Stress field disturbance analysis method for shale gas development zone based on multi-source data fusion

Abstract

The application discloses a shale gas development zone stress field disturbance analysis method based on multi-source data fusion, which comprises the following steps: obtaining initial structural form parameters and rock elastic parameters of a shale reservoir in a shale gas development zone, and constructing a three-dimensional static geomechanical model of the shale reservoir; calculating total stress of disturbance sources in production construction and production process; collecting microseismic data of historical effective microseismic events, and calculating spatial distribution density, microseismic energy release rate and energy release intensity of the effective microseismic events; inputting the three-dimensional static geomechanical model as a dynamic disturbance source to perform inversion, and calculating matching degree; and adopting a genetic algorithm to optimize the structural form parameters and rock mechanical parameters of the three-dimensional static geomechanical model, and analyzing stress disturbance risks of new dynamic disturbance sources to the shale gas development zone. The application systematically couples three types of data, i.e., static geology, dynamic engineering and dynamic monitoring, and constructs a trinity analysis framework of "geology-engineering-monitoring".

Description

Technical Field

[0001] This invention relates to the field of stress analysis in shale gas development, and specifically to a method for analyzing stress field disturbances in shale gas development areas based on multi-source data fusion. Background Technology

[0002] Shale gas development relies on large-scale hydraulic fracturing and long-term production operations. These engineering activities disrupt the original underground stress balance, causing severe disturbances in the stress field, which in turn induces geological disasters such as fault activation, wellbore instability, and formation collapse, seriously threatening development safety and economic benefits. Accurate analysis and dynamic prediction of stress field disturbances are crucial for achieving early warning of geological disasters and represent a key technical challenge for the efficient development of shale gas.

[0003] Existing stress field analysis methods have the following technical shortcomings: First, traditional static geomechanical models rely solely on monitoring three-dimensional seismic data and construct the initial stress field through rock physics inversion, without considering the dynamic disturbances of engineering activities. Furthermore, due to the defects, omissions, and inaccuracies in seismic data detection, they cannot accurately reflect the actual impact of seismic activity. Second, analysis methods based solely on microseismic monitoring data can only reflect the superficial changes in stress through source parameters, without establishing a causal relationship with geological background and engineering parameters. Their quantitative analysis lacks the support of mechanical theory and is difficult to meet the needs of engineering prevention and control.

[0004] Therefore, this application proposes a method for stress field disturbance analysis in shale gas development areas based on multi-source data fusion. Summary of the Invention

[0005] To address the aforementioned shortcomings of existing technologies, this invention provides a method for analyzing stress field disturbances in shale gas development areas based on multi-source data fusion, which solves the defects of existing technologies such as single microseismic data stress disturbance analysis and inaccurate analysis results.

[0006] To achieve the above-mentioned objectives, the technical solution adopted by this invention is as follows:

[0007] A method for stress field disturbance analysis in shale gas development areas based on multi-source data fusion is provided, which includes:

[0008] Step S1: Obtain the initial structural morphology parameters and rock elastic parameters of the shale reservoir in the shale gas development area, calculate the initial rock mechanical parameters, input them into the finite element analysis software, and construct a three-dimensional static geomechanical model of the shale reservoir.

[0009] Step S2: Collect drilling trajectory parameters, fracturing operation parameters and production dynamic data of shale reservoirs, calculate the stress increment during the operation process and the stress change during the production process, and fuse the stress increment and stress change to calculate the total stress of disturbance sources during the production operation and production process.

[0010] Step S3: Collect microseismic data of historical effective microseismic events, and calculate the spatial distribution density, microseismic energy release rate, and energy release intensity of effective microseismic events;

[0011] Step S4: Input the spatial distribution density, microseismic energy release rate, energy release intensity, and total stress of the disturbance source as dynamic disturbance sources into the three-dimensional static geomechanical model for inversion. Calculate the matching degree of the three-dimensional static geomechanical model based on the distribution of high-stress disturbance areas and concentrated microseismic event areas during the inversion process.

[0012] Step S5: Construct iterative optimization objective functions for structural morphology parameters and rock mechanics parameters based on matching degree, and use a genetic algorithm to optimize the structural morphology parameters and rock mechanics parameters of the three-dimensional static geomechanical model. Use the optimized three-dimensional static geomechanical model to analyze the stress disturbance risk of new dynamic disturbance sources to the shale gas development area.

[0013] Further, step S1 includes:

[0014] Step S11: Obtain the initial structural morphology parameters and rock elastic parameters of the shale reservoir in the shale gas development area. The structural morphology parameters include fault dip angle. α Fault strike β Fault extension length L and fracture density l Rock elastic parameters include longitudinal wave velocity. V p transverse wave velocity V s and rock density r ;

[0015] Step S12: Based on P-wave velocity V p transverse wave velocity V s and rock density r Calculate the initial rock mechanics parameters, including Young's modulus. E Poisson's ratio bulk modulus K and shear modulus G ;

[0016] , , , ;

[0017] Step S13: Input the structural morphology parameters and rock mechanics parameters into the finite element analysis software to construct a three-dimensional static geomechanical model of the shale reservoir.

[0018] Further, step S2 includes:

[0019] Step S21: Collect drilling trajectory parameters, fracturing operation parameters, and production dynamic data of the shale reservoir. Drilling trajectory parameters include wellbore azimuth. i , well inclination angle c Fracturing parameters include pump pressure p Displacement q , liquid volume V , sand amount M Production dynamic data includes bottom hole flowing pressure. p wf Gas production Q g Production time t ;

[0020] Step S22: Quantify the fracturing operation parameters into stress increments during the operation process. ;

[0021] ;

[0022] in, This refers to the energy conversion efficiency during the fracturing process. For fracturing operation time, This represents the effective volume of the shale reservoir.

[0023] Step S23: Calculate the original reservoir pressure and bottom hole flowing pressure p wf The pressure difference between them yields the long-term pressure relief during the production process. Long-term pressure relief Quantified as stress change ;

[0024] ;

[0025] in, The coefficient of Brønsted;

[0026] Step S24: Calculate the stress change and stress increment Couple the stresses to calculate the total stress of disturbance sources in the production construction and production process. ;

[0027] ;

[0028] in, k For stress over time t The attenuation coefficient.

[0029] Further, step S3 includes:

[0030] Step S31: Collect the three-dimensional distance of the impact of historical effective microseismic events on shale reservoirs, and convert the three-dimensional distance into a three-dimensional static geomechanical model to obtain the three-dimensional side length of the three-dimensional distance in the three-dimensional static geomechanical model. 3D side length Microseismic statistical units are formed in a three-dimensional static geomechanical model to calculate the spatial distribution density of effective microseismic events. ;

[0031] ;

[0032] in, This represents the number of valid microseismic events occurring within the microseismic statistical unit. m For microseismic labeling;

[0033] Step S32: Estimate the energy release intensity of effective microseismic events in the microseismic statistical unit using the Gutenberg-Rickett law. And calculate the microseismic energy release rate in the microseismic statistical unit per unit time. ;

[0034] ;

[0035] in, For regional feature parameters, b For feature parameters, i Earthquake numbering for valid microseismic events. For the first effective microseismic event i The magnitude of a micro-earthquake. The specific magnitude estimated in effective microseismic events The number of large micro-earthquakes. The actual specific magnitude in effective microseismic events The number of large micro-earthquakes. w The actual specific magnitude in effective microseismic events Large micro-earthquakes numbered. Specific magnitude in effective microseismic events The magnitude of large micro-earthquakes. The actual specific magnitude in effective microseismic events The average magnitude of large micro-earthquakes The specific magnitude estimated in effective microseismic events The number of large micro-earthquakes and their relative magnitudes The difference in the number of large micro-earthquakes, This is the magnitude amplification factor. This is the effective monitoring time window for microseismic events.

[0036] Further, step S4 includes:

[0037] Step S41: Spatial distribution density Energy release intensity Microseismic energy release rate and total stress of disturbance source As a dynamic disturbance source input into the three-dimensional static geomechanical model, the three-dimensional static geomechanical model is inverted, and the stress field equilibrium equation and stress-strain constitutive relation model of the three-dimensional static geomechanical model are specifically as follows:

[0038] Stress field equilibrium equations: ;

[0039] in, For vector differential operators, In a three-dimensional static geomechanical model, time t spatial point The stress tensor, For time t spatial point The volume force tensor;

[0040] Stress-strain constitutive model: ;

[0041] in, Let be the total stress tensor at a point in space. For the elasticity matrix, Let S be the total strain tensor at a point in space. For plastic strain tensor;

[0042] Step S42: Obtain the high-stress disturbance region and the concentrated distribution region of microseismic events in the inversion process, and determine the element mesh number of the high-stress disturbance region. The number of cell grids in areas with concentrated microseismic events Calculate the matching degree of the three-dimensional static geomechanical model J ;

[0043] ;

[0044] in, This represents the number of intersecting element meshes between high-stress disturbance regions and regions with concentrated microseismic events.

[0045] Further, step S5 includes:

[0046] Step S51: Based on matching degree J Construct an iterative optimization objective function for structural morphology parameters and rock mechanical parameters;

[0047] ;

[0048] in, To construct populations of morphological parameters and rock mechanical parameters, These are the weights for the matching degree and the proportion of inverted stress perturbation, respectively. fitness function value, The stress disturbance intensity is simulated in a three-dimensional static geomechanical model. The stress disturbance intensity is derived from the inversion of microseismic events;

[0049] Step S52: Use the initial structural morphology parameters and rock mechanical parameters as the initial population. Genetic algorithms are used to process the initial population. Individuals within the organism undergo mutation and genetic manipulation;

[0050] Step S53: Input the population after each mutation into the three-dimensional static geomechanical model, update the three-dimensional static geomechanical model, and execute steps S41-S51 until the matching degree is reached. Stop the mutation and manipulation of the population, output the latest structural morphology parameters and rock mechanics parameters in the population, and complete the optimization of the three-dimensional static geomechanical model;

[0051] Step S54: Set the population mutation and number of genetic iterations. C When population variation and genetic operations reach the required number of variation iterations... C Even after that, the matching degree still cannot be satisfied. It also stops population variation, manipulates genetics, and selects... C The population that satisfies the iterative optimization objective function during the secondary mutation and genetic iteration process is used to optimize the three-dimensional static geomechanical model using the structural morphology parameters and rock mechanics parameters in the population that satisfies the iterative optimization objective function.

[0052] Step S55: Input the new dynamic disturbance source into the optimized three-dimensional static geomechanical model for further inversion, and assess whether there is a stress disturbance risk in the shale gas development area based on the maximum principal stress offset and minimum principal stress offset generated by the new dynamic disturbance source.

[0053] The beneficial effects of this invention are as follows:

[0054] This invention systematically couples three types of data: static geology, dynamic engineering, and dynamic monitoring, constructing a three-in-one analysis framework of "geology-engineering-monitoring," which fundamentally solves the problems of single data source and static model in traditional methods.

[0055] This invention uses the actual microseismic response as the "benchmark" for the model, forming a closed-loop correction mechanism of "simulation-monitoring-correction". By iteratively correcting the three-dimensional static geomechanical model, the output of the three-dimensional static geomechanical model is made to highly match the actual geological response, which greatly improves the accuracy and reliability of stress field inversion.

[0056] This invention not only achieves accurate quantitative inversion of stress field disturbances, but also enables mechanical disturbance analysis of multi-source stress disturbances throughout the development process. It can be used to guide well location optimization, fracturing parameter adjustment, and safety control, possessing both significant theoretical and engineering practical value. Attached Figure Description

[0057] Figure 1 This is a method for analyzing stress field disturbances in shale gas development areas based on multi-source data fusion. Detailed Implementation

[0058] The specific embodiments of the present invention are described below to enable those skilled in the art to understand the present invention. However, it should be understood that the present invention is not limited to the scope of the specific embodiments. For those skilled in the art, various changes are obvious as long as they are within the spirit and scope of the present invention as defined and determined by the appended claims. All inventions utilizing the concept of the present invention are protected.

[0059] like Figure 1 As shown, a method for stress field disturbance analysis in shale gas development areas based on multi-source data fusion includes:

[0060] Step S1: Obtain the initial structural morphology parameters and rock elastic parameters of the shale reservoir in the shale gas development area, calculate the initial rock mechanical parameters, input them into the finite element analysis software, and construct a three-dimensional static geomechanical model of the shale reservoir.

[0061] Step S1 specifically includes:

[0062] Step S11: Obtain the initial structural morphology parameters and rock elastic parameters of the shale reservoir in the shale gas development area. The structural morphology parameters include fault dip angle. α Fault strike β Fault extension length L and fracture density l Rock elastic parameters include longitudinal wave velocity. V p transverse wave velocity V s and rock density r ;

[0063] Step S12: Based on P-wave velocity V p transverse wave velocity V s and rock density r Calculate the initial rock mechanics parameters, including Young's modulus. E Poisson's ratio bulk modulus K and shear modulus G ;

[0064] , , , ;

[0065] Step S13: Input the structural morphology parameters and rock mechanics parameters into the finite element analysis software to construct a three-dimensional static geomechanical model of the shale reservoir. In this embodiment, the finite element analysis software used is FLAC3D software, and the three-dimensional static geomechanical model is generated in FLAC3D software.

[0066] Step S2: Collect drilling trajectory parameters, fracturing operation parameters and production dynamic data of shale reservoirs, calculate the stress increment during the operation process and the stress change during the production process, and fuse the stress increment and stress change to calculate the total stress of disturbance sources during the production operation and production process.

[0067] Step S2 specifically includes:

[0068] Step S21: Collect drilling trajectory parameters, fracturing operation parameters, and production dynamic data of the shale reservoir. Drilling trajectory parameters include wellbore azimuth. i , well inclination angle c Fracturing parameters include pump pressure p Displacement q , liquid volume V , sand amount M Production dynamic data includes bottom hole flowing pressure. p wf Gas production Q g Production time t ;

[0069] Step S22: Quantify the fracturing operation parameters into stress increments during the operation process. ;

[0070] ;

[0071] in, The energy conversion efficiency (dimensionless) during the fracturing process. For fracturing operation time, The effective volume of the shale reservoir (m³) 3 ); Pump pressure in this embodiment p (pa), displacement q (m) 3 / s), bulk modulus K (pa), the calculated stress increment The dimension of is pa, which is used to describe the change in formation stress caused by the instantaneous load of fracturing.

[0072] Step S23: Calculate the original reservoir pressure and bottom hole flowing pressure p wf The pressure difference between them yields the long-term pressure relief during the production process. Long-term pressure relief Quantified as stress change ;

[0073] ;

[0074] in, The coefficient of Bishop's coefficient; the coefficient of Bishop's coefficient Compared to Poisson All are dimensionless, long-term pressure relief The dimension of is (Pa), which is the difference between the original reservoir pressure and the current bottom hole flowing pressure; stress change. The dimension of is (pa), which means that the long-term decrease in reservoir pressure leads to a decrease in pore fluid pressure, which in turn changes the effective stress of the rock mass through fluid-rock mass coupling, and finally manifests as a change in macroscopic stress field.

[0075] This invention utilizes stress increments during the construction process. and long-term pressure relief Quantified stress change By superimposing the stresses, the total engineering disturbance stress is obtained, ensuring the uniformity of the parameters and the logical closed loop of the stress field equilibrium equation and the elastoplastic constitutive equation.

[0076] Step S24: Calculate the stress change and stress increment Couple the stresses to calculate the total stress of disturbance sources in the production construction and production process. ;

[0077] ;

[0078] in, k For stress over time t The attenuation coefficient.

[0079] Step S3: Collect microseismic data of historical effective microseismic events, and calculate the spatial distribution density, microseismic energy release rate, and energy release intensity of effective microseismic events.

[0080] Step S3 specifically includes:

[0081] Step S31: Collect the three-dimensional distance of the impact of historical effective microseismic events on shale reservoirs, and convert the three-dimensional distance into a three-dimensional static geomechanical model to obtain the three-dimensional side length of the three-dimensional distance in the three-dimensional static geomechanical model. 3D side length Microseismic statistical units are formed in a three-dimensional static geomechanical model to calculate the spatial distribution density of effective microseismic events. ;

[0082] ;

[0083] in, This represents the number of valid microseismic events occurring within the microseismic statistical unit. m For microseismic labeling;

[0084] Step S32: Estimate the energy release intensity of effective microseismic events in the microseismic statistical unit using the Gutenberg-Rickett law. And calculate the microseismic energy release rate in the microseismic statistical unit per unit time. ;

[0085] ;

[0086] in, For regional feature parameters, b For feature parameters, i Earthquake numbering for valid microseismic events. For the first effective microseismic event i The magnitude of a micro-earthquake. The specific magnitude estimated in effective microseismic events The number of large micro-earthquakes. The actual specific magnitude in effective microseismic events The number of large micro-earthquakes. w The actual specific magnitude in effective microseismic events Large micro-earthquakes numbered. Specific magnitude in effective microseismic events The magnitude of large micro-earthquakes. The actual specific magnitude in effective microseismic events The average magnitude of large micro-earthquakes The specific magnitude estimated in effective microseismic events The number of large micro-earthquakes and their relative magnitudes The difference in the number of large micro-earthquakes, This is the magnitude amplification factor. This is the effective monitoring time window for microseismic events.

[0087] During the occurrence of effective microseismic events, the ideal situation is within the monitoring time window. All seismic events within the region have been captured and recorded in the earthquake catalog by the earthquake monitoring network. However, the catalog may miss some microseismic events below the corresponding magnitude, making it incomplete. Therefore, this invention estimates the number of larger microseismic magnitudes using the Gutenberg-Richard law to reflect undetected microseisms. The current magnitude is amplified by the average of the actual larger microseismic magnitudes to ensure a more accurate microseismic energy release rate after effective microseismic events occur, thereby increasing the accuracy and reliability of the analysis of the impact of effective microseismic events on the stress field of shale gas development areas.

[0088] Step S4: Input the spatial distribution density, microseismic energy release rate, energy release intensity, and total stress of the disturbance source as dynamic disturbance sources into the three-dimensional static geomechanical model for inversion. Calculate the matching degree of the three-dimensional static geomechanical model based on the distribution of high-stress disturbance areas and concentrated microseismic event areas during the inversion process.

[0089] Step S4 specifically includes:

[0090] Step S41: Spatial distribution density Energy release intensity Microseismic energy release rate and total stress of disturbance source As a dynamic disturbance source input into the three-dimensional static geomechanical model, the three-dimensional static geomechanical model is inverted, and the stress field equilibrium equation and stress-strain constitutive relation model of the three-dimensional static geomechanical model are specifically as follows:

[0091] Stress field equilibrium equations: ;

[0092] in, For vector differential operators, In a three-dimensional static geomechanical model, time t spatial point The stress tensor, For time t spatial point The volume force tensor;

[0093] Stress-strain constitutive model: ;

[0094] in, Let be the total stress tensor at a point in space. For the elasticity matrix, Let S be the total strain tensor at a point in space. For plastic strain tensor;

[0095] Step S42: Obtain the high-stress disturbance region and the concentrated distribution region of microseismic events in the inversion process, and determine the element mesh number of the high-stress disturbance region. The number of cell grids in areas with concentrated microseismic events Calculate the matching degree of the three-dimensional static geomechanical model J ;

[0096] ;

[0097] in, This represents the number of intersecting element meshes between high-stress disturbance regions and regions with concentrated microseismic events.

[0098] This invention introduces a matching degree J This method quantifies the spatial overlap between the "high-stress disturbance area derived from inversion" and the "actual microseismic event concentration area," determines whether the three-dimensional static geomechanical model accurately captures the causal relationship between stress disturbance and geological response, and assists in the iterative optimization and accuracy improvement of the model.

[0099] Step S5: Construct iterative optimization objective functions for structural morphology parameters and rock mechanics parameters based on matching degree, and use a genetic algorithm to optimize the structural morphology parameters and rock mechanics parameters of the three-dimensional static geomechanical model. Use the optimized three-dimensional static geomechanical model to analyze the stress disturbance risk of new dynamic disturbance sources to the shale gas development area.

[0100] Step S5 specifically includes:

[0101] Step S51: Based on matching degree J Construct an iterative optimization objective function for structural morphology parameters and rock mechanical parameters;

[0102] ;

[0103] in, To construct populations of morphological parameters and rock mechanical parameters, These are the weights for the matching degree and the proportion of inverted stress perturbation, respectively. fitness function value, The stress disturbance intensity is simulated in a three-dimensional static geomechanical model. The stress disturbance intensity is derived from the inversion of microseismic events;

[0104] Step S52: Use the initial structural morphology parameters and rock mechanical parameters as the initial population. Genetic algorithms are used to process the initial population. Individuals in the population undergo mutation and genetic manipulation, with the individual mutation rate set to 20% and the population mutation rate set to 10%.

[0105] Step S53: Input the population after each mutation into the three-dimensional static geomechanical model, update the three-dimensional static geomechanical model, and execute steps S41-S51 until the matching degree is reached. Stop the mutation and manipulation of the population, output the latest structural morphology parameters and rock mechanics parameters in the population, and complete the optimization of the three-dimensional static geomechanical model;

[0106] Step S54: Set the population mutation and number of genetic iterations. C When population variation and genetic operations reach the required number of variation iterations... C Even after that, the matching degree still cannot be satisfied. It also stops population variation, manipulates genetics, and selects... C The population that satisfies the iterative optimization objective function during the secondary mutation and genetic iteration process is used to optimize the three-dimensional static geomechanical model using the structural morphology parameters and rock mechanics parameters in the population that satisfies the iterative optimization objective function.

[0107] Step S55: Input the new dynamic disturbance source into the optimized three-dimensional static geomechanical model for further inversion, and assess whether there is a stress disturbance risk in the shale gas development area based on the maximum principal stress offset and minimum principal stress offset generated by the new dynamic disturbance source.

[0108] The larger the maximum principal stress offset and the minimum principal stress offset, the greater the stress disturbance of the new dynamic disturbance source on the shale gas development area, and the greater the stress disturbance risk of the shale gas development area; conversely, the smaller the offset and the smaller the offset, the greater the stress disturbance.

[0109] This invention systematically couples three types of data: static geology, dynamic engineering, and dynamic monitoring, constructing a three-in-one analysis framework of "geology-engineering-monitoring," which fundamentally solves the problems of single data source and static model in traditional methods.

[0110] This invention uses the actual microseismic response as the "benchmark" for the model, forming a closed-loop correction mechanism of "simulation-monitoring-correction". By iteratively correcting the three-dimensional static geomechanical model, the output of the three-dimensional static geomechanical model is made to highly match the actual geological response, which greatly improves the accuracy and reliability of stress field inversion.

[0111] This invention not only achieves accurate quantitative inversion of stress field disturbances, but also enables mechanical disturbance analysis of multi-source stress disturbances throughout the development process. It can be used to guide well location optimization, fracturing parameter adjustment, and safety control, possessing both significant theoretical and engineering practical value.

Claims

1. A method for analyzing stress field disturbances in shale gas development areas based on multi-source data fusion, characterized in that, include: Step S1: Obtain the initial structural morphology parameters and rock elastic parameters of the shale reservoir in the shale gas development area, calculate the initial rock mechanical parameters, input them into the finite element analysis software, and construct a three-dimensional static geomechanical model of the shale reservoir. Step S2: Collect drilling trajectory parameters, fracturing operation parameters and production dynamic data of shale reservoirs, calculate the stress increment during the operation process and the stress change during the production process, and fuse the stress increment and stress change to calculate the total stress of disturbance sources during the production operation and production process. Step S3: Collect microseismic data of historical effective microseismic events, and calculate the spatial distribution density, microseismic energy release rate, and energy release intensity of effective microseismic events; Step S4: Input the spatial distribution density, microseismic energy release rate, energy release intensity, and total stress of the disturbance source as dynamic disturbance sources into the three-dimensional static geomechanical model for inversion. Calculate the matching degree of the three-dimensional static geomechanical model based on the distribution of high-stress disturbance areas and concentrated microseismic event areas during the inversion process. Step S5: Construct an iterative optimization objective function for structural morphology parameters and rock mechanics parameters based on the matching degree, and use a genetic algorithm to optimize the structural morphology parameters and rock mechanics parameters of the three-dimensional static geomechanical model. Use the optimized three-dimensional static geomechanical model to analyze the stress disturbance risk of new dynamic disturbance sources to the shale gas development area. The iterative optimization objective function is: ； in, To construct populations of morphological parameters and rock mechanical parameters, These are the weights for the matching degree and the proportion of inverted stress perturbation, respectively. fitness function value, The stress disturbance intensity is simulated in a three-dimensional static geomechanical model. The stress disturbance intensity is derived from the inversion of microseismic events. J For matching degree.

2. The method for stress field disturbance analysis in shale gas development areas based on multi-source data fusion according to claim 1, characterized in that, Step S1 includes: Step S11: Obtain the initial structural morphology parameters and rock elastic parameters of the shale reservoir in the shale gas development area. The structural morphology parameters include fault dip angle. α Fault strike β Fault extension length L and fracture density λ Rock elastic parameters include longitudinal wave velocity. V p transverse wave velocity V s and rock density ρ ; Step S12: Based on P-wave velocity V p transverse wave velocity V s and rock density ρ Calculate the initial rock mechanics parameters, including Young's modulus. E Poisson's ratio bulk modulus K and shear modulus G ; ， ， ， ； Step S13: Input the structural morphology parameters and rock mechanics parameters into the finite element analysis software to construct a three-dimensional static geomechanical model of the shale reservoir.

3. The method for stress field disturbance analysis in shale gas development areas based on multi-source data fusion according to claim 2, characterized in that, Step S2 includes: Step S21: Collect drilling trajectory parameters, fracturing operation parameters, and production dynamic data of the shale reservoir. Drilling trajectory parameters include wellbore azimuth. θ , well inclination angle γ Fracturing parameters include pump pressure p Displacement q , liquid volume V , sand amount M Production dynamic data includes bottom hole flowing pressure. p wf Gas production Q g Production time t ; Step S22: Quantify the fracturing operation parameters into stress increments during the operation process. ; ； in, This refers to the energy conversion efficiency during the fracturing process. For fracturing operation time, This represents the effective volume of the shale reservoir. Step S23: Calculate the original reservoir pressure and bottom hole flowing pressure p wf The pressure difference between them yields the long-term pressure relief during the production process. Long-term pressure relief Quantified as stress change ; ； in, The coefficient of Brønsted; Step S24: Calculate the stress change and stress increment Couple the stresses to calculate the total stress of disturbance sources in the production construction and production process. ; ； in, k For stress over time t The attenuation coefficient.

4. The method for stress field disturbance analysis in shale gas development areas based on multi-source data fusion according to claim 3, characterized in that, Step S3 includes: Step S31: Collect the three-dimensional distance of the impact of historical effective microseismic events on shale reservoirs, and convert the three-dimensional distance into a three-dimensional static geomechanical model to obtain the three-dimensional side length of the three-dimensional distance in the three-dimensional static geomechanical model. 3D side length Microseismic statistical units are formed in a three-dimensional static geomechanical model to calculate the spatial distribution density of effective microseismic events. ; ； in, This represents the number of valid microseismic events occurring within the microseismic statistical unit. m For microseismic labeling; Step S32: Estimate the energy release intensity of effective microseismic events in the microseismic statistical unit using the Gutenberg-Rickett law. And calculate the microseismic energy release rate in the microseismic statistical unit per unit time. ; ； in, For regional feature parameters, b For feature parameters, i Earthquake numbering for valid microseismic events. For the first effective microseismic event i The magnitude of a micro-earthquake. The specific magnitude estimated in effective microseismic events The number of large micro-earthquakes. The actual specific magnitude in effective microseismic events The number of large micro-earthquakes. w The actual specific magnitude in effective microseismic events Large micro-earthquakes numbered. Specific magnitude in effective microseismic events The magnitude of large micro-earthquakes. The actual specific magnitude in effective microseismic events The average magnitude of large micro-earthquakes The specific magnitude estimated in effective microseismic events The number of large micro-earthquakes and their relative magnitudes The difference in the number of large micro-earthquakes, This is the magnitude amplification factor. This is the effective monitoring time window for microseismic events.

5. The method for stress field disturbance analysis in shale gas development areas based on multi-source data fusion according to claim 4, characterized in that, Step S4 includes: Step S41: Spatial distribution density Energy release intensity Microseismic energy release rate and total stress of disturbance source As a dynamic disturbance source input into the three-dimensional static geomechanical model, the three-dimensional static geomechanical model is inverted, and the stress field equilibrium equation and stress-strain constitutive relation model of the three-dimensional static geomechanical model are specifically as follows: Stress field equilibrium equations: ; in, For vector differential operators, In a three-dimensional static geomechanical model, time t spatial point The stress tensor, For time t spatial point The volume force tensor; Stress-strain constitutive model: ; in, Let be the total stress tensor at a point in space. For the elasticity matrix, Let S be the total strain tensor at a point in space. For plastic strain tensor; Step S42: Obtain the high-stress disturbance region and the concentrated distribution region of microseismic events in the inversion process, and determine the element mesh number of the high-stress disturbance region. The number of cell grids in areas with concentrated microseismic events Calculate the matching degree of the three-dimensional static geomechanical model J ; ； in, This represents the number of intersecting element meshes between high-stress disturbance regions and regions with concentrated microseismic events.

6. The method for stress field disturbance analysis in shale gas development areas based on multi-source data fusion according to claim 5, characterized in that, Step S5 includes: Step S51: Based on matching degree J Construct an iterative optimization objective function for structural morphology parameters and rock mechanical parameters; ； in, To construct populations of morphological parameters and rock mechanical parameters, These are the weights for the matching degree and the proportion of inverted stress perturbation, respectively. fitness function value, The stress disturbance intensity is simulated in a three-dimensional static geomechanical model. The stress disturbance intensity is derived from the inversion of microseismic events; Step S52: Use the initial structural morphology parameters and rock mechanical parameters as the initial population. Genetic algorithms are used to process the initial population. Individuals within the organism undergo mutation and genetic manipulation; Step S53: Input the population after each mutation into the three-dimensional static geomechanical model, update the three-dimensional static geomechanical model, and execute steps S41-S51 until the matching degree is reached. Stop the mutation and manipulation of the population, output the latest structural morphology parameters and rock mechanics parameters in the population, and complete the optimization of the three-dimensional static geomechanical model; Step S54: Set the population mutation and number of genetic iterations. C When population variation and genetic operations reach the required number of variation iterations... C Even after that, the matching degree still cannot be satisfied. It also stops population variation, manipulates genetics, and selects... C The population that satisfies the iterative optimization objective function during the secondary mutation and genetic iteration process is used to optimize the three-dimensional static geomechanical model using the structural morphology parameters and rock mechanics parameters in the population that satisfies the iterative optimization objective function. Step S55: Input the new dynamic disturbance source into the optimized three-dimensional static geomechanical model for further inversion, and assess whether there is a stress disturbance risk in the shale gas development area based on the maximum principal stress offset and minimum principal stress offset generated by the new dynamic disturbance source.

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