A method for designing fracturing parameters for repeated fracturing and temporary plugging of horizontal wells

Abstract

The present invention relates to a method for designing parameters of horizontal well repeated fracturing energization temporary plugging fracturing. The technical scheme includes the following steps: structural modeling and small layer modeling; reservoir attribute modeling based on lithofacies modeling; natural fracture modeling; three-dimensional rock mechanics field based on indoor mechanical experiments and single well logging interpretation results; inversion of the transformation morphology of the initial fracturing fracture in combination with the microseismic data of the initial fracturing, and then historical fitting of the pore pressure field and fracture parameters of the initial fracturing; importing the pore pressure field at different times into a geomechanical simulator to calculate the dynamic rock stress field, and performing dynamic stress field calculation; selecting a low-value area of ​​two-way stress difference; numerical simulation of the injection of energizing fluid, obtaining the law of increasing formation pressure after fluid injection, carrying out numerical-production integrated simulation of temporary plugging fracturing fracture expansion, and determining the optimal energizing temporary plugging fracturing process parameters to restore and further increase oil and gas production.

Description

Technical Field

[0001] The invention relates to the field of oil and gas production enhancement and development, and in particular to a method for designing fracturing parameters for repeated fracturing energy enhancement and temporary plugging of horizontal wells. Background Art

[0002] Refracturing technology has formed a relatively complete technical system in North America and has been widely used in unconventional oil and gas reservoirs, making important contributions to extending the life of old wells and improving and improving oil and gas recovery. At present, my country's refracturing technology is still mainly in the theoretical research stage, and there are relatively few real horizontal well field practices, especially a complete and mature refracturing process system has not yet been formed.

[0003] The reservoir geomechanical environment during horizontal well re-fracturing has changed significantly compared to the initial formation geomechanical environment, mainly because the initial fracturing of the horizontal well will significantly change the pore pressure field near the wellbore. The continuous production of oil and gas will cause changes in the rock mechanical properties, the direction and size of the stress around the wellbore, thereby affecting the subsequent repeated fracturing crack extension morphology. At the same time, due to the large formation deficit before re-fracturing, and the difference in the degree of transformation of each fracturing section during the initial pressure, the extension and expansion of the fractures during re-fracturing are further affected. Energy-enhanced fracturing is a production-enhancing process that supplements energy to the formation before fracturing. In particular, studies have found that the production deficit of the fracturing well will cause an increase in the horizontal stress difference in both directions. Through the continuous injection of energy-enhancing fluid, the formation pressure can be restored and the horizontal stress difference in both directions can be reduced, so that a more uniform fracture system can be formed during repeated fracturing and a larger reservoir transformation volume can be created.

[0004] At present, most horizontal well re-fracturing construction is mainly achieved through the ball-throwing temporary plugging process. During the application process, the main problems exposed are that the re-fracturing position is difficult to control, the temporary plugging ball is not in place, resulting in incomplete use of the core layer, and the fracture direction is uncontrolled. Secondly, the heterogeneous stress conditions of the reservoir itself also cause the current temporary plugging design scheme to be somewhat blind, so how to consider the complex stress field changes of re-fracturing and carry out re-fracturing design on this basis is crucial. Summary of the invention

[0005] The purpose of the present invention is to address the above-mentioned defects in the prior art and provide a method for designing parameters of horizontal well repeated fracturing energy-enhancing temporary plugging fracturing, by pre-energizing the reservoir and then further combining the temporary plugging repeated fracturing technology to carry out reservoir transformation again, so as to restore and further increase oil and gas production.

[0006] The present invention provides a method for designing parameters of horizontal well repeated fracturing energy enhancement temporary plugging fracturing, and the technical scheme thereof comprises the following steps:

[0007] (1) Use "well seismic" data to carry out structural modeling and small layer modeling; (2) Based on lithofacies modeling, reservoir attribute modeling is carried out; (3) Natural fracture modeling is carried out by combining outcrop, special logging and seismic attribute information; (4) Three-dimensional rock mechanics field based on indoor mechanical experiments and single well logging interpretation results; (5) Combined with the initial fracturing microseismic data, the initial fracture transformation morphology is inverted through random fracture inversion technology, and then the pore pressure field and fracture parameters of the initial fracturing are historically fitted; (6) Through the cross-iterative coupling method, the pore pressure field at different times is imported into the geomechanical simulator for dynamic simulation. (7) The dynamic rock stress field calculation is performed; (8) The dynamic geostress field calculation results near the wellbore of the horizontal well are extracted, and the area with low two-way stress difference is selected; (9) Numerical simulation is performed to inject energized fluid, and the law of increasing formation pressure after fluid injection is obtained to achieve the recovery of the two-way horizontal stress difference in the local area. The hydraulic stress difference along the entire horizontal well section is calculated using the deviation coefficient. When the deviation coefficient meets the conditions, the injection of energized fluid is stopped; (10) Based on the dynamic stress field after energization, the numerical-production integrated simulation of temporary plugging fracturing crack expansion is continued to be carried out to determine the optimal energized temporary plugging fracturing process parameters.

[0008] Preferably, the method for designing fracturing parameters for repeated fracturing and energy enhancement and temporary plugging of horizontal wells mentioned in the present invention specifically comprises the following steps:

[0009] (1) Through the combination of well and seismic data, reservoir unit division, layer interface structural interpretation and layer modeling of seismic interpretation are carried out to achieve geological structure modeling;

[0010] (2) Based on core observation and thin section identification data, lithofacies division is carried out, and based on the lithology interpretation results of single well logging, the sedimentary microfacies variation functions are analyzed respectively, and the lithofacies model is established by using the Gaussian sequential simulation method in combination with the structural model with lithology constraints;

[0011] (3) On the basis of structural modeling, the Gaussian sequential simulation method is used to establish a reservoir attribute parameter model based on the logging interpretation results. The relevant attribute parameters mainly include the porosity and permeability of the reservoir;

[0012] (4) Further develop natural fracture modeling based on the geological model. Natural fractures of different scales have different fracture distribution characteristics. Therefore, the integration and characterization of natural fractures of different scales are achieved through the step-by-step superposition of natural fracture modeling technology.

[0013] (5) Carry out rock mechanics field modeling, mainly based on well logging data and indoor core test data to calculate the rock mechanics parameters of a single well; use seismic data to calculate the rock mechanics parameters between wells; finally, calculate the rock mechanics parameters of the entire work area through the Kriging interpolation method;

[0014] (6) After the rock mechanics field is established, the static geostress field is modeled using the finite element method. The data obtained through indoor experiments or field floor drain experiments are used as hard point data to control the geostress magnitude regression accuracy. The direction of the static geostress field is controlled by the wellbore collapse and induced fracture direction data collected on site.

[0015] (7) Process the microseismic data collected on site and reconstruct the horizontal well segmented fracture network system using the microseismic unstructured grid discrete fracture technology;

[0016] (8) The seepage equation is constructed based on the seepage characteristics, and numerical simulation is carried out based on the embedded discrete fracture network model. The historical fitting is performed in combination with the pressure data collected on site. Since the historical fitting is an optimization process, the ensemble Kalman filter algorithm EnKF is used to improve the optimization speed and fitting accuracy of the objective function, and finally the inversion of specific reservoir properties and pressure field parameters is completed, thereby obtaining the pore pressure field under different time conditions;

[0017] (9) The pore pressure field data at different times are again transferred into the geostress field simulator to carry out numerical simulation of geostress at different times to obtain the geostress field under different time conditions;

[0018] (10) Extract the calculation results of the ground stress field near the wellbore, calculate the two-way horizontal stress difference under different time conditions, and determine the deviation coefficient to calculate the distribution of the two-way horizontal stress difference along the entire wellbore;

[0019] (11) Determine the deviation coefficient threshold, simulate the injection process of the energizing fluid, study the formation pressure change law under different energizing fluid injection conditions, and obtain the formation pressure recovery of the entire horizontal wellbore. When the calculated deviation coefficient threshold of each wellbore meets the requirements, carry out subsequent temporary plugging hydraulic fracturing simulation;

[0020] (12) Based on the updated geostress field after energy enhancement, numerical simulation of hydraulic fracturing is carried out, and the optimal energy enhancement fracturing process parameters are determined by taking the optimal temporary plugging and repeated fracturing fracture expansion volume as the optimization target.

[0021] Preferably, the calculation formula related to rock mechanics in step (5) is:

[0022] (1)

[0023] (2)

[0024] (3)

[0025] In the formula, E dis the dynamic elastic modulus, MPa; v d is the dynamic Poisson's ratio; t s is the shear wave time difference, μs / ft; △ t p is the longitudinal wave time difference, μs / ft; r is the density, g / cm 3 .

[0026] Preferably, the main steps of the Kriging interpolation method in step (5) are: under the condition that the regionalized variables have spatial correlation, let the study area be A, the studied physical attribute variable be {Z(X)∈A}, X represents the spatial position (coordinate), and Z(X) at the sampling point x i The attribute value at is Z (X i ), then according to the ordinary Kriging interpolation principle, the attribute value Z(X0) at the unsampled point x0 is the attribute value Z(X0) of n known sampling points i ), can be expressed as:

[0027] (4)

[0028] Where: i are the weight coefficients to be determined.

[0029] Under the unbiased condition, λ i The solution equation is:

[0030] (5)

[0031] Where: Cov( x i , x j ) is Z(X i ) and Z(X j ). When λ is found i Then Z(X0) at the unsampled point can be obtained.

[0032] Preferably, the calculation formula of the geostress in step (6) is:

[0033] (6)

[0034] In the formula, s H is the maximum horizontal principal stress, MPa; s h is the minimum horizontal principal stress, MPa; s v is the overburden pressure, MPa; P p is the pore pressure, MPa; e H is the strain coefficient in the direction of maximum horizontal principal stress; e h is the strain coefficient in the direction of minimum horizontal principal stress; e tect is the tectonic strain coefficient in the horizontal direction; α is the Biot coefficient, which is 0.6; E s is the static Young's modulus, MPa; v is Poisson's ratio; w 1 and w 2 is the tectonic stress coefficient in the direction of maximum horizontal principal stress and minimum horizontal principal stress.

[0035] Preferably, in step (8), a tight oil numerical simulation based on an embedded discrete fracture model is performed by establishing a seepage equation, wherein the entire reservoir is assumed to be a dual-medium reservoir, wherein the governing equations for fluid flow in the matrix and the fracture are:

[0036] (7)

[0037] (8)

[0038] Where: f m and f f represents matrix and fracture porosity; r Represents density, kg / m 3 ; q mf and q fm represents the exchange term between the matrix and the fracture. The change of fluid pressure in the pores causes the stress of the rock to change, and then the permeability of the matrix and fractures will change dynamically during the production process. This model uses an empirical formula to consider this phenomenon:

[0039] (9)

[0040] (10)

[0041] Where: k mi , k fi are the initial matrix and fracture permeabilities, respectively; β and α are two stress sensitivity coefficients; p mi , p fiare the initial matrix and rupture pressures, respectively; p m , p f They are the dynamic matrix and burst pressure during production, respectively.

[0042] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0043] The present invention realizes the calculation of dynamic stress and fracture mechanical parameters under different production conditions, and restores the stress difference caused by production failure by injecting energizing fluid, and realizes the balanced initiation of each fracture in repeated fracturing by temporary plugging fracturing, thereby ensuring that the subsequent repeated fracturing expansion and transformation area forms uniformly expanded hydraulic fractures, thereby improving the efficiency of horizontal well repeated fracturing operations. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 It is a schematic diagram of a horizontal well energy storage repeated temporary plugging fracturing simulation process formed by the present invention;

[0045] Figure 2 It is a schematic diagram of static three-dimensional rock mechanics field modeling in the research area formed by the present invention;

[0046] Figure 3 It is a schematic diagram of modeling the two-way geostress difference in the research area formed by the present invention;

[0047] Figure 4 It is a schematic diagram of numerical simulation of formation pressure before and after energy storage temporary plugging and fracturing of a horizontal well formed by the present invention;

[0048] Figure 5 It is a schematic diagram of numerical simulation of ground stress before and after energy storage temporary plugging and fracturing of a horizontal well formed by the present invention;

[0049] Figure 6 It is a schematic diagram of simulation of fracture expansion after repeated temporary plugging and fracturing of a horizontal well formed by the present invention;

[0050] Figure 7 It is a schematic diagram of the production change after the horizontal well energy storage temporary plugging and fracturing formed by the present invention. DETAILED DESCRIPTION

[0051] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0052] Example 1, the present invention proposes a method for designing fracturing parameters for repeated fracturing and energy enhancement and temporary plugging of horizontal wells, comprising the following steps:

[0053] (1) First, use seismic data to identify and model faults. Then, use seismic velocity field data to perform time-depth conversion, complete the interpretation of layer interface structure, and use single well data from drilling layers to construct structural maps of each layer. Geological structure modeling is achieved through layer models and fault models.

[0054] (2) After the structural model is completed, a sedimentary phase model is further established. The lithofacies analysis and classification are carried out using microscopic thin section analysis, mineral composition analysis and other data. A quantitative classification standard for lithofacies types is established based on the three-mineral method of quartz + feldspar, clay and carbonate. Then, a detailed description of geological characteristics is made on this basis. For particularly complex lithofacies, methods such as neural network simulation can be used to distinguish lithofacies.

[0055] (3) Based on the lithology model, the geological attribute model is further established. The attribute modeling mainly adopts the interpolation method including trend analysis. First, the indoor porosity and permeability test results are statistically analyzed to obtain the single well porosity and permeability logging interpretation results, and the trend is assigned to the grid attributes.

[0056] (4) Under seismic constraints, ant tracking technology is used to achieve large-scale fracture characterization. Considering the distance between the distribution of fractures and the distribution area of ​​natural fractures, geological statistical methods are used to randomly generate small and medium-scale fracture systems. The density distribution equation of natural fractures can be established using random distribution functions or fractal theory. At the same time, the distribution density and development characteristics of natural fractures in the study area are further constrained by using fracture intensity data volume data, drilling loss data, and combined with on-site microseismic data, so as to achieve a comprehensive characterization of natural fractures under small-scale conditions in the study area.

[0057] (5) Carry out single-well rock mechanics modeling, and then calculate the rock mechanics parameters of the entire work area through the Kriging interpolation method. The specific rock mechanics parameters include uniaxial compressive strength, tensile strength, Young's modulus, Poisson's ratio, brittleness index, etc. The relevant formula for calculating single-well rock mechanics is:

[0058] (1)

[0059] (2)

[0060] (3)

[0061] In the formula, E d is the dynamic elastic modulus, MPa; v d is the dynamic Poisson's ratio; t s is the shear wave time difference, μs / ft; △t p is the longitudinal wave time difference, μs / ft; r is the density, g / cm 3 .

[0062] (6) Interwell rock mechanics is completed by the Kriging interpolation method. The main steps of the Kriging interpolation method are: under the condition that the regionalized variables have spatial correlation, let the study area be A, the physical property variable to be studied be {Z(X)∈A}, X represents the spatial position (coordinate), and Z(X) at the sampling point x i The attribute value at is Z (X i ), then according to the ordinary Kriging interpolation principle, the attribute value Z(X0) at the unsampled point x0 is the attribute value Z(X0) of n known sampling points i ), can be expressed as:

[0063] (4)

[0064] Where: i are the weight coefficients to be determined.

[0065] Under the unbiased condition, λ i The solution equation is:

[0066] (5)

[0067] Where: Cov( x i , x j ) is Z(X i ) and Z (X j ). When λ is found i Then Z(X0) at the unsampled point can be obtained.

[0068] (7) The direction of geostress can be obtained through indoor paleomagnetic methods through logging data. Secondly, the direction of geostress can be determined through imaging logging data, because the direction of geostress is closely related to the direction of induced fractures. Therefore, the direction of minimum or maximum horizontal principal stress can be determined by analyzing the development direction of drilling-induced fractures from the microresistivity scanning imaging logging (FMI) image. Common single-well stress models include the Matthews and Kelly model, the Anderson model, the Huang model, etc. Among them, the combined spring geostress model is the most widely used. The combined spring model takes into account the influence of overburden pressure, tectonic stress and pore pressure on geostress. Assuming the entire formation to be a homogeneous and isotropic body, the formula for calculating its geostress is:

[0069] (6)

[0070] In the formula, s H is the maximum horizontal principal stress, MPa; s h is the minimum horizontal principal stress, MPa; s v is the overburden pressure, MPa; P p is the pore pressure, MPa; e H is the strain coefficient in the direction of maximum horizontal principal stress; e h is the strain coefficient in the direction of minimum horizontal principal stress; e tect is the tectonic strain coefficient in the horizontal direction; α is the Biot coefficient, which is 0.6; E s is the static Young's modulus, MPa; v is Poisson's ratio; w 1 and w 2 is the tectonic stress coefficient in the direction of maximum horizontal principal stress and minimum horizontal principal stress.

[0071] (8) Carry out three-dimensional geostress field calculation. The three-dimensional geostress field specifically includes pore pressure field, vertical geostress and two-dimensional horizontal principal stress maximum horizontal principal stress and minimum horizontal principal stress model. For new blocks, since the three-dimensional horizontal principal stress model is difficult to obtain, the horizontal principal stress can be calculated using the simple and practical effective stress ratio principle. For old blocks, the relationship between the three-dimensional geostress can be determined based on past geostress results. The modeling steps of three-dimensional geostress are as follows: based on the geological model, it is necessary to determine the material properties and stress environment of different geological units in the study block, determine the key rock mechanics parameters at different locations, mainly including the range of rock mechanics parameters such as Young's modulus and Poisson's ratio, set the boundaries and constraints of the geological body, establish the target optimization function of the geostress field in the formation area based on the known geostress data near the wellbore, and combine optimization and finite element numerical simulation theory to perform geostress inversion solution. The main steps are to run the finite element calculation model based on the elastic modulus field after the geomechanical properties are updated and the given finite element boundary conditions, calculate the displacement of the nodes in the system in equilibrium, and calculate the strain and stress of each grid unit based on these displacements. Finally, the strains, stresses, or displacements are output as element properties of the mesh.

[0072] (9) The microseismic unstructured grid discrete fracture technology is used to reconstruct the horizontal well segmented fracture network system, merging the microfractures of each hydraulic pressure segment together to obtain the discrete fracture network of the fracture system. The production numerical simulation is carried out based on this model, and the historical fitting is performed with the actual production data to determine the proportionality coefficient D. The numerical simulation is performed until the system reaches a pseudo-steady state, and the pressure distribution field is used to obtain the statistical distribution function of the pressure. The inflection point of the statistical distribution function is calculated as the boundary pressure of the dynamic reservoir stimulation volume (SRV), and the SRV range of the fracturing is obtained.

[0073] (10) By establishing the seepage equation, the numerical simulation of tight oil based on the embedded discrete fracture model is carried out, in which the entire reservoir is assumed to be a dual-medium reservoir, where the governing equations for fluid flow in the matrix and fractures are:

[0074] (7)

[0075] (8)

[0076] Where: f m and f f represents matrix and fracture porosity; r Represents density, kg / m 3 ; q mf and q fm represents the exchange term between the matrix and the fracture; the change of fluid pressure in the pores causes the stress of the rock to change, and then the permeability of the matrix and fractures will change dynamically during the production process. This model uses an empirical formula to consider this phenomenon:

[0077] (9)

[0078] (10)

[0079] Where: k mi , k fi are the initial matrix and fracture permeabilities, respectively; β and α are two stress sensitivity coefficients; p mi , p fi are the initial matrix and rupture pressures, respectively; p m , p f They are the dynamic matrix and burst pressure during production, respectively.

[0080] (11) Use the Ensemble Kalman Filter (EnFK) algorithm to update data. In the Ensemble Kalman Filter method, a set of initial samples generated based on prior information is used to predict the model and is updated at the time of data acquisition. The correlation information between the data required for updating and the state vector is obtained by sample statistics. This method has obvious advantages in dealing with large-scale problems.

[0081] (11)

[0082] Where: is the state vector; m is the static variables of the model, such as porosity and permeability; u is the dynamic variables, such as pressure and saturation; subscript k is the time step; R is a real vector space; N m and N u The vectors are m and u The dimension of .

[0083] New expression of EnFK method:

[0084] (12)

[0085] Where: For the j The state vector corresponding to the model.

[0086] (12) The pore pressure at different times obtained by numerical simulation of the reservoir, reservoir physical property data, and rock mechanical parameters are used as boundary conditions for different calculation time steps. The three-dimensional geostress model after stress initialization is used as the initial model. The data is re-imported into the geostress model for geostress calculation, thereby obtaining the dynamic geostress field under different time conditions. Loads are applied to the three-dimensional geostress model at different time steps, including gravity, hydrostatic pressure, pore pressure, temperature, etc. Among them, the three-dimensional pore pressure field and temperature field at different times predicted in the interpolation calculation of reservoir rock physical properties and rock mechanical parameters are used as external loads, as the initial conditions and boundary conditions of each calculation time step, and the three-dimensional geostress model after stress initialization is used as the initial model for dynamic stress field calculation.

[0087] (13) Extract the two-way hydraulic stress difference parameters along the horizontal wellbore, and the calculation formula is as follows:

[0088] (13)

[0089] In the formula, s H is the maximum horizontal principal stress, MPa; sh is the minimum horizontal principal stress, MPa;

[0090] By defining the deviation coefficient, the stress non-uniformity along the entire horizontal well section is characterized.

[0091] (14)

[0092] In the formula, the standard deviation is defined as s With the average Ratio.

[0093] (14) Carry out numerical simulation of energized fluid injection. The energized fluid can be one of water, carbon dioxide, etc. The distribution of the energized fluid in the reservoir is simulated to obtain the law of change of the relevant pressure field. The dynamic stress field simulation is carried out with the pressure field after energization as the initial condition, and the deviation coefficient is used as the constraint condition (generally the deviation coefficient is required) to calculate the total injection amount of the energized fluid.

[0094] (15) Considering the updated dynamic stress field, the temporary plugging fracturing numerical simulation is carried out on this basis. Finally, the construction parameters are further optimized with the maximum reservoir transformation volume as the goal. The specific optimization includes: the spacing between clusters within the segment, the average sand addition amount of a single cluster, the average liquid addition amount of a single cluster, etc.

[0095] The above are only some preferred embodiments of the present invention. Any person skilled in the art may modify the above technical solutions or modify them into equivalent technical solutions. Therefore, the corresponding simple modifications or equivalent transformations made according to the technical solutions of the present invention shall fall within the scope of protection claimed by the present invention.

Claims

1. A method for designing parameters of horizontal well repeated fracturing energy enhancement temporary plugging fracturing, characterized in that The following steps are involved: (1) Use "well seismic" data to carry out structural modeling and small layer modeling; (2) Based on lithofacies modeling, reservoir attribute modeling is carried out; (3) Natural fracture modeling is carried out by combining outcrop, special logging and seismic attribute information; (4) Three-dimensional rock mechanics field based on indoor mechanical experiments and single well logging interpretation results; (5) Combined with the initial fracturing microseismic data, the initial fracture transformation morphology is inverted through random fracture inversion technology, and then the pore pressure field and fracture parameters of the initial fracturing are historically fitted; (6) The pore pressure field at different times is imported into the geomechanical simulator through the cross-iterative coupling method for dynamic simulation. (7) The dynamic rock stress field calculation is performed; (8) The dynamic geostress field calculation results near the wellbore of the horizontal well are extracted, and the area with low two-way stress difference is selected; (9) Numerical simulation is performed to inject energized fluid, and the law of increasing formation pressure after fluid injection is obtained to achieve the recovery of the two-way horizontal stress difference in the local area. The hydraulic stress difference along the entire horizontal well section is calculated using the deviation coefficient. When the deviation coefficient meets the conditions, the injection of energized fluid is stopped; (10) Based on the dynamic stress field after energization, the numerical-production integrated simulation of temporary plugging fracturing crack expansion is continued to be carried out to determine the optimal energized temporary plugging fracturing process parameters.

2. The method for designing fracturing parameters for repeated fracturing and energy enhancement and temporary plugging of horizontal wells according to claim 1 is characterized by: The specific steps include: (1) Through the combination of well and seismic data, reservoir unit division, layer interface structural interpretation and layer modeling of seismic interpretation are carried out to achieve geological structure modeling; (2) Based on core observation and thin section identification data, lithofacies division is carried out, and based on the lithology interpretation results of single well logging, the sedimentary microfacies variation functions are analyzed respectively, and the lithofacies model is established by using the Gaussian sequential simulation method in combination with the structural model with lithology constraints; (3) Based on the structural modeling, the Gaussian sequential simulation method is used to establish the reservoir attribute parameter model according to the logging interpretation results. The relevant attribute parameters include the reservoir porosity and permeability; (4) Further develop natural fracture modeling based on the geological model. Natural fractures of different scales have different fracture distribution characteristics. Therefore, the integration and characterization of natural fractures of different scales are achieved through the step-by-step superposition of natural fracture modeling technology. (5) Carry out rock mechanics field modeling, calculate the rock mechanics parameters of a single well based on well logging data and indoor core test data; use seismic data to calculate the rock mechanics parameters between wells; finally, calculate the rock mechanics parameters of the entire work area through the Kriging interpolation method; (6) After the rock mechanics field is established, the static geostress field is modeled using the finite element method. The data obtained through indoor experiments or field floor drain experiments are used as hard point data to control the geostress magnitude regression accuracy. The direction of the static geostress field is controlled by the wellbore collapse and induced fracture direction data collected on site. (7) Process the microseismic data collected on site and reconstruct the horizontal well segmented fracture network system using the microseismic unstructured grid discrete fracture technology; (8) The seepage equation is constructed based on the seepage characteristics, and numerical simulation is carried out based on the embedded discrete fracture network model. The historical fitting is performed in combination with the pressure data collected on site. Since the historical fitting is an optimization process, the ensemble Kalman filter algorithm EnKF is used to improve the optimization speed and fitting accuracy of the objective function, and finally the inversion of specific reservoir properties and pressure field parameters is completed, thereby obtaining the pore pressure field under different time conditions; (9) The pore pressure field data at different times are again transferred into the geostress field simulator to carry out numerical simulation of geostress at different times to obtain the geostress field under different time conditions; (10) Extract the calculation results of the ground stress field near the wellbore, calculate the two-way horizontal stress difference under different time conditions, and determine the deviation coefficient to calculate the distribution of the two-way horizontal stress difference along the entire wellbore; (11) Determine the deviation coefficient threshold, simulate the injection process of the energizing fluid, study the formation pressure change law under different energizing fluid injection conditions, and obtain the formation pressure recovery of the entire horizontal wellbore. When the calculated deviation coefficient threshold of each wellbore meets the requirements, carry out subsequent temporary plugging hydraulic fracturing simulation; (12) Based on the updated geostress field after energy enhancement, numerical simulation of hydraulic fracturing is carried out, and the optimal energy enhancement fracturing process parameters are determined by taking the optimal temporary plugging and repeated fracturing fracture expansion volume as the optimization target.

3. The method for designing fracturing parameters for repeated fracturing and energy enhancement and temporary plugging of horizontal wells according to claim 2 is characterized by: The relevant formula for calculating rock mechanics in step (5) is: （1） （2） （3） In the formula, E d is the dynamic elastic modulus, MPa; v d is the dynamic Poisson's ratio; t s is the shear wave time difference, μs / ft; △ t p is the longitudinal wave time difference, μs / ft; ρ is the density, g / cm 3 .

4. The method for designing fracturing parameters for repeated fracturing and energy enhancement and temporary plugging of horizontal wells according to claim 3 is characterized by: The steps of the Kriging interpolation method in step (5) are as follows: Under the condition that the regionalized variables have spatial correlation, let the study area be A, the physical attribute variable to be studied be {Z(X)∈A}, X represents the spatial position coordinate, and Z(X) at the sampling point x i The attribute value at is Z (X i ), then according to the ordinary Kriging interpolation principle, the attribute value Z(X0) at the unsampled point x0 is the attribute value Z(X0) of n known sampling points i ), can be expressed as: (4) Where: i are the weight coefficients to be determined; Under the unbiased condition, λ i The solution equation is: (5) Where: Cov( x i , x j ) is Z(X i ) and Z(X j ), when we find λ i Then Z(X0) at the unsampled point can be obtained.

5. The method for designing fracturing parameters for repeated fracturing and energy enhancement and temporary plugging of horizontal wells according to claim 4 is characterized by: The calculation formula of the ground stress in step (6) is: （6） In the formula, σ H is the maximum horizontal principal stress, MPa; σ h is the minimum horizontal principal stress, MPa; σ v is the overburden pressure, MPa; P p is the pore pressure, MPa; ε H is the strain coefficient in the direction of maximum horizontal principal stress; ε h is the strain coefficient in the direction of minimum horizontal principal stress; α is the Biot coefficient, which is 0.6; E s is the static Young's modulus, MPa; v is Poisson's ratio.

6. The method for designing fracturing parameters for repeated fracturing and energy enhancement and temporary plugging of horizontal wells according to claim 4 is characterized by: In step (8), the tight oil numerical simulation based on the embedded discrete fracture model is carried out by establishing the seepage equation, in which the entire reservoir is assumed to be a dual-medium reservoir, and the flow control equations of the fluid in the matrix and the fracture are: （7） （8） Where: φ m and φ f represents matrix and fracture porosity; ρ Represents density, kg / m 3 ; q mf and q fm represents the exchange term between the matrix and the fracture. The change of fluid pressure in the pores causes the stress of the rock to change, and then the permeability of the matrix and fractures will change dynamically during the production process. This model uses an empirical formula to consider this phenomenon: （9） （10） Where: k mi , k fi are the initial matrix and fracture permeabilities, respectively; β and α are two stress sensitivity coefficients; p mi , p fi are the initial matrix and rupture pressures, respectively; p m , p f They are the dynamic matrix and burst pressure during production, respectively.

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