2 fracturing in the tight layer are obtained, including:

[0015] Embedding the fracture condition and the fluid-solid coupling algorithm into the discrete element model of the tight layer;

[0016] Based on the discrete element model of the tight layer obtained after embedding, micro-parameters are adjusted;

[0017] Based on the fracturing simulation test of the discrete element model of the tight layer obtained by micro-adjustment, the CO2 fracturing results in the tight layer are obtained.

[0018] In a specific embodiment of the present invention, the fracture condition simultaneously satisfies the following two conditions:

[0019] Condition 1: σ t ≥pb_tan

[0020] Condition 2:

[0021] Wherein, σ t is the tensile stress, MPa, τ is the shear stress, MPa, pb_tan is the tensile strength value, MPa, pb_coh is the shear strength value, MPa, σ n is the compressive stress value, MPa, is the friction angle set by the model.

[0022] In a specific embodiment of the present invention, the fluid-solid coupling algorithm includes the fluid viscosity property and the fluid penetration algorithm.

[0023] In a specific embodiment of the present invention, the fluid penetration algorithm includes the fluid pore pressure algorithm and the remaining pore diameter algorithm. Among them, the fluid pore pressure algorithm is calculated according to the following formula:

[0024]

[0025] Wherein, Q is the fluid volume flow rate, and

[0026] w is the channel width, m; μ is the viscosity of the fracturing medium, mPa·s; dp is the pressure difference between both sides of the pipeline, MPa; l is the length of the fluid pipeline, m;

[0027] ∑QΔt is the volume change caused by fluid exchange;

[0028] ΔV d represents the volume change of the promoting particles;

[0029] Δp is the change in pore pressure in the model, MPa; K is the bulk modulus of the fluid, GPa;

[0030] V d is the reservoir volume, m 3 ;

[0031] The remaining pore diameter w1 algorithm is calculated according to the following formula:

[0032]

[0033] w 0 is the residual pore diameter, m; F is the compressive normal force at the contact, N; F0 is the normal force when the tube pore diameter is reduced to half of its remaining pore diameter, N.

[0034] In a specific embodiment of the present invention, in the fracturing simulation test of the dense layer discrete element model obtained by microscopic adjustment, the dense layer CO2 fracturing results are obtained, including:

[0035] At the drilling area of the dense layer discrete element model obtained by microscopic adjustment, the fracturing borehole is set to be circular;

[0036] The area around the fracturing borehole is encrypted to form a fracturing surrounding area;

[0037] A fracturing simulation test is carried out;

[0038] Based on the results of the fracturing simulation test, the dense layer CO2 fracturing results are obtained.

[0039] The second object of the present invention is to provide a dense layer CO2 fracturing numerical simulation system based on the discrete element method, including:

[0040] The particle size sorting module is used to obtain the particle size sorting parameter distribution of the sandy conglomerate core based on the CT scan of the sandy conglomerate core;

[0041] The model establishment module is used to establish a dense layer discrete element model based on the particle size sorting parameter distribution;

[0042] The simulation module is used to obtain the dense layer CO2 fracturing results based on the dense layer discrete element model and the fracturing simulation test.

[0043] In a specific embodiment of the present invention, the simulation module includes an embedding sub-module, a test sub-module and an obtaining sub-module;

[0044] The embedding sub-module is used to embed the fracture condition and the fluid-solid coupling algorithm into the dense layer discrete element model;

[0045] The test sub-module is used to perform microscopic parameter adjustment based on the dense layer discrete element model obtained after embedding;

[0046] The obtained sub-module is used for a fracturing simulation test based on the compacted layer discrete element model obtained by micro-adjustment, and the CO2 fracturing result of the compacted layer is obtained.

[0047] The third object of the present invention is to provide an electronic device, including: a processor, the processor is coupled with a memory;

[0048] The memory is used for storing a computer program;

[0049] The processor is used for executing the computer program stored in the memory, so that the electronic device executes the method as described above.

[0050] The fourth object of the present invention is to provide a computer-readable storage medium, the computer-readable storage medium stores a program or an instruction, when the program or the instruction runs on a computer, the computer executes the method as described above.

[0051] The beneficial effects of the present invention:

[0052] The numerical simulation method and system for CO2 fracturing of a compacted layer based on the discrete element method provided by the present invention, on the basis of distinguishing the gravel particle distribution inside different compacted layers by CT scanning of the compacted layer core, introduces a dimensionless particle size sorting index, and then establishes a discrete element model of the compacted layer with different sorting indexes according to the particle size sorting index. The obtained discrete element model of the compacted layer can accurately reflect the physical object of the compacted layer core;

[0053] On this basis, in order to further improve the accuracy of the fracturing simulation result, the present invention embeds a fracture condition and a fluid-solid coupling algorithm in the discrete element model of the compacted layer, further ensuring the consistency between the simulation result and the test result;

[0054] Finally, a CO2 fracturing simulation test is carried out by using the embedded discrete element model of the compacted layer to obtain the CO2 fracturing result, and then the numerical simulation of CO2 fracturing is realized, making the simulation result more in line with the actual situation.

[0055] Other features and advantages of the present invention will be described in the following specification, and, in part, will be obvious from the specification, or will be understood by implementing the present invention. The objects and other advantages of the present invention can be realized and obtained by the structures pointed out in the specification, the claims and the drawings. Description of the Drawings

[0056] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0057] Figure 1 Shows a flowchart of a numerical simulation method for tight layer CO2 fracturing based on the discrete element method according to an embodiment of the present invention;

[0058] Figure 2 Shows a schematic diagram of core CT scanning according to an embodiment of the present invention;

[0059] Figure 3 Shows a schematic diagram of a discrete element model of a tight layer with different particle size sorting indexes according to an embodiment of the present invention;

[0060] Figure 4 Shows a schematic diagram of a fluid-solid coupling calculation domain according to an embodiment of the present invention;

[0061] Figure 5 Shows a schematic diagram of the distribution of fracturing drilling areas according to an embodiment of the present invention;

[0062] Figure 6 Shows a schematic diagram of the failure mode and fracture distribution of a fracturing drill according to an embodiment of the present invention;

[0063] Figure 7 Shows a framework diagram of a numerical simulation system for tight layer CO2 fracturing based on the discrete element method according to an embodiment of the present invention;

[0064] Figure 8 Shows a framework diagram of an electronic device according to an embodiment of the present invention;

[0065] In the figure:

[0066] Particle size sorting module 1; Model establishment module 2; Simulation module 3; Electronic device 300; Processor 301; Memory 302. Specific embodiments

[0067] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art without creative efforts based on the embodiments of the present invention belong to the scope of protection of the present invention.

[0068] AsFigure 1 As shown in Figure 1 , a numerical simulation method for CO2 fracturing of a tight layer based on the discrete element method according to an embodiment of the present invention includes:

[0069] Step S1: Based on the CT scan of the sandstone core, obtain the particle size sorting parameter distribution of the sandstone core;

[0070] Step S2: Based on the particle size sorting parameter distribution, establish a discrete element model of the tight layer;

[0071] Step S3: Based on the discrete element model of the tight layer and the fracturing simulation test, obtain the CO2 fracturing result of the tight layer.

[0072] In step S1, the obtaining the particle size sorting parameter distribution of the sandstone core based on the CT scan of the sandstone core includes:

[0073] Step A1: Perform a CT scan on the selected tight layer core to identify the distribution of gravel particles inside different tight layers. Figure 2 Exemplarily, different CT scan pictures of the tight layer core in the embodiment of the present invention are given. Figure 2 In Figure 2 , a is the CT scan picture of the a tight layer core, b is the CT scan picture of the b tight layer core, and c is the CT scan picture of the c tight layer core;

[0074] Step A2: Statistically analyze the tight layer gravel particles and the matrix as different groups respectively, and the average particle surface area of different gravel particles can be obtained, and the calculation is carried out according to formula (1);

[0075]

[0076] In formula (1), S a is the average area of the gravel particles, m is the number of gravel particles, and r i is the radius of the gravel particles;

[0077] Step A3: Based on the average particle surface area of different gravel particles, calculate the particle size sorting parameter, where the particle size sorting parameter H is calculated according to formula (2):

[0078]

[0079] Among them, S i is the area of the i-th gravel particle. When the distribution of gravel particles in the tight layer changes, the particle size sorting characteristics of the tight layer will also change accordingly. The higher the particle size sorting index, the worse the non-uniformity of the distribution of gravel particles.

[0080] In step S2, a discrete element model of the dense layer (abbreviated as DEM, the same below) is established based on the particle size sorting parameter distribution, that is, a discrete element model of the dense layer is established based on the different particle size sorting parameters (i.e., the particle size sorting parameter distribution) obtained in step S1. Figure 3 Exemplarily, a schematic diagram of the discrete element model of the dense layer with different particle size sorting indexes in the embodiment of the present invention is given. Figure 3 In, a is the discrete element model of the dense layer of the a dense layer core, b is the discrete element model of the dense layer of the b dense layer core, and c is the discrete element model of the dense layer of the c dense layer core. From Figure 2 and Figure 3 From the comparison, it can be seen that the dimensionless particle size sorting parameter distribution introduced in the present invention can well reflect the change of gravel particle distribution in the dense layer.

[0081] In step S3, based on the discrete element model of the dense layer and the fracturing simulation test, the numerical simulation results of CO2 fracturing in the dense layer are obtained, including:

[0082] Step B1: Embed the fracture condition and the fluid-solid coupling algorithm into the discrete element model of the dense layer;

[0083] Step B2: Based on the discrete element model of the dense layer obtained after embedding, perform microscopic parameter adjustment;

[0084] Step B3: Based on the fracturing simulation test of the discrete element model of the dense layer obtained after microscopic adjustment, obtain the CO2 fracturing result of the dense layer.

[0085] In step B1, the rock material in the DEM is modeled as a combination of small rigid circles (in 2D) or spherical particles (in 3D), and every two adjacent blocks are glued together. The parallel bond model is usually used to represent the continuous rock sample material. This bond acts on the cross-section between two particles and can transfer force and moment;

[0086] The parallel bond contact is the mechanical behavior of a finite-size cement-like material between two contacts, and the parallel bond establishes an elastic interaction between the contacts through normal, shear, and rotational springs. The motion of a particle is described by Newton's second law, and the contact force between particles is updated by the force-displacement law. The calculation formulas for the normal force, shear force, and bending moment of the bond are shown in Eqs. (3)-(5):

[0087]

[0088]

[0089]

[0090] In Eqs. (3)-(5), is the normal force (N) on the parallel bond, is the normal force (N) at the last moment on the parallel key, is the shear force (N) on the parallel key, is the shear force (N) at the last moment on the parallel key, is the torque (N*m) on the parallel key, is the torque (N*m) at the last moment on the parallel key, is the normal stiffness (MPa / m) of the parallel key, is the shear stiffness (MPa / m) of the parallel key, is the transverse contact area (m2) of the parallel key, is the moment of inertia (m4) of the cross-section of the parallel key, Δδ n is the normal increment (m) between parallel keys, δ s is the shear increment (m) between parallel keys, Δδ t is the torque increment (m) between parallel keys;

[0091] For the normal and tangential stiffness between parallel keys, they can be calculated and derived through the Young's modulus of the model itself. The main calculation formulas are as shown in Eqs. (6)-(7):

[0092]

[0093]

[0094] In Eqs. (6)-(7), E is the Young's modulus (MPa) of the model, L is the length of the parallel key. For ball-ball contact, it is equal to the sum of the two radii; for spherical surface contact, it is equal to the radius of the contact ball (m), r k is the ratio of the normal stiffness to the shear stiffness.

[0095] When the normal stress caused by tension exceeds the strength of the normal spring, the bonds between the contacting particles break and tensile microcracks are formed, while compression cannot damage these bonds. In addition, when the shear stress exceeds the strength of the shear spring, slip occurs between the two contacting particles and shear microcracks are formed. The two failure conditions of the maximum tensile stress criterion and the Mohr-Coulomb strength theory are that the following two conditions are satisfied simultaneously:

[0096] Condition 1: σ t ≥ pb_tan(8)

[0097] Condition 2:

[0098] In Eqs. (8)-(9), σ t is the tensile stress, MPa, τ is the shear stress, MPa, pb_tan is the tensile strength value, MPa, pb_coh is the shear strength value, MPa, σ nis the compressive stress value, MPa, is the friction angle set in the model.

[0099] After bond fracture, the bonded material and its accompanying forces, moments, and stiffness are removed from the model, and then the inter-particle forces are represented by a linear model with normal and shear springs, providing linear elastic (tension-free), frictional behavior. The calculation formulas for the normal and shear forces between particles are shown in Eqs. (10)-(11):

[0100] F n =(F n ) 0 +k n Δδ n (10)

[0101] F s =(F s ) 0 +k s Δδ s (11)

[0102] In Eqs. (10)-(11), F n is the normal force (N), (F n ) 0 is the normal force in the last step (N), F s is the shear force (N), (F s ) 0 is the shear force in the last step (N), k n is the normal stiffness (N / m), k s is the shear stiffness (N / m).

[0103] In step B1, the fluid-structure coupling algorithm ( Figure 4An exemplary schematic diagram of the fluid-structure interaction calculation domain in the embodiments of the present invention is given. Specifically, an explicit fluid-mechanics coupling method is adopted and implemented using the fluid-structure interaction program (PFC2D) in particle flow. The flow of fluid in porous media will generate a complex flow-stress deformation process. Different from the discrete particles in DEM, the fluid flow is usually simulated as a continuum in a fixed-coarse grid format. The flow pipes connecting adjacent reservoirs are assumed to be located at each contact point and perpendicular to the domain boundary. For the unbroken bonding condition, a residual pore diameter is set for the flow pipes. Therefore, due to the difference in fluid pore pressure, the fluid can be exchanged between adjacent reservoirs, and when the fluid flows into or out of the reservoir, the fluid pore pressure increases or decreases respectively. The residual pore diameter decreases with the increase of inter-particle compression. When the inter-particle bond is broken, the pore diameter of the flow pipe at the contact increases correspondingly and the flow resistance decreases. The fluid viscosity property and fluid penetration algorithm are considered and introduced into the DEM program. In the fluid flow algorithm, it is assumed that the pore throats connecting the fluids are flow channels, and a series of closed domains are created by connecting the centers of adjacent particles. Therefore, the following equation gives the volumetric laminar flow rate. For a two-dimensional model, the flow tubes can be assumed to be a set of parallel plates with an out-of-plane thickness of 1. The fluid is simulated with the Poiseuille equation, and the volumetric flow rate through the water flow pipe between two adjacent reservoirs can be given by the following formula:

[0104]

[0105] In Equation (12), w is the channel width (m), μ is the viscosity of the fracturing medium (mPa·s), dp is the pressure difference between both sides of the pipe (MPa), and l is the length of the fluid pipe (m);

[0106] The simulated fluid pore pressure distribution depends on the apparent volume of the reservoir and the fluid. The fluid exchange between adjacent reservoirs can change the local fluid pore pressure. The pore pressure acts on the surrounding particles as an equivalent body force, causing particle movement. In addition, the particle migration subsequently changes the apparent volume of the model, which in turn affects the fluid pore pressure. Finally, the change in the fluid pore pressure in the reservoir is calculated according to the following formula (13) based on the fluid bulk modulus and the apparent volume of the reservoir:

[0107]

[0108] ∑QΔt is the volume change caused by fluid exchange;

[0109] ΔV d represents the volume change contributing to the particles;

[0110] Δp is the change in pore pressure in the model, MPa; K is the bulk modulus of the fluid, GPa;

[0111] V d is the reservoir volume, m3 。

[0112] The forces acting on the particles can be divided into mechanical forces and hydraulic forces. The mechanical forces are caused by the interaction between particles, and the hydraulic forces are caused by the fluid pressure. The resultant force of the mechanical and hydraulic forces causes the particles to migrate, thereby changing the pore size of the flow tube. For open contacts, the pore size is equal to the actual opening at the contact and is modified by a multiplier less than 1. Since the fluid can still pass through the porous medium without cracks, for the case of only contacting particles, it is assumed that the remaining pore size decreases with the increase in the contact force due to compression, and the remaining pore size w1 algorithm is calculated according to Equation (14):

[0113]

[0114] In Equation (14), w 0 is the residual pore size, m; F is the compressive normal force at the contact, N; F0 is the normal force when the tube pore size is reduced to half of its residual pore size, N.

[0115] In step B2, based on the discrete element model of the compacted layer obtained after embedding, microparameters are adjusted, that is, for the discrete element model of the compacted layer processed in step B1, microparameters are adjusted, specifically:[[]]

[0116] First, the Brazilian splitting test and uniaxial test are carried out on the original compacted layer to obtain the conventional mechanical parameters of the compacted layer. The flat joint model is used to simulate the bonding between particles, and the parallel bond model is used between gravel particles and matrix particles. Then, microparameters are adjusted to finally obtain the basic parameters of the discrete element model of the compacted layer;

[0117] This is because the correct selection of microparameters is the key to numerical analysis. To ensure the accuracy of the numerical model, the consistency between the simulation results and the test results is achieved by adjusting the changes in microparameters.

[0118] In step B3, based on the fracturing simulation test of the discrete element model of the compacted layer obtained by micro-adjustment, the CO2 fracturing results of the compacted layer are obtained, including:

[0119] Step C1: At the drilling area of the discrete element model of the compacted layer obtained after embedding, the fracturing drill hole is set to be circular;

[0120] Step C2: The area around the fracturing drill hole is encrypted to form a fracturing surrounding area;

[0121] Step C3: Conduct a fracturing simulation test;

[0122] Step C4: Based on the results of the fracturing simulation test, the CO2 fracturing results of the compacted layer are obtained;

[0123] That is, in certain embodiments of the present invention, before the fracturing simulation test is performed, the drilling setting operation in the discrete element model of step C1 and step C2 is performed, and such operation is for a more realistic simulation of the sample fracturing test;

[0124] Among them, in the drilling area of ​​the discrete element model, the fracturing drilling hole is first set to be circular to prevent the tip stress concentration caused by uneven contact distribution in some areas, thereby preventing crack initiation during the fracturing process and generating complex rupture cracks;

[0125] Secondly, the surrounding area of ​​the fracturing drill hole is intensified to avoid the stress concentration caused by small holes or uneven particle size distribution in the surrounding area of ​​the drill hole, which may cause crack tip cracking during the fracturing process, thereby affecting the subsequent crack propagation;

[0126] Combining the above two points, we can try to avoid the problems of fracturing crack initiation and expansion caused by artificial discrete element modeling factors during the fracturing process;

[0127] Figure 5 Schematic diagram of the distribution of fracturing drilling areas in an embodiment of the present invention is shown.

[0128] In step C3-C4, the fracturing simulation test is performed based on the discrete element model processed in step C1-C2 to obtain the CO2 fracturing result of the dense layer. Figure 6 The following is an exemplary diagram of the damage morphology and crack distribution of the fracturing drill in the embodiment of the present invention. Figure 6 In the figure, a is the failure morphology diagram of the fracturing simulation test, and b is the schematic diagram of the crack distribution of the fracturing simulation test.

[0129] like Figure 7 As shown, a numerical simulation system for dense layer CO2 fracturing based on discrete element method according to an embodiment of the present invention includes:

[0130] Grain size sorting model 1 is used based on CT scanning of sandstone core to obtain the distribution of grain size sorting parameters of sandstone core;

[0131] The model building module 2 is used to build a dense layer discrete element model based on the particle size sorting parameter distribution;

[0132] The simulation module 3 is used to obtain the CO2 fracturing results of the dense layer based on the dense layer discrete element model and simulation test.

[0133] In an embodiment of the present invention, the simulation module 3 includes an embedding submodule, a testing submodule and an obtaining submodule;

[0134] The embedding submodule is used to embed the fracture conditions and fluid-solid coupling algorithm into the dense layer discrete element model;

[0135] The test sub-module is used to adjust the microscopic parameters based on the discrete element model of the dense layer obtained after embedding;

[0136] The acquisition sub-module is used to obtain the numerical simulation results of CO2 fracturing of the dense layer based on the discrete element model of the dense layer and the fracturing simulation test.

[0137] As Figure 8 shown, in some embodiments of the present invention, an electronic device is provided. The electronic device 300 includes: a processor 301, and the processor 301 is coupled to a memory 302;

[0138] The memory 302 is used to store a computer program;

[0139] The processor 301 is used to execute the computer program stored in the memory 302 so that the electronic device executes the method described in the above embodiments.

[0140] In some embodiments of the present invention, a computer-readable storage medium is provided. The computer-readable storage medium stores a program or instructions. When the program or instructions run on a computer, the computer is made to execute the method described in the above embodiments.

[0141] According to an embodiment of the present invention, the computer-readable storage medium may be a non-volatile computer-readable storage medium. For example, it may include but is not limited to: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present invention, the computer-readable storage medium may be any tangible medium that contains or stores a program, and the program can be used by or in combination with an instruction execution system, an electronic device, or a device.

[0142] Although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements on some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. Numerical simulation method for CO2 fracturing of tight layer based on discrete element method, Characterized in that, It includes: Based on the CT scan of the sandstone core, obtain the particle size sorting parameter distribution of the sandstone core; Based on the particle size sorting parameter distribution, establish a discrete element model of the tight layer; Based on the discrete element model of the tight layer and the fracturing simulation test, obtain the CO2 fracturing result of the tight layer.

2. The numerical simulation method for CO2 fracturing of tight layer based on discrete element method according to claim 1, Characterized in that, The particle size sorting parameter H is calculated according to the following formula: Among them, S a is the average area of the gravel particles, m is the number of gravel particles, r i is the radius of the gravel particles; S i is the area of the i-th gravel particle; The higher the particle size sorting index, the poorer the non-uniformity of the gravel particle distribution.

3. The numerical simulation method for CO2 fracturing of tight layer based on discrete element method according to claim 1, Characterized in that, Based on the discrete element model of the tight layer and the fracturing simulation test, obtain the numerical simulation result of CO2 fracturing of the tight layer, including: Embed the fracture condition and the fluid-solid coupling algorithm into the discrete element model of the tight layer; Based on the discrete element model of the tight layer obtained after embedding, perform microscopic parameter adjustment; Based on the fracturing simulation test of the discrete element model of the tight layer obtained by microscopic adjustment, obtain the CO2 fracturing result of the tight layer.

4. The numerical simulation method for CO2 fracturing of tight layer based on discrete element method according to claim 3, Characterized in that, The fracture condition is that the following two conditions are simultaneously satisfied: Condition 1: σ t ≥ pb_tan Condition 2: Among them, σ t is the tensile stress, in MPa, τ is the shear stress, in MPa, pb_tan is the tensile strength value, in MPa, pb_coh is the shear strength value, in MPa, σ n is the compressive stress value, in MPa, is the friction angle set by the model.

5. The numerical simulation method for CO2 fracturing of tight layer based on discrete element method according to claim 3, Characterized in that, The fluid-solid coupling algorithm is the fluid viscosity property and the fluid penetration algorithm.

6. The numerical simulation method for CO2 fracturing of tight layer based on discrete element method according to claim 5, Characterized in that, The fluid penetration algorithm includes the fluid pore pressure algorithm and the remaining pore diameter algorithm. Among them, the fluid pore pressure algorithm is calculated according to the following formula: where Q is the fluid volume flow rate, and w is the channel width, m; μ is the viscosity of the fracturing medium, mPa·s; dp is the pressure difference on both sides of the pipeline, MPa; l is the length of the fluid pipeline, m; ∑QΔt is the volume change caused by fluid exchange; ΔV d represents the volume change of the promoting particles; Δp is the change in pore pressure in the model, MPa; K is the bulk modulus of the fluid, GPa; V d is the reservoir volume, m 3 ; The remaining pore diameter w1 algorithm is calculated according to the following formula: w 0 is the residual aperture, m; F is the compressive normal force at the contact, N; F0 is the normal force when the tube aperture is reduced to half of its residual aperture, N.

7. The numerical simulation method for CO2 fracturing of tight layer based on discrete element method according to claim 3, Characterized in that, Based on the fracturing simulation test of the discrete element model of the tight layer obtained by microscopic adjustment, obtain the CO2 fracturing result of the tight layer, including: At the drilling area of the discrete element model of the tight layer obtained by microscopic adjustment, set the fracturing drill hole as a circle; Densify the area around the fracturing drill hole to form a fracturing surrounding area; Perform a fracturing simulation test; Based on the results of the fracturing simulation test, obtain the CO2 fracturing result of the tight layer.

8. Numerical simulation system for CO2 fracturing of tight layer based on discrete element method, Characterized in that, It includes: The particle size sorting module is used to obtain the particle size sorting parameter distribution of the sandstone core based on the CT scan of the sandstone core; The model establishment module is used to establish a discrete element model of the tight layer based on the particle size sorting parameter distribution; The simulation module is used to obtain the CO2 fracturing results of the tight layer based on the discrete element model of the tight layer and the fracturing simulation test.

9. The numerical simulation system for CO2 fracturing of tight layers based on the discrete element method according to claim 8, wherein, the simulation module includes an embedding sub-module, a test sub-module and an obtaining sub-module; the embedding sub-module is used to embed the fracture condition and the fluid-solid coupling algorithm into the discrete element model of the tight layer; the test sub-module is used to adjust the microscopic parameters based on the discrete element model of the tight layer obtained after embedding; the obtaining sub-module is used to obtain the CO2 fracturing results of the tight layer based on the fracturing simulation test of the discrete element model of the tight layer obtained by microscopic adjustment.

10. An electronic device, wherein, comprising: a processor, the processor is coupled with a memory; the memory, used to store a computer program; the processor, used to execute the computer program stored in the memory, so that the electronic device executes the method according to any one of claims 1 to 7.

11. A computer-readable storage medium, wherein, the computer-readable storage medium stores a program or an instruction, when the program or the instruction runs on a computer, the computer is enabled to execute the method according to any one of claims 1 to 7.

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