Simulation method for perforating completion under simulated formation conditions

Abstract

The present invention discloses a simulation method for perforating completion under simulated formation conditions. Based on the results of sensitivity analysis of material constitutive equation parameters and material experiment results, random modeling is performed on the material constitutive equation parameters to obtain a parameter probability model. Random parameters are obtained by sampling the parameter probability model, and a basic finite element model is built. The optimal mesh parameters of the finite element model are determined through mesh independence analysis of the basic finite element model. Sensitivity analysis is performed on the model parameters of the finite element model, and orthogonal test analysis is carried out on the model parameters in the finite element model. The optimal parameters are determined according to the sensitivity analysis results and the orthogonal test analysis results. A perforating completion finite element simulation model under simulated formation conditions is established based on the determined optimal parameters, and simulation analysis is carried out. The present invention can more accurately simulate the real situation under formation conditions, can provide high-precision results for the evaluation of perforating completion effects under real formation conditions, and provides support for the formulation of perforating completion schemes.

Description

Technical Field

[0001] The present invention relates to a simulation method for perforating completion under simulated formation conditions, which is mainly used for simulation analysis of the perforating completion process during the exploitation of oil and gas reservoirs, and belongs to the field of mineral resource development. Background Art

[0002] Perforating completion is one of the most commonly used technologies in the development of mineral resources such as oil and gas underground. This technology is to penetrate the downhole string and the formation through a perforator, and then enable the oil and gas reservoir to flow into the downhole string and be transported to the ground through the string. As a key link in the exploitation process of oil and gas reservoirs, perforating completion is crucial for reservoir development. Therefore, it is of great significance to evaluate the effect of perforating completion. In the past, the evaluation of the perforating completion process mainly measured the perforating completion effect of the perforator according to the penetration of the ground perforator into steel targets, cement targets and sandstone targets, or evaluated it through finite element simulation.

[0003] The ground experiment method requires a special explosion-proof experimental site, and the experimental process is time-consuming and costly. Moreover, it is difficult to simulate the actual situation of downhole completion. Although pressure simulation experiments can be carried out through a simulated downhole experimental device, the experimental device has a complex structure, a very high manufacturing and use cost, and is not conducive to daily experiments. Finite element simulation analysis has a low cost and high speed, and multiple groups of simulation analyses can be carried out simultaneously. However, due to random errors in the perforator and formation conditions during the actual perforating completion process, and errors also exist in the finite element model and simulation algorithm, etc., this leads to a large gap between the simulation results and the perforating completion effect under actual formation conditions, and the actual perforating completion effect under real formation conditions cannot be accurately evaluated, and the practicability is poor. Summary of the Invention

[0004] The purpose of the present invention is to overcome the above problems existing in the prior art, and provide a simulation method for perforating completion under simulated formation conditions. The present invention can more accurately simulate the real situation under formation conditions, can provide high-precision results for the evaluation of the perforating completion effect under real formation conditions, and provide support for the formulation of perforating completion plans.

[0005] To achieve the above purpose, the technical solution adopted by the present invention is as follows:

[0006] A simulation method for perforating completion under simulated formation conditions, characterized in that: a parameter probability model is obtained by randomly modeling the parameters of the material constitutive equation according to the results of the sensitivity analysis of the material constitutive equation parameters and the material experiment results, random parameters are obtained by sampling the parameter probability model, a basic finite element simulation model is built according to the random parameters, the optimal mesh parameters of the basic finite element simulation model are determined through grid independence analysis of the basic finite element simulation model, the sensitivity analysis of the model parameters of the basic finite element simulation model is carried out with the accuracy of the finite element solution result and the calculation cost as the objective function, and the orthogonal test analysis is carried out on the model parameters in the basic finite element simulation model, and the optimal parameters are determined according to the sensitivity analysis result and the orthogonal test analysis result; a perforating completion basic finite element simulation model simulating the formation conditions is established according to the determined optimal parameters, and the perforating completion process is simulated and analyzed.

[0007] In the said simulation analysis, if the result error is less than 5%, the simulation is completed; if the result error is greater than 5%, a result error calculation and calculation cost proxy model is established, the sensitivity analysis of all the model parameters is carried out with the model error and the calculation cost as the objective function, then the reliability optimization of all the parameters is carried out with the model error and the calculation cost as the objective function, the optimal parameters are determined according to the sensitivity analysis and optimization results, an optimal basic finite element simulation model is built according to the optimal parameters, and then the simulation analysis is carried out again.

[0008] The said method specifically includes the following steps:

[0009] Step 1: Sample the perforator material, perforating gun material, and pipe string material, obtain the yield strength, stress-strain change data, thermal hardening, thermal softening, and crack parameters of the materials through experiments, sample the formation rock sample and cement sheath, measure the densities of the two and the strength parameters of the rock sample, and measure the unconfined compressive strength and tensile strength of the cement sheath sample.

[0010] Step 2: With the model response accuracy and response time as the objective function, carry out the sensitivity analysis of the parameters of the JC constitutive equation, RHT constitutive equation, and shock equation of state, and determine the influence degree of the parameters on the constitutive equation and equation of state.

[0011] Step 3: According to the parameters measured in Step 1, fit some of the parameters of the JC constitutive equation, RHT constitutive equation, and shock equation of state, and solve some of the parameters to be solved to obtain the parameters of the JC constitutive equation, RHT constitutive equation, and shock equation of state.

[0012] Step 4: According to the parameter sensitivity analysis results in Step 2 and the parameters measured in Step 1, establish the probability models of the JC constitutive equation, RHT constitutive equation, and shock equation of state.

[0013] Step 5: Build the probability model established in Step 4, and sample the probability model to obtain the random parameters of the JC constitutive equation, the RHT constitutive equation, and the shock equation of state;

[0014] Step 6: Build the first-round basic finite element simulation model of perforated completion based on the parameters measured in Step 1, the fitted parameters in Step 3, and the random parameters obtained by sampling in Step 4;

[0015] Step 7: Conduct a grid independence analysis on the grid parameters of the first-round basic finite element simulation model established in Step 6, and determine the optimal grid of the first-round basic finite element simulation model according to the analysis results;

[0016] Step 8: Take the accuracy of the finite element simulation analysis results and the calculation cost as the objective function, and conduct a parameter sensitivity analysis on the contact type, contact parameters, solution algorithm, solution parameters, and boundary conditions of the first-round basic finite element model;

[0017] Step 9: Build the second-round basic finite element simulation model based on the optimal grid obtained in Step 7 and the first-round basic finite element simulation model established in Step 6. Conduct an orthogonal experiment analysis on the contact type, contact parameters, solution algorithm, solution parameters, and boundary conditions in the second-round basic finite element simulation model. Determine the best contact type, contact parameters, solution algorithm, solution parameters, and boundary conditions according to the sensitivity analysis results in Step 8 and the orthogonal experiment analysis results;

[0018] Step 10: Build the third-round basic finite element simulation model based on the best contact type, contact parameters, solution algorithm, solution parameters, and boundary conditions determined in Step 9 and the second-round basic finite element simulation model, and conduct an orthogonal experiment analysis of different parameter simulations using different finite element simulation solvers. Compare the simulation results with the actual well condition parameters to determine the optimal solver and optimal simulation parameters;

[0019] Step 11: Build the fourth-round basic finite element simulation model based on the optimal solver, optimal simulation parameters determined in Step 10, and the third-round basic finite element simulation model, and conduct a simulation analysis on the perforated completion process under actual well conditions.

[0020] When conducting the simulation analysis on the perforated completion process under actual well conditions, if the error is greater than 5%, it also includes:

[0021] Step 12: Conduct a sensitivity analysis on all parameters of the fourth-round basic finite element simulation model, determine the reliability optimization parameters of the fourth-round basic finite element simulation model according to the sensitivity analysis results and the experimental results in Step 1, and establish a reliability optimization model;

[0022] Step 13: Take the model error and the calculation cost as the objective function, conduct reliability-based parameter optimization, and determine the optimal parameters according to the sensitivity analysis results in Step 12;

[0023] Step 14: Build an optimal finite element model based on the optimal parameters determined in Step 13, and then perform a simulation analysis on the perforating completion process under actual well conditions.

[0024] In Step 4, according to the results of the sensitivity analysis of the parameters of the JC constitutive equation, the RHT constitutive equation, and the shock equation of state in Step 2, select the top three parameters with the greatest influence on the model. According to the parameters measured in Step 1, determine the random distribution type of the selected parameters, and establish probability models for the JC constitutive equation, the RHT constitutive equation, and the shock equation of state.

[0025] In Step 6, the charge of the perforator, the liner, and the formation are modeled using the discrete element method, and the perforating gun, the tubing string, and the cartridge case are modeled using the Lagrangian method.

[0026] In Step 7, perform a grid independence analysis on the grid size, grid type, grid distribution, and grid parameters of the first-round basic finite element simulation model. According to the analysis results, determine the optimal grid parameters, grid size, grid type, and grid distribution of the first-round basic finite element model.

[0027] In Step 9, perform an orthogonal experiment analysis on the contact type, contact parameters, solution algorithm, solution parameters, and boundary conditions in the second-round basic finite element simulation model. According to the sensitivity analysis results in Step 8 and the orthogonal experiment analysis results, determine the optimal contact type, contact parameters, solution algorithm, solution parameters, and boundary conditions.

[0028] In Step 10, perform an orthogonal experiment analysis on different parameters using different finite element simulation solvers. Compare the simulation results with the actual well conditions parameters to determine the optimal solver and the optimal simulation parameters.

[0029] In Step 12, build a model error calculation and computational cost surrogate model using the response surface method. Taking the model error and computational cost as the objective functions, perform a sensitivity analysis on all parameters of the fourth-round basic finite element simulation model using the Sobol sensitivity analysis method; establish a reliability optimization model using polynomial chaos.

[0030] The advantages of adopting the present invention are as follows:

[0031] The present invention provides a high-precision method for evaluating the perforating completion effect under different formation conditions, which has important practical application value. The simulation method can adapt to oil and gas reservoirs with different formation conditions, can effectively evaluate the perforating completion effect, and provides data support for the formulation of perforating completion plans. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 It is the analysis result diagram in Step 2 of the method of the present invention;

[0033] Figure 2 Ten sampling diagrams for one parameter in Step 5 of the method of the present invention;

[0034] Figure 3 The first-round basic finite element simulation model diagram in the method of the present invention;

[0035] Figure 4 The second-round basic finite element simulation model diagram in the method of the present invention;

[0036] Figure 5 The third-round basic finite element simulation model diagram in the method of the present invention;

[0037] Figure 6 The fourth-round basic finite element simulation model diagram in the method of the present invention. Detailed implementation manners

[0038] Example 1

[0039] The present invention performs stochastic modeling on the material constitutive equation parameters according to the material constitutive equation parameter sensitivity analysis results and material experiment results to evaluate the uncertainty in the actual process. The optimal mesh parameters of the finite element model are determined through mesh independence analysis of the finite element model. The sensitivity analysis of contact parameters and solution parameters, etc. is carried out with the accuracy of the finite element solution result and the calculation cost as the objective functions. Orthogonal test analysis is carried out on the contact type, contact parameters, solution algorithm, solution parameters, and boundary conditions in the finite element model. The optimal contact type, contact parameters, solution algorithm, solution parameters, and boundary conditions are determined according to the sensitivity analysis results and orthogonal test analysis results. Then, a perforated completion finite element simulation model simulating the formation conditions is established based on all the obtained parameters, and orthogonal analysis of different parameters is carried out on different solvers to determine the optimal solver and parameters, and simulation analysis is carried out. If the result error is less than 5%, the simulation is completed. If the result error is greater than 5%, a result error calculation and calculation cost surrogate model are established, and the sensitivity analysis of all the parameters of the model is carried out with the model error and calculation cost as the objective functions. Then, reliability optimization of all the parameters is carried out with the model error and calculation cost as the objective functions. The optimal model parameters are determined according to the sensitivity analysis and optimization results, and then simulation analysis is carried out again.

[0040] For a clearer understanding of the technical features, objectives, and beneficial effects of the present invention, the technical solution of the present invention will be described in detail below, but it should not be construed as a limitation on the implementable scope of the present invention.

[0041] The simulation method for perforating completion under simulated formation conditions provided by the present invention obtains the basic parameters of materials through experiments such as material compression, evaluates the uncertainties in actual situations through sensitivity analysis of constitutive equation parameters and stochastic modeling, fits the constitutive equation parameters using a BP neural network, conducts a grid independence analysis on the finite element model to obtain the optimal grid parameters, determines the optimal parameters such as contact parameters through orthogonal test analysis and sensitivity analysis of simulation parameters, establishes a surrogate model for model error and calculation cost, conducts sensitivity analysis of parameters, then optimizes the reliability of all model parameters to obtain the optimal model parameters, and then conducts simulation analysis.

[0042] This method may include the following specific steps:

[0043] Step 1: Sample perforator materials, perforating gun materials, and tubing materials. Obtain the yield strength, stress-time data, strain-time data, thermal hardening, thermal softening, and crack parameters of the materials through Taylor bar impact experiments and isothermal compression experiments. Sample formation rock samples and cement sheaths, measure their densities, measure the strength parameters of the rock samples based on the Hoek-Brown criterion, and measure the unconfined compressive strength and tensile strength of the cement sheath samples;

[0044] Step 2: Taking the model response accuracy and response time as the objective functions, use the Sobol sensitivity analysis method to conduct sensitivity analysis on the parameters of the Johnson-Cook (JC) constitutive equation, Riedel-Hiermaier-Thoma (RHT) constitutive equation, and shock equation of state to determine the influence degree of the parameters on the constitutive equation and equation of state.

[0045] Step 3: According to the parameters measured in the experiment in Step 1, use a BP neural network to fit some of the parameters of the JC constitutive equation, RHT constitutive equation, and shock equation of state, and solve some of the parameters to be solved to obtain the parameters of the JC constitutive equation, RHT constitutive equation, and shock equation of state;

[0046] Step 4: According to the sensitivity analysis results of the parameters of the JC constitutive equation, RHT constitutive equation, and shock equation of state in Step 2, select the top three parameters with the greatest influence on the model. Determine the random distribution type of the selected parameters according to the parameters measured in the experiment in Step 1, and then use the polynomial chaos method to establish the probability models of the JC constitutive equation, RHT constitutive equation, and shock equation of state;

[0047] Step 5: Build the probability models established in Step 4 in matlab, and use the Latin hypercube sampling method to sample the probability models to obtain the random parameters of the JC constitutive equation, RHT constitutive equation, and shock equation of state;

[0048] Step 6: Build the first-round basic finite element simulation model of perforating completion based on the experimental measurement parameters in Step 1, the fitting parameters in Step 3, and the random parameters obtained by sampling in Step 4. The charge of the perforator, the liner, and the formation are modeled using the discrete element method, and the perforating gun, tubing, and cartridge case are modeled using the Lagrangian method;

[0049] Step 7: Conduct a grid independence analysis on the grid size, grid type, grid distribution, and grid parameters of the first-round basic finite element simulation model of perforating completion established in Step 6. Determine the optimal grid parameters, grid size, grid type, and grid distribution of the first-round basic finite element simulation model according to the analysis results;

[0050] Step 8: Take the accuracy of the finite element simulation analysis results and the computational cost as the objective function, and use the Sobol sensitivity analysis method to conduct a parameter sensitivity analysis on the contact type, contact parameters, solution algorithm, solution parameters, and boundary conditions;

[0051] Step 9: Build the second-round basic finite element simulation model again based on the optimal grid obtained in Step 7 and the first-round basic finite element simulation model built in Step 6. Conduct an orthogonal test analysis on the contact type, contact parameters, solution algorithm, solution parameters, and boundary conditions in the second-round basic finite element simulation model. Determine the optimal contact type, contact parameters, solution algorithm, solution parameters, and boundary conditions according to the sensitivity analysis results in Step 8 and the orthogonal test analysis results;

[0052] Step 10: Build the third-round basic finite element simulation model again based on the optimal contact type, contact parameters, solution algorithm, solution parameters, boundary conditions determined in Step 9 and the first-round basic finite element simulation model, and conduct an orthogonal test analysis of different parameter simulations using different finite element simulation solvers. Compare the simulation results with the actual well condition parameters to determine the optimal solver and optimal simulation parameters;

[0053] Step 11: Build the fourth-round basic finite element simulation model again using the optimal solver, optimal simulation parameters determined in Step 10, and the parameters of the third-round basic finite element simulation model, and conduct a simulation. Compare the simulation results with the actual well condition parameters. If the error is greater than 5%, build a model error calculation and computational cost surrogate model using the response surface method;

[0054] Step 12: Take the model error and computational cost as the objective function, use the Sobol sensitivity analysis method to conduct a sensitivity analysis on all parameters of the fourth-round basic finite element simulation model. Determine the reliability optimization parameters of the fourth-round basic finite element simulation model according to the sensitivity analysis results and the experimental results in Step 1, and establish a reliability optimization model using the polynomial chaos-Kriging method;

[0055] Step 13: Taking the model error and calculation cost as the objective function, perform reliability-based parameter optimization using the optimum safety factor method, and determine the optimal parameters according to the sensitivity analysis results in Step 12;

[0056] Step 14: Build an optimal finite element model according to the optimal parameters determined in Step 13, and then perform a simulation analysis on the perforating completion process under the actual well conditions.

[0057] Example 2

[0058] The present invention is applied to the simulation analysis of the perforating completion of a certain type of perforator in a certain onshore oilfield.

[0059] Step 1: Sample the materials of the perforator, perforating gun, and tubing string. Obtain the yield strength, stress-time data, strain-time data, thermal softening, and crack parameters of the materials through Taylor bar impact experiments and isothermal compression experiments. Sample the formation rock samples and cement sheath, measure their densities, measure the strength parameters of the rock samples based on the Hoek-Brown criterion, and measure the unconfined compressive strength and tensile strength of the cement sheath samples. The unconfined compressive strength and tensile strength of the cement sheath are 32 Mpa and 27 Mpa respectively, and the other parameters are shown in Table 1 and Table 2;

[0060] Table 1 Metal material parameters

[0061]

[0062] Table 2 Hoek-Brown criterion strength parameters of formation rock samples

[0063]

[0064] Step 2: Taking the model response accuracy and response time as the objective function, use the Sobol sensitivity analysis method to perform sensitivity analysis on the parameters of the Johnson-Cook (JC) constitutive equation, Riedel-Hiermaier-Thoma (RHT) constitutive equation, and shock equation of state to determine the influence degree of the parameters on the constitutive equation and equation of state. The analysis results are as attached Figure 1 .

[0065] Step 3: According to the parameters measured in Step 1, use the BP neural network to fit some parameters of the JC constitutive equation, RHT constitutive equation, and shock equation of state, and solve some parameters that need to be solved to obtain the parameters of the JC constitutive equation, RHT constitutive equation, and shock equation of state. Some parameters are shown in Table 3;

[0066] Table 3 Some parameters of the JC constitutive equation, RHT constitutive equation, and shock equation of state

[0067]

[0068] Step 4: According to the parameter sensitivity analysis results of the JC constitutive equation, RHT constitutive equation, and shock equation of state in Step 2, select the top three parameters with the greatest influence on the model. Determine the random distribution type of the selected parameters based on the parameters measured in Step 1, and then use the polynomial chaos method to establish the probability models of the JC constitutive equation, RHT constitutive equation, and shock equation of state;

[0069] Step 5: Build the probability models established in Step 4 in Matlab, and use the Latin hypercube sampling method to sample the probability models to obtain the random parameters of the JC constitutive equation, RHT constitutive equation, and shock equation of state. Ten samples of one parameter are shown in the appendix Figure 2 ;

[0070] Step 6: Build the first-round basic finite element simulation model of perforating completion based on the experimental measurement parameters in Step 1, the fitting parameters in Step 3, and the random parameters obtained by sampling in Step 4 (as Figure 3 shown). The charge of the perforator, the liner, and the formation are modeled using the discrete element method, and the perforating gun, tubing, and cartridge case are modeled using the Lagrangian method;

[0071] Step 7: Conduct mesh independence analysis on the mesh size, mesh type, mesh distribution, and mesh parameters of the first-round basic finite element simulation model established in Step 6. Determine the optimal mesh parameters, mesh size, mesh type, and mesh distribution of the first-round basic finite element simulation model according to the analysis results, as shown in Table 4;

[0072] Table 4 Some mesh-related parameters

[0073]

[0074] Step 8: Take the accuracy and computational cost of the finite element simulation analysis results as the objective function, and use the Sobol sensitivity analysis method to conduct parameter sensitivity analysis on the contact type, contact parameters, solution algorithm, solution parameters, and boundary conditions;

[0075] Step 9: Build the second-round basic finite element simulation model again based on the optimal mesh obtained in Step 7 and the first-round basic finite element simulation model established in Step 6 (as Figure 4 shown). Conduct orthogonal experiment analysis on the contact type, contact parameters, solution algorithm, solution parameters, and boundary conditions in the second-round basic finite element simulation model. Determine the optimal contact type, contact parameters, solution algorithm, solution parameters, and boundary conditions according to the sensitivity analysis results in Step 8 and the orthogonal experiment analysis results. The optimal contact type is full contact and fully coupled fluid-solid contact, and the gap in the contact parameters is 0.032 mm;

[0076] Step Ten: Based on the best contact type, contact parameters, solution algorithm, solution parameters, boundary conditions determined in Step Nine and the second-round basic finite element simulation model, build the third-round basic finite element simulation model again (as shown in Figure 5 ), and use different finite element simulation solvers to conduct orthogonal experiment analysis of different parameter simulations. Compare the simulation results with the actual well conditions parameters to determine the optimal solver autodyn, and the optimal simulation parameters are as follows in the table;

[0077]

[0078] Step Eleven: Based on the optimal solver, optimal simulation parameters and the parameters of the third-round basic finite element simulation model determined in Step Ten, build the fourth-round basic finite element simulation model again (as shown in Figure 6 ), and conduct simulation. Compare the simulation results with the actual well conditions parameters. If the error is greater than 5%, use the response surface method to build a model error calculation and calculation cost surrogate model;

[0079] Step Twelve: Take the model error and calculation cost as the objective function, use the Sobol sensitivity analysis method to conduct sensitivity analysis on all parameters of the fourth-round basic finite element simulation model. According to the sensitivity analysis results and the experimental results in Step One, determine the reliability optimization parameters of the fourth-round basic finite element simulation model, and use the polynomial chaos-Kriging method to establish a reliability optimization model;

[0080] Step Thirteen: Take the model error and calculation cost as the objective function, use the optimum safety factor method to conduct reliability-based parameter optimization, and determine the optimal parameters according to the sensitivity analysis results in Step Twelve;

[0081] Step Fourteen: Build the optimal finite element model according to the optimal parameters determined in Step Thirteen, and then conduct simulation analysis on the perforating completion process under the actual well conditions.

[0082] The aperture and penetration depth errors between the simulation results and the sandstone perforation experiment results under the simulated formation conditions are less than 5%. It can accurately analyze the perforating completion effect of the perforator under the actual downhole conditions, greatly reducing the experimental cost and time, and proving the accuracy of the proposed solution of the present invention.

Claims

1. A simulation method for perforating completion under simulated formation conditions, characterized in that: The method specifically includes the following steps: Step 1: Sample the materials of the perforator, the perforating gun, and the tubing string. Obtain the yield strength, stress-strain change data, thermal hardening, thermal softening, and crack parameters of the materials through experiments. Sample the formation rock sample and the cement sheath, measure the densities of both and the strength parameters of the rock sample, and measure the unconfined compressive strength and tensile strength of the cement sheath sample; Step 2: Take the model response accuracy and response time as the objective functions, conduct a sensitivity analysis on the parameters of the JC constitutive equation, the RHT constitutive equation, and the shock equation of state, and determine the influence degree of the parameters on the constitutive equation and the equation of state; Step 3: According to the parameters measured in the experiment in Step 1, fit some parameters of the JC constitutive equation, the RHT constitutive equation, and the shock equation of state, and solve some parameters that need to be solved to obtain the parameters of the JC constitutive equation, the RHT constitutive equation, and the shock equation of state; Step 4: Establish the probability models of the JC constitutive equation, the RHT constitutive equation, and the shock equation of state according to the parameter sensitivity analysis results in Step 2 and the parameters measured in the experiment in Step 1; Step 5: Build the probability models established in Step 4, and sample the probability models to obtain the random parameters of the JC constitutive equation, the RHT constitutive equation, and the shock equation of state; Step 6: Build the first-round basic finite element simulation model of the perforating completion according to the parameters measured in the experiment in Step 1, the fitting parameters in Step 3, and the random parameters obtained by sampling in Step 4; Step 7: Conduct a grid independence analysis on the grid parameters of the first-round basic finite element simulation model established in Step 6, and determine the optimal grid of the first-round basic finite element simulation model according to the analysis results; Step 8: Take the accuracy of the finite element simulation analysis results and the calculation cost as the objective functions, and conduct a sensitivity analysis on the contact type, contact parameters, solution algorithm, solution parameters, and boundary conditions of the first-round basic finite element model; Step 9: Build the second-round basic finite element simulation model according to the optimal grid obtained in Step 7 and the first-round basic finite element simulation model established in Step 6. Conduct an orthogonal test analysis on the contact type, contact parameters, solution algorithm, solution parameters, and boundary conditions in the second-round basic finite element simulation model. Determine the best contact type, contact parameters, solution algorithm, solution parameters, and boundary conditions according to the sensitivity analysis results in Step 8 and the orthogonal test analysis results; Step 10: Build the third-round basic finite element simulation model according to the best contact type, contact parameters, solution algorithm, solution parameters, boundary conditions determined in Step 9 and the second-round basic finite element simulation model, and conduct an orthogonal test analysis of different parameter simulations using different finite element simulation solvers. Compare the simulation results with the actual well condition parameters to determine the optimal solver and the optimal simulation parameters; Step 11: Build the fourth-round basic finite element simulation model according to the optimal solver, the optimal simulation parameters determined in Step 10, and the third-round basic finite element simulation model, and conduct a simulation analysis on the perforating completion process under the actual well conditions.

2. The simulation method of perforating completion under simulated formation conditions according to claim 1, characterized in that: In the simulation analysis, if the result error is less than 5%, the simulation is completed; if the result error is greater than 5%, a result error calculation and a computational cost surrogate model are established. Sensitivity analysis is performed on all parameters of the model with the model error and computational cost as the objective functions. Then, reliability optimization is performed on all parameters with the model error and computational cost as the objective functions. The optimal parameters are determined according to the sensitivity analysis and optimization results. An optimal basic finite element simulation model is built based on the optimal parameters, and then the simulation analysis is carried out again.

3. The simulation method for perforating completion under simulated formation conditions according to claim 2, wherein: When performing simulation analysis on the perforating completion process under actual well conditions, if the error is greater than 5%, it also includes: Step 12: Perform sensitivity analysis on all parameters of the fourth-round basic finite element simulation model. Determine the reliability optimization parameters of the fourth-round basic finite element simulation model according to the sensitivity analysis results and the experimental results in Step 1, and establish a reliability optimization model; Step 13: Perform reliability-based parameter optimization with the model error and computational cost as the objective functions, and determine the optimal parameters according to the sensitivity analysis results in Step 12; Step 14: Build an optimal finite element model according to the optimal parameters determined in Step 13, and then perform simulation analysis on the perforating completion process under actual well conditions.

4. The simulation method for perforating completion under simulated formation conditions according to claim 2 or 3, characterized in that: In Step 4, it includes: According to the sensitivity analysis results of the parameters of the JC constitutive equation, RHT constitutive equation, and shock equation of state in Step 2, select the top three parameters with the greatest influence on the model. Determine the random distribution types of the selected parameters according to the parameters measured in the experiment in Step 1, and establish the probability models of the JC constitutive equation, RHT constitutive equation, and shock equation of state.

5. The simulation method for perforating completion under simulated formation conditions according to claim 2 or 3, characterized in that: In Step 6, it includes: Modeling the perforator charge, liner, and formation using the discrete element method, and modeling the perforating gun, tubing, and cartridge case using the Lagrangian method.

6. The simulation method for perforating completion under simulated formation conditions according to claim 2 or 3, characterized in that: In Step 7, it includes: Perform mesh independence analysis on the mesh size, mesh type, mesh distribution, and mesh parameters of the first-round basic finite element simulation model, and determine the optimal mesh parameters, mesh size, mesh type, and mesh distribution of the first-round basic finite element model according to the analysis results.

7. The simulation method for perforating completion under simulated formation conditions according to claim 2 or 3, characterized in that: In Step 9, it includes: Perform orthogonal experiment analysis on the contact type, contact parameters, solution algorithm, solution parameters, and boundary conditions in the second-round basic finite element simulation model. Determine the optimal contact type, contact parameters, solution algorithm, solution parameters, and boundary conditions according to the sensitivity analysis results in Step 8 and the orthogonal experiment analysis results.

8. The simulation method for perforating completion under simulated formation conditions according to claim 2 or 3, characterized in that: In Step 10, it includes: Perform orthogonal experiment analysis on different parameters using different finite element simulation solvers, and compare the simulation results with the actual well condition parameters to determine the optimal solver and optimal simulation parameters.

9. The simulation method of perforating completion under simulated formation conditions according to claim 3, characterized in that: In Step 12, it includes: Build a result error calculation and computational cost surrogate model using the response surface method. Perform sensitivity analysis on all parameters of the fourth-round basic finite element simulation model with the model error and computational cost as the objective functions using the Sobol sensitivity analysis method; Build a reliability optimization model using polynomial chaos.

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