A method and device for predicting elastic wave velocity in strongly transversely isotropic media

Abstract

The present invention discloses a method and device for predicting elastic wave velocity in a strongly transversely isotropic medium, and relates to the technical field of geophysical oil and gas exploration. An elastic wave velocity model is constructed using the rock attribute information of the target section of the reservoir, and the elastic wave velocity is predicted based on the elastic wave velocity model. The present invention provides an elastic wave velocity model in which the elastic wave velocity uses the fracture weakness as an independent variable, which is convenient for determining the elastic wave velocity based on the fracture parameters and can be applied to strong anisotropy conditions. Moreover, in the case of strong anisotropy, the seismic elastic wave velocity prediction results provided by the present invention are more consistent with the precise values ​​and have a wider range of applications. In the process of establishing the elastic wave velocity model, the rock attribute information of the target section of the reservoir is fully utilized to accurately construct the corresponding rock physics model, which can accurately determine the corresponding reservoir rock and the fluid properties contained therein based on the seismic response characteristics.

Description

Technical Field

[0001] The present invention relates to the technical field of geophysical oil and gas exploration, and in particular to a method and device for predicting elastic wave velocity in a strongly transversely isotropic medium. Background Art

[0002] Rock physics models bridge seismic data (elastic parameters) with reservoir characteristics (physical parameters). They primarily investigate the intrinsic relationship between seismic response characteristics and the properties of reservoir rocks and their fluids. Elastic wave velocity characterization is crucial in seismic exploration, encompassing all aspects of seismic data processing and inversion. Linearization and first-order perturbation theory are widely used to derive approximate formulas for anisotropic media. Currently, most elastic wave velocity formulas are based on anisotropy parameters and weak anisotropy assumptions. Although the definitions of anisotropy parameters vary slightly, the core principle is to convert elastic parameters into easily observable and representative indices. The physical meaning of some anisotropy parameters (such as δ, a common anisotropy parameter) is unclear, and there is no unified understanding or standard. Numerous scholars have proposed different forms of anisotropy parameters. Furthermore, perturbation theory assumes small independent variables, and first-order velocity formulas based on anisotropy parameters are often only applicable to weakly anisotropic media and are not applicable to strongly anisotropic conditions. Summary of the Invention

[0003] In order to solve the above problems, the inventors have made the present invention, and through specific implementation methods, provide a method and device for predicting elastic wave velocity in a strongly transversely isotropic medium, which can describe strongly anisotropic geological conditions and effectively characterize seismic wave velocity.

[0004] In a first aspect, an embodiment of the present invention provides a method for predicting elastic wave velocity in a strongly transversely isotropic medium, comprising the following steps:

[0005] Predict elastic wave velocity based on elastic wave velocity model;

[0006] The elastic wave velocity model is:

[0007]

[0008] Among them, V P Indicates the P-wave velocity of the target reservoir segment, V SV Indicates the SV wave velocity of the target reservoir segment, V SH represents the SH wave velocity of the target reservoir section, ΔN and ΔT are the fracture weakness parameters of the target reservoir section, α and β are the longitudinal and shear wave velocities of the rock matrix in the target reservoir section, respectively, and θ is the elastic wave incident angle.

[0009] Specifically, establishing the elastic wave velocity model includes the following steps:

[0010] The elastic parameters and density of the fluid-saturated rock in the target section of the reservoir are input into the elastic wave equation and solved to determine the elastic wave velocity model.

[0011] Specifically, determining the elastic parameters and density of fluid-saturated rock includes the following steps:

[0012] The elastic parameters and density of the fluid-saturated rock are determined based on the elastic parameters and density of the dry rock skeleton in the target reservoir section and the fluid attributes in the attribute information.

[0013] Specifically, determining the elastic parameters and density of the dry rock skeleton includes the following steps:

[0014] The elastic parameters and density of the dry rock skeleton are determined based on the elastic parameters and density of the porous rock matrix in the target reservoir section and the parameters of the directional arranged fractures in the attribute information.

[0015] Specifically, determining the elastic parameters and density of the porous rock matrix includes the following steps:

[0016] The elastic parameters and density of the porous rock matrix are determined based on the elastic parameters and density of the rock mineral mixture in the target reservoir section and the pore parameters in the attribute information.

[0017] Specifically, determining the elastic parameters and density of the rock mineral mixture includes the following steps:

[0018] The elastic parameters and density of the rock-mineral mixture are determined based on the volume content, density and elastic parameters of various minerals in the reservoir target section attribute information.

[0019] In a second aspect, an embodiment of the present invention provides a device for predicting elastic wave velocity in a strongly transversely isotropic medium, comprising:

[0020] An elastic wave velocity prediction module, used for predicting the elastic wave velocity according to the elastic wave velocity model;

[0021] The elastic wave velocity model is:

[0022]

[0023] Among them, V P Indicates the P-wave velocity of the target reservoir segment, V SV Indicates the SV wave velocity of the target reservoir segment, V SH represents the SH wave velocity of the target reservoir section, ΔN and ΔT are the fracture weakness parameters of the target reservoir section, α and β are the longitudinal and shear wave velocities of the rock matrix in the target reservoir section, respectively, and θ is the elastic wave incident angle.

[0024] In a third aspect, an embodiment of the present invention provides a method for constructing a prediction model for elastic wave velocity in a strongly transversely isotropic medium, comprising the following steps:

[0025] Determine the elastic parameters and density of the rock-mineral mixture based on the volume content, density and elastic parameters of various minerals in the target reservoir segment attribute information;

[0026] Determine the elastic parameters and density of the porous rock matrix based on the elastic parameters and density of the rock mineral mixture and the pore parameters in the attribute information;

[0027] Determine the elastic parameters and density of the dry rock skeleton based on the elastic parameters and density of the porous rock matrix and the parameters of the directional cracks in the attribute information;

[0028] Determine the elastic parameters and density of the fluid-saturated rock based on the elastic parameters and density of the dry rock skeleton and the fluid properties in the property information;

[0029] The elastic parameters and density of the fluid-saturated rock are input into the elastic wave equation and solved to determine the elastic wave velocity model.

[0030] Specifically, the elastic wave velocity model is:

[0031]

[0032] Among them, V P Indicates the P-wave velocity of the target reservoir segment, V SV Indicates the SV wave velocity of the target reservoir segment, V SH represents the SH wave velocity of the target reservoir section, ΔN and ΔT are the fracture weakness parameters of the target reservoir section, α and β are the longitudinal and shear wave velocities of the rock matrix in the target reservoir section, respectively, and θ is the elastic wave incident angle.

[0033] In a fourth aspect, an embodiment of the present invention provides a system for constructing a prediction model for elastic wave velocity in a strongly transversely isotropic medium, comprising:

[0034] The elastic parameter and density determination module is used to determine the elastic parameters and density of the rock mineral mixture based on the volume content, density and elastic parameters of various minerals in the target reservoir segment attribute information; determine the elastic parameters and density of the porous rock matrix based on the elastic parameters and density of the rock mineral mixture and the pore parameters in the attribute information; determine the elastic parameters and density of the dry rock skeleton based on the elastic parameters and density of the porous rock matrix and the directional fracture parameters in the attribute information; and determine the elastic parameters and density of the fluid-saturated rock based on the elastic parameters and density of the dry rock skeleton and the fluid properties in the attribute information;

[0035] The elastic wave velocity model determination module is used to input the elastic parameters and density of the fluid-saturated rock into the elastic wave equation and solve it to determine the elastic wave velocity model.

[0036] Specifically, the elastic wave velocity model is:

[0037]

[0038] Among them, V P Indicates the P-wave velocity of the target reservoir segment, V SV Indicates the SV wave velocity of the target reservoir segment, V SH represents the SH wave velocity of the target reservoir section, ΔN and ΔT are the fracture weakness parameters of the target reservoir section, α and β are the longitudinal and shear wave velocities of the rock matrix in the target reservoir section, respectively, and θ is the elastic wave incident angle.

[0039] Based on the same inventive concept, an embodiment of the present invention provides a computer storage medium, wherein the computer storage medium stores computer-executable instructions. When the computer-executable instructions are executed, the aforementioned method for predicting elastic wave velocity in a strongly transversely isotropic medium or the aforementioned method for constructing a model for predicting elastic wave velocity in a strongly transversely isotropic medium are implemented.

[0040] The beneficial effects of the above technical solutions provided by the embodiments of the present invention include at least:

[0041] This invention provides an elastic wave velocity model that uses fracture weakness as an independent variable. This facilitates the determination of elastic wave velocity based on fracture parameters and is applicable to conditions with strong anisotropy. In these conditions, the seismic elastic wave velocity predictions provided by the invention are more consistent with the precise values, extending its applicability. In establishing the elastic wave velocity model, rock property information of the target reservoir section is fully utilized to accurately construct a corresponding rock physics model. This model can accurately determine the properties of the corresponding reservoir rock and its contained fluids based on seismic response characteristics.

[0042] Other features and advantages of the present invention will be described in the following description, and in part will become apparent from the description, or will be understood by practicing the present invention. The purposes and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description, claims, and drawings.

[0043] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0045] Figure 1 This is a flow chart of a method for predicting elastic wave velocity in a strongly transversely isotropic medium according to an embodiment of the present invention;

[0046] Figure 2A schematic diagram of a rock physics modeling method according to an embodiment of the present invention;

[0047] Figure 3 Schematic diagram showing the comparison between the predicted longitudinal wave velocity and the exact solution in an embodiment of the present invention;

[0048] Figure 4 Schematic diagram showing the comparison between the predicted SV wave velocity and the exact solution in an embodiment of the present invention;

[0049] Figure 5 Schematic diagram showing the comparison between the predicted SH wave velocity and the exact solution in an embodiment of the present invention;

[0050] Figure 6 Schematic diagram showing the comparison between the predicted longitudinal wave velocity in an embodiment of the present invention and the results of the exact solution and Thomsen theory;

[0051] Figure 7 Schematic diagram showing the comparison between the predicted SV wave velocity in an embodiment of the present invention and the results of the exact solution and Thomsen theory;

[0052] Figure 8 This is a flow chart of a method for constructing a model for predicting elastic wave velocity in a strongly transversely isotropic medium according to an embodiment of the present invention;

[0053] Figure 9 A system block diagram for constructing a prediction model for elastic wave velocity in strongly transversely isotropic media in an embodiment of the present invention. DETAILED DESCRIPTION

[0054] Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. Rather, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0055] In order to solve the problems existing in the prior art, an embodiment of the present invention provides a method and device for predicting elastic wave velocity in a strongly transversely isotropic medium.

[0056] The embodiment of the present invention provides a method for predicting elastic wave velocity in a strongly transversely isotropic medium, the process of which is as follows: Figure 1 As shown, the following steps are included:

[0057] Step S1: Input parameters such as the longitudinal and shear wave velocities of the target reservoir rock matrix into the elastic wave velocity model.

[0058] The elastic wave velocity model is:

[0059]

[0060] or

[0061]

[0062] or

[0063]

[0064] or

[0065]

[0066] Among them, V P Indicates the P-wave velocity of the target reservoir segment, V SV Indicates the SV wave velocity of the target reservoir segment, V SH represents the SH wave velocity of the target reservoir segment, ΔN and ΔT are the fracture weakness parameters of the target reservoir segment, α and β are the P- and S-wave velocities of the rock matrix in the target reservoir segment, and θ is the elastic wave incident angle. Elastic waves include P waves, SV waves, and SH waves.

[0067] Transverse isotropy (TI) is an anisotropic medium. The P- and S-wave velocities of the rock matrix in the target reservoir section are part of the elastic parameters of the fluid-saturated rock. In some specific embodiments, the process of determining the elastic parameters and density of the fluid-saturated rock is as follows: Figure 2 As shown, determining the elastic parameters and density of fluid-saturated rock includes the following steps: determining the elastic parameters and density of the fluid-saturated rock based on the elastic parameters and density of the dry rock skeleton in the target reservoir section and the fluid attributes in the attribute information. In some specific embodiments, establishing the elastic wave velocity model includes the following steps: inputting the elastic parameters and density of the fluid-saturated rock in the target reservoir section into the elastic wave equation and solving it to determine the elastic wave velocity model. Furthermore, by substituting the elastic parameters and density of the fluid-saturated rock into the Christoffel equation and solving the equation, the elastic wave velocity formula can be obtained.

[0068] In some specific embodiments, Figure 2 As shown, determining the elastic parameters and density of the dry rock skeleton includes the following steps: determining the elastic parameters and density of the dry rock skeleton based on the elastic parameters and density of the porous rock matrix in the target section of the reservoir and the parameters of the directional arranged cracks in the attribute information.

[0069] In some specific embodiments, such as Figure 2As shown, determining the elastic parameters and density of a porous rock matrix includes the following steps: determining the elastic parameters and density of the porous rock matrix based on the elastic parameters and density of the rock mineral mixture in the target reservoir section and the pore parameters in the attribute information. For example, based on the elastic parameters and density of the rock mineral mixture in the target reservoir section and the pore parameters in the attribute information, the elastic parameters and density of the porous rock matrix are obtained using one of the known models such as the DEM model and the SCA model. The DEM model is an equivalent medium model based on the fracture interaction hypothesis, which gradually adds fractures to the equivalent matrix. In some cases, the rock mineral mixture includes calcite, dolomite, quartz, clay particles, etc.

[0070] In some specific embodiments, determining the elastic parameters and density of the rock-mineral mixture includes the following steps: determining the elastic parameters and density of the rock-mineral mixture based on the volume content, density, and elastic parameters of each mineral in the target reservoir segment attribute information. For example, the elastic parameters and density of the rock-mineral mixture may be obtained using one of known models, such as the VRH model or the Hashin-Shtrikman model, based on the volume content, density, and elastic parameters of each mineral in the target reservoir segment attribute information.

[0071] Step S2: Predicting the elastic wave velocity according to the elastic wave velocity model.

[0072] According to the elastic wave velocity model, the P wave velocity, SV wave velocity, and SH wave velocity of the target reservoir section are predicted. Among them, the P wave is a longitudinal wave, and the SV wave and SH wave are two modes of shear waves. Under strong anisotropy conditions, the comparison between the P wave velocity prediction result and the accurate value is as follows: Figure 3 As shown in the figure, the comparison between the predicted SV wave velocity and the exact value is shown in the figure. Figure 4 As shown in the figure, the comparison between the predicted SH wave velocity and the accurate value is shown in the figure. Figure 5 As shown, Figures 3 to 5 The waveforms of the predicted value and the precise value are basically consistent, and the difference is within a small range, indicating that the prediction effect is relatively accurate. In addition, the SH wave velocity prediction result and the precise value curve completely coincide, indicating that the prediction is very accurate.

[0073] Under strong anisotropy, after the medium is rotated into a VTI medium, the comparison between the predicted longitudinal and transverse velocities of this embodiment, the corresponding accurate values, and the predicted values ​​obtained according to the Thomsen theory is shown in FIG. Figure 6 and 7 As shown in the figure, it can be seen that the predicted P-wave and S-wave velocities of this embodiment are more consistent with the exact solution. The SV wave predicted value obtained according to Thomsen theory is quite different from the exact value, indicating that it is less applicable to strong anisotropy.

[0074] This embodiment provides an elastic wave velocity model that uses fracture weakness as an independent variable. This facilitates the determination of elastic wave velocity based on fracture parameters and is applicable to situations with strong anisotropy. Furthermore, in these situations, the seismic elastic wave velocity predictions provided by the present invention are more consistent with the precise values, extending its applicability. In establishing the elastic wave velocity model, rock property information for the target reservoir segment is fully utilized to accurately construct a corresponding rock physics model. This model can accurately determine the properties of the corresponding reservoir rock and its contained fluids based on seismic response characteristics.

[0075] Those skilled in the art can change the above sequence without departing from the scope of protection of the present disclosure.

[0076] Another embodiment of the present invention provides a device for predicting elastic wave velocity in a strongly transversely isotropic medium, comprising:

[0077] An elastic wave velocity prediction module, used for predicting the elastic wave velocity according to the elastic wave velocity model;

[0078] The elastic wave velocity model is:

[0079]

[0080] or

[0081]

[0082] or

[0083]

[0084] or

[0085]

[0086] Among them, V P Indicates the P-wave velocity of the target reservoir segment, V SV Indicates the SV wave velocity of the target reservoir segment, V SH represents the SH wave velocity of the target reservoir section, ΔN and ΔT are the fracture weakness parameters of the target reservoir section, α and β are the longitudinal and shear wave velocities of the rock matrix in the target reservoir section, respectively, and θ is the elastic wave incident angle.

[0087] Regarding the apparatus in the above embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment of the method, and will not be elaborated here.

[0088] In this embodiment, an elastic wave velocity model is provided in which the elastic wave velocity uses the fracture weakness as the independent variable, which facilitates the determination of the elastic wave velocity based on the fracture parameters and is applicable to the case of strong anisotropy. Moreover, in the case of strong anisotropy, the seismic elastic wave velocity prediction results provided by the present invention are more consistent with the precise values ​​and have a wider range of applicability.

[0089] Another embodiment of the present invention provides a method for constructing a prediction model for elastic wave velocity in a strongly transversely isotropic medium. Figure 8 As shown, the following steps are included:

[0090] Determine the elastic parameters and density of the rock-mineral mixture based on the volume content, density and elastic parameters of various minerals in the target reservoir segment attribute information;

[0091] Determine the elastic parameters and density of the porous rock matrix based on the elastic parameters and density of the rock mineral mixture and the pore parameters in the attribute information;

[0092] Determine the elastic parameters and density of the dry rock skeleton based on the elastic parameters and density of the porous rock matrix and the parameters of the directional cracks in the attribute information;

[0093] Determine the elastic parameters and density of the fluid-saturated rock based on the elastic parameters and density of the dry rock skeleton and the fluid properties in the property information;

[0094] The elastic parameters and density of the fluid-saturated rock are input into the elastic wave equation and solved to determine the elastic wave velocity model.

[0095] Specifically, the elastic wave velocity model is:

[0096]

[0097] or

[0098]

[0099] or

[0100]

[0101] or

[0102]

[0103] Among them, V P Indicates the P-wave velocity of the target reservoir segment, V SV Indicates the SV wave velocity of the target reservoir segment, V SH represents the SH wave velocity of the target reservoir section, ΔN and ΔT are the fracture weakness parameters of the target reservoir section, α and β are the longitudinal and shear wave velocities of the rock matrix in the target reservoir section, respectively, and θ is the elastic wave incident angle.

[0104] In this embodiment, in the process of establishing the elastic wave velocity model, the rock attribute information of the target reservoir section is fully utilized to accurately construct the corresponding rock physics model, which can accurately determine the corresponding reservoir rock and the fluid properties contained therein based on the seismic response characteristics.

[0105] Another embodiment of the present invention provides a system for constructing a prediction model for elastic wave velocity in a strongly transversely isotropic medium. Figure 9 As shown, including:

[0106] The elastic parameter and density determination module is used to determine the elastic parameters and density of the rock mineral mixture based on the volume content, density and elastic parameters of various minerals in the target reservoir segment attribute information; determine the elastic parameters and density of the porous rock matrix based on the elastic parameters and density of the rock mineral mixture and the pore parameters in the attribute information; determine the elastic parameters and density of the dry rock skeleton based on the elastic parameters and density of the porous rock matrix and the directional fracture parameters in the attribute information; and determine the elastic parameters and density of the fluid-saturated rock based on the elastic parameters and density of the dry rock skeleton and the fluid properties in the attribute information;

[0107] The elastic wave velocity model determination module is used to input the elastic parameters and density of the fluid-saturated rock into the elastic wave equation and solve it to determine the elastic wave velocity model.

[0108] Specifically, the elastic wave velocity model is:

[0109]

[0110] or

[0111]

[0112] or

[0113]

[0114] or

[0115]

[0116] Among them, V P Indicates the P-wave velocity of the target reservoir segment, V SV Indicates the SV wave velocity of the target reservoir segment, V SH represents the SH wave velocity of the target reservoir section, ΔN and ΔT are the fracture weakness parameters of the target reservoir section, α and β are the longitudinal and shear wave velocities of the rock matrix in the target reservoir section, respectively, and θ is the elastic wave incident angle.

[0117] In this embodiment, in the process of establishing the elastic wave velocity model, the rock attribute information of the target reservoir section is fully utilized to accurately construct the corresponding rock physics model, which can accurately determine the corresponding reservoir rock and the fluid properties contained therein based on the seismic response characteristics.

[0118] Based on the same inventive concept, an embodiment of the present invention provides a computer storage medium, wherein the computer storage medium stores computer-executable instructions. When the computer-executable instructions are executed, the aforementioned method for predicting elastic wave velocity in a strongly transversely isotropic medium or the aforementioned method for constructing a model for predicting elastic wave velocity in a strongly transversely isotropic medium are implemented.

[0119] Any modifications, supplements and equivalent substitutions made within the scope of the principles of the present invention shall still fall within the scope of the patent coverage of the present invention.

Claims

1. A method for predicting elastic wave velocity in a strongly transversely isotropic medium, characterized in that: The following steps are involved: Predict elastic wave velocity based on elastic wave velocity model; The elastic wave velocity model is: in, V P Indicates the P-wave velocity of the target reservoir segment, V SV Indicates the SV wave velocity of the target reservoir segment, V SH Indicates the SH wave velocity of the target reservoir segment, ΔN and ΔT is the fracture weakness parameter of the target reservoir segment, α and β are the longitudinal and shear wave velocities of the rock matrix in the target reservoir section, θ is the elastic wave incident angle.

2. The method according to claim 1, wherein Establishing the elastic wave velocity model includes the following steps: The elastic parameters and density of the fluid-saturated rock in the target section of the reservoir are input into the elastic wave equation and solved to determine the elastic wave velocity model.

3. The method according to claim 2, wherein Determining the elastic parameters and density of fluid-saturated rock involves the following steps: The elastic parameters and density of the fluid-saturated rock are determined based on the elastic parameters and density of the dry rock skeleton in the target reservoir section and the fluid attributes in the attribute information.

4. The method according to claim 3, wherein Determine the elastic parameters and density of the dry rock skeleton, including the following steps: The elastic parameters and density of the dry rock skeleton are determined based on the elastic parameters and density of the porous rock matrix in the target reservoir section and the parameters of the directional arranged fractures in the attribute information.

5. The method according to claim 4, wherein Determining the elastic parameters and density of a porous rock matrix includes the following steps: The elastic parameters and density of the porous rock matrix are determined based on the elastic parameters and density of the rock mineral mixture in the target reservoir section and the pore parameters in the attribute information.

6. The method according to claim 5, wherein Determining the elastic parameters and density of a rock-mineral mixture involves the following steps: The elastic parameters and density of the rock-mineral mixture are determined based on the volume content, density and elastic parameters of various minerals in the reservoir target section attribute information.

7. A method for predicting elastic wave velocity in a strongly transversely isotropic medium, characterized in that: The following steps are involved: Predict elastic wave velocity based on elastic wave velocity model; The elastic wave velocity model is: in, V P Indicates the P-wave velocity of the target reservoir segment, ΔN and ΔT is the fracture weakness parameter of the target reservoir segment, α and β are the longitudinal and shear wave velocities of the rock matrix in the target reservoir section, θ is the elastic wave incident angle.

8. A method for predicting elastic wave velocity in a strongly transversely isotropic medium, characterized in that: The following steps are involved: Predict elastic wave velocity based on elastic wave velocity model; The elastic wave velocity model is: in, V SV Indicates the SV wave velocity of the target reservoir segment, ΔN and ΔT is the fracture weakness parameter of the target reservoir segment, α and β are the longitudinal and shear wave velocities of the rock matrix in the target reservoir section, θ is the elastic wave incident angle.

9. A device for predicting elastic wave velocity in a strongly transversely isotropic medium, characterized in that: include: An elastic wave velocity prediction module, used for predicting the elastic wave velocity according to the elastic wave velocity model; The elastic wave velocity model is: or or in, V P Indicates the P-wave velocity of the target reservoir segment, V SV Indicates the SV wave velocity of the target reservoir segment, V SH Indicates the SH wave velocity of the target reservoir segment, ΔN and ΔT is the fracture weakness parameter of the target reservoir segment, α and β are the longitudinal and shear wave velocities of the rock matrix in the target reservoir section, θ is the elastic wave incident angle.

10. A method for constructing a prediction model for elastic wave velocity in a strongly transversely isotropic medium, characterized in that: The following steps are involved: Determine the elastic parameters and density of the rock-mineral mixture based on the volume content, density and elastic parameters of various minerals in the target reservoir segment attribute information; Determine the elastic parameters and density of the porous rock matrix based on the elastic parameters and density of the rock mineral mixture and the pore parameters in the attribute information; Determine the elastic parameters and density of the dry rock skeleton based on the elastic parameters and density of the porous rock matrix and the parameters of the directional cracks in the attribute information; Determine the elastic parameters and density of the fluid-saturated rock based on the elastic parameters and density of the dry rock skeleton and the fluid properties in the property information; The elastic parameters and density of the fluid-saturated rock are input into the elastic wave equation and solved to determine the elastic wave velocity model. The elastic wave velocity model is: or in, V P Indicates the P-wave velocity of the target reservoir segment, V SV Indicates the SV wave velocity of the target reservoir segment, V SH Indicates the SH wave velocity of the target reservoir segment, ΔN and ΔT is the fracture weakness parameter of the target reservoir segment, α and β are the longitudinal and shear wave velocities of the rock matrix in the target reservoir section, θ is the elastic wave incident angle.

11. A system for constructing a prediction model for elastic wave velocity in strongly transversely isotropic media, characterized in that: include: The elastic parameter and density determination module is used to determine the elastic parameters and density of the rock mineral mixture based on the volume content, density and elastic parameters of various minerals in the target reservoir segment attribute information; determine the elastic parameters and density of the porous rock matrix based on the elastic parameters and density of the rock mineral mixture and the pore parameters in the attribute information; determine the elastic parameters and density of the dry rock skeleton based on the elastic parameters and density of the porous rock matrix and the directional fracture parameters in the attribute information; and determine the elastic parameters and density of the fluid-saturated rock based on the elastic parameters and density of the dry rock skeleton and the fluid properties in the attribute information; The elastic wave velocity model determination module is used to input the elastic parameters and density of the fluid-saturated rock into the elastic wave equation and solve it to determine the elastic wave velocity model. The elastic wave velocity model is: or or in, V P Indicates the P-wave velocity of the target reservoir segment, V SV Indicates the SV wave velocity of the target reservoir segment, V SH Indicates the SH wave velocity of the target reservoir segment, ΔN and ΔT is the fracture weakness parameter of the target reservoir segment, α and β are the longitudinal and shear wave velocities of the rock matrix in the target reservoir section, θ is the elastic wave incident angle.

12. A computer storage medium, characterized in that The computer storage medium stores computer executable instructions, which, when executed, implement the method for predicting the elastic wave velocity of a strongly transversely isotropic medium described in any one of claims 1 to 8, or implement the method for constructing a model for predicting the elastic wave velocity of a strongly transversely isotropic medium described in claim 10.

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