A method, device, equipment and medium for predicting ground stress of a complex fracture zone

Abstract

The present application relates to a kind of complex fracture zone's stress prediction method, device, equipment and medium, belong to oil and gas field development technical field, its method includes: according to rock physical parameter calculation formula calculation complex fracture zone's rock physical parameter;According to rock mechanics parameter calculation formula calculation complex fracture zone's rock mechanics parameter;The well logging curve of complex fracture zone is reconstructed, and the well logging curve after reconstruction is obtained;Through three-dimensional stress model, and in combination with the well logging curve after reconstruction, the rock mechanics parameter and the rock physical parameter are used to predict the stress of complex fracture zone.By the present application scheme, the well logging curve of complex fracture zone is reconstructed, and the well logging curve after reconstruction is obtained, to make up data missing or distortion.The present application breaks through the application bottleneck of traditional method under the complex geological conditions of super deep oil and gas reservoir, significantly improves the prediction accuracy, and provides technical support for the safe and efficient development of super deep oil and gas reservoir.

Description

Technical Field

[0001] The present invention relates to the technical field of oil and gas field development, and in particular to a method, device, equipment and medium for predicting ground stress in a complex fault zone. Background Art

[0002] With the increasing exploration and development of oil and gas, ultra-deep carbonate reservoirs have attracted considerable attention due to their enormous potential reserves. However, these reservoirs are often accompanied by complex fault zones and multi-stage strike-slip faults, making it difficult to accurately characterize the geological and mechanical characteristics of the reservoirs. Traditional rock mechanics parameter modeling relies primarily on well logging and seismic data. However, due to the lack of well logging curves, complex fault zone structures, and limited measured formation pressure and stress data, existing geostress prediction methods have low accuracy when applied to ultra-deep reservoirs and cannot meet the needs of wellbore stability prediction and reservoir reconstruction design.

[0003] Existing geostress prediction methods primarily rely on the use of well logging data or seismic inversion data alone. These methods often suffer from insufficient accuracy when dealing with complex geological conditions, such as fault zones and ultra-deep wells. Well logging data can be distorted by conditions such as borehole expansion and data loss, resulting in reduced accuracy in geostress prediction. Furthermore, while seismic inversion technology can provide three-dimensional geostress distribution information, it is limited by its resolution and data integration capabilities, making it difficult to accurately describe the local stress field. Summary of the Invention

[0004] In view of this, it is necessary to provide a method, device, equipment and medium for predicting geostress in complex fault zones to solve the problem that existing methods are insufficiently accurate when dealing with complex geological conditions (such as fault zones, ultra-deep wells, etc.), and that logging data will be distorted due to wellbore expansion, data missing, etc., resulting in a decrease in the accuracy of geostress prediction.

[0005] To address the problem that existing methods are insufficiently accurate when dealing with complex geological conditions (such as fault zones and ultra-deep wells), well logging data may be distorted due to wellbore expansion and data loss, resulting in a decrease in the accuracy of geostress prediction, the present invention provides a geostress prediction method for complex fault zones, comprising:

[0006] Calculate the rock physical parameters of complex fault zones according to the rock physical parameter calculation formula;

[0007] Calculate the rock mechanics parameters of complex fault zones according to the rock mechanics parameter calculation formula;

[0008] Reconstruct the logging curve of the complex fault zone to obtain the reconstructed logging curve;

[0009] The in-situ stress of a complex fault zone is predicted by using a three-dimensional in-situ stress model in combination with the reconstructed well logging curve, the rock mechanical parameters and the rock physical parameters.

[0010] In a possible implementation, the method further includes establishing the rock physical parameter calculation formula and the rock mechanical parameter calculation formula based on lithologic data of different strata.

[0011] In a possible implementation, the method further includes fitting the rock physical parameter calculation formula and the rock mechanical parameter calculation formula to obtain the well logging curve.

[0012] In a possible implementation, the well logging curve includes: a density curve and a shear wave time difference curve;

[0013] The fitting of the rock physical parameter calculation formula and the rock mechanical parameter calculation formula to obtain the well logging curve specifically includes:

[0014] Obtaining a density curve by fitting the petrophysical parameter calculation formula;

[0015] By fitting the rock mechanics parameter calculation formula, a shear wave time difference curve is obtained.

[0016] In a possible implementation, the reconstructing of the well logging curve of the complex fault zone specifically includes:

[0017] The density curve is reconstructed according to the formation mineral composition and formation porosity of the complex fault zone to obtain a reconstructed density curve.

[0018] In a possible implementation, the method further includes: calculating elastic parameters using seismic inversion data to obtain rock elastic parameters;

[0019] Assigning the rock elastic parameters to the three-dimensional geostress model to obtain the assigned three-dimensional geostress model;

[0020] The method of predicting the in-situ stress of a complex fault zone by using a three-dimensional in-situ stress model and combining the reconstructed well logging curve, the rock mechanical parameters, and the rock physical parameters specifically includes:

[0021] The in-situ stress of a complex fault zone is predicted by using the assigned three-dimensional in-situ stress model in combination with the reconstructed well logging curve, the rock mechanical parameters and the rock physical parameters.

[0022] In a possible implementation, the method further includes: verifying the geostress through three-dimensional geostress simulation, and when the verification result meets the requirements, performing stability analysis on the wellbore wall of the complex fault zone based on the geostress.

[0023] The present invention also provides a device for predicting ground stress in a complex fault zone, comprising: a first calculation module, a second calculation module, a reconstruction module, and a prediction module;

[0024] The first calculation module is used to calculate the rock physical parameters of the complex fault zone according to the rock physical parameter calculation formula;

[0025] The second calculation module is used to calculate the rock mechanical parameters of the complex fault zone according to the rock mechanical parameter calculation formula;

[0026] The reconstruction module is used to reconstruct the logging curve of the complex fault zone to obtain the reconstructed logging curve;

[0027] The prediction module is used to predict the in-situ stress of a complex fault zone by using a three-dimensional in-situ stress model in combination with the reconstructed well logging curve, the rock mechanical parameters and the rock physical parameters.

[0028] Another technical solution of the present invention to solve the above technical problems is as follows:

[0029] The present invention also provides an electronic device, comprising a memory and a processor, wherein:

[0030] The memory is used to store programs;

[0031] The processor is coupled to the memory and is used to execute the program stored in the memory to implement the steps of a method for predicting ground stress in a complex fault zone in any of the above solutions.

[0032] Another technical solution of the present invention to solve the above technical problems is as follows:

[0033] The present invention also provides a computer-readable storage medium for storing a computer-readable program or instruction, which, when executed by a processor, can implement the steps of a method for predicting ground stress in a complex fault zone of any of the above-mentioned schemes.

[0034] The present invention has the following beneficial effects: by reconstructing the logging curves of complex fault zones, the reconstructed logging curves are obtained, compensating for data loss or distortion. This invention breaks through the application bottleneck of traditional methods under the complex geological conditions of ultra-deep oil and gas reservoirs, significantly improves prediction accuracy, and provides technical support for the safe and efficient development of ultra-deep oil and gas reservoirs. This solution has broad market application prospects. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 A schematic flow chart of an embodiment of a method for predicting geostress in a complex fault zone provided by the present invention;

[0036] Figure 2 A schematic flow chart of another embodiment of a method for predicting geostress in a complex fault zone provided by the present invention;

[0037] Figure 3 for Figure 2 A flow chart of an embodiment of step S202;

[0038] Figure 4 A structural framework diagram of an embodiment of a device for predicting ground stress in a complex fault zone provided by the present invention;

[0039] Figure 5 A schematic structural diagram of an embodiment of an electronic device provided by the present invention;

[0040] Figure 6 A vertical geostress distribution diagram provided by the present invention;

[0041] Figure 7 A horizontal geostress distribution diagram provided by the present invention;

[0042] Figure 8 A schematic diagram of the decreasing shear wave propagation provided by the present invention;

[0043] Figure 9 A schematic diagram of the incremental shear wave propagation provided by the present invention;

[0044] Figure 10 Schematic diagram of the failure conditions under different normal stresses and shear stresses provided by the present invention;

[0045] Figure 11 The displacement field diagram provided by the present invention;

[0046] Figure 12 A schematic diagram of the expansion direction of the hydraulic fracturing cracks in Shunbei area provided by the present invention;

[0047] Figure 13 A schematic diagram of the three-dimensional hydraulic fracturing crack expansion provided by the present invention;

[0048] Figure 14 The stress distribution around the wellbore in Shunbei area provided by the present invention;

[0049] Figure 15 This is the geostress profile diagram of Shunbei area provided by the present invention. DETAILED DESCRIPTION

[0050] The principles and features of the present invention are described below with reference to the accompanying drawings. The embodiments given are only used to explain the present invention and are not used to limit the scope of the present invention.

[0051] like Figure 1 As shown, a specific embodiment of the present invention discloses a method for predicting ground stress in a complex fault zone, comprising:

[0052] S101. Calculate the rock physical parameters of the complex fault zone according to the rock physical parameter calculation formula. It should be noted that, in a certain embodiment, the rock physical parameters include: total density of the rock, longitudinal wave velocity, and shear wave velocity.

[0053] The total density of the rock is calculated based on the mineral composition. , the formula is as follows:

[0054] ,

[0055] in Indicates the Density of the mineral; Indicates the Volume fraction of the minerals; represents the volume fraction of pore fluid; Indicates porosity.

[0056] The longitudinal wave velocity and the shear wave velocity are calculated by first calculating the bulk modulus and the shear modulus of the rock, and then calculating the longitudinal wave velocity and the shear wave velocity using the elastic modulus of the rock.

[0057] According to the effective medium theory of mixed media, such as the Chladni-Hamilton (Kuster-Toksöz) model, the elastic modulus of rock can be expressed as a combination of minerals and pore fluids. First, calculate the bulk modulus of rock and shear modulus :

[0058] ,

[0059] ,

[0060] in: represents the bulk modulus and shear modulus of dry rock; 、 It represents the bulk modulus and shear modulus of the mineral, which can be obtained by weighted average of the mineral components; 、 represents the bulk modulus and shear modulus of the pore fluid (for fluid, ).

[0061] Then, the elastic modulus of rock is used to calculate and :

[0062] ,

[0063] ,

[0064] S102. Calculate the rock mechanical parameters of the complex fault zone according to the rock mechanical parameter calculation formula; it should be noted that, in a certain embodiment, the rock mechanical parameters are specifically calculated Young's modulus and Poisson's ratio, shear modulus and bulk modulus, Lame constant and rock strength parameters.

[0065] (a) Young's modulus and Poisson's ratio Calculation

[0066] Young's modulus and Poisson's ratio can be calculated from the bulk modulus and shear modulus:

[0067] ,

[0068] ,

[0069] The derivation process is based on the elastic mechanics relationship:

[0070] ,

[0071] ,

[0072] (b) Shear modulus and bulk modulus Calculation, known and , calculated directly from the above

[0073] (c) Lamé constant calculate:

[0074] ,

[0075] (d) Rock strength parameters, specifically the rock compressive strength is calculated by the rock tensile strength, and the rock compressive strength is calculated according to the Hooke-Brown criterion. Determine the Hooke-Brown parameter based on lithology , combined with the minimum principal stress and the tensile strength of rock , calculate the compressive strength of rock , the specific formula is as follows:

[0076] ,

[0077] S103. Reconstruct the logging curves of the complex fault zone to obtain reconstructed logging curves. The logging curves include density curves and shear wave time difference curves. The density curve is reconstructed using mineral composition and porosity. Due to the high cost or missing data of shear wave logging, other logging curves can be used for prediction.

[0078] S104: Predicting the in-situ stress of a complex fault zone using a three-dimensional in-situ stress model in combination with the reconstructed well logging curve, the rock mechanical parameters, and the rock physical parameters. The in-situ stress of a complex fault zone includes horizontal stress, vertical stress, and tectonic stress of the wellbore.

[0079] It should be noted that, in a certain embodiment, establishing a geostress model, calculating vertical geostress and horizontal geostress, and estimating tectonic stress specifically include:

[0080] Vertical geostress , the vertical in-situ stress is usually equal to the weight of the overlying rock layer of the formation, which can be calculated by density integration:

[0081] ,

[0082] in: Indicates depth; Indicates depth The density at Represents the acceleration due to gravity.

[0083] The vertical ground stress diagram is as follows Figure 6 As shown in the figure, the stress changes from high to low from top to bottom, showing a typical vertical stress gradient. This distribution may be due to the stress increase caused by the weight of the material.

[0084] The stress distribution in the figure is relatively uniform, with no obvious stress concentration or mutation areas, indicating that the vertical stress field in this area is relatively stable.

[0085] Horizontal ground stress and , the calculation of horizontal ground stress can adopt the plane strain model of elastic mechanics:

[0086] ,

[0087]

[0088] in ： is the maximum horizontal principal stress; is the minimum horizontal principal stress; is Poisson's ratio; is the Biot poroelastic coefficient, i.e., the rock elastic parameter; is the pore pressure; ， is the tectonic stress increment.

[0089] Schematic diagram of horizontal ground stress distribution, such as Figure 7As shown, stress increases horizontally from left to right, indicating a horizontal stress gradient. Vertical stress distribution is relatively uniform, with no significant vertical variation, indicating that stress is primarily influenced by horizontal position. This horizontal stress distribution diagram reveals stress variations at different horizontal locations. The gradual increase in stress from left to right may reflect a tendency for lateral stress concentration in the material or formation in this area. This diagram can be used to analyze the impact of horizontal stress on the wellbore or formation, particularly in stability assessments of high-stress areas.

[0090] The estimation of tectonic stress may include: using seismic data and fault slip trends in combination with finite element simulation to estimate tectonic stress increment. In one embodiment, the estimation of tectonic stress may specifically include:

[0091] Through multi-angle seismic data, the longitudinal wave impedance, shear wave impedance, and density are obtained by inversion.

[0092] 1. Data collection and preprocessing:

[0093] Seismic data and fault slip trend data are the basis for estimating tectonic stress increments. The specific steps include:

[0094] Seismic data: Extract information such as fault location, orientation, and dip from seismic data. This data helps determine the geometry and distribution of faults.

[0095] Fault slip trend: The slip trend of a fault can usually be obtained through seismic analysis, including information such as slip direction and slip rate. These parameters help determine the direction and magnitude of stress release on the fault under tectonic stress fields.

[0096] 2. Establish a 3D geological model:

[0097] Based on seismic data and fault geometry, a 3D geological model is constructed using geological modeling software (such as Petrel, GOCAD, etc.), including:

[0098] Stratigraphic boundaries: Different strata are divided based on seismic reflection layers.

[0099] Fault structure: The 3D geometry of the fault is embedded into the geological model to ensure that the fault orientation, dip, and displacement are consistent with the actual seismic data.

[0100] 3. Stress boundary conditions and initial tectonic stress field:

[0101] Based on the 3D geological model, the boundary conditions and initial tectonic stress field of the finite element simulation are set:

[0102] Boundary conditions: Boundary conditions set the structural environment of the corresponding area (such as compression, tension, shear, etc.), usually including displacement boundary conditions or stress boundary conditions. Figure 11 As shown in the figure, the displacement reaches its maximum at the top of the region (top center region) and gradually decreases towards the sides and bottom. This distribution forms a parabola-like shape.

[0103] The displacement field distribution shown in the figure usually corresponds to a deformation caused by a concentrated load or bending, indicating that there is a large stress or deformation influence above the area, resulting in an arc-shaped displacement distribution in the area. This displacement field diagram can be used to analyze the deformation of materials or strata under loading or external stress. The displacement in the top center area is the largest, which may be affected by concentrated stress or boundary conditions. Such displacement distribution diagrams are often used in structural analysis or geotechnical engineering to help identify high-displacement areas to assess the potential impact of deformation on the structure. In geological and engineering applications, this diagram helps to identify possible unstable areas or predict force distribution patterns.

[0104] Initial tectonic stress field: The initial stress field is set based on geological background information (such as regional tectonic background and historical tectonic events). These data can be determined through previous stress measurement results and literature data.

[0105] 4. Finite element meshing:

[0106] Finite element analysis software is used to mesh the 3D geological model. Meshing needs to be refined, especially in areas near faults, to improve simulation accuracy.

[0107] Mesh refinement near faults: To accurately simulate the stress distribution along the fault, a denser mesh is usually required in the fault region.

[0108] Appropriate element type: Select an appropriate element type (such as tetrahedral elements or hexahedral elements) to ensure simulation accuracy.

[0109] 5. Simulating fault slip and tectonic stress increment:

[0110] The fault slip trend is applied to the finite element model to simulate the stress release process of the fault under the initial tectonic stress field and calculate the tectonic stress increment. The key steps are as follows:

[0111] Apply fault slip: Apply slip boundary conditions on the fault plane to simulate the sliding behavior of the fault under the action of regional tectonic stress.

[0112] Stress calculation: The stress field changes during fault slip are obtained through finite element simulation, and then the structural stress increment around the fault is calculated.

[0113] In one embodiment, the three-dimensional geostress field model mainly involves the superposition of vertical stress, horizontal stress, and tectonic stress. Combined with the equilibrium equation of elasticity, the model formula can be summarized as follows: The three-dimensional geostress field model mainly involves the superposition of vertical stress, horizontal stress, and tectonic stress. Combined with the equilibrium equation of elasticity, the model formula can be summarized as follows:

[0114] ,

[0115] in, is the stress tensor, which represents the stress component in each direction in the three-dimensional coordinate system ; is the contribution of the vertical stress, which is obtained by integrating the weight of the overlying rock layer of the formation:

[0116] ,

[0117] in, With depth Varying density, is the acceleration due to gravity.

[0118] and are the contributions to the horizontal stresses, calculated using the plane strain model of elasticity theory, and represent the maximum and minimum horizontal principal stresses, respectively:

[0119] ,

[0120] in, is Poisson's ratio; is the Biot poroelastic coefficient, i.e., the rock elastic parameter; is the pore pressure; and are the increments of tectonic stress, respectively. The impact of tectonic stress on the overall stress field is primarily estimated using seismic data and finite element simulations. Tectonic stress has different components in different regions and has a significant impact on the final geostress field.

[0121] Preferably, in one of the above embodiments, Figure 2 As shown, it also includes:

[0122] S201. Establishing the rock physical parameter calculation formula and the rock mechanical parameter calculation formula according to the lithologic data of different strata.

[0123] Preferably, in one of the above embodiments, the method further includes: S202, fitting the rock physical parameter calculation formula and the rock mechanical parameter calculation formula to obtain the well logging curve. It should be noted that in one embodiment, based on the theoretical model of the above rock physical parameters and rock mechanical parameters, using core experimental data and measured data, multivariate nonlinear regression is used to fit the rock physical and mechanical parameter calculation formulas for different lithologies.

[0124] For example, for Young's modulus:

[0125] ,

[0126] in: is the regression coefficient; is the error term; is Young's modulus, is the total density of the rock, is the longitudinal wave velocity.

[0127] Preferably, in one of the above embodiments, the logging curves include: a density curve and a shear wave time difference curve;

[0128] The fitting of the rock physical parameter calculation formula and the rock mechanical parameter calculation formula to obtain the well logging curve specifically includes:

[0129] S301, obtaining a density curve by fitting the petrophysical parameter calculation formula;

[0130] S302. Obtain a shear wave time difference curve by fitting the rock mechanics parameter calculation formula.

[0131] It should be noted that the rock mechanics parameter calculation formula is obtained through logging data, and the shear wave time difference curve is obtained by fitting according to the rock mechanics parameter calculation formula.

[0132] It should be noted that, in a certain implementation, Figure 8 As shown in the figure, the S-wave velocity decreases with increasing distance, which may reflect that the resistance of the stratum or material to the propagation of shear waves increases with the depth or position. This trend of decreasing velocity is usually related to changes in parameters such as stratum density and porosity, and may be caused by changes in material properties or geological structure.

[0133] like Figure 9 As shown in the figure, the S-wave time difference increases with the distance. This indicates that on the same propagation path, the propagation speed of the S-wave gradually decreases with the increase of distance, resulting in an increase in the cumulative time difference.

[0134] This increase in time difference may be related to changes in formation properties, such as increased formation density or changes in porosity, which affect the propagation speed of S waves.

[0135] Preferably, in one of the above embodiments, reconstructing the well logging curves of the complex fault zone specifically includes:

[0136] The density curve is reconstructed according to the formation mineral composition and formation porosity of the complex fault zone to obtain a reconstructed density curve.

[0137] It should be noted that, in a certain embodiment, the well logging curve is reconstructed, the density curve based on the mineral composition is reconstructed, and the shear wave time difference curve is reconstructed;

[0138] Density curve reconstruction based on mineral components. If a certain section of the density curve is missing or distorted, it can be reconstructed using mineral components and porosity. Reconstruction formula:

[0139] ,

[0140] in: is the mineral volume fraction; Well logging data is the volume fraction of pore fluid; is the porosity.

[0141] Mineral volume fraction It can be calculated through logging data (such as natural gamma, spectral gamma, nuclear magnetic resonance, etc.) and mineral models.

[0142] Due to the high cost or lack of data for shear wave logging, the reconstruction of shear wave time difference curve can be predicted using other logging curves, such as compressional wave time difference curve, density curve, and natural gamma ray curve.

[0143] The high shear wave time difference area corresponds to the low ground stress area:

[0144] In some areas of Shunbei Oilfield, if the shear wave time difference curve shows a high time difference value, it usually indicates that the rock formation in this area is relatively weak and the wave velocity is low. Since stress affects the compactness and crack characteristics of the rock, a higher shear wave time difference usually corresponds to a lower ground stress. Such areas have more stress release and are prone to cracks, so it is necessary to pay attention to the risk of well wall collapse during mining. Figure 12 Figure 2 shows the propagation of hydraulic fractures in the Shunbei area along different stress directions. Fractures propagate longer in the direction of maximum principal stress, indicating greater stress in that direction, which is more conducive to fracture extension. In oil and gas field development, understanding the direction of fracture propagation helps optimize fracturing strategies and thus increase oil and gas recovery. This diagram can help engineers predict fracture propagation paths, allowing them to more effectively guide fracture growth within the formation and improve reservoir connectivity.

[0145] like Figure 13As shown, the 3D fracture propagation map demonstrates the fracture propagation characteristics of the Shunbei area in different stress directions. Fractures propagate more strongly in the direction of maximum principal stress (lighter colors) and less strongly in the direction of minimum principal stress (darker colors). This information is valuable for optimizing fracturing operations, helping engineers predict fracture propagation directions, improve fracturing effectiveness, and optimize production capacity layout.

[0146] like Figure 14 The figure below illustrates the stress distribution around the wellbore in the Shunbei area, showing low radial stress and high hoop stress. A significant increase in hoop stress can affect wellbore stability, potentially leading to instability or wellbore failure. In practical applications, this figure helps engineers assess the stress state around the wellbore and guide wellbore support and fracturing operations.

[0147] like Figure 15 As shown, the vertical stress (Sv) curve shows how vertical stress increases with depth. Vertical stress generally has a linear relationship with depth; greater depth increases the vertical stress. The maximum horizontal principal stress (SH) curve shows how the maximum horizontal principal stress increases with depth. This stress value increases with depth but is generally smaller than the vertical stress. The minimum horizontal principal stress (Sh) curve shows how the minimum horizontal principal stress increases with depth. The minimum horizontal principal stress is generally the smallest of the three stresses, and the rate of stress increase with depth is also lower.

[0148] Gray area (stress area): The gray-filled area represents the stress interval between different types of stress. This area is usually used to represent the stress state of the formation within a specific depth range and is a key area for the assessment of wellbore stability and fracture pressure. Stress variation characteristics: The vertical stress Sv curve increases rapidly with increasing depth, showing the most obvious depth dependence. The maximum horizontal stress SH curve and the minimum horizontal stress Sh also increase with depth, but the increase is smaller than the vertical stress. With increasing depth, different types of stress gradually differentiate, and the gap between the maximum and minimum horizontal principal stresses and the vertical stress widens. This stress difference affects the stability of the formation and the behavior of fracture propagation. This figure shows the distribution of ground stress with depth in the Shunbei area through a cross-section, which helps to understand the stress state of the formation. With increasing depth, the vertical stress, maximum horizontal principal stress and minimum horizontal principal stress all show different growth trends. Understanding the distribution characteristics of these stresses is crucial for wellbore stability assessment and fracturing design, especially the stress state in the gray area, which can guide the design of protection and support measures in wellbore and reservoir development. The low shear wave time difference area corresponds to the high ground stress area:

[0149] Areas with lower shear wave transit time often indicate denser rock formations and faster wave velocities. Dense rock formations typically generate higher in-situ stresses because they are densely compacted and have fewer internal fractures. These higher in-situ stresses result in more stable wellbore walls, but higher drilling pressures may be required to prevent blowouts.

[0150] The gradient change of shear wave time difference reflects the stress concentration area:

[0151] If the gradient of the shear-wave transit time curve changes significantly at certain depths, it may indicate a sudden change in the geostress field. This is particularly common near geological faults or fractures. Stress concentration areas appear as sudden changes or sharp increases on the shear-wave transit time curve. This change can help identify potential stress concentration locations and guide drilling operations to avoid high-risk areas.

[0152] Calibration of shear wave time difference and ground stress prediction:

[0153] By comparing S-wave transit time data with actual downhole ground stress data, a prediction model for S-wave transit time and ground stress can be established. For example, by using linear or nonlinear regression models of S-wave transit time and ground stress values, ground stress can be predicted using S-wave transit time in other undrilled areas, thereby enabling a more comprehensive prediction of ground stress distribution.

[0154] In the Shunbei Oilfield, shear wave transit time curves can be used as an auxiliary tool for geostress prediction. High shear wave transit time curves generally indicate areas of low geostress, while low shear wave transit time curves are associated with areas of high geostress. By analyzing the changing trends of shear wave transit time curves, the geostress distribution in the oilfield can be more accurately assessed, providing guidance for wellbore stability and fracture development.

[0155] Multiple regression model:

[0156] ,

[0157] in: represents the shear wave time difference; represents the longitudinal wave time difference; represents natural gamma; represents the neutron porosity; represents density log; represents the regression coefficient.

[0158] Preferably, in one of the above embodiments, the method further comprises: calculating elastic parameters through seismic inversion data to obtain rock elastic parameters;

[0159] It should be noted that, in a certain embodiment, three-dimensional geostress prediction is performed based on seismic data, elastic parameters are obtained through seismic inversion, AVO analysis and elastic parameter calculation are performed; three-dimensional geostress simulation is performed, including numerical simulation, calculation of stress field, and geostress analysis around the well.

[0160] Step (a) AVO (amplitude variation with offset) analysis using the Aki-Richards approximation:

[0161] ,

[0162] in: represents the reflection coefficient; represents the angle of incidence; 、 、 Represents the coefficient related to rock elastic parameters.

[0163] Through multi-angle seismic data, the longitudinal wave impedance is obtained by inversion and shear wave impedance , and density .

[0164] Step (b) elastic parameter calculation, using the inversion obtained 、 and , calculate the elastic modulus:

[0165] ,

[0166] Assigning the rock elastic parameters to the three-dimensional geostress model to obtain the assigned three-dimensional geostress model;

[0167] The method of predicting the in-situ stress of a complex fault zone by using a three-dimensional in-situ stress model and combining the reconstructed well logging curve, the rock mechanical parameters, and the rock physical parameters specifically includes:

[0168] The in-situ stress of a complex fault zone is predicted by using the assigned three-dimensional in-situ stress model in combination with the reconstructed well logging curve, the rock mechanical parameters and the rock physical parameters.

[0169] It should be noted that, in one embodiment, obtaining elastic parameters through seismic inversion includes:

[0170] (a) AVO (amplitude variation with offset) analysis:

[0171] Using the Aki-Richards approximation formula:

[0172] ,

[0173] in: represents the reflection coefficient; represents the angle of incidence; 、 、 Represents the coefficient related to rock elastic parameters.

[0174] Through multi-angle seismic data, the longitudinal wave impedance is obtained by inversion and shear wave impedance , and density .

[0175] (b) Elastic parameter calculation, using the inversion 、 and , calculate the elastic modulus:

[0176] ,

[0177] Preferably, in one of the above embodiments, the method further includes: verifying the geostress through three-dimensional geostress simulation, and when the verification result meets the requirements, performing stability analysis on the wellbore wall of the complex fault zone based on the geostress.

[0178] It should be noted that, in a certain embodiment, the three-dimensional geostress field simulation:

[0179] (a) Numerical simulation:

[0180] Establish a three-dimensional geological model, including stratigraphic structure, faults, lithology distribution, etc.;

[0181] Assign the elastic parameters obtained from seismic inversion to the model;

[0182] The finite element method is applied to simulate the ground stress field by imposing boundary conditions and tectonic stress.

[0183] (b) Stress field calculation:

[0184] Solve the elasticity equation:

[0185] ,

[0186] in: represents the stress tensor; Indicates body density (such as gravity).

[0187] Combined with the geological structure characteristics, the stress components of each point are calculated.

[0188] (c) Analysis of ground stress around the well:

[0189] Extract the ground stress distribution around the wellbore;

[0190] Considering the disturbance effect of the wellbore, the stress concentration at the wall is calculated. The ultimate goal of the geostress field prediction is to optimize the wellbore stability and reservoir reconstruction design:

[0191] In one embodiment, the method further includes: performing wellbore stability analysis and fracturing parameter optimization, wellbore peripheral stress calculation, and instability criteria.

[0192] Wellbore stability analysis: Based on the three-dimensional geostress field, the possibility of wellbore instability is determined by the Mohr-Coulomb criterion or the Drucker-Prager criterion. The main causes of wellbore instability include high stress concentration areas and low stress release areas, and a comprehensive risk assessment of the geostress field is required. Figure 10 As shown, the Mohr-Coulomb criterion describes the failure conditions of a material under varying normal and shear stresses. The solid envelope is the Mohr-Coulomb failure line, representing the maximum shear stress the material can withstand under varying normal stresses. The dashed line represents the material's ultimate tensile strength. In engineering analysis, this graphical representation is used to determine material instability and help determine the risk of failure of structures such as wellbore walls under complex stress conditions.

[0193] (a) Calculation of wellbore stress:

[0194] Considering the existence of the wellbore, the Cauchy-Davenport (Kirsch) solution is used to calculate the stress around the wellbore:

[0195] ,

[0196] ,

[0197] ,

[0198] ,

[0199] in: 、 、 Indicates radial, hoop and axial stresses; Indicates the distance from any position to the well center; Represents the wellbore radius; Indicates azimuth; Indicates the difference between the wellbore pressure (mud pressure) and the formation pore pressure; represents Poisson's ratio.

[0200] (b) Instability criteria:

[0201] Use the Mohr-Coulomb criterion or the Drucker-Prager criterion to determine the possibility of wellbore instability:

[0202] Mohr-Coulomb criterion:

[0203] ,

[0204] in: represents the maximum shear stress; represents the effective normal stress; It indicates cohesion; represents the internal friction angle. Figure 10 As shown, the Mohr-Coulomb criterion describes the failure conditions of a material under varying normal and shear stresses. The solid envelope is the Mohr-Coulomb failure line, representing the maximum shear stress the material can withstand under varying normal stresses. The dashed line represents the material's ultimate tensile strength. In engineering analysis, this graphical representation is used to determine material instability and help determine the risk of failure of structures such as wellbore walls under complex stress conditions.

[0205] Derek Prager Criteria:

[0206] ,

[0207] in: represents the second deviatoric stress invariant; represents the mean normal stress; 、 Represents material parameters.

[0208] In one embodiment, the optimization of fracturing parameters includes: predicting the expansion direction and shape of the crack based on the ground stress field, and calculating the fracture pressure. :

[0209]

[0210] in: Indicates the tensile strength of rock.

[0211] Optimize fracturing fluid viscosity, injection rate and proppant properties to control fracture morphology.

[0212] In one embodiment, an example of a wellbore stability analysis application might include: Within the Shunbei oil and gas field, the Shunbei No. 1 and Shunbei No. 5 fault zones are important oil and gas producing areas. However, due to the deep burial depth and complex fault structures in this area, the risk of wellbore instability is high. The region is subject to multiple strike-slip faults, resulting in dramatic changes in lithology and a highly uneven distribution of geostress. In particular, geostress concentrations near the faults pose significant challenges to wellbore stability.

[0213] Analysis of geostress around the wellbore: In Shunbei area, a three-dimensional geostress model is used to conduct a detailed analysis of the geostress around the wellbore, mainly including:

[0214] vertical stress : Determined by the weight of the overlying rock strata, the vertical stress in the Shunbei area is usually higher due to its great burial depth.

[0215] Horizontal stress : Due to the existence of faults, the distribution of horizontal stress in Shunbei area is significantly uneven, especially the tectonic stress increment near the faults is significant.

[0216] The application of the wellbore instability criterion, combined with the calculation results of the wellbore circumferential stress in the Shunbei area, uses the following criteria to evaluate the wellbore instability risk. The Mohr-Coulomb criterion is used to predict the instability risk of the wellbore under high shear stress conditions. , hoop stress and effective normal stress , combined with the internal friction angle and cohesion of the rock, it can be determined whether there is a risk of shear instability in the wellbore wall.

[0217] Near the Shunbei No. 1 fault zone, due to the combined effect of horizontal stress and tectonic stress, the hoop stress in some well sections is The shear failure risk can be effectively reduced by increasing the drilling fluid density to increase the wellbore pressure.

[0218] The Shunbei area is characterized by well-developed faults and complex formation stress states. The Derek-Prager criterion is well-suited to describing rock yield behavior under these complex stress conditions. By calculating stress around the wellbore wall, high-risk areas for plastic yield were identified.

[0219] Case application: Near the Shunbei No. 5 fault zone, due to the large tectonic stress increment in the formation, the stress state in some well sections meets the yield condition of the Derek-Prager criterion. In these sections, optimizing the wellbore trajectory to avoid areas of high tectonic stress can effectively reduce the possibility of instability.

[0220] Mud pressure optimization: To ensure wellbore stability, drilling fluid pressure must be properly controlled. Due to the large variations in formation pressure in the Shunbei area, optimizing mud pressure can balance the external pressure on the wellbore with the ground stress, preventing wellbore collapse and lost circulation.

[0221] In Shunbei No. 1 Well, the mud pressure was adjusted to a range slightly higher than the pore pressure but lower than the fracture pressure, thereby reducing the risk of wellbore instability in areas of high stress concentration.

[0222] Wellbore reinforcement measures: Casing reinforcement measures are recommended for areas of high stress concentration identified during the analysis. For example, in the critical section of Shunbei Well No. 5, expansion tubing was installed to enhance the wellbore's pressure-bearing capacity, effectively reducing the risk of wellbore instability.

[0223] The solution of the present invention establishes a high-precision three-dimensional geostress field model and optimizes reservoir fracturing design and wellbore stability analysis through multi-source data fusion, including logging data reconstruction, seismic inversion and finite element simulation. Specific technical solutions include: reconstruction based on logging data such as mineral composition and porosity to compensate for data loss or distortion; optimizing rock mechanics parameter modeling using the GABP genetic algorithm and neural network model to improve prediction accuracy; and generating three-dimensional geostress fields in complex fault zones through seismic data and finite element simulation technology to optimize reservoir fracturing and wellbore stability design. This technology breaks through the application bottleneck of traditional methods under the complex geological conditions of ultra-deep oil and gas reservoirs, significantly improves prediction accuracy, provides technical support for the safe and efficient development of ultra-deep oil and gas reservoirs, and has broad market application prospects.

[0224] In one embodiment, a method for predicting in-situ stress in ultra-deep carbonate oil and gas reservoirs includes:

[0225] Establish calculation formulas for rock physics and rock mechanics parameters of different lithologies;

[0226] Calculate rock physical parameters;

[0227] Calculate rock mechanical parameters;

[0228] Fitting calculation formulas for rock physical and mechanical parameters of different lithologies;

[0229] Reconstruct logging curves, density curves based on mineral components, and shear wave time difference curves;

[0230] Establishing a geostress model;

[0231] Calculate vertical and horizontal ground stresses, and estimate tectonic stresses;

[0232] 3D ground stress prediction based on seismic data;

[0233] Obtain elastic parameters through seismic inversion, perform AVO analysis and elastic parameter calculation;

[0234] Conduct three-dimensional geostress simulation, including numerical simulation, calculation of stress field, and analysis of geostress around the well;

[0235] 3D ground stress prediction based on seismic data;

[0236] Conduct wellbore stability analysis and fracturing parameter optimization;

[0237] Wellbore stress calculation, instability criteria.

[0238] According to a specific embodiment of the present invention, the calculation of rock physical parameters is specifically the calculation of the total density, longitudinal wave velocity and shear wave velocity of the rock.

[0239] According to a specific embodiment of the present invention, the total density of the rock is calculated based on the mineral components. , the formula is as follows:

[0240]

[0241] in Indicates the Density of the mineral; Indicates the Volume fraction of the minerals; represents the volume fraction of pore fluid; represents porosity; n represents a conventional coefficient, for example: 1.2.3….

[0242] According to a specific embodiment of the present invention, the calculation of the longitudinal wave velocity and the shear wave velocity is specifically to first calculate the bulk modulus and shear modulus of the rock, and then calculate the longitudinal wave velocity and the shear wave velocity using the elastic modulus of the rock.

[0243] According to a specific embodiment of the present invention, the calculation of rock mechanics parameters is specifically the calculation of Young's modulus and Poisson's ratio, shear modulus and bulk modulus, Lame constant, and rock strength parameters.

[0244] According to a specific embodiment of the present invention, the Young's modulus, Poisson's ratio and Lame constant are calculated, and the Young's modulus, Poisson's ratio and Lame constant can be calculated by bulk modulus and shear modulus.

[0245] According to a specific embodiment of the present invention, the rock strength parameter is calculated according to the Hooke-Brown criterion to calculate the compressive strength of the rock. Determine the Hooke-Brown parameter based on lithology , combined with the minimum principal stress and the tensile strength of rock , calculate the compressive strength of rock , the specific formula is as follows:

[0246] ,

[0247] According to a specific embodiment of the present invention, the rock physical and mechanical parameter calculation formulas for different lithologies are fitted by using core experimental data and measured data through multivariate nonlinear regression.

[0248] According to a specific embodiment of the present invention, the well logging curve is reconstructed, the density curve based on the mineral components is reconstructed, and the shear wave time difference curve is reconstructed.

[0249] According to a specific embodiment of the present invention, the density curve reconstruction based on mineral components, assuming that a certain section of the density curve is missing or distorted, can be reconstructed using mineral components and porosity.

[0250] According to a specific embodiment of the present invention, the shear wave time difference curve reconstruction can be predicted using other logging curves due to the high cost or data loss of shear wave logging.

[0251] According to a specific embodiment of the present invention, a geostress model is established, vertical geostress and horizontal geostress are calculated, and tectonic stress is estimated.

[0252] According to a specific embodiment of the present invention, three-dimensional geostress prediction is performed based on seismic data, elastic parameters are obtained through seismic inversion, AVO analysis and elastic parameter calculation are performed; three-dimensional geostress simulation is performed, including numerical simulation, calculation of stress field, and analysis of geostress around the well.

[0253] According to one embodiment of the present invention, a wellbore stability analysis is performed. Taking into account the presence of the wellbore, the Cauchy-Davenport (Kirsch) solution is used to calculate the wellbore stress. The Mohr-Coulomb criterion or the Drucker-Prager criterion is used to determine the possibility of wellbore instability.

[0254] This invention improves the accuracy of rock mechanical parameter calculations. Through precise logging data reconstruction and multidimensional correction techniques, it addresses the problems of distorted and missing logging data in complex geological conditions. This improves the accuracy of rock mechanical parameter calculations, particularly in complex formations such as fault zones and ultra-deep wells, accurately reflecting the true physical and mechanical properties of the rock. This lays a solid foundation for the precise prediction of geostress fields and addresses the shortcomings of traditional methods in complex structural conditions.

[0255] This invention generates a high-precision three-dimensional geostress field. Combining seismic data inversion with finite element simulation, a high-precision three-dimensional geostress field model was successfully constructed. This model fully accounts for the anisotropy of geological conditions and the dynamic influence of fault activity, accurately describing stress gradients and variations in complex geological structures. This is of great significance for predicting stress distribution in fault zones and ultra-deep formations, improving the reliability and accuracy of geostress field predictions.

[0256] This invention optimizes reservoir transformation design and improves fracturing effectiveness. Using a high-precision geostress field model, it simulates the propagation path of reservoir fracturing cracks, ensuring that the cracks extend along the direction of maximum principal stress. This enhances reservoir transformation effectiveness, increases oil and gas production, and achieves efficient resource development. It provides a scientific basis for fracturing operations, optimizes fracturing parameter design, and significantly improves the success rate and economic benefits of fracturing operations.

[0257] This invention reduces the risk of wellbore instability and ensures safe production. It dynamically analyzes wellbore stability and predicts the instability risks of different well sections, particularly those in areas of high stress concentration and low stress release. It also proposes solutions for wellbore reinforcement and drilling fluid optimization, reducing engineering risks such as wellbore collapse and lost circulation. This provides reliable technical support for safe production in oil and gas fields and reduces the risks of drilling operations in complex geological conditions.

[0258] This invention provides a comprehensive solution that meets key technical requirements. The method integrates well logging data, seismic data, and dynamic rock mechanical properties to provide a comprehensive rock mechanical parameter modeling and geostress prediction solution. It is applicable to specialized geological environments such as complex fault zones, ultra-deep wells, and high-temperature and high-pressure formations, meeting key technical requirements in engineering practice. It improves the optimization of oil and gas well development plans and promotes the efficient and safe development of oil and gas resources.

[0259] In one embodiment, if Figure 4 As shown, a device 400 for predicting ground stress in a complex fault zone includes: a first calculation module 401, a second calculation module 402, a reconstruction module 403 and a prediction module 404;

[0260] The first calculation module 401 is used to calculate the rock physical parameters of the complex fault zone according to the rock physical parameter calculation formula;

[0261] The second calculation module 402 is used to calculate the rock mechanical parameters of the complex fault zone according to the rock mechanical parameter calculation formula;

[0262] The reconstruction module 403 is used to reconstruct the well logging curve of the complex fault zone to obtain the reconstructed well logging curve;

[0263] The prediction module 404 is used to predict the in-situ stress of a complex fault zone by using a three-dimensional in-situ stress model in combination with the reconstructed well logging curve, the rock mechanical parameters, and the rock physical parameters.

[0264] The above embodiment provides a device for predicting geostress in a complex fault zone, which can implement the technical solution described in the above embodiment of a method for predicting geostress in a complex fault zone. The specific implementation principles of the above modules or units can be found in the corresponding contents of the above embodiment of a method for predicting geostress in a complex fault zone, which will not be repeated here.

[0265] like Figure 5 As shown, the present invention also provides an electronic device 500. The electronic device 500 includes a processor 501, a memory 502 and a display 503. Figure 5Only some of the components of the electronic device 500 are shown, but it should be understood that implementation of all of the shown components is not required, and more or fewer components may be implemented instead.

[0266] In some embodiments, the memory 502 may be an internal storage unit of the electronic device 500, such as a hard disk or memory of the electronic device 500. In other embodiments, the memory 502 may also be an external storage device of the electronic device 500, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) card, a Flash Card, etc. equipped on the electronic device 500.

[0267] Furthermore, the memory 502 may include both an internal storage unit of the electronic device 500 and an external storage device. The memory 502 is used to store application software installed in the electronic device 500 and various data.

[0268] In some embodiments, the processor 501 may be a central processing unit (CPU), a microprocessor, or other data processing chip, used to run program codes or process data stored in the memory 502, such as a method for predicting ground stress in a complex fault zone in the present invention.

[0269] In some embodiments, display 503 can be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, or an OLED (Organic Light-Emitting Diode) touchscreen. Display 503 is used to display information on electronic device 500 and to display a visual user interface. Components 501-503 of electronic device 500 communicate with each other via a system bus.

[0270] In some embodiments of the present invention, when the processor 501 executes the complex fault zone ground stress prediction program in the memory 502, the following steps may be implemented:

[0271] Calculate the rock physical parameters of complex fault zones according to the rock physical parameter calculation formula;

[0272] Calculate the rock mechanics parameters of complex fault zones according to the rock mechanics parameter calculation formula;

[0273] Reconstruct the logging curve of the complex fault zone to obtain the reconstructed logging curve;

[0274] The in-situ stress of a complex fault zone is predicted by using a three-dimensional in-situ stress model in combination with the reconstructed well logging curve, the rock mechanical parameters and the rock physical parameters.

[0275] It should be understood that, when the processor 501 executes the complex fault zone ground stress prediction program in the memory 502 , in addition to the above functions, it can also implement other functions. For details, please refer to the description of the corresponding method embodiment above.

[0276] Furthermore, the embodiment of the present invention does not specifically limit the type of the electronic device 500 mentioned. The electronic device 500 may be a portable electronic device such as a mobile phone, a tablet computer, a personal digital assistant (PDA), a wearable device, a laptop computer, or the like. Exemplary embodiments of portable electronic devices include but are not limited to portable electronic devices equipped with IOS, Android, Microsoft, or other operating systems. The above-mentioned portable electronic devices may also be other portable electronic devices, such as a laptop computer with a touch-sensitive surface (e.g., a touch panel). It should also be understood that in some other embodiments of the present invention, the electronic device 500 may not be a portable electronic device, but a desktop computer with a touch-sensitive surface (e.g., a touch panel).

[0277] In another aspect, the present invention further provides a non-transitory computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the method for predicting in-situ stress in a complex fault zone provided by the above methods is implemented. The method comprises:

[0278] Calculate the rock physical parameters of complex fault zones according to the rock physical parameter calculation formula;

[0279] Calculate the rock mechanics parameters of complex fault zones according to the rock mechanics parameter calculation formula;

[0280] Reconstruct the logging curve of the complex fault zone to obtain the reconstructed logging curve;

[0281] The in-situ stress of a complex fault zone is predicted by using a three-dimensional in-situ stress model in combination with the reconstructed well logging curve, the rock mechanical parameters and the rock physical parameters.

[0282] Those skilled in the art will appreciate that all or part of the process steps of the above-described embodiments can be implemented by instructing related hardware through a computer program, and the program can be stored in a computer-readable storage medium, such as a magnetic disk, an optical disk, a read-only memory, or a random access memory.

[0283] The above is a detailed introduction to the method, device, equipment and medium for predicting ground stress in a complex fault zone provided by the present invention. Specific examples are used herein to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core ideas. At the same time, for those skilled in the art, according to the ideas of the present invention, there may be changes in the specific implementation methods and application scopes. In summary, the contents of this specification should not be understood as limiting the present invention.

Claims

1. A method for predicting ground stress in a complex fault zone, characterized in that: include: Calculate the rock physical parameters of complex fault zones according to the rock physical parameter calculation formula; Calculate the rock mechanics parameters of complex fault zones according to the rock mechanics parameter calculation formula; Fitting the rock physical parameter calculation formula and the rock mechanical parameter calculation formula to obtain a well logging curve, wherein the well logging curve includes: a density curve and a shear wave time difference curve; Reconstruct the logging curve of the complex fault zone to obtain the reconstructed logging curve; Predicting the in-situ stress of a complex fault zone by using a three-dimensional in-situ stress model and combining the reconstructed well logging curve, the rock mechanical parameters, and the rock physical parameters; The step of fitting the rock physical parameter calculation formula and the rock mechanical parameter calculation formula to obtain the well logging curve specifically includes: Obtaining a density curve by fitting the petrophysical parameter calculation formula; By fitting the rock mechanics parameter calculation formula, a shear wave time difference curve is obtained; The reconstruction of the logging curve of the complex fault zone specifically includes: The density curve is reconstructed according to the formation mineral composition and formation porosity of the complex fault zone to obtain a reconstructed density curve.

2. The method for predicting ground stress in a complex fault zone according to claim 1, characterized in that: Also includes: The rock physical parameter calculation formula and the rock mechanical parameter calculation formula are established according to the lithologic data of different strata.

3. The method for predicting ground stress in a complex fault zone according to claim 1, characterized in that: Also includes: Calculate elastic parameters through seismic inversion data to obtain rock elastic parameters; Assigning the rock elastic parameters to the three-dimensional geostress model to obtain the assigned three-dimensional geostress model; The method of predicting the in-situ stress of a complex fault zone by using a three-dimensional in-situ stress model and combining the reconstructed well logging curve, the rock mechanical parameters, and the rock physical parameters specifically includes: The in-situ stress of a complex fault zone is predicted by using the assigned three-dimensional in-situ stress model in combination with the reconstructed well logging curve, the rock mechanical parameters and the rock physical parameters.

4. The method for predicting ground stress in a complex fault zone according to claim 1, characterized in that: Also includes: The in-situ stress is verified through three-dimensional in-situ stress simulation. When the verification result meets the requirements, the stability analysis of the wellbore wall of the complex fault zone is performed based on the in-situ stress.

5. A device for predicting ground stress in a complex fault zone, characterized in that: include: a first calculation module, a second calculation module, a reconstruction module, and a prediction module; The first calculation module is used to calculate the rock physical parameters of the complex fault zone according to the rock physical parameter calculation formula; The second calculation module is used to calculate the rock mechanical parameters of the complex fault zone according to the rock mechanical parameter calculation formula, and fit the rock physical parameter calculation formula with the rock mechanical parameter calculation formula to obtain a logging curve, wherein the logging curve includes: a density curve and a shear wave time difference curve; The reconstruction module is used to reconstruct the logging curve of the complex fault zone to obtain the reconstructed logging curve; The prediction module is used to predict the in-situ stress of a complex fault zone by using a three-dimensional in-situ stress model and combining the reconstructed well logging curve, the rock mechanical parameters and the rock physical parameters; The step of fitting the rock physical parameter calculation formula and the rock mechanical parameter calculation formula to obtain the well logging curve specifically includes: Obtaining a density curve by fitting the petrophysical parameter calculation formula; By fitting the rock mechanics parameter calculation formula, a shear wave time difference curve is obtained; The reconstruction of the logging curve of the complex fault zone specifically includes: The density curve is reconstructed according to the formation mineral composition and formation porosity of the complex fault zone to obtain a reconstructed density curve.

6. An electronic device, characterized in that: comprising a memory and a processor, wherein, The memory is used to store programs; The processor is coupled to the memory and is used to execute the program stored in the memory to implement the steps of the method for predicting ground stress in a complex fault zone as described in any one of claims 1 to 4 above.

7. A computer-readable storage medium, characterized in that Used to store computer-readable programs or instructions, which, when executed by a processor, can implement the steps of the method for predicting ground stress in a complex fault zone as described in any one of claims 1 to 4 above.

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