Numerical simulation method for whole process of sand carrying-sand control assisted by fracturing flexible material of unconventional oil and gas reservoir

Abstract

The invention relates to the technical field of oil and gas field development engineering, in particular to an unconventional oil and gas reservoir fracturing flexible material assisted sand carrying-sand control whole process numerical simulation method which comprises the following steps: 1) acquiring a basic parameter data set; 2) respectively establishing corresponding liquid phase-solid phase interaction force models for the proppant and the flexible material; and 3) establishing a numerical model according to the liquid phase-solid phase interaction force model of the proppant and the flexible material, and simulating the whole process of flexible material-proppant cluster conveying, laying and backflow. Through the numerical simulation method provided by the invention, the change conditions of the flexible material-proppant cluster laying form, such as a visual cloud picture, an effective laying area, a particle average flow velocity change curve, flow conductivity and fracture permeability, under different working condition parameters can be simulated; therefore, objective evaluation of the efficient laying effect and the flow conductivity of the fracturing propping agent assisted by the flexible material is realized, and suggestions are provided for site construction parameter optimization.

Description

Technical Field

[0001] The present invention belongs to the technical field of oil and gas field development engineering, and particularly relates to a full-process numerical simulation method for sand carrying and controlling assisted by flexible materials in unconventional oil and gas reservoir fracturing. Background Art

[0002] Unconventional oil and gas reservoirs, characterized by low porosity and low permeability, require fracturing for effective development. Currently, volumetric fracturing, a key technology for the efficient development of unconventional oil and gas resources, faces two major technical challenges. First, during the fracturing process, the poor sand-carrying properties of slickwater hinder proppant transport to the distal end of the fracture, preventing optimal fracture propagation. Second, during flowback, the initial fracture walls have a weak ability to hold the proppant, leading to significant proppant backflow during flowback, which in turn impacts post-fracturing productivity. Using flexible materials to assist with sand transport and control is an effective approach to addressing these challenges. While improving the sand-carrying properties of fracturing fluids, it can significantly reduce proppant backflow. However, the mechanism of action of flexible materials in assisting sand transport and stabilization remains unclear, leading to a lack of theoretical guidance for optimizing flexible material construction parameters and developing flexible material modifications. Therefore, it is necessary to investigate the mechanisms of sand transport and control employed by flexible materials in fracturing unconventional oil and gas reservoirs.

[0003] Numerous researchers have conducted extensive laboratory experiments and numerical simulations on the sand-carrying and sand-control capabilities of flexible materials. Experimental research methods for studying the sand-carrying capacity of flexible materials fall into two main categories: one is to indirectly study the sand-carrying performance of flexible materials through sedimentation experiments involving flexible materials mixed with proppants; the other is to directly assess the sand-carrying performance of the materials through sand-carrying experiments involving the addition of flexible materials. Numerical simulation methods primarily simulate the transport, placement, and backflow of proppants in fractures under different operating conditions by establishing corresponding numerical models, with relatively simple simulation stages. Although current experimental research has provided preliminary insights into the sand-carrying and sand-control capabilities of flexible materials, the microscopic control mechanisms of flexible materials over proppant transport, placement, and backflow remain unclear. Numerical simulations lack comprehensive simulations of the entire process of proppant transport, placement, and backflow under the influence of flexible materials, due to difficulties in modeling flexible materials and setting particle parameters. This ultimately results in a lack of mechanisms and evaluation methods for the impact of flexible materials on proppant placement and fracture flow capacity. Summary of the Invention

[0004] To overcome the problems in the prior art, the present invention provides a numerical simulation method for the entire process of sand carrying and sand control assisted by flexible materials in unconventional oil and gas reservoir fracturing. The technical solution of the present invention is as follows:

[0005] A numerical simulation method for the entire process of flexible material-assisted sand carrying and sand control in unconventional oil and gas reservoir fracturing includes the following steps:

[0006] 1) obtaining a basic parameter data set, wherein the basic parameter data set includes fracture physical parameters, proppant physical parameters, flexible material physical parameters, fluid parameters, and contact parameters;

[0007] 2) Establish corresponding liquid-solid interaction force models for proppants and flexible materials respectively;

[0008] 3) Based on the liquid-solid interaction force model of proppants and flexible materials, a numerical model was established. The basic parameter data set was substituted into the numerical model to simulate the entire process of flexible material-proppant cluster transportation, laying, and reflux. The influence of different parameters on proppant laying and reflux was analyzed to optimize the on-site construction parameters.

[0009] Preferably, the crack physical property parameters in step 1) include one or more parameters of crack length, crack height, crack width, wall Young's modulus, wall Poisson's ratio, and crack inlet geometry parameters.

[0010] Preferably, the proppant physical property parameters in step 1) include one or more parameters of proppant particle size, proppant density, proppant Poisson's ratio, proppant Young's modulus, proppant inlet velocity, and proppant surface shape.

[0011] Preferably, the physical property parameters of the flexible material in step 1) include one or more parameters of the flexible material geometric size, the flexible material Poisson's ratio, the flexible material Young's modulus, the flexible material inlet velocity, and the number of flexible material nodes.

[0012] Preferably, the fluid parameters in step 1) include one or more parameters of fluid inlet flow rate, fluid viscosity, fluid density, and turbulence intensity.

[0013] Preferably, the contact parameters in step 1) include one or more parameters of proppant-proppant collision recovery coefficient, proppant-wall collision recovery coefficient, proppant-flexible material collision recovery coefficient, flexible material-flexible material collision recovery coefficient, proppant-proppant static friction coefficient, proppant-wall static friction coefficient, proppant-flexible material static friction coefficient, flexible material-flexible material static friction coefficient, proppant-proppant kinetic friction coefficient, flexible material-wall contact recovery coefficient, flexible material-wall contact kinetic friction coefficient, flexible material-wall contact static friction coefficient, proppant-wall kinetic friction coefficient, proppant-flexible material kinetic friction coefficient, flexible material-flexible material kinetic friction coefficient, flexible material-proppant adhesion distance, flexible material-flexible material adhesion distance, flexible material-flexible material adhesion coefficient, and flexible material-proppant adhesion coefficient.

[0014] Preferably, the liquid-solid interaction force model of the proppant and the flexible material in step 2) is as follows:

[0015] buoyancy:

[0016]

[0017] Among them, V s —Particle volume, m 3 ρ l —Carrying liquid density, kg / m 3 ; g—gravity coefficient, 9.8N / kg.

[0018] Proppant drag:

[0019]

[0020]

[0021] Among them, F ls —Drag force of fluid on proppant particle phase (s), N; C D —Drag coefficient, dimensionless; ε s —The volume fraction of proppant particles, dimensionless; u s —Motion velocity of proppant particles, m / s; d s —Particle size of proppant particles, m; u l —Fracturing fluid viscosity, mPa·s; Re s —Particle Reynolds number, dimensionless;

[0022] Flexible material drag:

[0023]

[0024]

[0025]

[0026]

[0027] Among them, u rel —Flow velocity of the fluid relative to the flexible material, m / s, u—Flow velocity of the fluid without the disturbance of the flexible material, m / s; v p —Speed at the geometric center of the flexible material particle, m / s; —Relative velocity of the fluid in the tangential direction, m / s; — tangential component of the characterization direction; —Relative velocity of the fluid in the normal direction, m / s; F lf —Drag force of the fluid on the flexible material phase (f), N; ρ l —Fluid density, kg / m 3 ;d f —Diameter of the flexible material particle phase, m.

[0028] Preferably, step 2) further comprises:

[0029] When dynamic modeling is performed on proppant particle materials, the geometric shape of the proppant particle materials is meshed using fixed triangles, and the mesh structure remains unchanged during the calculation process;

[0030] When dynamic modeling of flexible materials, the geometric shape of the flexible material is structurally divided using a multi-node cylindrical model, and the flexible material is treated as a cylindrical particle chain that is evenly distributed and in contact with each other along the axis.

[0031] Preferably, a constant adhesion force model is used to simulate the mutual adhesion characteristics of the modified fibers:

[0032]

[0033] Where F n,adh —Normal adhesive contact force, N; s n —Contact normal overlap, m; m1, m2—masses of the contact particles, kg; g—gravitational acceleration, taken as 9.8 m / s 2 ; δ adh —Model parameters.

[0034] Preferably, the entire process of flexible material-assisted sand carrying and sand control includes the transportation, laying and backflow processes of the flexible material-proppant cluster.

[0035] In another aspect, the present invention provides a terminal for numerical simulation of the entire process of sand carrying and sand control assisted by flexible materials in unconventional oil and gas reservoir fracturing, comprising:

[0036] Memory for storing computer programs;

[0037] A processor is used to execute the computer program to implement the steps of any one of the numerical simulation methods described above.

[0038] On the other hand, the present invention provides a computer-readable storage medium, characterized in that a computer program is stored on the computer-readable storage medium, and the computer program is executed by a processor to implement the steps of any one of the numerical simulation methods described above.

[0039] The present invention provides a full-process numerical simulation method for flexible material-assisted sand carrying and control in unconventional oil and gas reservoir fracturing. By using different node structure divisions and force models to achieve particle modeling of proppants and flexible materials, a microscopic model of flexible material-proppant clusters transporting and refluxing in hydraulic fractures is constructed using a coupled CFD-DEM method. The efficient placement effect and conductivity of flexible material-assisted fracturing proppants can be comprehensively evaluated based on visual cloud maps of the flexible material-proppant cluster placement morphology, visual cloud maps of conductivity, effective placement area and average particle velocity curves, and differences in fracture permeability under different working conditions. The numerical simulation method constructed by the present invention is quick to adjust, the full-process simulation is visually intuitive, and the results are accurate and reliable. The present invention is conducive to promoting theoretical research related to flexible material fracturing and provides guidance for optimizing flexible material parameters during field engineering practice. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 This is a flow chart of the whole process numerical simulation method of the present invention;

[0041] Figure 2 Schematic diagram of the flexible material rod chain structure in an embodiment of the present invention;

[0042] Figure 3 Schematic diagram of force analysis and deformation analysis of the flexible material in an embodiment of the present invention;

[0043] Figure 4 Schematic diagram of CFD-DEM coupling in an embodiment of the present invention;

[0044] Figure 5 Schematic diagram of the geometric model of the sedimentation device and the sedimentation velocity of the flexible material in the example of the present invention;

[0045] Figure 6 Schematic diagram of experimental and simulation results of a particle transport reflux device in an example of the present invention;

[0046] Figure 7 A stacked contour diagram of experimental and simulation results of a particle transport reflux device in an example of the present invention;

[0047] Figure 8 Schematic diagram of the simulation of the entire process of flexible material-assisted sand carrying and sand control in an example of the present invention;

[0048] Figure 9 A schematic diagram of a flow chart for calculating fracture flow capacity in an embodiment of the present invention;

[0049] Figure 10 The graphs of EPPA, the number of particles retained in the fracture, proppant velocity, fracture width, and inter-particle contact force over time in the examples of the present invention are shown;

[0050] Figure 11 Schematic diagram of proppant flow rate and fluid flow rate at different times in an example of the present invention;

[0051] Figure 12 The effect of flexible material concentration on proppant delivery in the examples of the present invention: (a) Change in effective proppant placement area; (b) Change in proppant velocity; (c) Proppant placement morphology and velocity at t = 0.1 s; (d) Proppant placement morphology and velocity at t = 5 s.

[0052] Figure 13 Effect of flexible material concentration on proppant flowback in the examples of the present invention: (a) Change in effective proppant placement area; (b) Change in proppant velocity; (c) Proppant placement morphology and velocity at t = 0.1 s; (d) Proppant placement morphology and velocity at t = 5 s;

[0053] Figure 14 The formation and development of the flexible material-proppant cluster structure in the examples of the present invention;

[0054] Figure 15 Schematic diagram of the flow capacity of the particle pile in the particle transport stage, crack closure stage and particle backflow end stage in the example of the present invention. DETAILED DESCRIPTION

[0055] The present invention will be described in detail below with reference to the accompanying drawings.

[0056] To further clarify the objectives, technical solutions, and advantages of the present invention, the present invention is further described below in conjunction with the accompanying drawings and examples. It should be understood that the specific embodiments described herein are intended only to illustrate the present invention and are not intended to limit it. The following describes a specific embodiment of the present invention using the example of a composite plugging system using flaky fibers and spherical particles.

[0057] Assisting fracturing operations with flexible materials is a common method of on-site hydraulic fracturing modification. Currently, the mechanism by which flexible materials, represented by fibers, affect proppant transport, placement, and backflow is still unclear. Indoor experiments make it difficult to observe the microscopic information of proppant transport, placement, and backflow under the action of flexible materials throughout the entire process, and it is difficult to quantitatively describe the mechanism of action of flexible materials. Numerical simulations of the entire process of proppant transport, placement, and backflow under the influence of flexible materials are lacking due to difficulties in modeling flexible materials and calibration of particle physical parameters. The above-mentioned defects lead to insufficient mechanisms and theories for the influence of flexible materials on the placement effect of hydraulic fracturing proppant and the flow capacity of fractures.

[0058] To address this technical problem, the present invention adopts a computational fluid dynamics-discrete element method (CFD-DEM) coupling method to establish a microscopic model of the transport, placement and backflow of flexible material-proppant clusters in hydraulic fractures, analyzes the flow, aggregation and deposition behavior of flexible material-proppant clusters in hydraulic fractures, and explores the mechanism of action of flexible materials on proppant transport, placement and backflow and its influence law, thereby being able to evaluate the fracture flow capacity under different working conditions, and providing technical support for the optimization of flexible material sand fracturing construction parameters and the research and development of flexible material modification.

[0059] like Figure 1 As shown, the present invention provides a numerical simulation method for the entire process of sand carrying and sand control assisted by flexible materials in fracturing unconventional oil and gas reservoirs, comprising the following steps:

[0060] 1) obtaining a basic parameter data set, wherein the basic parameter data set includes fracture physical parameters, proppant physical parameters, flexible material physical parameters, fluid parameters, and contact parameters;

[0061] In step 1), it is necessary to first obtain the relevant physical parameters of the corresponding proppant and flexible material migration in the fracture, which mainly include: fracture physical parameters, proppant physical parameters, flexible material physical parameters, fluid parameters, contact parameters, etc.

[0062] Specifically, the fracture physical parameters may include fracture length, fracture height, fracture width, wall Young's modulus, wall Poisson's ratio, and fracture flow inlet geometry parameters; the proppant physical parameters may include proppant particle equivalent diameter, proppant particle density, proppant particle Poisson's ratio, proppant particle Young's modulus, proppant particle inlet velocity, etc.; the flexible material physical parameters may include flexible material geometric dimensions, flexible material Poisson's ratio, flexible material Young's modulus, flexible material inlet velocity, and flexible material node number; the fluid parameters include fluid inlet flow velocity, fluid viscosity, and fluid density; the contact parameters may include proppant-proppant collision recovery coefficient, proppant-wall collision recovery coefficient, proppant-flexible material Material collision recovery coefficient, flexible material-flexible material collision recovery coefficient, proppant-proppant static friction coefficient, proppant-wall static friction coefficient, proppant-flexible material static friction coefficient, flexible material-flexible material static friction coefficient, proppant-proppant kinetic friction coefficient, flexible material-wall contact recovery coefficient, flexible material-wall contact kinetic friction coefficient, flexible material-wall contact static friction coefficient, proppant-wall kinetic friction coefficient, proppant-flexible material kinetic friction coefficient, flexible material-flexible material kinetic friction coefficient, flexible material-proppant adhesion distance, flexible material-flexible material adhesion distance, flexible material-flexible material adhesion coefficient, flexible material-proppant adhesion coefficient.

[0063] 2) For two different particle models of proppant and flexible material, corresponding liquid-solid interaction force models are established respectively;

[0064] In the present invention, the CFD-DEM method is used to study the physical processes of transportation, laying and backflow of flexible material-proppant clusters in hydraulic fractures. When establishing its numerical model, the calculation model includes the liquid phase control equation, solid phase control equation, solid phase contact force model, and liquid-solid phase interaction force model under the Euler-Lagrangian framework.

[0065] In a specific embodiment, when constructing the liquid phase governing equation, the infinitesimal fluid element is used as the research object, and then the continuity equation based on the conservation of mass and the momentum equation based on Newton's second law are derived. The continuity equation and the momentum equation need to consider the influence of the volume fraction of the solid phase in the liquid phase.

[0066] In a specific embodiment, when constructing the solid-phase governing equations, the discrete element method (DEM) in a Lagrangian coordinate system is used to solve the solid-phase particles. The velocity and position of the particles per unit time are calculated using the external forces acting on the particles, and both follow Newton's second law. The forces acting on the solid-phase particles during motion are considered, as are the forces between the particles, the walls, and the fluid.

[0067] In a specific embodiment, the solid phase contact force model may respectively adopt the Hertzian spring-dashpot normal force model and the Mindlin-Deresiewicz tangential force model.

[0068] In addition, the liquid phase control equation, the solid phase control equation, and the solid phase contact force model may also adopt other models in the prior art, and their specific embodiments will not be repeated in this application.

[0069] It should be noted that, in the present invention, different liquid-solid interaction force models are adopted for the proppant and the flexible material, respectively.

[0070] Among them, flexible materials are linear particles with a small diameter and a certain length. They have a large aspect ratio and their tensile strength is much higher than their bending strength and shear strength, which makes them easily deformed under external forces. When performing dynamic modeling on flexible materials, the geometric shape of the flexible material particles adopts a composite structure connected by spherical cylinders, and adjacent units are connected by columnar rod chains. When the flexible material is subjected to external forces, only the joints are deformed, and the force and torque are transmitted through the connected cylinders, such as Figure 2 The above method is used to simulate the flexibility of the material.

[0071] Two forces and moments in different directions are generated between the flexible material elements. Figure 3Figure 1 shows a schematic diagram of the force analysis between flexible material elements. Different forces act on the midpoint of the cylindrical link chain near the joint. In response to linear and angular deformation, forces and moments opposite to the deformation are generated at the endpoints of the centerline segments of two adjacent spherical cylinders. The force and moment vectors can be decomposed into normal and shear components. The liquid-solid interaction force model for the flexible material is as follows:

[0072]

[0073] In this formula Represents the normal and tangential forces (N) and moments (N·m), n i and t i The unit vector of the contact plane. The cohesive force and moment keep the constituent particles connected within the flexible material and resist deformation of the flexible material under external forces.

[0074] The linear deformation of the connection point is caused by the relative displacement of the connected elements, which is represented by the relative displacement vector d rel To quantify, decompose the displacement into normal components and tangential component The unit vector is defined as There are two types of angular deformation between flexible material elements. The first is torsion deformation, which occurs when two adjacent elements rotate around their respective axes at different angles. The second is bending deformation, which occurs when one element rotates relative to another element in the same plane defined by its centerline. Figure 3 The following is a deformation analysis diagram of the flexible material unit. The angle θ described in the figure B The linear and angular deformations of flexible materials are described using a linear elastic model, in which each force and moment is proportional to the corresponding linear or angular joint deformation:

[0075]

[0076] In this formula They represent normal stiffness (N·m), tangential stiffness (N·m), torsional stiffness (N·m / rad) and bending stiffness (N·m / rad), respectively. θ T ,θ B They represent normal relative displacement (m), tangential relative displacement (m), torsion angle (rad), and bending angle (rad), respectively.

[0077] A columnar rod chain structure model is used to describe the flexible material. For the calculation of fluid drag, the Gidaspow model is used for proppant particles, and the Marheineke & Wegener model is used for flexible material particles.

[0078] In the Gidaspow model, when the liquid volume fraction ε l When the liquid volume fraction ε is less than or equal to 0.8, the drag force does not change with the particle Reynolds number; when the liquid volume fraction ε l When it is greater than 0.8, the Reynolds number of the particle will affect the drag force. The specific calculation formula is as follows:

[0079]

[0080]

[0081] Where, s refers to the proppant particle phase; F ls is the drag force of the fluid on the proppant particle phase (s), N; C D is the drag coefficient, dimensionless; ε s is the volume fraction of the proppant particle phase, dimensionless; u s is the velocity of proppant particles, m / s; d s is the particle size of the proppant particle phase, m; u l is the viscosity of the fracturing fluid, mPa·s; Re s is the particle Reynolds number, dimensionless. The specific calculation formula of the Marheineke & Wegener model is as follows:

[0082] u rel =uv p (5)

[0083]

[0084]

[0085]

[0086] Where u rel is the flow velocity of the fluid relative to the flexible material, m / s; u is the flow velocity of the fluid without the disturbance of the flexible material, m / s; ν p is the velocity of the geometric center of the flexible material particle, m / s; u τ rel is the relative flow velocity in the tangential direction of the fluid, m / s; is the tangential component, representing the direction, dimensionless; u n rel is the relative velocity of the fluid in the normal direction, m / s; F lf is the drag force of the fluid on the flexible material particle phase (f), N; ρ l is the fluid density, kg / m 3 ;d f is the diameter of the flexible material particle phase, m.

[0087] In liquid-solid multiphase flow, proppants and flexible material particles are subject to a variety of liquid forces, including drag, buoyancy, added mass, pressure gradient, Basset, Saffman, and Magnus forces. However, not all forces are equally important. In practical calculations, depending on the research question, only the forces with the greatest impact may be considered. In this paper, we ignore the forces with lesser impact and consider the buoyancy and drag of the liquid on the solid phase.

[0088]

[0089] Where, F F is the buoyancy force on the particle, N; V S is the volume of the particle, m 3 ρ l is the density of the carrying liquid, kg / m 3 ;d s is the equivalent diameter of the particle, m; g is the gravity coefficient, 9.8 N / kg.

[0090] 3) Based on the liquid-solid interaction force model of proppants and flexible materials, a numerical model is established, and the basic parameter data set is substituted to simulate different working conditions.

[0091] The corresponding numerical model can be established in combination with the force model and solved using the CFD-DEM method. The coupling implementation allows the DEM solver and CFD solver to work in parallel, using N processors for fluid phase solution and M processors or GPU processing for particle phase solution to solve the DEM part. Figure 4 Figure 2 shows a schematic diagram of the bidirectional coupling algorithm. During the particle system solution, the volume fraction of the particle phase and initial interaction terms are first calculated using the DEM solver and transferred to the CFD solver. The initial fluid flow field calculation, including physical properties such as velocity and pressure, is performed on the CFD solver and transferred to the DEM solver. This process is repeated until the total simulation time is reached. To ensure computational stability, the CFD time step is typically kept at least 10 times longer than the DEM time step. The model's mesh size and boundary conditions are determined based on the model.

[0092] Furthermore, in one embodiment, to verify the effect of flexible materials on proppants, the sedimentation of a single proppant in still water was used as a case study for model verification. A numerical model with a 1:1 resemblance to the experimental model was established to simulate the sedimentation process of the proppant in liquids containing flexible materials such as fibers and in pure liquids.

[0093] like Figure 5Figure 2 shows the geometric model of the settling device and a schematic diagram of the flexible material settling velocity described in the present invention. The proppant hydrostatic settling experimental results closely match the simulation results, verifying the accuracy of the model parameter settings and demonstrating the reliability of the constructed two-phase fluid-solid coupling model. Furthermore, the results demonstrate that the terminal velocity of the settling particles is reduced by 66.3% with the addition of the flexible material compared to without it. This demonstrates the flexible material's ability to reduce settling velocity and support proppant particle migration.

[0094] Based on the same inventive concept as the method of the present invention, the present invention provides an electronic terminal, comprising a memory, a processor, and a computer program stored in the memory and runnable on the processor. When the processor executes the computer program, the steps of the full-process simulation method of flexible material-assisted sand carrying and sand control in unconventional oil and gas reservoir fracturing are implemented.

[0095] In addition, the present invention also provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, it implements the steps of the full-process simulation method of flexible material-assisted sand carrying and sand control in unconventional oil and gas reservoir fracturing.

[0096] It will be understood by those skilled in the art that embodiments of the present invention may be provided as methods, systems, computer terminals, or computer program products. Thus, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0097] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowcharts and / or block diagrams, as well as combinations of processes and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowcharts and / or block diagrams. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0098] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0099] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0100] Example 1

[0101] In a computational example, Figure 6 As shown in FIG, the geometric model established by the numerical simulation is a 1:10 reduction simulation of the real visual crack experimental device, and the size of the crack geometry is 5 mm × 400 mm × 3000 mm.

[0102] Secondly, the inlet velocity of the particle fluid flow changes by adjusting the magnitude of the inlet velocity. The standard k-epsilon (2eqn) was selected for the fluid turbulence model. For the wall function of the fluid field, a near-wall treatment with an scalable wall function was selected. A fine mesh model (mesh count 240,000) was used to ensure mesh independence, and the rationality of the fine mesh model was demonstrated by comparing different mesh models. Based on the collection and calculation of fluid parameters in fracturing operations using flexible materials, such as fibers, the fluid turbulence intensity was set to 5%, and the flow rate and viscosity parameters simulated in the basic simulation were determined. The particle size, density, and geometric characteristics of the fibers and proppants were all 1:1 reproductions of the real materials. The microscopic contact parameters between the flexible material, proppant, and wall were obtained through laboratory experiments and calibrated through virtual experiments. Detailed basic parameters are shown in Table 1.

[0103] Table 1 Basic parameters

[0104]

[0105]

[0106] Figure 6This is a schematic diagram of the numerical simulation results of flexible material fracturing proppant delivery. The results show that there is good consistency between indoor experiments and numerical simulations. After adding flexible materials such as fibers, the laying distance and height of the proppant are increased. The flexible material is interspersed in the proppant, which is similar to the indoor simulation results, further verifying the reliability of the model. Figure 7 For the comparison of the accumulation profiles between the experiment and the numerical simulation, there is a certain deviation between the numerical simulation and experimental results, especially at the fracture mouth. This is because the particle inlet is set as a circular hole boundary in the experiment, while in the present invention, a square boundary is adopted to allow the flexible material to mix smoothly into the fracture, which reduces the strong vortex flushing effect of the jet at the inlet, resulting in a higher sand pile accumulation near the wellbore.

[0107] Example 2

[0108] In Example 2, the numerical simulation method provided by the present invention is used to simulate the above-mentioned fracture geometry model. Figure 8 As shown in the figure, the whole process of the fracturing procedure includes the transportation stage, the crack closure stage, the backflow stage, and the sand pile stabilization stage. By simulating the whole process of the flexible material fracturing operation, the influence of factors such as flexible material concentration, flexible material length, flexible material filling method, fluid flow rate, fluid viscosity, etc. on the proppant transportation stage, backflow stage, and the fracture flow capacity of each stage is studied, providing guidance for on-site engineers. It is worth noting that the fracture flow capacity is obtained by selecting a part of the area (2mm×5mm×10mm) after the proppant is transported, closed, and backflowed, extracting the position information of the proppant particles in the area, and extracting and reconstructing the geometry through Comsol with matlab, and then calculating the cross-sectional permeability of the particle accumulation body after dividing the fine grid through the central section, so as to analyze the fracture flow capacity. As shown in the figure, the whole process of the fracturing procedure includes the transportation stage, the crack closure stage, the backflow stage, the backflow stage, and the backflow stage. Figure 9 Figure 2 shows a flow chart of fracture flow capacity calculation.

[0109] All simulation parameters in Example 2 are consistent with those used in the particle settling simulation for model validation in Example 1. Using flexible materials as representative fibers as an example, a scheme was designed to simulate the entire process of flexible material-assisted sand carrying and control. The main simulation schemes are shown in Table 2, where flexible material injection method 4 represents full-process injection, 1 represents confining and supplementary injection, 2 represents secondary injection, and 3 represents tertiary injection. Parameters in bold represent the basic model parameters: fiber concentration 0.5%, fiber length 6 mm, primary injection, return velocity 0.25 m / s, and fluid viscosity 1 mPa·s.

[0110] Table 2 Simulation scheme settings

[0111]

[0112] It is worth noting that in Example 2, in order to quantitatively characterize the morphology of the proppant sand pile, the effective proppant paving area percentage (EPPA) was used for quantitative description, which is defined as:

[0113]

[0114] Where S Proppant is the plane area of sand bank accumulation in the crack, m 2 ;S Fracture , crack plate area, m 2 .

[0115] like Figure 10 As shown in Figure 1, the curves of EPPA, number of particles retained in the fracture, proppant velocity, fracture width and inter-particle contact force over time are shown. Figure 11 As shown, the sand pile morphology, proppant velocity and fluid flow rate at different times are displayed. Figure 10 and Figure 11 The results show that in the proppant delivery stage (from 0s to 5s), the amount of proppant increases linearly, while the effective proppant paving area increases slowly at first and then increases approximately linearly. This is because the particles have a high movement speed in the initial injection stage, and a large number of particles are still in suspension. Figure 11 As shown in the figure with t=1s, the proppant pile gradually develops with the increase of transport time. It first accumulates upwards and then gradually accumulates towards the far end of the fracture after reaching the equilibrium height. Figure 11 After the transport phase, the fracture closure phase begins (from 5s to 6s), and the fracture width decreases continuously, causing the contact force between particles to increase continuously. At the same time, the pump is stopped, causing the liquid velocity to be 0, which in turn causes the proppant particles to lose their power source and begin to settle, as shown in Figure 11 As shown in Figure 2, t = 6s. Subsequently, the flowback phase begins (from 6s to 11s), and the particles in the fracture flow back into the wellbore. The number of particles decreases, resulting in a continuous decrease in the effective paving area in the fracture. The flowback phase can be roughly divided into two stages. The first is that in the early stage, the edge of the sand pile is not clamped and is quickly washed away by the fluid, resulting in a sharp decrease in the contact force between the particles, as shown in Figure 2. Figure 11 As shown in the figure t=7s. Subsequently, the fluid channel above the proppant sand pile becomes larger, the fluid velocity slows down, the contact force between the particles remains stable, the particles slowly roll on the contour of the proppant sand pile, and steadily flow back into the wellbore, as shown in the figure. Figure 11 As shown in the figure, t = 9s. Finally, the clamping force on the particles and the fluid force are balanced, making the sand pile stable, as shown in the figure. Figure 11 As shown in the figure, t=11s.

[0116] like Figure 12The figure shows the effect of flexible material concentration on proppant transport. The calculation method of effective proppant laying area is as follows: Figure 12 As shown in the local grayscale image in (a), the proppant velocity map is converted into a grayscale map, and then the grayscale values of the image are separated to depict the outline of the proppant sand pile, and finally the effective paving area of the proppant is obtained. Figure 12 As can be seen from the curve in (a), with the increase in the concentration of flexible material, the effective paving area of the proppant after 5s is 0.41, 0.58 and 0.69, respectively, which is an increase of 18.82%, 58.63% and 99.1% compared with the case without adding flexible material. These changes show that the increase in the concentration of flexible material first promotes the expansion of the effective paving area, but as the concentration further increases, the increase gradually decreases, and finally reaches a maximum value before declining, which are 75.28%, 152.04% and 84.54% respectively. This shows that there is an optimal flexible material concentration, which makes the flexible material sand carrying effect most significant. Figure 12 (b) It can be seen that the addition of flexible materials mainly enhances the average velocity of proppant particles. With the increase of the concentration of flexible materials, the average velocity of particles after 5 seconds is 0.034m / s, 0.039m / s and 0.049m / s, respectively, which is an increase of 1.4%, 16.7% and 47.48% compared with the case without adding flexible materials. The trend of the growth rate is similar to the change of the effective paving area, which first increases and then decreases, and is 5.86%, 99.84% and 61.48% respectively. It also shows that there is an optimal concentration of flexible materials, which makes the sand carrying effect the best. Combined with Figure 12 (b) with Figure 12 From the analysis results in (c) and (d), it can be seen that the addition of flexible materials significantly changed the proppant transport pattern. The flexible materials formed a complex spider web structure in the liquid, hindering the sedimentation of the proppant. At the same time, the proppant and fibers migrated to the far end of the fracture in the form of clusters, enabling the proppant to be transported over longer distances, such as Figure 14 As the flexible material concentration increases, more flexible material-proppant clumps appear in the fracture, allowing the proppant to be transported farther and over a larger effective paving area in the same amount of time. This phenomenon is attributed to the fluffy clumps formed by the flexible material and proppant, which have a larger volume and can more easily and quickly accumulate in the fracture, thereby improving proppant delivery efficiency.

[0117] like Figure 13 The figure shows the effect of flexible material concentration on proppant flowback. Figure 13 (a) It can be seen that after 5s of backflow, the effective laying area of the proppant increased by -17.6%, 17.2% and 137.4% compared with the case without fiber. When no fiber was added, the effective laying area of the proppant decreased rapidly at the beginning of the backflow, and then remained stable. Figure 13 As can be seen from the black curve in (b), the reason why the proppant reflux velocity is faster in the initial stage is that the unfilled part of the channel is narrow and the flow velocity is faster. At the same time, the edge of the proppant sand pile is unstable and easily thrown up, resulting in rapid reflux. Figure 13 As shown by the pink mark in (c), after the addition of the flexible material, as the concentration of the flexible material increases, the flexible material-proppant clusters become larger and more numerous, resulting in an increase in the initial proppant effective area, as shown in Figure 13 As shown in (c). As the fiber concentration increases from 0.25% to 1%, during the reflux process, the rate of decrease of the effective paving area of the proppant first increases and then slows down, with the rate of decrease being 0.0438 / s, 0.0547 / s, and 0.0227 / s, respectively. This is because as the concentration of the flexible material increases, the force between the flexible material-proppant clusters that resists the movement of the particles and the force of the liquid on the clusters gradually balance. Figure 13 It can also be seen in (b) that after adding fibers, since the proppant and the flexible material move together in the form of clusters, the average movement speed of the proppant after adding the flexible material is greater than the average speed of the proppant without adding fibers, which leads to a faster decrease in the effective paving area of the support after adding the flexible material. Figure 13 (a) and Figure 13 (d) It can also be seen that when the flexible material concentration is 0.25%, the flexible material does not effectively prevent particle backflow, resulting in an effective placement area smaller than that without fiber after 5 seconds of backflow. As the flexible material concentration increases, the initial proppant placement area increases, resulting in a smaller unfilled area, a higher proppant flow rate, and a faster backflow rate. However, overall, when the flexible material concentration exceeds 0.25%, a good effective placement area is maintained after backflow.

[0118] After the sand pile is stable at the end of each stage, a portion of the sand pile space is taken to calculate the permeability. Figure 15 As shown in the figure, the permeability and flow field changes of the sand pile after proppant sand pile delivery, fracture closure, and proppant return are shown. As the concentration of flexible material increases, the fracture permeability increases exponentially. When no flexible material is added, the fracture permeability after proppant return is only 1.38×10 -8 m 2 , the crack permeability after adding 0.25%, 0.5%, and 1% flexible materials were 1.21×10 -7 m 2 , 3.46×10 -7 m 2 ,2.64×10 -8 m 2The permeability increased by one to two orders of magnitude, significantly improving the fracture's conductivity. This is because the addition of the flexible material formed a loose flexible material-proppant cluster structure, significantly improving the proppant placement structure, resulting in a larger pore space and greater fracture permeability. At different flexible material concentrations, the fracture permeability was highest after the transport phase, lowest during the fracture closure phase, and recovered somewhat during the reflow phase. After fracture closure, the fracture permeability lost an average of nearly 70% compared to pre-closure. After proppant reflow, the fracture permeability increased by 20% compared to pre-reflow. This is because the proppant reflow redirected the displacement between the particles and the flexible material, making the flow space in the fracture more unobstructed and leading to increased permeability.

[0119] The present invention provides a numerical simulation method for the entire process of flexible material-assisted sand carrying and sand control in unconventional oil and gas reservoir fracturing. The method realizes particle modeling of proppants and flexible materials through different grid structure divisions and force models, and constructs a microscopic model of the entire process of transportation, laying and backflow of flexible material-proppant clusters in hydraulic fractures through integrated CFD-DEM. The simulation results can be analyzed based on the visualization cloud map of the laying morphology of the flexible material-proppant clusters, the effective laying area of the flexible material-proppant clusters and the average particle flow velocity change curve, the visualization cloud map of the conductivity of the flexible material-proppant clusters, and the difference in fracture permeability under different working conditions to evaluate the efficient laying effect and conductivity of the flexible material fracturing proppant. The model is quick to adjust, the simulation process is visually intuitive, and the results are accurate and reliable. The present invention is conducive to promoting research on flexible material fracturing and provides technical support for field engineers to optimize the flexible material addition parameters.

[0120] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A numerical simulation method for the entire process of sand carrying and sand control assisted by flexible materials in unconventional oil and gas reservoir fracturing, comprising the following steps: 1) obtaining a basic parameter data set, wherein the basic parameter data set includes fracture physical parameters, proppant physical parameters, flexible material physical parameters, fluid parameters, and contact parameters; 2) Establish corresponding liquid-solid interaction force models for proppants and flexible materials respectively; 3) Based on the liquid-solid interaction force model of proppants and flexible materials, a numerical model was established and substituted into the basic parameter data set to simulate the entire process of flexible material-proppant cluster transportation, laying and reflux.

2. The full-process numerical simulation method of flexible material-assisted sand carrying and sand control according to claim 1, wherein the fracture physical property parameters in step 1) include one or more parameters of fracture length, fracture height, fracture width, wall Young's modulus, wall Poisson's ratio, and fracture inlet geometry parameters.

3. The full-process numerical simulation method of flexible material-assisted sand carrying and sand control according to claim 1, wherein the proppant physical property parameters in step 1) include one or more parameters selected from the group consisting of proppant particle size, proppant density, proppant Poisson's ratio, proppant Young's modulus, proppant inlet velocity, and proppant surface shape.

4. The method for numerically simulating the whole process of sand carrying and sand control assisted by a flexible material according to claim 1, wherein the flexible material physical property parameters in the step 1) include one or more parameters selected from the group consisting of flexible material geometric dimensions, flexible material Poisson's ratio, flexible material Young's modulus, flexible material inlet velocity, and flexible material node number.

5. The full-process numerical simulation method of flexible material-assisted sand carrying and sand control according to claim 1, wherein the fluid parameters in step 1) include one or more parameters of fluid inlet flow velocity, fluid viscosity, fluid density, and turbulence intensity.

6. The method for numerically simulating the entire process of sand carrying and controlling assisted by flexible materials according to claim 1 further comprises, in step 2): When dynamic modeling is performed on proppant particle materials, the geometric shape of the proppant particle materials is meshed using fixed triangles, and the mesh structure remains unchanged during the calculation process; When dynamic modeling of flexible materials, the geometric shape of the flexible material is structurally divided using a multi-node cylindrical model, and the flexible material is treated as a cylindrical particle chain that is evenly distributed and in contact with each other along the axis.

7. The method for numerically simulating the entire process of flexible material-assisted sand carrying and sand control according to claim 1, wherein step 2) further comprises: The constant adhesion force model is used to simulate the mutual adhesion characteristics of modified fibers: Where F n,adh —Normal adhesive contact force, N; s n —Contact normal overlap, m; m1, m2—the mass of the contact particles, kg; g—gravitational acceleration, taken as 9.8 m / s 2 ; δ adh —Model parameters.

8. The numerical simulation method for the entire process of flexible material-assisted sand carrying and sand control according to claim 1, wherein the entire process of flexible material-assisted sand carrying and sand control includes the transportation, laying and reflux processes of the flexible material-proppant cluster.

9. A full-process numerical simulation terminal for flexible material-assisted sand carrying and sand control in unconventional oil and gas reservoir fracturing, comprising: memory for storing computer programs; A processor, configured to execute the computer program to implement the steps of the numerical simulation method according to any one of claims 1 to 8.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, and the computer program is executed by a processor to implement the steps of the numerical simulation method according to any one of claims 1 to 8.

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