Method for simulating flowback value of fiber-containing proppant

Abstract

The invention relates to the technical field of hydraulic fracturing, in particular to a method for simulating a flowback numerical value of a fiber-containing proppant, which comprises the following steps of: establishing a flowback simplified crack grid model, and setting a crack fracturing fluid inlet and a fracturing fluid outlet; setting a proppant particle model, namely setting basic properties of particles and an inter-particle contact model, and calibrating parameters of the inter-particle contact model by utilizing a stacking experiment method; establishing a flexible fiber by using a Bonding V2 model, and calibrating the size of the fiber and parameters among particle elements in the Bonding V2 model; according to the set mass proportion, the fibers and the propping agent are stacked in the cracks; setting a flow equation, fracturing fluid material attributes and fracture inlet and outlet flow velocity parameters in finite element software; and reading the coupling file, starting to simulate flowback, and post-processing a calculation result. Through the method, the sand stabilizing and sand consolidating capabilities of different fiber lengths, different fiber concentrations and different fiber mixing proportions can be researched.

Description

Technical Field

[0001] The present invention relates to the technical field of hydraulic fracturing, and in particular to a numerical method for simulating flowback of fiber-containing proppants. Background Art

[0002] In order to reduce production costs and improve the effect of fracturing construction, the use of low-viscosity slick water to carry sand has become the main measure for fracturing construction of shale gas, tight gas and other reservoirs. Taking shale reservoirs as an example, volume fracturing has problems such as poor slick water carrying sand performance, long crack closure time, and weak clamping force of the crack wall on the proppant. During the backflow, the cracks in the shale reservoir may not be completely closed, so the clamping force of the crack wall on the proppant is relatively weak. Under the high-speed flushing of fracturing fluid and natural gas, the proppant is dragged into the wellbore.

[0003] There are two main reasons for proppant backflow. One is that the flow velocity in the fracture is too high during flowback, which causes the proppant on the sand bank surface to fluidize, thereby causing a large amount of proppant backflow. The other is that the proppant filling layer forms a hemispherical sand arch near the perforation. When the mechanical balance of the sand body is destroyed, the filling layer becomes unstable and backflows.

[0004] Using fiber is a method to improve the strength of sand bodies. In the existing technology, the fiber action mechanism is mainly analyzed through mathematical models and experimental methods, and the research mainly focuses on the fiber sand stabilization mechanism when the mechanical balance of the sand body is destroyed. There are fewer studies on the fiber sand control mechanism during fluid fluidization of sand embankments, and the methods are relatively simple. Summary of the invention

[0005] In order to solve the above technical problems, the present invention proposes a numerical method for simulating the backflow of fiber-containing proppants. By establishing a fiber model and using the fluid-solid coupling method, the sand stabilization mechanism of the fiber is studied. That is, the sand stabilization and sand consolidation capabilities of different fiber lengths, different fiber concentrations and different fiber mixing ratios can be studied, thereby further studying the mechanism of fiber control of proppant backflow.

[0006] The present invention is achieved by adopting the following technical solutions:

[0007] A numerical method for simulating fiber-containing proppant flowback comprises the following steps:

[0008] Step S1. Establish a simplified fracture grid model for flowback, and set the fracture fracturing fluid inlet and outlet;

[0009] Step S2. Setting the proppant particle model, including setting the basic properties of the particles and the inter-particle contact model, and then calibrating the parameters of the inter-particle contact model using a stacking experiment method; using the Bonding V2 model to establish flexible fibers, and calibrating the fiber size and the parameters between each particle element in the Bonding V2 model;

[0010] Step S3. stacking the fiber and the proppant in the fracture according to a set mass ratio;

[0011] Step S4. In the finite element software, set the flow equation, the material properties of the fracturing fluid, and the flow rate parameters of the fracture inlet and outlet;

[0012] Step S5: Read the coupling file, start flowback simulation, and post-process the calculation results.

[0013] The method also includes step S6. Changing the fiber length, fiber concentration and the mixing ratio of different fibers to perform multiple flowback simulations.

[0014] The fracture grid model is established based on a fluid mechanics method.

[0015] The inter-particle contact model adopts the Hertz-Mindlin no-slip contact model.

[0016] The parameters of the particle contact model calibrated by the stacking test method specifically refer to:

[0017] The stacking angle of the proppant particles is obtained through stacking experiments. The parameters of the inter-particle contact model are adjusted in the discrete software, that is, the friction coefficient, restitution coefficient and dynamic friction coefficient between the particles are adjusted. The slope angle formed by the proppant stacking on the plane under different parameters is obtained by numerical simulation and compared with the stacking angle. If the error is within 10%, the parameter corresponding to the slope angle is calibrated as the parameter of the inter-particle contact model.

[0018] Calibrating the parameters between the particle elements in the Bonding V2 model specifically refers to: calibrating the parameters between the particle elements in the Bonding V2 model by trial and error.

[0019] The calibration of the parameters between the particle elements in the Bonding V2 model specifically refers to: statistically analyzing the fiber distribution angles in the flow area of ​​the crack; injecting fibers into the cracks, adjusting the parameters between the particle elements in the Bonding V2 model by trial and error, observing the fiber angles obtained by numerical simulation at the same flow rate, and comparing them with the statistical fiber distribution angles in the flow area of ​​the cracks. If they match, the corresponding parameters are calibrated as the parameters between the particle elements in the Bonding V2 model.

[0020] The parameters between the particle elements in the Bonding V2 model include normal stiffness per unit area, normal range, tangential stiffness per unit area, tangential range, critical normal stress and critical shear stress.

[0021] The flow equation is a k-ε model.

[0022] In step S5, the calculation results include the motion state of the particles, the particle speed and the data of the force on the fibers.

[0023] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0024] 1. The present invention provides a numerical method for simulating the flowback of fiber-containing proppants. First, various models required for numerical simulation are established. Then, the sand stabilization and consolidation capabilities of different fiber lengths, fiber concentrations, and different fiber mixing ratios during flowback are studied by fluid-solid coupling. It has the advantages of simple operation and high calculation efficiency.

[0025] 2. The existing technology mainly obtains the constitutive equation of the fiber through uniaxial experiments, but the diameter of the fiber used in actual fracturing is extremely small, and it is difficult to calibrate it through tensile and compression experiments. The present invention obtains the basic parameters of the fiber by trial and error through the obtained fiber distribution angle, which is more in line with the actual situation.

[0026] 3. The study of sand stability by numerical simulation method has the characteristics of high computational efficiency. It takes 12 hours to complete a set of experimental evaluations of the stability of the flushing or fiber-reinforced proppant filling layer. However, a set of flowback numerical simulation methods only requires 4 hours of simulation on a 48-core computer. The computational efficiency is greatly improved. It is conducive to the rapid screening of fiber parameters on site. Among them, the experimental evaluation of the stability of the fiber-reinforced proppant filling layer specifically refers to: the fiber and proppant are evenly mixed and placed between the plates of the diversion chamber of the proppant tester to form an artificial fracture of about 3 to 4 mm thick, and then the plate is slowly pressurized to simulate the gradual closure of the formation fracture and the clamping of the proppant. Finally, the artificial fracture is flushed with different concentrations of fracturing fluid, and the critical sand flow rate of the proppant produced by the artificial fracture is recorded. At the same time, a comparative experiment is carried out, that is, only the proppant is used for the experiment, and then the critical sand flow rate of the artificial fracture is recorded. By comparing the two, the contribution of the fiber to the stability of the enhanced proppant filling layer can be quantitatively evaluated.

[0027] 4. The sand stabilization and consolidation capabilities of different fiber lengths and fiber concentrations during flowback were studied. We found that after increasing the fiber length and fiber concentration, the sand bank was more difficult to be washed away during fluid scouring. For example, the critical sand production velocity of 1.2% fiber concentration was 2.21m / s, while the critical sand production velocity of 0.4% fiber concentration was 1.8m / s. This shows that increasing the fiber concentration effectively improves the sand stability of the sand body. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments, wherein:

[0029] Figure 1 It is a schematic diagram of the force condition of the fiber during the backflow in the present invention;

[0030] Figure 2 It is a schematic diagram of the results of the stacking experiment in the present invention;

[0031] Figure 3 It is a schematic diagram of the results of numerical simulation in the present invention;

[0032] Figure 4 It is a schematic diagram of the flexible fiber model in the present invention;

[0033] Figure 5 It is a schematic diagram of the fiber proppant stacking result in the present invention. DETAILED DESCRIPTION

[0034] Example 1

[0035] As a basic embodiment of the present invention, the present invention includes a numerical method for simulating fiber-containing proppant flowback, comprising the following steps:

[0036] Step S1. Establish a simplified fracture grid model for flowback, and set the fracture fracturing fluid inlet and outlet.

[0037] Step S2. Setting the proppant particle model, including setting the basic properties of the particles and the inter-particle contact model, and then calibrating the parameters of the inter-particle contact model using the stacking experiment method. Using the Bonding V2 model to establish flexible fibers, calibrate the fiber size and the parameters between each particle element in the Bonding V2 model.

[0038] Step S3: According to a set mass ratio, the fiber and the proppant are stacked in the fracture.

[0039] Step S4. In the finite element software, set the flow equation, fracturing fluid material properties, and fracture inlet and outlet flow rate parameters.

[0040] Step S5: Read the coupling file, start flowback simulation, and post-process the calculation results.

[0041] Example 2

[0042] As a preferred embodiment of the present invention, the present invention includes a numerical method for simulating fiber-containing proppant flowback, comprising the following steps:

[0043] Step S1. Establish a simplified fracture grid model for flowback based on a fluid mechanics method, and set the fracture fracturing fluid inlet and outlet.

[0044] Step S2. Setting the proppant particle model, including setting the basic properties of the particles and the inter-particle contact model, and then calibrating the parameters of the inter-particle contact model using the stacking experiment method. The inter-particle contact model adopts the Hertz-Mindlin no-slip contact model. The Bonding V2 model is used to establish flexible fibers, and the fiber size and the parameters between each particle element in the Bonding V2 model are calibrated.

[0045] Step S3: According to a set mass ratio, the fiber and the proppant are stacked in the fracture.

[0046] Step S4. In the finite element software, set the flow equation, the material properties of the fracturing fluid, and the flow rate parameters of the fracture inlet and outlet;

[0047] Step S5. Read the coupling file, start the flowback simulation, and post-process the calculation results. Specifically, read the journal script file to couple the discrete element software and the finite element software, and post-process the results after the flowback simulation, including the particle motion state, particle velocity, fiber force and other data.

[0048] Step S6. Change the fiber length, fiber concentration and different fiber mixing ratios, perform multiple flowback simulations, study the morphological changes of the sand bank during the flowback process and the mechanical properties of fiber sand stabilization, and analyze the sand stabilization and consolidation capabilities of different fiber lengths, different fiber concentrations and different fiber mixing ratios.

[0049] Example 3

[0050] As another preferred embodiment of the present invention, the present invention includes a numerical method for simulating flowback of fiber-containing proppants, comprising the following steps:

[0051] Step S1. Establish a simplified fracture grid model for flowback, and set the fracture fracturing fluid inlet and outlet.

[0052] Step S2: Setting the proppant particle model, including setting the basic properties of the particles and the inter-particle contact model, and then calibrating the parameters of the inter-particle contact model using a stacking experiment method.

[0053] Among them, the parameters of the particle contact model calibrated by the stacking test method specifically refer to:

[0054] The stacking angle of proppant particles is obtained through stacking experiments. The parameters of the inter-particle contact model are adjusted in the discrete software, that is, the friction coefficient, restitution coefficient and dynamic friction coefficient between particles are adjusted. The slope angle formed by the accumulation of proppant on the plane under different parameters is obtained by numerical simulation and compared with the stacking angle. If the error is within 10%, the parameter corresponding to the slope angle is calibrated as the parameter of the inter-particle contact model.

[0055] The flexible fiber is established using the Bonding V2 model, and the fiber size and the parameters between the particle elements in the Bonding V2 model are calibrated. The parameters between the particle elements in the Bonding V2 model are calibrated specifically by using a trial and error method to calibrate the parameters between the particle elements in the Bonding V2 model.

[0056] Step S3: According to a set mass ratio, the fiber and the proppant are stacked in the fracture.

[0057] Step S4. In the finite element software, set the flow equation, fracturing fluid material properties, and fracture inlet and outlet flow rate parameters.

[0058] Step S5: Read the coupling file, start flowback simulation, and post-process the calculation results.

[0059] Step S6. Change the fiber length, fiber concentration and different fiber mixing ratios, perform multiple flowback simulations, study the morphological changes of the sand bank during the flowback process and the mechanical properties of fiber sand stabilization, and analyze the sand stabilization and consolidation capabilities of different fiber lengths, different fiber concentrations and different fiber mixing ratios.

[0060] Example 4

[0061] As a best embodiment of the present invention, the present invention includes a numerical method for simulating fiber-containing proppant flowback, comprising the following steps:

[0062] Step S1. Establish a simplified fracture grid model for flowback based on a fluid mechanics method, and set the fracture fracturing fluid inlet and outlet.

[0063] Step S2. Setting the proppant particle model, including setting the basic properties of the particles and the inter-particle contact model, and then using the stacking test method to calibrate the parameters of the inter-particle contact model. The basic properties of the particles include mass, shear modulus, Poisson's ratio, shape and particle size, etc. The inter-particle contact model is the Hertz-Mindlin no-slip contact model:

[0064] F c,ij =F cn，ij +F ct，ij

[0065] In the formula, F c,ij is the contact force between particles i and j, N; F cn，ij is the normal contact force between particles i and j, N; F ct，ij is the tangential contact force between particles i and j, N.

[0066] Furthermore, the calculation method of the normal contact force is:

[0067] F cn，ij=k n,ij δ n,ij n+γ n,ij u n,ij

[0068] In the formula, k n,ij is the normal stiffness coefficient; δ n,ij is the normal displacement between the colliding particles, m; n is the normal unit vector between the contacting particles; γ n,ij is the normal dissipation coefficient; u n,ij is the normal component of the relative velocity between the colliding particles.

[0069] Furthermore, the calculation method of the normal stiffness coefficient and the normal dissipation coefficient is:

[0070]

[0071]

[0072]

[0073]

[0074] Where Y * is the elastic modulus of the effective elastic model, Pa; Y i is the elastic modulus of spherical particle i, Pa; Y j is the elastic modulus of spherical particle j, Pa; R * is the effective particle radius, m.

[0075] The tangential contact force is calculated as:

[0076] F ct，ij =k t,ij δ t,ij t+γ t,ij u t,ij

[0077] In the formula, k t,ij is the tangential stiffness coefficient; δ t,ij is the normal displacement between the colliding particles, m; t is the tangential unit vector between the contacting particles; γ t,ij is the tangential dissipation coefficient; u t,ij is the tangential component of the relative velocity between the colliding particles.

[0078] Tangential stiffness coefficient k t,ij and the tangential dissipation coefficient γ t,ij It is also calculated from the physical parameters of the particles such as Young's modulus and Poisson's ratio:

[0079]

[0080]

[0081] in,

[0082] The parameters of the particle contact model calibrated by the stacking test method specifically refer to:

[0083] The stacking angle of the proppant particles is obtained through the stacking experiment. That is, a hollow cylinder is used for the proppant stacking experiment. 1 / 3 of the volume of proppant is added to the hollow cylinder, and then the hollow cylinder is slowly lifted to allow the particles to flow out of the cylinder until all the particles are naturally stacked on the bottom plate, and the stacking angle of the corresponding proppant particles is calculated.

[0084] A hollow cylinder model of the same size was established, 1 / 3 volume of proppant was added to the hollow cylinder model, and then the cylinder was lifted until the particles formed a complete and stable particle pile on the chassis. By adjusting the parameters of the inter-particle contact model in the discrete software, that is, adjusting the friction coefficient, restitution coefficient and dynamic friction coefficient between the particles, the slope angle formed by the accumulation of proppant on the plane under different parameters was obtained by numerical simulation. Among them, the setting of the dynamic friction coefficient between particles is related to the sliding friction force when sliding occurs between particles. The inter-particle collision restitution coefficient refers to the ratio of the relative velocity of two particles after the collision to the relative velocity before the collision. The inter-particle friction coefficient refers to the binding force between particles when the particles are stationary.

[0085] The slope angle obtained by numerical simulation is compared with the stacking angle obtained by the stacking experiment. If the error is within 10%, it means that the parameter setting is correct. The parameters corresponding to the slope angle are calibrated as the parameters of the inter-particle contact model.

[0086] The Bonding V2 model is used to establish flexible fibers, calibrate the fiber size, and calibrate the parameters between the particle elements in the Bonding V2 model by trial and error. Specifically, the fiber is formed by the bonding of particles one by one, and the bonding bond force model in the Bonding V2 model is:

[0087] δF n =-v n S n Aδt

[0088] δF t =-v t S t Aδt

[0089] δM n =-ω n S t Aδt

[0090]

[0091] A=πR B 2

[0092]

[0093] In the above formula, F n and F t are the normal force and tangential force on the bond, S n and S t are the normal and shear stiffness, V n and V t are the normal and tangential velocities of the particle, R B is the bond radius and δt is the time step.

[0094] When the normal and tangential stresses exceed the critical values, the judgment criteria for the destruction of the bonding bonds between particles are:

[0095]

[0096]

[0097] Medium: σ max and τ max are the critical values ​​of normal and tangential shear stress, respectively.

[0098] Fibers are formed by connecting particles with bonding bonds. The properties of particles and bonding bonds are generally obtained by uniaxial compression tests in EDEM software. This embodiment calibrates the parameters between each particle element in the Bonding V2 model by trial and error, specifically including:

[0099] The flow area of ​​the crack is photographed, and the fiber distribution angle in the flow area of ​​the crack is statistically analyzed.

[0100] The fiber is injected into the crack, and the parameters between the particle elements in the Bonding V2 model are adjusted by trial and error. The fiber angle obtained by numerical simulation at the same flow rate is observed and compared with the statistical fiber distribution angle in the flow area of ​​the crack. If they match, the corresponding parameters are calibrated as the parameters between the particle elements in the Bonding V2 model. The parameters between the particle elements in the Bonding V2 model include normal stiffness per unit area, normal range, tangential stiffness per unit area, tangential range, critical normal stress and critical shear stress.

[0101] Step S3. The fibers and proppants are stacked in the fracture according to the set mass ratio, and the stacking is stopped when the stacking height reaches the fracture entrance.

[0102] Step S4. In the finite element software, set the flow equation, fracturing fluid material properties, and fracture inlet and outlet flow rate parameters. Specifically, in the CFD Fluent software, set the fracturing fluid viscosity and density, inlet flow rate, and outlet pressure, and set the flow equation to the k-ε model:

[0103]

[0104]

[0105] In the formula, G k is the turbulent kinetic energy generated by the mean velocity gradient, G b is the turbulent kinetic energy generated by buoyancy, Y M is the fluctuation caused by transition diffusion in compressible turbulence, kg / (m 3 ·s); σ k , σ ε is the Prandtl number for the k equation and the ε equation, the default value is σ k =1.0,σ ε =1.3; C 1ε , C 2ε , C μ is a constant, C 1ε =1.44, C 2ε =1.9, C μ =0.09; S k , S ε is a user-defined source term; μ t is the eddy viscosity,

[0106] Step S5. Read the journal script file to couple the discrete element software and the finite element software, start simulating the flowback, and post-process the calculation results, including the particle motion state, particle velocity, fiber force and other data.

[0107] Step S6. Change the fiber length, fiber concentration and different fiber mixing ratios, perform multiple flowback simulations, study the morphological changes of the sand bank during the flowback process and the mechanical properties of fiber sand stabilization, and analyze the sand stabilization and consolidation capabilities of different fiber lengths, different fiber concentrations and different fiber mixing ratios.

[0108] Example 5

[0109] As another preferred embodiment of the present invention, the present invention includes a numerical method for simulating flowback of fiber-containing proppants, comprising the following steps:

[0110] Step S1. Establish a simplified fracture grid model for flowback, and set the fracture fracturing fluid inlet and outlet. Specifically, use ICEM software to establish a simplified fracture model with a fracture width of 3 mm, a fracture height of 4 mm, and a fracture length of 3 mm, and define the fracturing fluid inlet and outlet as the flow channel for simulating flowback.

[0111] Step S2: Setting the proppant particle model, including setting the basic properties of the particles and the inter-particle contact model, and then calibrating the parameters of the inter-particle contact model using a stacking experiment method.

[0112] Establish a proppant spherical model and set parameters such as particle size, Young's modulus and Poisson's ratio. Figure 2 A hollow cylinder with a diameter of 4 mm and a height of 100 mm was used for the proppant stacking experiment. 1 / 3 volume of proppant was added into the cylinder, and then the cylinder was slowly lifted to allow the particles to flow out of the cylinder until all the particles naturally stacked on the glass bottom plate, and the stacking angle of the proppant particles was calculated.

[0113] Refer to the instruction manual Figure 3 , a hollow cylinder model of the same size was established, 1 / 3 volume of proppant was added to the cylinder, and then the cylinder was lifted at 0.015m / s until the particles formed a complete and stable particle pile on the bottom plate, and the slope angle formed by the accumulation of proppant on the plane under different parameters was obtained by numerical simulation. The slope angle was compared with the accumulation angle, and if the error was within 10%, the parameter corresponding to the slope angle was calibrated as the parameter of the particle contact model.

[0114] This method is used to calibrate the friction coefficient, restitution coefficient and dynamic friction coefficient between particles.

[0115] The flexible fiber was established using the Bonding V2 model, and the parameters between the fiber size and each particle element in the Bonding V2 model were calibrated.

[0116] The fiber diameter is 40um, so spherical particles with a diameter of 40um are established as the particle elements of the fiber. Figure 4 , use bonding bonds to bond the particle elements to form 3mm long fibers. Set the contact radius of the particle element to 24um (1-1.2 times the particle element radius). Set the parameters between the particle elements in the Bonding V2 model by researching the literature. The normal stiffness per unit area, normal range, tangential stiffness per unit area, tangential range, critical normal stress, and critical shear stress are set to 1.5e+12N / m3, 1N / m3, 1e+12N / m3, 1N / m3, 2e+11Pa, and 3.1e+11Pa, respectively.

[0117] Step S3. Refer to the instructions attached Figure 5, the fibers and proppants are stacked in the fractures according to a set mass ratio.

[0118] The mass of a single fiber and a single proppant were calculated. According to the set fiber injection mass fraction of 1.2%, the ratio of proppant to fiber injection was calculated to be about 40:1, that is, one fiber was injected for every 40 proppant injections. When the fiber proppant accumulation reached the fracturing fluid inlet, the particle injection was stopped.

[0119] Step S4. In the finite element software, set the flow equation, fracturing fluid material properties, and fracture inlet and outlet flow rate parameters.

[0120] In the Fluent software, the fluid flow equation was set to the k-ε model, the fracturing fluid viscosity was 5 mPa·s, the fracturing fluid inlet velocity was 1 m / s, and the fracturing fluid outlet was set to the pressure outlet.

[0121] Step S5. Read the coupling file, start simulating the backflow, and post-process the calculation results. The fiber stress during the backflow can be found in the attached manual. Figure 1 shown.

[0122] Read the coupling journal file, start the calculation after the coupling results, and post-process the data such as the particle motion state, particle velocity, fiber force, etc.

[0123] It can be seen that the present invention uses the CFD-DEM coupling method to simulate the flushing result of the fluid above the sand bank on the proppant particles when the proppant is returned. This method can study the sand stabilization and sand consolidation capabilities of different fiber lengths, different fiber concentrations and different fiber mixing ratios, so as to further study the mechanism of fiber control of proppant return. For example, the critical sand production velocity of 1.2% concentration fiber is 2.21m / s, while the critical sand production velocity of 0.4% concentration fiber is 1.8m / s. It shows that after increasing the fiber concentration, the sand stability of the sand body is effectively improved.

[0124] In summary, after reading the present invention document, ordinary technicians in this field can make various other corresponding transformation schemes based on the technical scheme and technical concept of the present invention without creative mental labor, which all fall within the scope of protection of the present invention.

Claims

1. A numerical method for simulating fiber-containing proppant flowback, characterized in that: The following steps are involved: Step S1. Establish a simplified fracture grid model for flowback, and set the fracture fracturing fluid inlet and outlet; Step S2. Setting the proppant particle model, including setting the basic properties of the particles and the inter-particle contact model, and then calibrating the parameters of the inter-particle contact model using a stacking experiment method; using the Bonding V2 model to establish flexible fibers, and calibrating the fiber size and the parameters between each particle element in the Bonding V2 model; Step S3. stacking the fiber and the proppant in the fracture according to a set mass ratio; Step S4. In the finite element software, set the flow equation, the material properties of the fracturing fluid, and the flow rate parameters of the fracture inlet and outlet; Step S5: Read the coupling file, start flowback simulation, and post-process the calculation results.

2. A numerical method for simulating fiber-containing proppant flowback according to claim 1, characterized in that: The method also includes step S6. Changing the fiber length, fiber concentration and the mixing ratio of different fibers to perform multiple flowback simulations.

3. A numerical method for simulating fiber-containing proppant flowback according to claim 1, characterized in that: The fracture grid model is established based on a fluid mechanics method.

4. A numerical method for simulating fiber-containing proppant flowback according to claim 1, characterized in that: The inter-particle contact model adopts the Hertz-Mindlin no-slip contact model.

5. A numerical method for simulating fiber-containing proppant flowback according to claim 4, characterized in that: The parameters of the particle contact model calibrated by the stacking test method specifically refer to: The stacking angle of the proppant particles is obtained through stacking experiments. The parameters of the inter-particle contact model are adjusted in the discrete software, that is, the friction coefficient, restitution coefficient and dynamic friction coefficient between the particles are adjusted. The slope angle formed by the proppant stacking on the plane under different parameters is obtained by numerical simulation and compared with the stacking angle. If the error is within 10%, the parameter corresponding to the slope angle is calibrated as the parameter of the inter-particle contact model.

6. A numerical method for simulating fiber-containing proppant flowback according to claim 1, characterized in that: Calibrating the parameters between the particle elements in the Bonding V2 model specifically refers to: calibrating the parameters between the particle elements in the Bonding V2 model by trial and error.

7. A numerical method for simulating fiber-containing proppant flowback according to claim 6, characterized in that: The calibration of the parameters between the particle elements in the Bonding V2 model specifically refers to: statistically analyzing the fiber distribution angles in the flow area of ​​the crack; injecting fibers into the cracks, adjusting the parameters between the particle elements in the Bonding V2 model by trial and error, observing the fiber angles obtained by numerical simulation at the same flow rate, and comparing them with the statistical fiber distribution angles in the flow area of ​​the cracks. If they match, the corresponding parameters are calibrated as the parameters between the particle elements in the Bonding V2 model.

8. A numerical method for simulating fiber-containing proppant flowback according to claim 6 or 7, characterized in that: The parameters between the particle elements in the Bonding V2 model include normal stiffness per unit area, normal range, tangential stiffness per unit area, tangential range, critical normal stress and critical shear stress.

9. A numerical method for simulating fiber-containing proppant flowback according to claim 1, characterized in that: The flow equation is a k-ε model.

10. A numerical method for simulating fiber-containing proppant flowback according to claim 1, characterized in that: In step S5, the calculation results include the motion state of the particles, the particle speed and the data of the force on the fibers.

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