Full three-dimensional fracturing design method based on the spatial distribution of geomechanical characteristics

Abstract

The present invention provides a full 3D fracturing design method based on the spatial distribution of geomechanical characteristics, including: Step 1, establishing a single-well rock mechanics model and conducting model verification; Step 2: establishing a single-well in-situ stress model and conducting model verification; Step 3: performing fine structural interpretation of the reservoir; Step 4: using geological modeling software to conduct formation and structure modeling; Step 5: establishing a reservoir parameter model and conducting model verification; Step 6: converting 3D geomechanical data into planar data; Step 7: designing using full 3D fracturing design software and conducting fracture parameter verification. This full 3D fracturing design method based on the spatial distribution of geomechanical characteristics effectively integrates geological modeling technology and fracturing optimization technology. By establishing a 3D geomechanical field, it realizes full 3D fracturing optimization design, and the simulated fracture morphology is more realistic, improving the level of fracturing design.

Description

Technical Field

[0001] The present invention relates to the technical field of oil and gas development, and particularly to a full three-dimensional fracturing design method based on the spatial distribution of geomechanical characteristics. Background Art

[0002] The geometric shape of hydraulic fractures is one of the main factors affecting the fracturing effect. For an economical and effective fracturing, the fractures should extend in the reservoir as much as possible, and the penetration of water layers and low-pressure permeable layers by the fractures should be prevented. If the fractures penetrate the water layer or the interlayer, it will not only lead to the failure of the fracturing operation, but also cause the destruction of the reservoir pressure system. A main reason for the failure of hydraulic fracturing operations is the failure to effectively control and predict the fracture geometry. The study of fracture morphology is a combination of two processes: establishing a fracture extension model and performing mathematical solutions on it. From the 1950s to the end of the 1980s, domestic and foreign scholars studied two-dimensional models, pseudo-three-dimensional models, and full three-dimensional models that describe the geometric shape and extension law of hydraulic fractures. In the 1990s, pseudo-three-dimensional and full three-dimensional fracturing design optimization software were developed based on the fracture models. Since the three-dimensional model reflects the true deformation of the rock and fluid flow, it can more accurately reflect the fracture geometry.

[0003] Although the pseudo-three-dimensional / full three-dimensional method is currently adopted in fracturing optimization design, in actual fracturing design simulations, the formation is assumed to be a homogeneous reservoir, which is obviously inconsistent with the actual formation situation. On the one hand, due to the limitations of the functions of fracturing design software, only homogeneous grids can be adopted, which is also the default grid type of most fracturing design software. On the other hand, for grid-based fracturing design software, such as GOHFER software, the reservoir can be divided into unit grids, and the grid properties can be modified to achieve non-homogeneity simulation. However, conventional logging curves only reflect the rock properties at the wellbore. Even if grid technology is adopted, uniform grids are often used for calculation during calculation. Therefore, we invented a new full three-dimensional fracturing design method based on the spatial distribution of geomechanical characteristics to solve the above technical problems. Summary of the Invention

[0004] The object of the present invention is to provide a method aiming to improve the fracturing design level, effectively integrating geological modeling technology and fracturing optimization technology, and realizing full three-dimensional fracturing optimization design by establishing a three-dimensional geomechanical field, so that the simulated fracture morphology is more realistic.

[0005] The object of the present invention can be achieved by the following technical measures: a full 3D fracturing design method based on the spatial distribution of geomechanical characteristics. The full 3D fracturing design method based on the spatial distribution of geomechanical characteristics includes: Step 1, establishing a single-well rock mechanics model and validating the model; Step 2: establishing a single-well in-situ stress model and validating the model; Step 3: conducting fine structural interpretation of the reservoir; Step 4: using geological modeling software to perform formation and structure modeling; Step 5: establishing a reservoir parameter model and validating the model; Step 6: converting 3D geomechanical data into planar data; Step 7: designing using full 3D fracturing design software and validating the fracture parameters.

[0006] The object of the present invention can also be achieved by the following technical measures:

[0007] In Step 1, the rock mechanics model includes a shear wave velocity model, a density model, a Young's modulus and Poisson's ratio model; there are two methods for establishing the shear wave velocity model, namely the empirical formula method and the method using a rock physics model; the density calculation model is the Gardner formula; the Young's modulus and Poisson's ratio model are calculated based on the longitudinal wave velocity, shear wave velocity and density.

[0008] In Step 1, the rock mechanics model validation includes model selection and result comparison; the shear wave velocity model validation includes comparing the calculated shear wave velocity with the shear wave logging results to select the most suitable model; the density model validation includes fitting the Gardner formula coefficients using the measured density logging curve; the Young's modulus and Poisson's ratio validation is to compare the measured Young's modulus model and Poisson's ratio results with the results calculated using the shear wave velocity model or density model to validate the shear wave velocity and density models.

[0009] In Step 2, the in-situ stress model validation includes in-situ stress model selection and result comparison; the in-situ stress model uses the following formula:

[0010]

[0011] where, σ V is the overburden pressure, MPa; σ H is the maximum horizontal principal in-situ stress, MPa; σ h is the minimum horizontal principal in-situ stress, MPa; ρ(h) is the formation density, g / cm 3 ; P p is the formation pore pressure, MPa; ν is the static Poisson's ratio of the formation, dimensionless; α is the effective stress coefficient, dimensionless; β, γ are tectonic stress coefficients, dimensionless; the values of β and γ are calculated by back-calculating the in-situ stress values measured by laboratory experiments. The in-situ stress is calculated using the β and γ coefficients and compared with the in-situ stress values calculated during on-site construction to validate the model.

[0012] In Step 3, the fine structural interpretation includes unifying the main standard reflection horizons and establishing a structural map of the reflection horizons; using the information such as drilling, logging, and electric logging interpretation results together with synthetic seismograms for comprehensive calibration, including the preparation of basic work, the production of fine synthetic seismograms, the output of time-depth relationships and velocity parameters, and secondary calibration; the structural interpretation process is to use three-dimensional fine structural interpretation techniques to complete the structural map of the reflection horizons.

[0013] In Step 4, the stratigraphic modeling includes determining a unified stratigraphic division and correlation standard; clarifying the stratigraphic contact relationships through stratigraphic correlation, understanding the vertical and horizontal variations of the strata, determining a unified stratigraphic division and correlation standard, and establishing a correct and reasonable stratigraphic framework.

[0014] In Step 4, the structural modeling includes establishing a fault model and a horizon model; the study of the structural model takes the fault and horizon data interpreted from stratigraphic division and correlation as the input data source, establishes a fault model and a horizon model, studies the variation law of stratigraphic thickness, the interlayer contact relationships, and the development characteristics of the fault system, and provides a three-dimensional framework for modeling; establishing the structural model includes cross-section modeling, grid design, and horizon modeling; the horizon model applies the multiple grid approximation method.

[0015] In Step 5, establishing the reservoir parameter model includes selecting the reservoir parameter modeling method; in reservoir parameter modeling, the principle of facies-controlled modeling is adopted, and different parameter distributions are assigned to different flow unit types to reflect the differences in the spatial variation of reservoir parameters within different flow units; the sequential Gaussian method is used to simulate the stochastic modeling method of rock physical parameters.

[0016] In Step 5, the reservoir parameters include reservoir physical properties parameters and geomechanical parameters; the reservoir physical properties parameters include porosity and permeability; the geomechanical parameters include Young's modulus, Poisson's ratio, and minimum principal stress.

[0017] In Step 5, the verification of the reservoir parameter model includes comparing the predicted parameters with the actual logging parameters; in model verification, first, based on the well data excluding the test well, the attribute models of various parameters are established using the sequential Gaussian simulation algorithm, and the attributes at the test well trajectory are extracted and compared with the actual logging results.

[0018] In Step 6, the plane data includes the attribute data of the plane where the maximum principal stress direction is located; the geological modeling software uses corner point grids, while the fracturing design software reads plane attributes, and data format conversion is required; there are two common data conversion methods. One is to use the geological modeling software for conversion, and the other is to directly read the corner point grid file for conversion.

[0019] In step 7, the full 3D fracturing design software conducts optimization design including importing geological mechanics plane data and simulating the fracturing crack morphology; the 3D geological mechanics design method is significantly different from the conventional design method, and the crack morphology simulated using 3D mechanical data is no longer a symmetric double-wing crack.

[0020] In step 7, the crack parameter verification includes comparing the crack parameters simulated by the fracturing design with the crack parameters monitored on-site, comparing the designed double-wing crack length with the lengths of the left and right wings of the monitored crack.

[0021] In the full 3D fracturing design method based on the spatial distribution of geological mechanics characteristics in the present invention, a set of 3D geological mechanics numerical simulation methods is established, which not only overcomes the defects of high cost and long cycle for obtaining rock mechanics parameters through laboratory experiments, but also solves the drawback of poor prediction accuracy of the commonly used finite element method at present. This method changes the conventional fracturing design method, organically combines geological modeling technology and fracturing design optimization technology, realizes the stochastic simulation of 3D geological mechanics using the geological modeling method, and truly realizes the spatial simulation of hydraulic fractures using the full 3D fracturing design software based on meshing. The establishment of this method not only provides accurate physical and mechanical parameters for fracturing design, but also can provide an important basis for the formulation of drilling, completion and oil and gas development plans and engineering construction measures. Brief Description of the Drawings

[0022] Figure 1 It is a flowchart of a specific embodiment of the full 3D fracturing design method based on the spatial distribution of geological mechanics characteristics of the present invention;

[0023] Figure 2 It is a comparison diagram of the calculated shear wave and the measured shear wave in a specific embodiment of the present invention;

[0024] Figure 3 It is a comparison diagram of the calculated density curve and the measured density curve in a specific embodiment of the present invention;

[0025] Figure 4 It is a comparison diagram of the calculated shear modulus, Young's modulus and the measured shear modulus, Young's modulus in a specific embodiment of the present invention;

[0026] Figure 5 It is a layer model diagram established in a specific embodiment of the present invention;

[0027] Figure 6 It is a reservoir geological mechanics parameter model diagram in a specific embodiment of the present invention;

[0028] Figure 7 It is a reservoir geological mechanics parameter verification diagram in a specific embodiment of the present invention;

[0029] Figure 8It is a cross-sectional view of reservoir geomechanical parameters in a specific embodiment of the present invention;

[0030] Figure 9 It is a software diagram for converting reservoir three-dimensional grid data in a specific embodiment of the present invention;

[0031] Figure 10 It is a plan view of reservoir geomechanical parameters in a specific embodiment of the present invention;

[0032] Figure 11 It is a verification diagram of full three-dimensional simulation of fractures in a specific embodiment of the present invention. Detailed implementation manners

[0033] To make the above and other objects, features, and advantages of the present invention more obvious and understandable, the following particularly gives preferred embodiments and, in conjunction with the accompanying drawings, makes detailed descriptions as follows.

[0034] As Figure 1 shown, Figure 1 It is a flow chart of the full three-dimensional fracturing design method based on the spatial distribution of geomechanical characteristics of the present invention.

[0035] Step 1: Establish a single-well rock mechanics model and conduct model verification.

[0036] The shear wave velocity is an important parameter for rock physics analysis, but actual shear wave logging is very rare. Currently, the methods for obtaining the shear wave velocity using the longitudinal wave velocity mainly include the empirical formula method and the method using the rock physics model. The empirical formula method uses regression, but for blocks with relatively few shear wave logs, the error calculated using the empirical formula is relatively large.

[0037] For the rock physics model method, according to the wave equation and Gassmann theory, it can be obtained that:

[0038] The longitudinal wave velocity is:

[0039] The shear wave velocity is:

[0040] Among them, V P is the longitudinal wave velocity, m / s; V s is the shear wave velocity, m / s; K is the effective bulk modulus of elasticity, Pa; μ is the effective shear modulus of elasticity, Pa; ρ is the density of the medium, kg / m 3 .

[0041] Figure 2Comparison between the shear wave velocity calculated by the petrophysical model method and the measured shear wave velocity in Well Gao 94. Only Well Gao 94 in the block has been measured for shear waves, and the model is established by the Gassmann method. In the whole well section, the comparability and similarity between the calculated shear wave velocity curve and the measured shear wave velocity curve are very good, the changing trends are consistent, and the relative error is generally less than 5%. The Gassmann method is the closest to the measured results, so the Gassmann method is selected.

[0042] Since density logging is not carried out for every well, density value calculation is generally required, and the Gardner formula is generally used for the density calculation model.

[0043] Gardner formula:

[0044] where ρ is the density, g / cm 3 ; V P is the P-wave velocity, m / s; b and c are constants, and the common coefficient c = 0.31 and b = 0.25.

[0045] Figure 3 It is the comparison chart of the measured density curve and the calculated density curve in Well Gao 94. Only two wells in the block have density logging. According to the regression coefficient of the relationship between the P-wave velocity and the density, the coefficients of the Gardner formula are adjusted, and the applicable coefficients of the Gardner formula for the block are calculated as follows:

[0046] Shale: c = 0.2795, b = 0.265

[0047] Sandstone: c = 0.2733, b = 0.261

[0048] Based on the shear wave velocity and density model, the rock mechanical parameters are verified according to the Young's modulus, shear modulus and Poisson's ratio.

[0049] Young's modulus model:

[0050] Shear modulus model:

[0051] Poisson's ratio model:

[0052] where E is the Young's modulus, MPa; G is the shear modulus, MPa; v is the Poisson's ratio, dimensionless; ρ is the density of the rock, g / cm 3 ; Δt s , Δt p is the shear wave and P-wave travel time difference of the rock, μs / m; V s , V p is the shear wave and P-wave velocity of the rock, m / s.

[0053] Figure 4 It is the comparison result of the calculated shear modulus and Young's modulus values with the measured values in Well Gao 94. Well Gao 94 is the only well with shear modulus and Young's modulus curves in the block, and the obtained results have a very high degree of coincidence.

[0054] Step 2: Establish a single-well in-situ stress model and conduct model verification.

[0055] Currently, the main horizontal stress calculation models include the Mohr-Coulomb formation failure model, the uniaxial strain model, Huang's model, the combined spring model, and the differential model, etc. For the case where the hydraulic fracturing fracture is a vertical fracture and without considering the change of formation temperature, we adopt the following in-situ stress calculation model:

[0056]

[0057] Among them, σ V is the overburden pressure, MPa; σ H is the maximum horizontal principal in-situ stress, MPa; σ h is the minimum horizontal principal in-situ stress, MPa; ρ(h) is the formation density, g / cm 3 ; P p is the formation pore pressure, MPa; ν is the static Poisson's ratio of the formation, dimensionless; α is the effective stress coefficient, dimensionless; β, γ are the tectonic stress coefficients, dimensionless.

[0058] β and γ can be determined by the acoustic emission Kaiser effect experiment. By back-calculation, for Well Gao 94: β = 0.509, γ = 0.232; for Well Gao 944: β = 0.503, γ = 0.241.

[0059] Statistical data of the construction pressure of the fracturing construction wells in the block are calculated, and the comparison between the minimum principal stress and the measured value is shown in Table 1. The error is controlled within 7%, and the model accuracy is relatively high.

[0060] Table 1 Comparison of calculated in-situ stress and measured value

[0061]

[0062] Step 3: Conduct fine structural interpretation of the reservoir.

[0063] Horizon calibration is a comprehensive calibration carried out by using various information such as drilling, logging, and electric logging interpretation results together with the synthetic seismogram, which can improve the accuracy of calibration.

[0064] The implementation of comprehensive calibration is divided into two steps: primary calibration and secondary calibration. Primary calibration uses the geological stratification of the well and the regional marker beds as constraints, and makes a correlation comparison of reflection information such as reflection wave groups and energy between the refined synthetic seismogram and the VSPLOG profile and the seismic trace beside the well. Through repeated debugging, the correlation is made the best, so as to obtain an accurate time-depth relationship. Secondary calibration is carried out after the primary calibration is completed. On the basis of accurate horizon calibration, using the time-depth relationship, relevant information (such as well geological stratification, well logging interpretation and oil testing results, velocity curve or acoustic curve reflecting the wave impedance interface, spontaneous potential curve reflecting reservoir physical properties, etc.) is converted from the depth domain to the time domain, and placed on the seismic trace beside the well together with the synthetic seismogram for secondary calibration of horizons. Comprehensive calibration includes the preparation of basic work, the production of refined synthetic seismograms, the output of time-depth relationships and velocity parameters, secondary calibration, etc.

[0065] The three-dimensional fine structure interpretation technology is adopted in the structure interpretation process, which can improve the fault interpretation accuracy, implement the fault combination law and the occurrence of fault block strata. When there are lateral changes in the strata or special geological bodies, the scope and boundary can also be determined.

[0066] Combined with the drilling and logging, geological data of the block, through comprehensive calibration, the main standard reflection horizons are unified, and the geological meanings and seismic reflection horizon characteristics of the main reflection horizons are clarified. According to the 400×400m grid, the basic profile network of the main reflection horizons in the whole area is established, and after being encrypted to 100×100m, 50×100m or 50×50m grids, the fine structure interpretation of the whole area is carried out for the lower Es3, lower Es4 and Kongdian Formation, and the structure maps of the reflection horizons such as the lower Es3, lower Es4 and Kongdian Formation in this area are completed.

[0067] Step 4: Use geological modeling software to carry out stratigraphic and structural modeling.

[0068] Through stratigraphic correlation, the stratigraphic contact relationship is clarified, the vertical and horizontal changes of the strata are understood, the unified stratigraphic division and correlation standard are determined, and a correct and reasonable stratigraphic framework is established.

[0069] The study of the structural model takes the faults and horizon data interpreted by stratigraphic division and correlation as the input data source, and applies certain calculation methods to establish a fault model and a horizon model, and studies the variation law of stratigraphic thickness, the contact relationship between layers and the development characteristics of the fault system, providing a three-dimensional framework for modeling.

[0070] The calculation of structural modeling mainly focuses on the process of structural horizon modeling. The structural horizon modeling generally adopts the modeling methods of interpolation between wells and extrapolation outside wells, belonging to the category of deterministic modeling. Common methods include: triangular mesh interpolation method, distance inverse weighted method, multi-grid approximation method, etc. The multi-grid approximation method is a method that decomposes the whole interpolation process into multiple iterative calculations with grids from coarse to fine. The algorithm has high efficiency and good stability, so this method is used for calculation.

[0071] Building a structural model involves three technical steps: cross-section modeling, grid design, and horizon modeling. The horizon model applies the multi-grid approximation method. First, a horizon model is established using structural contour data, and then the well point stratification data is used to correct the local structural undulations. A horizon model of 5 horizons in 4 layers of the Es4 lower - Ek3 sand group is established, which better controls the morphology of the structural model in this area. Since the structure of the block is not very complex, the built horizon model is the structural model of this area. Based on the well point data, a horizon model is established using seismic constraints, as Figure 5 shown.

[0072] Step 5: Establish a reservoir parameter model and conduct model verification.

[0073] The reservoir parameter modeling adopts the idea of facies-controlled modeling. Different parameter distributions are assigned to different flow unit types to reflect the differences in the spatial variation of reservoir parameters within different flow units. The principle of facies-controlled modeling is adopted, that is, first establish the sedimentary facies, reservoir structure or flow unit, and then according to the quantitative distribution law of reservoir parameters of different sedimentary facies (sand body types or flow units), conduct interpolation between wells or stochastic simulation by phase (sand body or flow unit) to establish the reservoir parameter distribution model.

[0074] The stochastic models mainly used for stochastic modeling of rock physical parameters include Gaussian random field, fractal random field, indicator simulation, and Markov random field. The Gaussian random field is suitable for stochastic simulation of continuous variables under the condition of weak anisotropy. The commonly used simulation method in general continuous parameter modeling is sequential Gaussian simulation, which is a common method of the Gaussian model.

[0075] Sequential Gaussian simulation is used for facies-controlled reservoir parameter modeling, as Figure 6 shown. Based on the well point data, a horizon model is established using seismic constraints. According to the scope of the work area and the requirements of model accuracy, the plane grid is 50m×50m, 2m longitudinally, and the total number of nodes is 9.02 million. A geomechanical model is established using single-well logging curves. Based on the single-well well point data, the corresponding attribute model is established using the sequential Gaussian algorithm.

[0076] Verify the reservoir geomechanical parameter model, as Figure 7 shown. First, based on the well data excluding Well GaoXie 947, an attribute model of various parameters is established using the sequential Gaussian simulation algorithm, and the attributes at the trajectory of Well GaoXie 947 are extracted and compared with the actual results after drilling. The comparison results show a high degree of agreement between the two.

[0077] Step 6: Convert the three-dimensional geomechanical data into planar data.

[0078] The geological modeling software uses corner point grids, while the fracturing design software reads planar properties, and the data needs to be converted in format. There are two common data conversion methods. One is to use the geological modeling software for conversion, and the other is to directly read the corner point grid file for conversion.

[0079] Using the geological modeling software, property slices can be made in any direction. In the plane of the slice, reservoir physical properties and geomechanical parameters can be output in the format required for engineering construction. Using the geological modeling software to make property slices along the direction of the maximum principal stress, as Figure 8 shown. The direction of the maximum principal stress is the direction of the fracture, and the slice map shows the heterogeneity of the reservoir.

[0080] The other method is to directly read the corner point grid model and intercept the planar data as needed. Read the attribute values stored in the corner point grid format, use the target horizon as the reference point, and make a slice in a certain direction (the direction of the maximum principal stress). The parameter attribute values within the slice grid should be the corner point grid attribute values at that point. First, read the corner point grid data according to the number of grids in the XYZ directions and the origin coordinates. The read grid data is uniquely determined by eight corner points for the attribute values. Secondly, according to the oil layer coordinate values and the slice direction, combined with the horizontal and vertical grid accuracies, read the slice grid data. Finally, save the attributes to a file for easy reading by the fracturing design software. For this purpose, we have developed software to convert the corner point grid data format into the planar data format of the fracturing software, and the interface is as Figure 9 shown. The software can realize the reading of the corner point grid, export the target well depth position, and the slice data in any direction of the in-situ stress.

[0081] Step 7: Use the full 3D fracturing design software for optimization design and verify the fracture parameters.

[0082] Through the method in Step 6, the 3D mechanical field data can be converted into planar grid data.

[0083] Convert the grid attributes of the 3D geomechanical field into 2D planar grid data, as Figure 10 shown. The 2D geomechanical data can be called by the full 3D fracturing design software based on grids, and the grid data can also reflect the heterogeneity of the formation.

[0084] There are significant differences between using the 3D geomechanical design method and the conventional design method. The conventional design method assumes a homogeneous reservoir, and the fracture shape is a symmetric two-wing fracture. When using 3D mechanical data for simulation, the fracture shape is no longer symmetric.

[0085] Compare the fracture shape of the 3D geomechanical fracturing simulation with the actual monitored fracture shape, as Figure 11As shown. The ground microseismic method is used for fracture monitoring in Well Gao Xie 947. The fracture monitoring results show that the azimuth of the main fracture is N68.8°E. The length of the left wing of this fracture is about 167.6 meters, the length of the right wing is about 172.2 meters, and the total length is about 339.8 meters. The comparison between the design results and the fracture monitoring results is shown in Table 2. The relative error between the on-site fracture monitoring results and the simulation results does not exceed 6%. The three-dimensional mechanical field is used for fracturing optimization design, and the design results are more reliable.

[0086] Table 2 Comparison table of fracture morphology under different design methods

[0087] On-site monitoring results Three-dimensional field fracturing simulation Fracture length difference Relative error Left-wing fracture length, m 167.6 158 9.6 5.7 Right-wing fracture length, m 172.2 162 10.2 5.9

[0088] The full three-dimensional fracturing design method based on the spatial distribution of geomechanical characteristics of the present invention establishes a geomechanical calculation model for a single well by optimizing the shear wave velocity model, density model, Young's modulus and Poisson's ratio model, and in-situ stress model. Based on the geomechanical parameters of a single well, an attribute model is established by using a geological modeling software and the stochastic modeling method. The three-dimensional attribute values in the geological model are converted into attribute values in the plane (the direction of the maximum principal stress), and the plane grid data required by the fracturing design software is generated. The fracture simulation is carried out by using the full three-dimensional fracturing design software, and an asymmetric fracture morphology is simulated. The present invention realizes the effective integration of geological modeling technology and fracturing optimization technology, and truly realizes the full three-dimensional fracturing design.

Claims

1. A full three-dimensional fracturing design method based on the spatial distribution of geomechanical characteristics, characterized in that, The full 3D fracturing design method based on the spatial distribution of geomechanical characteristics includes: Step 1: Establish a single-well rock mechanics model and conduct model verification; Step 2: Establish a single-well in-situ stress model and conduct model verification; Step 3: Conduct fine structural interpretation of the reservoir; Step 4: Use geological modeling software to perform formation and structure modeling; Step 5: Establish a reservoir parameter model and conduct model verification; Step 6: Convert 3D geomechanical data into planar data; Step 7: Design using full 3D fracturing design software and conduct fracture parameter verification; In Step 1, the rock mechanics model includes a shear wave velocity model, a density model, a Young's modulus and Poisson's ratio model; there are two methods for establishing the shear wave velocity model, namely the empirical formula method and the method using a rock physics model; the density calculation model is the Gardner formula; the Young's modulus and Poisson's ratio model are calculated based on the longitudinal wave velocity, shear wave velocity and density. In Step 2, the in-situ stress model verification includes in-situ stress model selection and result comparison; the in-situ stress model uses the following formula: Among them, σ V is the overburden pressure, MPa; σ H is the maximum horizontal principal in-situ stress, MPa; σ h is the minimum horizontal principal in-situ stress, MPa; ρ(h) is the formation density, g / cm 3 ; P p is the formation pore pressure, MPa; v is the static Poisson's ratio of the formation, dimensionless; α is the effective stress coefficient, dimensionless; β and γ are tectonic stress coefficients, dimensionless; the values of β and γ are back-calculated using the in-situ stress values measured from laboratory test results; the in-situ stress is calculated using the β and γ coefficient values and compared with the in-situ stress values calculated during field construction to verify the model.

2. The full three-dimensional fracturing design method based on the spatial distribution of geomechanical characteristics according to claim 1, characterized in that, In Step 1, the rock mechanics model verification includes model selection and result comparison; the shear wave velocity model verification includes comparing the calculated shear wave velocity with the shear wave logging results to select the most suitable model; the density model verification includes fitting the Gardner formula coefficients using the measured density logging curve; the verification of the Young's modulus and Poisson's ratio is to compare the measured Young's modulus model and Poisson's ratio results with the calculation results using the shear wave velocity model or density model to verify the shear wave velocity and density models.

3. The full three-dimensional fracturing design method based on the spatial distribution of geomechanical characteristics according to claim 1, characterized in that, In Step 3, the fine structural interpretation includes unifying the main standard reflection horizons and establishing a reflection horizon structure map; using information such as drilling, logging, and electric logging interpretation results together with synthetic seismograms for comprehensive calibration, including the preparation of basic work, the production of fine synthetic seismograms, the output of time-depth relationship and velocity parameters, and secondary calibration; The structural interpretation process uses 3D fine structural interpretation technology to complete the reflection horizon structure map.

4. The full three-dimensional fracturing design method based on the spatial distribution of geomechanical characteristics according to claim 1, characterized in that, In Step 4, formation modeling includes determining a unified formation division and correlation standard; through formation correlation, clarify the formation contact relationship, understand the vertical and horizontal changes of the formation, determine a unified formation division and correlation standard, and establish a correct and reasonable formation framework.

5. The full three-dimensional fracturing design method based on the spatial distribution of geomechanical characteristics according to claim 1, characterized in that, In Step 4, structure modeling includes establishing a fault model and a horizon model; the structure model research takes the fault and horizon data interpreted by formation division and correlation as the input data source to establish a fault model and a horizon model, study the variation law of formation thickness, the interlayer contact relationship and the development characteristics of the fault system, and provide a 3D framework for modeling; establishing a structure model includes cross-section modeling, grid design, and horizon modeling; the horizon model applies the multiple grid approximation method.

6. The full three-dimensional fracturing design method based on the spatial distribution of geomechanical characteristics according to claim 1, characterized in that, In Step 5, establishing a reservoir parameter model includes selecting a reservoir parameter modeling method; in reservoir parameter modeling, the principle of facies-controlled modeling is adopted, and different parameter distributions are assigned to different flow unit types to reflect the spatial variation differences of reservoir parameters within different flow units; the sequential Gaussian method is used to simulate the stochastic modeling method of rock physical parameters.

7. The full three-dimensional fracturing design method based on the spatial distribution of geomechanical characteristics according to claim 1, characterized in that, In step 5, the reservoir parameters include reservoir physical property parameters and geomechanical parameters; the reservoir physical property parameters include porosity and permeability; the geomechanical parameters include Young's modulus, Poisson's ratio, and minimum principal stress.

8. The full three-dimensional fracturing design method based on the spatial distribution of geomechanical characteristics according to claim 1, characterized in that, In step 5, the verification of the reservoir parameter model includes comparing the predicted parameters with the actual logging parameters; in the model verification, first, based on the well data excluding the inspection well, the sequential Gaussian simulation algorithm is used to establish the attribute models of various parameters, and the attributes at the inspection well trajectory are extracted and compared with the actual logging results.

9. The full three-dimensional fracturing design method based on the spatial distribution of geomechanical characteristics according to claim 1, characterized in that, In step 6, the planar data includes the attribute data of the plane where the maximum principal stress direction is located; the geological modeling software uses corner point grids, while the fracturing design software reads planar attributes and data format conversion is required; there are two common data conversion methods. One is to use the geological modeling software for conversion, and the other is to directly read the corner point grid file for conversion.

10. The full three-dimensional fracturing design method based on the spatial distribution of geomechanical characteristics according to claim 1, characterized in that, In step 7, the optimization design by the full three-dimensional fracturing design software includes importing the geomechanical planar data and simulating the fracturing crack morphology; there are significant differences between the three-dimensional geomechanical design method and the conventional design method. The crack morphology simulated using three-dimensional mechanical data is no longer a symmetric double-wing crack.

11. The full three-dimensional fracturing design method based on the spatial distribution of geomechanical characteristics according to claim 10, wherein In step 7, the verification of the crack parameters includes comparing the crack parameters simulated by the fracturing design with the crack parameters monitored on-site, comparing the designed double-wing crack length with the lengths of the left and right wings of the monitored crack.

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