Shale gas well after-pressing soaking time optimization method based on rock tension shear failure criterion

Abstract

The invention discloses a shale gas well after-pressing soaking time optimization method based on a rock tension shear failure criterion, and belongs to the technical field of oil and gas reservoir development. According to the method, seepage mechanics, elastic mechanics and the Mohr-Coulomb's law are combined, natural fractures, fracturing fluid seepage, microseismic data, hydraulic fractures and a rock tension-shear failure mechanism are comprehensively considered, and a reservoir reform volume (SRV) recognition model, a natural fracture random distribution model, a seepage model and a rock failure criterion are constructed. The relation curve of the stratum tension shear failure volume and time in the soaking process is obtained through numerical simulation, and the time point at which the failure volume is not increased any more serves as the optimal soaking time. According to the method, the limitation that shale gas reservoir rock tension shear failure and natural fracture dynamic influence are not considered in a traditional method is broken through, the soaking time can be more accurately optimized, the fracturing fluid utilization rate is increased, the reservoir transformation volume SRV is maximized, and theoretical guidance is provided for efficient development of deep shale gas.

Description

Technical Field

[0001] The present invention relates to a method for optimizing the shut-in time of a shale gas well after shale gas well fracturing, taking into account natural fractures, fracturing fluid seepage, microseismic data, hydraulic fractures and rock tension-shear failure, and in particular to a method for optimizing the shut-in time by combining numerical simulation and taking into account natural fractures, fracturing fluid seepage, hydraulic fractures and rock tension-shear failure, belonging to the technical field of oil and gas reservoir development. Background Art

[0002] With the continuous deepening of shale gas exploration and exploitation in my country, deep shale gas development has become a strategic replacement resource for China's natural gas reserve and production. How to efficiently and reasonably exploit deep shale gas is a new challenge we face. Deep shale gas reservoirs usually have the characteristics of low porosity and low permeability. Affected by its reservoir characteristics, hydraulic fracturing technology and horizontal drilling technology have been widely used in the development of deep shale gas. At present, most shale gas reservoir development relies on high-displacement and large-liquid hydraulic fracturing technology. After fracturing, the fracturing fluid in the formation can still stimulate the reservoir to produce new reservoir reconstruction volume (SRV) under the action of high net pressure. In order to make full use of the remaining energy of the fracturing fluid and maximize the SRV, it is necessary to adopt post-fracturing well shut-in measures instead of rapid backflow. How to determine a reasonable well shut-in time has become a difficulty in current operations.

[0003] At present, domestic and foreign scholars have conducted a lot of research on post-pressure soaking of low-permeability tight shale oil reservoirs. Some scholars have mainly carried out research on soaking time optimization from the perspectives of shale oil soaking imbibition, soaking to improve formation capacity, and low-salinity water injection chemical potential (Li Chuanliang, Mao Wanyi, Wu Tingxin, et al. Research on the mechanism of imbibition oil recovery [J]. Xinjiang Petroleum Geology, 2019, 40(6): 687-694; Li Yaohua, Song Yan, Xu Xingyou, et al. Wettability and spontaneous imbibition characteristics of tuffaceous shale oil layer in the 7th member of the Yanchang Formation in the Ordos Basin [J]. Acta Petrolei Sinica, 2020, 41(10):1229-1237); other scholars have carried out a lot of research on soaking time optimization through indoor physical experiments combined with scale conversion methods (VALLURI MK, ALVAREZ JO, SCHECHTER DS. Study of the rock / fluid interactions of sodium and calcium brines with ultra-tight rock surfaces and their impact on improving oil recovery by spontaneous imbibition[R]. SPE180274-MS, 2016; ZHOU Z, ABASS H, LI X, et al. Mechanisms of imbibition during hydraulic fracturing in shale formations[J]. Journal of Petroleum Science andEngineering, 2016, 141: 125-132).Regarding the study of the shut-in time of shale gas reservoirs, some scholars have conducted a series of physical experiments and numerical simulation studies from the perspective of shale gas hydration (Wang Fei, Pan Ziqing. Numerical simulation of fracturing fluid flowback in shale reservoirs driven by chemical potential difference [J]. Petroleum Exploration and Development, 2016, 43(6): 971-977; LaiFP, Li ZP, Zhang TT, et al. Characteristics of microscopic pore structure and its influence on spontaneous imbibition of tight gas reservoir in the Ordos Basin, China [J]. Journal of Petroleum Science and Engineering, 2019, 172: 23-31.), and believed that microcracks can be generated through hydration operations, which is conducive to the discharge of shale gas after hydration. However, no theoretical model and optimization method for optimizing the shut-in time of shale gas wells after hydration have been proposed. A large number of literature surveys also show that most existing literature and patents do not have research on the prediction of reasonable shut-in time of shale gas wells based on rock tension shear failure theory.

[0004] Analysis of published studies shows that most studies on the soaking time target tight oil and shale oil reservoirs rather than shale gas reservoirs, and the mechanism of soaking time mainly considers oil-water replacement, osmotic pressure induced by chemical potential difference and soaking energy storage, rather than the mechanism of tension and shear failure induced by high-pressure fracturing fluid in soaked formations. To this end, it is necessary to consider natural fractures, fracturing fluid seepage, microseismic data, hydraulic fractures and rock tension-shear failure, and propose a new method for optimizing soaking time after fracturing for shale gas reservoirs. To achieve this goal, according to the theories of seepage mechanics, elastic mechanics, fluid mechanics, and SRV identification model constructed based on microseismic data, a deep shale gas matrix and fracture seepage model, a randomly distributed natural fracture model, a hydraulic fracture model based on fitted fracture data, and a rock shear-slip tensile failure criterion and SRV permeability model were established, thereby constructing a complete method for optimizing soaking time after fracturing for shale gas wells. Summary of the invention

[0005] The present invention mainly aims at how to determine the optimal shut-in time after shale gas reservoir fracturing, and proposes a new method for optimizing the shut-in time after fracturing. The method is based on seepage mechanics, elastic mechanics and Mohr-Coulomb's law, and takes into account natural fractures, fracturing fluid seepage, microseismic data, hydraulic fractures, rock shear failure and changes in permeability in the destruction zone, establishes a corresponding mathematical model, and finally proposes a new method for optimizing the shut-in time after shale gas pressure. Through this method, the relationship between the rock volume destruction and time during the shut-in process of the corresponding fracturing well can be obtained according to the input basic construction parameters and reservoir parameters, and the optimal shut-in time can be further obtained through this relationship. This method combines all the physical properties of shale gas reservoirs, is an important innovation in studying the optimization theory of the shut-in time after shale gas pressure, and can serve as a good reference for scientific research and shale gas development engineering applications.

[0006] The technical solution provided by the present invention to solve the above technical problems is: a method for optimizing the shut-in time of a shale gas well after pressure reduction based on the rock tension-shear failure criterion, comprising the following steps: (1) Based on the well logging data and geomechanical physical property parameters of the target shale gas reservoir, a physical model of the target reservoir is constructed. The main parameters include model size, boundary conditions, number of fracture clusters, and cluster spacing; (2) Based on the microseismic data monitored on site, the length and width of the transformed volume, the SRV range is obtained through boundary data identification, and then the fracturing construction pressure and construction data are fitted to obtain the parameters of each hydraulic fracture and use the SRV range and its fracture parameters as input parameters for simulation optimization; (3) A natural fracture random distribution model is constructed based on the location, density, azimuth and length of natural fractures, and the morphology of natural fractures in the actual reservoir can be characterized based on the input natural fracture parameters; (4) Based on seepage mechanics, the law of conservation of matter and Darcy's law, a fracturing fluid injection model and a shale reservoir well soaking seepage model were constructed to obtain the formation pressure distribution of the shale reservoir during the injection and soaking processes; (5) The stress distribution of natural fractures is deduced based on the orientation and magnitude of geostress, and the natural fracture failure criterion is constructed in combination with Moore's Coulomb's law to determine whether the natural fractures undergo tensile or shear failure under the action of formation pressure. For formations that undergo tensile or shear failure, an equivalent permeability model after formation failure is established based on the cubic law to characterize the continuous transformation of the reservoir by the fracturing fluid during the soaking process.

[0007] (6) Based on the initial conditions, boundary conditions, input parameters and theoretical model obtained in steps (1) to (5), the corresponding simulation code is compiled to perform simulation operations, and a relationship curve between shale gas formation tension, shear damage volume and soaking time during soaking can be obtained. When the formation damage volume no longer increases at a certain moment, this moment is considered to be the optimal soaking time.

[0008] A further technical solution is that in step (1), a physical model of the target reservoir is constructed based on the target shale gas reservoir logging data and geomechanical physical property parameters, wherein the main parameters include model size, boundary conditions, number of fracture clusters, and cluster spacing.

[0009] Further, the technical solution is that the specific process of step (2) is as follows: according to the microseismic data monitored on site, the length and width of the transformation volume, the range of the reservoir transformation volume (SRV) is obtained through boundary data identification, and then the parameters of each hydraulic fracturing crack, including the length, width and fracture conductivity, are obtained by fitting the fracturing construction pressure and construction data, and the SRV range and fracture parameters are used as input parameters for simulation optimization; Further, the technical solution is that the specific process of step (3) is as follows: a natural fracture random distribution model is constructed through the natural fracture position, density, azimuth and length, and the natural fracture morphology of the real reservoir can be characterized according to the input natural fracture parameters. Based on the following formulas (1) to (3), natural fracture zones of different scales and orientations can be generated: Assuming that the positions of natural fractures in discrete natural fracture groups obey random uniform distribution, the number of natural fractures (N) is calculated as: (1) In the formula, N is the number of natural fractures, bars; r nf is the density of natural fractures, lines / m 2 ; a is the length of the natural fracture zone, m; b is the width of the natural fracture zone, m.

[0010] The azimuth of the natural fracture ( β ) and length ( l ) can be described by Fisher distribution and normal distribution, namely: (2) (3) In the formula, β is the azimuth of the natural fracture, °; c is the angle between the natural fracture zone and the horizontal wellbore, °; arccos is the inverse cosine function, dimensionless;R It is a random number between 0 and 1, dimensionless; Z β is the coefficient of deviation, dimensionless; l is the characterization length of natural fractures, m; l ave is the average length of natural fractures, m; σ 1 is the standard deviation of length, m.

[0011] A further technical solution is that the specific process of step (4) is as follows: based on seepage mechanics, the law of conservation of matter and Darcy's law, a seepage model of shale reservoir during fracturing fluid injection and well soaking is constructed to obtain the formation pressure distribution in the shale reservoir during injection and well soaking: (4) In the formula is the symbol for partial differential, dimensionless; P is the reservoir pore pressure, MPa; H is the crack height, m; K f is the equivalent permeability, mD; m is the fracturing fluid viscosity, mPa·s; q L is the fluid loss per unit length of fracture, m 3 / s; is the reservoir porosity, dimensionless; B is the volume coefficient of the fracturing fluid under formation conditions, dimensionless; x is the coordinate along the x-axis; y For along y Coordinates in the axis direction; t is time, s; △ x For grid blocks in x The change in size in the direction, m; y For grid blocks in y The change in size in the direction, m.

[0012] For slightly compressible fluid, the volume coefficient expression in the formation is: (5) In the formula, B is the volume coefficient of the fracturing fluid under formation conditions, dimensionless; C 1 is the compressibility of the liquid, MPa -1 ; B 0 is the volume coefficient of the fracturing fluid at the reference pressure, dimensionless; P is the reference formation pressure, MPa; P i is the original pore pressure of the reservoir, MPa.

[0013] A further technical solution is that the specific process of step (5) is as follows: the force distribution of the natural fracture is deduced according to the orientation of the ground stress, and the natural fracture failure criterion is constructed in combination with Moore's Coulomb's law to determine whether the natural fracture undergoes tension or shear failure under the action of the formation pressure: The tensile failure discriminant is: (6) The shear failure discriminant is: (7) In the formula p nf is the fluid pressure in the fracture, MPa; p n is the normal stress on the crack surface, MPa; S t is the tensile strength of the crack surface, MPa; p τ is the shear stress on the crack surface, MPa; K nf is the friction coefficient on the natural fracture surface, dimensionless; t 0 is the cohesion of natural fractures, MPa.

[0014] For formations that have tensile or shear failure, an equivalent permeability model after formation failure is established based on the cubic law to characterize the continuous transformation of the reservoir by the fracturing fluid during well soaking: (8) In the formula K f is the equivalent permeability, mD; a f is the total opening of natural fractures, m; S f is the spacing of natural fractures, m.

[0015] According to the linear elastic theory, the total fracture aperture includes the normal aperture of the natural fracture, the shear dilation aperture and the original aperture, which can be expressed as: (9) In the formula a f is the total opening of natural fractures, m; a 0 is the initial opening of the natural fracture, m; a n is the normal opening of the natural fracture, m; a s is the dilatant shear opening, m; Pn is the reservoir pore pressure, MPa; σ n is the normal stress on the crack surface, MPa; K n is the positive stiffness of the crack, MPa / m; K s is the shear stiffness of the crack, MPa / m; t n is the shear stress on the crack surface, MPa; f dil is the shear expansion angle, °; tan is the sine function, dimensionless.

[0016] A further technical solution is that the specific process of step (6) is as follows: based on the initial conditions, boundary conditions, input parameters and theoretical model constructed in steps (1) to (5), a corresponding simulation code is compiled to perform simulation operations, thereby obtaining a relationship curve between shale gas formation tension, shear failure volume and soaking time during the soaking process.

[0017] The present invention is aimed at the well shut-in process after fracturing of shale gas reservoirs with natural fractures, and proposes a well shut-in time optimization method based on Moore-Coulomb's law. According to seepage mechanics, elastic mechanics, Darcy's law, etc., we established a natural fracture random distribution model, a fracturing fluid seepage model, a rock shear failure theoretical model and a damage zone permeability change model, and finally constructed a shale gas well shut-in time optimization method considering natural fractures, fracturing fluid seepage, microseismic data, hydraulic fractures, rock shear failure and damage zone permeability change. Compared with traditional conventional methods, this method takes into account the main characteristics of shale gas natural fracture development, rock shear failure and microseismic data. It is an important innovation in the study of shale gas well shut-in return flow theory after fracturing, and can provide scientific and reasonable guidance for shale gas well shut-in return flow practice, which has important engineering significance for further improving the efficiency of fracturing transformation. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 Schematic diagram of rock tension shear failure; Figure 2 Distribution cloud diagram of tensile failure (left) and shear failure (right) during well soaking in Example 1; Figure 3 The relationship between the tensile shear failure volume and the soaking time in Example 1. DETAILED DESCRIPTION

[0019] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention is further illustrated below with reference to the accompanying drawings and embodiments.

[0020] A method for optimizing the shut-in time of a shale gas well after pyrolysis based on the rock tension-shear failure criterion comprises the following steps: (1) Based on the well logging data and geomechanical physical property parameters of the target shale gas reservoir, a physical model of the target reservoir is constructed. The main parameters include model size, boundary conditions, number of fracture clusters, and cluster spacing; (2) Based on the microseismic data monitored on site, the length and width of the transformed volume, the SRV range is obtained through boundary data identification, and then the fracturing construction pressure and construction data are fitted to obtain the parameters of each hydraulic fracture and use the SRV range and its fracture parameters as input parameters for simulation optimization; (3) A natural fracture random distribution model is constructed based on the location, density, azimuth and length of natural fractures, and the morphology of natural fractures in the actual reservoir can be characterized based on the input natural fracture parameters; (4) Based on seepage mechanics, the law of conservation of matter and Darcy's law, a fracturing fluid injection model and a shale reservoir well soaking seepage model were constructed to obtain the formation pressure distribution of the shale reservoir during the injection and soaking processes; (5) The stress distribution of natural fractures is deduced based on the orientation and magnitude of geostress, and the natural fracture failure criterion is constructed in combination with Moore's Coulomb's law to determine whether the natural fractures undergo tensile or shear failure under the action of formation pressure. For formations that undergo tensile or shear failure, an equivalent permeability model after formation failure is established based on the cubic law to characterize the continuous transformation of the reservoir by the fracturing fluid during the soaking process.

[0021] (6) Based on the initial conditions, boundary conditions, input parameters and theoretical model obtained in steps (1) to (5), the corresponding simulation code is compiled to perform simulation operations, and a relationship curve between shale gas formation tension, shear damage volume and soaking time during soaking can be obtained. When the formation damage volume no longer increases at a certain moment, this moment is considered to be the optimal soaking time.

[0022] In step (1) of the present invention, it is necessary to construct a physical model of the target reservoir based on the well logging data and geomechanical physical property parameters of the target shale gas reservoir, which mainly includes model size, boundary conditions, number of fracture clusters, cluster spacing, etc.

[0023] In step (2) of the present invention, the reservoir stimulation volume (SRV) range is obtained by boundary data identification based on the microseismic data, stimulation volume length and width monitored on site, and then the parameters of each hydraulic fracturing crack, including length, width and fracture conductivity, are obtained by fitting the fracturing construction pressure and construction data, and the SRV range and fracture parameters are used as input parameters for simulation optimization.

[0024] In step (3) of the present invention, a natural fracture random distribution model is constructed by using the natural fracture position, density, azimuth and length, and the natural fracture morphology of the real reservoir can be characterized according to the input natural fracture parameters: In which, assuming that the positions of natural fractures in the discrete natural fracture group obey random uniform distribution, the calculation formula for the number of natural fractures (N) is: (1) In the formula, N is the number of natural fractures, bars; r nf is the density of natural fractures, lines / m 2 ; a is the length of the natural fracture zone, m; b is the width of the natural fracture zone, m.

[0025] The azimuth of the natural fracture ( β ) and length ( l ) can be described by Fisher distribution and normal distribution, namely: (2) (3) In the formula, β is the azimuth of the natural fracture, °; c is the angle between the natural fracture zone and the horizontal wellbore, °; arccos is the inverse cosine function, dimensionless; R It is a random number between 0 and 1, dimensionless; Z β is the coefficient of deviation, dimensionless; l is the characterization length of natural fractures, m; l ave is the average length of natural fractures, m; σ 1 is the standard deviation of length, m.

[0026] In step (4) of the present invention, a seepage model of shale reservoir during fracturing fluid injection and well soaking is constructed based on seepage mechanics, the law of conservation of matter and Darcy's law, and the formation pressure distribution in the shale reservoir during injection and well soaking is obtained: (4) In the formula is the symbol for partial differential, dimensionless; P is the reservoir pore pressure, MPa; H is the crack height, m; K f is the equivalent permeability, mD; m is the fracturing fluid viscosity, mPa·s; q L is the fluid loss per unit length of fracture, m 3 / s; is the reservoir porosity, dimensionless; B is the volume coefficient of the fracturing fluid under formation conditions, dimensionless;x is the coordinate along the x-axis; y For along y Coordinates in the axis direction; t is time, s; △ x For grid blocks in x The change in size in the direction, m; y For grid blocks in y The change in size in the direction, m.

[0027] For slightly compressible fluid, the volume coefficient expression in the formation is: (5) In the formula, B is the volume coefficient of the fracturing fluid under formation conditions, dimensionless; C 1 is the compressibility of the liquid, MPa -1 ; B 0 is the volume coefficient of the fracturing fluid at the reference pressure, dimensionless; P is the reference formation pressure, MPa; P i is the original pore pressure of the reservoir, MPa.

[0028] In step (5) of the present invention, the schematic diagram of the rock tension shear process simulated by the example is as follows: Figure 1 As shown in the figure, the force distribution of natural fractures should be deduced according to the orientation of ground stress, and the natural fracture failure criterion is constructed in combination with Moore-Coulomb's law as follows to determine whether natural fractures are capable of tensile or shear failure under the action of formation pressure: The tensile failure discriminant is: (6) The shear failure discriminant is: (7) In the formula p nf is the fluid pressure in the fracture, MPa; p n is the normal stress on the crack surface, MPa; S t is the tensile strength of the crack surface, MPa; p τ is the shear stress on the crack surface, MPa; K nf is the friction coefficient on the natural fracture surface, dimensionless; t 0 is the cohesion of natural fractures, MPa.

[0029] For formations that have tensile or shear failure, an equivalent permeability model after formation failure is established based on the cubic law to characterize the continuous transformation of the reservoir by the fracturing fluid during well soaking: (8) In the formula K f is the equivalent permeability, mD; a f is the total opening of natural fractures, m; S f is the spacing of natural fractures, m.

[0030] According to the linear elastic theory, the total fracture aperture includes the normal aperture of the natural fracture, the shear dilation aperture and the original aperture, which can be expressed as: (9) In the formula a f is the total opening of natural fractures, m; a 0 is the initial opening of the natural fracture, m; a n is the normal opening of the natural fracture, m; a s is the dilatant shear opening, m; P n is the reservoir pore pressure, MPa; σ n is the normal stress on the crack surface, MPa; K n is the positive stiffness of the crack, MPa / m; K s is the shear stiffness of the crack, MPa / m; t n is the shear stress on the crack surface, MPa; f dil is the shear expansion angle, °; tan is the sine function, dimensionless.

[0031] In step (6) of the present invention, based on the initial conditions, boundary conditions, input parameters and theoretical model constructed in steps (1) to (5), a corresponding simulation code is compiled to perform simulation operations, so as to obtain a relationship curve between shale gas formation tension, shear damage volume and soaking time during soaking. When the formation damage volume no longer increases at a certain moment of soaking time, it is considered that this moment is the optimal soaking time.

[0032] Example 1: This example is implemented in a shale gas reservoir in Da'anjing District. Through on-site logging and well testing, the geological data of the block are obtained, and the parameters obtained are representative. The specific simulation method steps are as follows: 1. The geological parameters of the reservoir were obtained through on-site logging: rock Poisson's ratio 0.21, rock elastic modulus 37.4 MPa, vertical depth of the well 4175 m, reservoir thickness 20 m, initial formation permeability 0.05 mD, initial porosity 5%, minimum horizontal geostress 104.2 MPa, maximum horizontal geostress 117.6 MPa, fracturing fluid viscosity 4 mpa·s, injection displacement 18 m³ / min, total injected fluid volume 2584 m³, number of fracture clusters 6, cluster spacing 7 m, etc.

[0033] 2. Based on steps (1) to (5), the corresponding simulation code is compiled, and the obtained geological parameters are introduced into the established code model, namely formulas (1) to (9), to obtain the reservoir reconstruction volume (SRV) range, build a random distribution model of natural fractures, obtain the formation pressure distribution in the shale reservoir during injection and well soaking, deduce the force distribution of natural fractures and judge whether the natural fractures are capable of tensile or shear failure under the action of formation pressure; finally, the proportion of tensile and shear failures during well soaking is obtained (such as Figure 2 ), and its relationship with the soaking time (such as Figure 3 ), in order to determine the best stewing time.

[0034] The above description is not intended to impose any form of limitation on the present invention. Although the present invention has been disclosed through the above embodiments, it is not intended to limit the present invention. Any technician familiar with the profession can make some changes or modifications to equivalent embodiments of equivalent changes using the technical contents disclosed above without departing from the scope of the technical solution of the present invention. However, any simple modification, equivalent change and modification made to the above embodiments based on the technical essence of the present invention without departing from the content of the technical solution of the present invention still falls within the scope of the technical solution of the present invention.

Claims

1. A method for optimizing the shut-in time of a shale gas well after pyrolysis based on the rock tension-shear failure criterion, characterized in that: The following steps are involved: (1) Based on the well logging data and geomechanical physical property parameters of the target shale gas reservoir, a physical model of the target reservoir is constructed. The main parameters include model size, boundary conditions, number of fracture clusters, and cluster spacing; (2) Based on the microseismic data monitored on site, the length and width of the transformed volume, the SRV range is obtained through boundary data identification, and then the fracturing construction pressure and construction data are fitted to obtain the parameters of each hydraulic fracture and use the SRV range and its fracture parameters as input parameters for simulation optimization; (3) A natural fracture random distribution model is constructed based on the location, density, azimuth and length of natural fractures, and the morphology of natural fractures in the actual reservoir can be characterized based on the input natural fracture parameters; (4) Based on seepage mechanics, the law of conservation of matter and Darcy's law, a fracturing fluid injection model and a shale reservoir well soaking seepage model were constructed to obtain the formation pressure distribution of the shale reservoir during the injection and soaking processes; (5) The stress distribution of natural fractures is derived based on the orientation and magnitude of ground stress, and the natural fracture failure criterion is constructed in combination with Moore-Coulomb's law to determine whether natural fractures undergo tensile or shear failure under the action of formation pressure. For formations that undergo tensile or shear failure, an equivalent permeability model after formation failure is established based on the cubic law to characterize the continuous transformation of the reservoir by the fracturing fluid during the well soaking process. (6) Based on the initial conditions, boundary conditions, input parameters and theoretical model obtained in steps (1) to (5), the corresponding simulation code is compiled to perform simulation operations, and a relationship curve between shale gas formation tension, shear damage volume and soaking time during soaking can be obtained. When the formation damage volume no longer increases at a certain moment, this moment is considered to be the optimal soaking time.

2. The method for optimizing the shut-in time of a shale gas well after shale gas well pressure reduction based on the rock tension-shear failure criterion according to claim 1, characterized in that: The step (2) specifically includes: obtaining the range of reservoir stimulation volume (SRV) through boundary data identification based on the microseismic data, stimulation volume length and width monitored on site, and then fitting the fracturing construction pressure and construction data to obtain the parameters of each hydraulic fracturing crack, including the length, width and fracture conductivity, and using the SRV range and fracture parameters as input parameters for simulation optimization.

3. The method for optimizing the shut-in time of a shale gas well after well pressure reduction based on the rock tension-shear failure criterion according to claim 1, characterized in that: The step (3) constructs a random distribution model of natural fractures, specifically comprising: assuming that the positions of natural fractures in the discrete natural fracture group obey a random uniform distribution, constructing a model according to the positions, density, azimuth and length of the natural fractures, and describing the azimuth and length of the natural fractures by Fisher distribution and normal distribution: The calculation formula for the number of natural fractures (N) is: （1） In the formula, N is the number of natural fractures, bars; ρ nf is the density of natural fractures, lines / m 2 ; a is the length of the natural fracture zone, m; b is the width of the natural fracture zone, m; The azimuth of the natural fracture ( β ) and length ( l ) is calculated as: （2） （3） In the formula, β is the azimuth of the natural fracture, °; γ is the angle between the natural fracture zone and the horizontal wellbore, °; arccos is the inverse cosine function, dimensionless; R It is a random number between 0 and 1, dimensionless; Z β is the coefficient of deviation, dimensionless; l is the characterization length of natural fractures, m; l ave is the average length of natural fractures, m; σ1 is the standard deviation of length, m.

4. The method for optimizing the shut-in time of a shale gas well after well pressure reduction based on the rock tension-shear failure criterion according to claim 1, characterized in that: The fracturing fluid injection model and shale reservoir well soaking seepage model constructed in step (4) specifically include: （4） In the formula is the symbol for partial differential, dimensionless; P is the reservoir pore pressure, MPa; H is the crack height, m; K f is the equivalent permeability, mD; μ is the fracturing fluid viscosity, mPa·s; q L is the fluid loss per unit length of fracture, m 3 / s; is the reservoir porosity, dimensionless; B is the volume coefficient of the fracturing fluid under formation conditions, dimensionless; x is the coordinate along the x-axis; y For along y Coordinates in the axis direction; t is time, s; △ x For grid blocks in x The change in size in the direction, m; y For grid blocks in y The change in size in the direction, m; Among them, for slightly compressible fluid, the volume coefficient expression in the formation is: （5） In the formula, B is the volume coefficient of the fracturing fluid under formation conditions, dimensionless; C 1 is the compressibility coefficient of the liquid, MPa -1 ; B 0 is the volume coefficient of the fracturing fluid at the reference pressure, dimensionless; P is the reference formation pressure, MPa; P i is the original pore pressure of the reservoir, MPa.

5. The method for optimizing the shut-in time of a shale gas well after well pressure reduction based on the rock tension-shear failure criterion according to claim 1, characterized in that: The natural fracture failure criterion and equivalent permeability model constructed in step (5) specifically include: The tensile failure discriminant is: （6） The shear failure discriminant is: （7） In the formula p nf is the fluid pressure in the fracture, MPa; p n is the normal stress on the crack surface, MPa; S t is the tensile strength of the crack surface, MPa; p τ is the shear stress on the crack surface, MPa; K nf is the friction coefficient on the natural fracture surface, dimensionless; τ 0 is the cohesion of natural fractures, MPa; The equivalent permeability model is: （8） In the formula, K f is the equivalent permeability, mD; a f is the total opening of natural fractures, m; S f is the spacing of natural fractures, m; According to the linear elastic theory, the total fracture aperture includes the normal aperture, shear dilation aperture and original aperture of the natural fracture, which can be expressed as: （9） In the formula a f is the total opening of natural fractures, m; a 0 is the initial opening of the natural fracture, m; a n is the normal opening of the natural fracture, m; a s is the dilatant shear opening, m; P n is the reservoir pore pressure, MPa; σ n is the normal stress on the crack surface, MPa; K n is the positive stiffness of the crack, MPa / m; K s is the shear stiffness of the crack, MPa / m; τ n is the shear stress on the crack surface, MPa; φ dil is the shear expansion angle, °; tan is the sine function, dimensionless.

6. The method for optimizing the shut-in time of a shale gas well after pyrolysis based on the rock tension-shear failure criterion according to claim 1, characterized in that: The simulation code described in step (6) specifically includes: a corresponding simulation code compiled based on the theoretical model constructed in steps (1) to (5), performing simulation operations, and finally obtaining a relationship curve between tensile properties, shear failure volume and soaking time.

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