Method and device for determining anisotropy parameter sensitivity matrix, equipment and medium

Abstract

The application provides a method and device for determining an anisotropy parameter sensitivity matrix, an apparatus, and a storage medium. The method comprises: obtaining an actual pre-stack azimuth angle gather, a P-wave impedance, a S-wave impedance, a density, and an initial model of an anisotropy parameter; constructing a simulated pre-stack azimuth angle gather based on the initial model of the anisotropy parameter, the P-wave impedance, the S-wave impedance, and the density; obtaining an error function of a plurality of actual seismic records and simulated seismic records with a preset azimuth angle and a preset incident angle according to the actual pre-stack azimuth angle gather and the simulated pre-stack azimuth angle gather; constructing a constraint term error function of the actual pre-stack azimuth angle gather and the simulated pre-stack azimuth angle gather based on the error function of each actual seismic record and simulated seismic record; and determining the anisotropy parameter sensitivity matrix according to the partial derivative of the anisotropy parameter with respect to the constraint term error function.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of oil geophysical exploration, in particular to a method and device for determining an anisotropy parameter sensitivity matrix, equipment and a storage medium. BACKGROUND

[0002] Anisotropy refers to the property of a medium that is not a constant value but varies with direction. In seismic exploration, anisotropy mainly refers to the characteristic that the propagation speed of seismic waves in the underground medium changes with the direction of propagation. With the gradual deepening of exploration and development, the types of oil and gas geophysical exploration have developed from conventional energy such as coal, oil and natural gas to unconventional energy such as coalbed methane, oil shale and shale gas. The exploration area has developed from inland to nearshore and even deep sea, and the exploration depth has gradually developed from the middle layer to the middle-deep layer. The development of the above-mentioned several types of oil and gas geophysical exploration inevitably encounters the problem of seismic anisotropy. With the increase of exploration depth, the offset of collected seismic data gradually increases, and the anisotropy phenomenon is particularly prominent. In addition, the nearshore and deep-sea sedimentary strata are mostly anisotropic. In unconventional energy, oil shale is taken as an example, which is mostly developed as continuous or discontinuous horizontal bedding structure, and the characteristic is that the thin layer is distributed in the form of sheet. These shale and oil shale with high content of sheet-shaped minerals generally have obvious anisotropy characteristics.

[0003] It can be seen that anisotropy plays an extremely important role in oil and gas exploration. However, in the related technology, it is difficult to obtain anisotropy parameters that can represent the degree of anisotropy of the medium, so that the efficiency and accuracy of prestack anisotropy parameter inversion are low. SUMMARY

[0004] In view of the above problems, the present application provides a method and device for determining an anisotropy parameter sensitivity matrix, equipment and a storage medium.

[0005] The present application provides a method for determining an anisotropy parameter sensitivity matrix, comprising:

[0006] obtaining an actual prestack azimuth angle gather, a P-wave impedance, a S-wave impedance, a density and an initial model of anisotropy parameters;

[0007] constructing a simulated prestack azimuth angle gather based on the P-wave impedance, the S-wave impedance, the density and the initial model of the anisotropy parameters;

[0008] obtaining an error function of a plurality of actual seismic records and simulated seismic records with a preset azimuth angle and a preset incidence angle according to the actual prestack azimuth angle gather and the simulated prestack azimuth angle gather;

[0009] constructing a constraint error function of the actual pre-stack azimuth angle gather and the simulated pre-stack azimuth angle gather based on error functions of each actual seismic record and simulated seismic record;

[0010] determining a sensitivity matrix of the anisotropy parameter based on a partial derivative of the constraint error function with respect to the anisotropy parameter.

[0011] In some embodiments, the constructing the simulated pre-stack azimuth angle gather based on the P-wave impedance, S-wave impedance, density and anisotropy parameter initial model comprises:

[0012] establishing a functional relationship of the P-wave reflection coefficient and the P-wave impedance, S-wave impedance, density and anisotropy parameter;

[0013] generating the simulated pre-stack azimuth angle gather by using the functional relationship and a seismic wavelet based on a convolution principle.

[0014] In some embodiments, the constructing the constraint error function of the actual pre-stack azimuth angle gather and the simulated pre-stack azimuth angle gather based on the error functions of each actual seismic record and simulated seismic record comprises:

[0015] accumulating error functions of a plurality of actual seismic records and simulated seismic records corresponding to different azimuth angles and different incident angles to obtain a matching term of simulated data and actual data;

[0016] calculating a constraint term of the anisotropy parameter initial model;

[0017] obtaining the constraint error function of the actual pre-stack azimuth angle gather and the simulated pre-stack azimuth angle gather based on the matching term of the simulated data and actual data and the constraint term of the anisotropy parameter initial model.

[0018] In some embodiments, the constraint term of the anisotropy parameter initial model comprises constraint terms of anisotropy parameter initial models in three different directions.

[0019] In some embodiments, the determining the sensitivity matrix of the anisotropy parameter based on the partial derivative of the constraint error function with respect to the anisotropy parameter comprises:

[0020] calculating partial derivatives of error functions of actual seismic records and simulated seismic records under a preset azimuth angle and a preset incident angle;

[0021] superimposing the partial derivatives of the error functions of each actual seismic record and simulated seismic record to obtain the partial derivative of the constraint error function with respect to the anisotropy parameter;

[0022] obtaining the sensitivity matrix of the anisotropy parameter based on the partial derivative of the constraint error function with respect to the anisotropy parameter.

[0023] In some embodiments, the superimposing the partial derivative of the error function of each of the actual seismic records and the simulated seismic records comprises:

[0024] The partial derivative of the error function of each of the actual seismic records and the simulated seismic records is superimposed in the order of the preset incident angle and the preset azimuth angle.

[0025] In some embodiments, the preset azimuth angle has a first angle range, and the difference between adjacent azimuth angles is 1 degree, and the preset incident angle has a second angle range, and the difference between adjacent incident angles is 1 degree.

[0026] Embodiments of the present application provide a device for determining an anisotropy parameter sensitivity matrix, comprising:

[0027] An acquisition module is configured to acquire an actual pre-stack azimuth angle gather, an initial model of P-wave impedance, S-wave impedance, density, and anisotropy parameter.

[0028] A first construction module is configured to construct a simulated pre-stack azimuth angle gather based on the initial model of P-wave impedance, S-wave impedance, density, and anisotropy parameter.

[0029] A second construction module is configured to obtain an error function of a plurality of actual seismic records and simulated seismic records with preset azimuth angles and preset incident angles according to the actual pre-stack azimuth angle gather and the simulated pre-stack azimuth angle gather.

[0030] A third construction module is configured to construct a constraint term error function of the actual pre-stack azimuth angle gather and the simulated pre-stack azimuth angle gather based on the error function of each of the actual seismic records and the simulated seismic records.

[0031] A determination module is configured to determine an anisotropy parameter sensitivity matrix according to the partial derivative of the anisotropy parameter in the constraint term error function.

[0032] Embodiments of the present application provide a device for determining an anisotropy parameter sensitivity matrix, comprising a memory and a processor, and the memory stores a computer program which is executed by the processor to perform the method for determining the anisotropy parameter sensitivity matrix.

[0033] Embodiments of the present application provide a storage medium which stores a computer program capable of being executed by one or more processors and capable of being used to implement the method for determining the anisotropy parameter sensitivity matrix.

[0034] The application provides a method, device and equipment for determining an anisotropy parameter sensitivity matrix and a storage medium. The method comprises the following steps: constructing a simulated pre-stack azimuth angle gather based on an initial model of a P-wave impedance, a S-wave impedance, a density and an anisotropy parameter; obtaining an error function of a plurality of actual seismic records and simulated seismic records with a preset azimuth angle and a preset incident angle from the simulated pre-stack azimuth angle gather and an actual pre-stack azimuth angle gather; constructing a constraint term error function of the actual pre-stack azimuth angle gather and the simulated pre-stack azimuth angle gather based on the error function of the actual seismic records and the simulated seismic records; and determining the anisotropy parameter sensitivity matrix according to the partial derivative of the anisotropy parameter and the constraint term error function. The sensitivity matrix information obtained can be used for pre-stack anisotropy parameter inversion work for extracting anisotropy parameters from pre-stack seismic data, and the convergence speed of the pre-stack anisotropy parameter inversion work algorithm and the accuracy of the inversion result are improved. BRIEF DESCRIPTION OF DRAWINGS

[0035] The application will be described in more detail below based on the embodiments and with reference to the drawings.

[0036] Figure 1 An implementation flowchart of a method for determining an anisotropy parameter sensitivity matrix provided by the embodiments of the application is shown in the figure.

[0037] Figure 2 An implementation flowchart of a method for constructing a simulated pre-stack azimuth angle gather based on the initial model of the P-wave impedance, the S-wave impedance, the density and the anisotropy parameter provided by the embodiments of the application is shown in the figure.

[0038] Figure 3 An implementation flowchart of a method for constructing a constraint term error function of an actual pre-stack azimuth angle gather and a simulated pre-stack azimuth angle gather provided by the embodiments of the application is shown in the figure.

[0039] Figure 4 An implementation flowchart of a method for determining an anisotropy parameter sensitivity matrix according to the partial derivative of the anisotropy parameter and the constraint term error function provided by the embodiments of the application is shown in the figure.

[0040] Figure 5 An actual pre-stack azimuth angle gather at different angles provided by the embodiments of the application is shown in the figure.

[0041] Figure 6 An actual well logging data diagram of a certain area provided by the embodiments of the application is shown in the figure.

[0042] Figure 7 A partial derivative curve diagram of an actual pre-stack angle gather, a simulated pre-stack angle gather and an error function when the azimuth angle is 180 degrees provided by the embodiments of the application is shown in the figure.

[0043] Figure 8 A sensitivity matrix of an anisotropy parameter provided by the embodiment of the present application is shown in the following table:

[0044] Figure 9 A structure diagram of a device for determining a sensitivity matrix of an anisotropy parameter provided by the embodiment of the present application is shown in the following table:

[0045] Figure 10 A structure diagram of a device for determining a sensitivity matrix of an anisotropy parameter provided by the embodiment of the present application is shown in the following table:

[0046] In the drawings, the same components are designated by the same reference numerals, and the drawings are not drawn according to the actual scale. DETAILED DESCRIPTION

[0047] In order to make the objects, technical solutions and advantages of the present application clearer, the present application will be further described in detail below with reference to the drawings, and the described embodiments should not be regarded as limiting the present application, and all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the present application.

[0048] In the following description, "some embodiments" are described, which describe a subset of all possible embodiments, but it can be understood that "some embodiments" can be the same subset or different subsets of all possible embodiments, and can be combined with each other without conflict.

[0049] If the similar description of "first\second\third" appears in the application file, the following description is added, in the following description, the term "first\second\third" referred to only distinguishes similar objects, and does not represent a specific order of the objects, and it can be understood that "first\second\third" can be interchanged with a specific order or sequence as allowed, so that the embodiments of the present application described herein can be implemented in an order other than that illustrated or described herein.

[0050] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the present application belongs. The terms used herein are only for the purpose of describing the embodiments of the present application, and are not intended to limit the present application.

[0051] Before introducing the method for determining a sensitivity matrix of an anisotropy parameter provided by the embodiment of the present application, the problems existing in the related art are briefly introduced:

[0052] Anisotropy refers to the property of a medium that is not constant but varies with direction. In seismic exploration, anisotropy mainly refers to the characteristic that the propagation speed of seismic waves in the underground medium changes with the direction of propagation. With the gradual deepening of exploration and development, oil and gas geophysical exploration types have gradually developed from conventional energy coal, oil and natural gas to unconventional energy coalbed methane, oil shale and shale gas, and the exploration area has gradually developed from inland to nearshore and even deep sea, and the exploration depth has gradually developed from middle layer to middle-deep layer. The development of the above-mentioned several types of oil and gas geophysical exploration inevitably encounters the problem of seismic anisotropy. With the increase of exploration depth, the offset of collected seismic data gradually increases, and the anisotropy phenomenon is particularly prominent. In addition, the nearshore and deep-sea sedimentary strata are mostly anisotropic. In unconventional energy, oil shale is taken as an example, which is mostly developed as continuous or discontinuous horizontal bedding structure, and the characteristic is that the thin layer is distributed in the form of sheet. These shale and oil shale with high content of sheet-shaped minerals generally have obvious anisotropy characteristics.

[0053] It can be seen that anisotropy plays an extremely important role in oil and gas exploration. In order to study the influence of anisotropy on seismic wave velocity, scholars Thomsen proposed parameters ε, δ and γ to characterize the anisotropy of the medium, wherein ε is approximately equal to the relative difference between the horizontal and vertical velocities of P wave, and its size reflects the anisotropy degree of longitudinal wave; δ represents the fast and slow degree of anisotropy change between transverse and vertical directions, and is the most important anisotropy parameter in anisotropy seismic data processing; γ represents the difference degree of fast and slow transverse wave velocity, and reflects the fracture development strength, which is a reference parameter for determining the well location of fracture type reservoir. Studies have shown that a slight change in the anisotropy of the medium will have a great influence on the reflection amplitude of seismic waves. In the aspect of anisotropy parameter inversion, Alkhalifah et al. first proposed to use P wave NMO velocity to invert the anisotropy parameters in tilted TI medium (Alkhalifah T, Tsvankin I. Velocity analysis in transversely isotropic media. Geophysics, 1995, 60(5): 1550-1566). At present, there is no mature technology to obtain anisotropy parameters representing the degree of anisotropy of the medium from seismic data.

[0054] In addition, the sensitivity matrix plays a role in searching direction in numerical optimization algorithm, and its accuracy directly affects the convergence and calculation efficiency of the inversion algorithm. The accuracy of the sensitivity matrix plays a crucial role in prestack anisotropy parameter inversion, therefore, the determination method of the anisotropy parameter sensitivity matrix directly affects the efficiency and accuracy of the prestack anisotropy parameter inversion work.

[0055] Based on the problems in the related art, the embodiment of the present application provides a method for determining an anisotropy parameter sensitivity matrix, which is applied to a device for determining an anisotropy parameter sensitivity matrix. The device for determining an anisotropy parameter sensitivity matrix can be an electronic device, such as a computer, a mobile terminal, or the like. The method for determining an anisotropy parameter sensitivity matrix provided in the embodiment of the present application can realize the functions by calling program codes of a processor of the electronic device, wherein the program codes can be stored in a computer storage medium.

[0056] Example One

[0057] The embodiment of the present application provides a method for determining an anisotropy parameter sensitivity matrix, Figure 1 The implementation flowchart of the method for determining an anisotropy parameter sensitivity matrix provided in the embodiment of the present application is shown in FIG. 1, which includes the following steps. Figure 1

[0058] In step S101, an actual pre-stack azimuth angle gather, a P-wave impedance, a S-wave impedance, a density, and an initial model of anisotropy parameters are obtained.

[0059] In the embodiment of the present application, the data information of the actual pre-stack azimuth angle gather, the P-wave impedance, the S-wave impedance, the density, and the initial model of the anisotropy parameters can be stored in a server in advance, and the device for determining an anisotropy parameter sensitivity matrix obtains the corresponding data by a communication connection with the server. In some embodiments, the device for determining an anisotropy parameter sensitivity matrix can also be connected with the data acquisition devices of the above-mentioned data to obtain the corresponding data directly from the data acquisition devices. Of course, in another embodiment, the above-mentioned data information can also be directly input into the device for determining an anisotropy parameter sensitivity matrix by the user through a reverse input method.

[0060] In step S102, a simulated pre-stack azimuth angle gather is constructed based on the initial model of the P-wave impedance, the S-wave impedance, the density, and the anisotropy parameters.

[0061] In the embodiment of the present application, for the convenience of description, the P-wave impedance can be represented as Z p , the S-wave impedance can be represented as Z s , the density can be represented as ρ, δ, ε, and γ represent the anisotropy parameters, M δ represents the initial model of the anisotropy parameter δ, M ε represents the initial model of the anisotropy parameter ε, and M γ represents the initial model of the anisotropy parameter γ, and the simulated pre-stack azimuth angle gather can be represented as In a specific embodiment, Z pj represents the P-wave impedance of the jth interface, and Z sj ​denotes the shear wave impedance of the jth interface, ρ j denotes the density of the jth interface, δ j , ε j , and γ j denote the anisotropy parameters of the jth interface, respectively, where j denotes the number of interfaces, and takes values j = 0... m, then is the simulated seismic record when the azimuth is θ and the incidence angle is is the i th sample value of the simulated seismic record , i.e.

[0062] In step S103, according to the actual pre-stack azimuth angle gather and the simulated pre-stack azimuth angle gather, an error function of a plurality of actual seismic records and simulated seismic records with a preset azimuth angle and a preset incidence angle is obtained.

[0063] In the embodiments of the present application, the actual pre-stack azimuth angle gather is composed of actual seismic records with different azimuth angles and different incidence angles, and the simulated pre-stack azimuth angle gather is composed of simulated seismic records with different azimuth angles and different incidence angles. In specific embodiments, the actual pre-stack azimuth angle gather is denoted by , and the simulated pre-stack azimuth angle gather is denoted by is the actual seismic record when the azimuth is θ and the incidence angle is is the i th sample value of the actual seismic record . Then, is the i th sample value of the error function of the actual seismic record and the simulated seismic record when the azimuth is θ and the incidence angle is , i.e. which can be expressed by the formula:

[0064]

[0065] Then, in a specific embodiment, the error function of the actual seismic record and the simulated seismic record when the azimuth is θ and the incidence angle is can be expressed by the formula:

[0066]

[0067] In step S104, based on the error function of each actual seismic record and simulated seismic record, a constraint term error function of the actual pre-stack azimuth angle gather and the simulated pre-stack azimuth angle gather is constructed.

[0068] In the embodiments of the present application, the error function of the actual seismic record and the simulated seismic record ​​​The magnitude of this value indicates the degree of matching (fit) between the simulated seismic record and the actual seismic record. Specifically, let F represent the constraint term error function between the actual and simulated pre-stack azimuth angle gathers. Then, the error function between the actual and simulated seismic records corresponding to different azimuth angles and incident angles is calculated. By summing the results and adding the prior constraint terms, we can obtain the constraint term error function F.

[0069] Step S105: Determine the anisotropic parameter sensitivity matrix based on the partial derivatives of the constraint term error function with respect to the anisotropic parameters.

[0070] In this embodiment, the constraint term error function F is the error function between the actual seismic record and the simulated seismic record. It was constructed from, and Furthermore, through actual front-angle gathers and simulated front-of-stack angle gather It is constructed from this. Therefore, taking the partial derivatives with respect to the anisotropic parameters in F is equivalent to taking the partial derivatives with respect to Z. p Z s We calculate the partial derivatives of ρ, δ, ε, and γ, and finally determine the anisotropic parameter sensitivity matrix G from these partial derivatives.

[0071] This application provides a method for determining the anisotropy parameter sensitivity matrix. It constructs a simulated pre-stack azimuth angle gather using initial models of P-wave impedance, S-wave impedance, density, and anisotropy parameters. Then, it obtains error functions for multiple actual and simulated seismic records with preset azimuth and incident angles from the simulated and actual pre-stack azimuth angle gathers. Based on these error functions, it constructs constraint term error functions for both the actual and simulated pre-stack azimuth angle gathers with prior geological constraints. Finally, it determines the anisotropy parameter sensitivity matrix based on the partial derivatives of the constraint term error functions with respect to the anisotropy parameters. This allows the obtained sensitivity matrix information to be used for pre-stack anisotropy parameter inversion work, which extracts anisotropy parameters from pre-stack seismic data. Furthermore, it improves the convergence speed and accuracy of the pre-stack anisotropy parameter inversion algorithm.

[0072] Example Two

[0073] Based on the foregoing embodiments, this application also provides a method for constructing a simulated pre-stack position angle gather based on the initial model of the longitudinal wave impedance, transverse wave impedance, density, and anisotropic parameters, such as... Figure 2 As shown, the method includes:

[0074] Step S201, a functional relationship between the P-wave reflection coefficient and the P-wave impedance, the S-wave impedance, the density and the anisotropy parameters is established.

[0075] In the embodiments of the present application, Z p represents the P-wave impedance, Z s represents the S-wave impedance, and ρ represents the density, and δ, ε and γ respectively represent the anisotropy parameters, M δ represents the initial model of the anisotropy parameter δ, M ε represents the initial model of the anisotropy parameter ε, and M γ represents the initial model of the anisotropy parameter γ. pj represents the P-wave impedance of the jth interface, Z sj represents the S-wave impedance of the jth interface, ρ j represents the density of the jth interface, δ j , ε j and γ j respectively represent the anisotropy parameters of the jth interface, where j represents the number of interfaces and takes values of j = 0...m. Let represent the actual pre-stack azimuth angle gather, and let represent the actual seismic record when the azimuth angle is θ and the incidence angle is is the ith sample value of the actual seismic record .

[0076] Let represent the P-wave reflection coefficient, then the functional relationship between the P-wave reflection coefficient and the P-wave impedance, the S-wave impedance, the density and the anisotropy parameters can be represented as:

[0077]

[0078] wherein, represents the P-wave reflection coefficient of the jth interface, and j represents the number of interfaces and takes values of j = 0...m. In the expression, ln represents taking the natural logarithm, and the coefficients c1, c2, c3, c4, c5 and c6 are shown in the expression (4) as a whole:

[0079]

[0080] In the expression (4), k is the ratio of the S-wave velocity to the P-wave velocity, specifically k = vs / vp, and k usually takes a constant value of 0.5.

[0081] In an embodiment, the expression (3) can also be simplified, specifically, as shown in the following expression (5), let:

[0082] ​

[0083] Then, expression (3) can be simplified as expression (6):

[0084] r pj =c1ΔL p +c2ΔL s +c3ΔL d +c4Δδ+c5Δε+c6Δγ (6)。

[0085] In step S202, based on the convolution theorem, the functional relationship and the seismic wavelet are used to generate the simulated pre-stack azimuth angle gather.

[0086] In the embodiments of the present application, w represents the seismic wavelet, and represents the simulated pre-stack azimuth angle gather, then is the simulated seismic record when the azimuth angle is θ and the incidence angle is is the i-th sample value of the simulated seismic record , that is can be expressed as:

[0087]

[0088] wherein m is the number of interfaces, and n is the number of samples. It should be noted that expression (7) applies the convolution formula in functional analysis, and the specific calculation process is: taking the inverse of the seismic wavelet time series w j , making w j flip 180 degrees with the vertical axis as the center, then multiplying the P-wave reflection coefficient r pj , and summing up. Wherein j is the subscript of the P-wave reflection coefficient r p , the P-wave reflection coefficient r pj has m samples, and the seismic wavelet w j has p samples. After the convolution of the m samples of the P-wave reflection coefficient r pj and the p samples of the seismic wavelet w j , the sample number n of the signal is m+p-1.

[0089] In addition, based on expression (6), expression (7) can also be expressed as:

[0090]

[0091] In one embodiment, based on expression (8), expression (2) can also be expressed as:

[0092]

[0093] ​The application provides a method for determining an anisotropy parameter sensitivity matrix, which can be used in prestack anisotropy parameter inversion work for extracting anisotropy parameters from prestack seismic data, and improves the convergence speed of an algorithm for prestack anisotropy parameter inversion work and the accuracy of an inversion result.

[0094] Example Three

[0095] Based on the foregoing embodiments, the application further provides a method for constructing a constraint term error function of actual prestack azimuth angle gathers and simulated prestack azimuth angle gathers based on an error function of actual seismic records and simulated seismic records, as shown in Figure 3 The method comprises the following steps.

[0096] In step S301, a plurality of error functions of actual seismic records corresponding to different azimuth angles and different incident angles and simulated seismic records are accumulated to obtain a matching term of simulated data and actual data.

[0097] In the application, the azimuth angle θ is set to have a first angle range, for example, the range is [P1, P2], that is, the minimum azimuth angle is P1, the maximum azimuth angle is P2, and the interval is 1 degree. In the application, the azimuth angle θ is set to have a first angle range, for example, the range is [P1, P2], that is, the minimum azimuth angle is P1, the maximum azimuth angle is P2, and the interval is 1 degree. In the application, the azimuth angle θ is set to have a first angle range, for example, the range is [P1, P2], that is, the minimum azimuth angle is P1, the maximum azimuth angle is P2, and the interval is 1 degree.

[0098] The matching term of simulated data and actual data obtained is

[0099] In step S302, a constraint term of the anisotropy parameter initial model is calculated.

[0100] In the application, the constraint term of the anisotropy parameter initial model comprises constraint terms of anisotropy parameter initial models in three different directions, and specifically, the anisotropy parameters in the three different directions can be represented by δ, ε and γ, and the initial model of the anisotropy parameter δ is represented by M δ The initial model of the anisotropy parameter ε is represented by M ε The initial model of the anisotropy parameter γ is represented by M γ .

[0101] The constraint term of the anisotropy parameter initial model is α(δ-M δ )+β(ε-M ε )+λ(γ-M γ ).

[0102] Where η, α, β, and λ are the weighting coefficients of each term in the error function, all of which are greater than 0, and η+α+β+λ=1.

[0103] Step S303: Based on the matching terms of the simulated data and the actual data, as well as the constraint terms of the initial model of the anisotropic parameters, obtain the constraint term error function of the actual pre-stack azimuth angle gather and the simulated pre-stack azimuth angle gather.

[0104] In this embodiment, the error functions of actual seismic records and simulated seismic records with different azimuth and incident angles are summed, and constraint terms of the anisotropic parameter initial model are added. The final result is the error function of the constraint terms between the actual pre-stack azimuth angle gather and the simulated pre-stack azimuth angle gather, which can be expressed as:

[0105]

[0106] This application provides a method for determining the sensitivity matrix of anisotropic parameters, which enables the obtained sensitivity matrix information to be used in pre-stack anisotropic parameter inversion work to extract anisotropic parameters from pre-stack seismic data, and improves the convergence speed of the pre-stack anisotropic parameter inversion algorithm and the accuracy of the inversion results.

[0107] Example Four

[0108] Based on the foregoing embodiments, this application also provides a method for determining the anisotropic parameter sensitivity matrix based on the partial derivatives of the constraint term error function with respect to the anisotropic parameters, such as... Figure 4 As shown, the method includes:

[0109] Step S401: Calculate the partial derivatives of the error function between the actual seismic record and the simulated seismic record under the preset azimuth angle and preset incident angle.

[0110] In this embodiment, the constraint term error function F is the error function between the actual seismic record and the simulated seismic record. It was constructed from, and Furthermore, through actual front-angle gathers and simulated front-of-stack angle gather Therefore, based on expression (10), the partial derivatives of the error functions between the actual seismic records and the simulated seismic records under the preset azimuth and preset incident angles can be calculated first.

[0111] Specifically, first calculate the given azimuth angle θ and the incident angle. hour The partial derivatives of .

[0112] For L pj Find the partial derivatives:

[0113]

[0114] L sj The partial derivative is:

[0115]

[0116] L dj The partial derivative is:

[0117]

[0118] δ j The partial derivative is:

[0119]

[0120] ε j The partial derivative is:

[0121]

[0122] γ j The partial derivative is:

[0123]

[0124] In step S402, the partial derivative of the error function of the simulated seismic record to each anisotropy parameter is obtained by superimposing the partial derivative of the error function of each actual seismic record to each anisotropy parameter.

[0125] In the embodiment, the partial derivatives of the error functions corresponding to each azimuth and incidence angle are sequentially accumulated in the order of incidence angle first and azimuth second. Since the seismic data of the pre-stack azimuth gather is stored in the order of incidence angle first and azimuth second, the accumulation order in the embodiment is based on the storage order of the actual seismic data, which is more intuitive and easy to understand. Of course, in other embodiments, the superposition can be performed in the order of azimuth first and incidence angle second.

[0126] Based on the above expressions (11)-(16), the partial derivatives of the error function of the constraint term to each anisotropy parameter are as follows:

[0127]

[0128]

[0129]

[0130]

[0131] ​

[0132]

[0133] Step S403, based on the partial derivative of the constraint term error function to the anisotropy parameter, the anisotropy parameter sensitivity matrix is obtained.

[0134] In the embodiment of the application, based on the above expression (17)-(22), the following expression of the anisotropy parameter sensitivity matrix G is obtained:

[0135]

[0136] The sensitivity matrix G of the error function obtained by the above method can be directly used for the inversion of the anisotropy parameter of the actual three-dimensional pre-stack seismic data, and the convergence speed of the inversion algorithm of the pre-stack anisotropy parameter and the accuracy of the inversion result are improved.

[0137] The application and effect of the sensitivity matrix are described below by taking the actual well seismic data of a certain area as an example.

[0138] Figure 5 (a)-(f) are actual pre-stack azimuth angle gathers, which are obtained from the well seismic data. Among them, Figure 5 (a)-(f) respectively show the cases when the azimuth angle is 0 degree, 90 degrees, 180 degrees, 210 degrees, 300 degrees and 360 degrees. The azimuth angle can be evenly valued between 0-360 degrees, and the more the azimuth angle values, the greater the calculation amount. The value of the incidence angle is 1-45 degrees, and the value range of the incidence angle is determined by the quality of the seismic data.

[0139] Figure 6 It is the actual logging data graph of a certain area, and the curves shown in the graph from left to right are the longitudinal wave impedance, the transverse wave impedance, the density, and the anisotropy parameters δ, ε and γ.

[0140] Figure 7 The left two graphs in the middle are the actual pre-stack angle gather and the simulated pre-stack angle gather when the azimuth angle is 180 degrees, and the right curve and the partial derivative curve of the error function to the longitudinal wave impedance, the transverse wave impedance, the density and the anisotropy parameter.

[0141] Figure 8The sensitivity matrixes of the longitudinal wave impedance, the transverse wave impedance, the density and the anisotropy parameter from left to right are obtained by calculating the error function of the constraint term. It can be seen from the numerical value or the amplitude value of the curve that the curve is obviously described for the target layer between 600-700 ms. The partial derivative of the error function of the constraint term with respect to the anisotropy parameter is used to determine the sensitivity matrix of the anisotropy parameter, so that the obtained sensitivity matrix information can be used for the prestack anisotropy parameter inversion work of extracting the anisotropy parameter from the prestack seismic data, and the convergence speed of the algorithm of the prestack anisotropy parameter inversion work and the accuracy of the inversion result are improved.

[0142] Example Five

[0143] Based on the foregoing embodiments, the embodiments of the present application provide a device for determining a sensitivity matrix of an anisotropy parameter, each module included in the device and each unit included in each module can be realized by a processor in a computer device; of course, it can also be realized by a specific logic circuit; in the implementation process, the processor can be a central processing unit (CPU), a microprocessor unit (MPU), a digital signal processor (DSP) or a field programmable gate array (FPGA) and the like.

[0144] The embodiments of the present application provide a device for determining a sensitivity matrix of an anisotropy parameter, Figure 9 A structural schematic diagram of the device for determining a sensitivity matrix of an anisotropy parameter provided by the embodiments of the present application is shown as Figure 9 The device 1000 for determining a sensitivity matrix of an anisotropy parameter includes:

[0145] The acquisition module 1001 is configured to acquire an actual prestack azimuth angle gather, an initial model of a longitudinal wave impedance, a transverse wave impedance, a density and an anisotropy parameter;

[0146] The first construction module 1002 is configured to construct a simulated prestack azimuth angle gather based on the initial model of the longitudinal wave impedance, the transverse wave impedance, the density and the anisotropy parameter;

[0147] The second construction module 1003 is configured to obtain an error function of a plurality of actual seismic records and simulated seismic records with a preset azimuth angle and a preset incident angle according to the actual prestack azimuth angle gather and the simulated prestack azimuth angle gather;

[0148] The third construction module 1004 is configured to construct a constraint error function of the actual pre-stack azimuth angle gather and the simulation pre-stack azimuth angle gather based on error functions of the actual seismic records and the simulation seismic records.

[0149] The determining module 1005 is configured to determine a parameter sensitivity matrix of the anisotropy parameter according to partial derivatives of the constraint error function with respect to the anisotropy parameter.

[0150] In some embodiments, the first construction module 1002 includes:

[0151] A first construction unit is configured to establish a functional relationship of a P-wave reflection coefficient with the P-wave impedance, the S-wave impedance, the density and the anisotropy parameter;

[0152] A second construction unit is configured to generate the simulation pre-stack azimuth angle gather by using the functional relationship and a seismic wavelet based on a convolution principle.

[0153] In one embodiment, the second construction module 1003 includes:

[0154] A third construction unit is configured to accumulate error functions of the actual seismic records and the simulation seismic records corresponding to different azimuth angles and different incident angles to obtain a matching item of the simulation data and the actual data.

[0155] A fourth construction unit is configured to calculate a constraint item of the initial model of the anisotropy parameter.

[0156] A fifth construction unit is configured to obtain the constraint error function of the actual pre-stack azimuth angle gather and the simulation pre-stack azimuth angle gather based on the matching item of the simulation data and the actual data and the constraint item of the initial model of the anisotropy parameter.

[0157] In some embodiments, the determining module 1005 includes:

[0158] A first determining unit is configured to calculate partial derivatives of the error functions of the actual seismic records and the simulation seismic records at a preset azimuth angle and a preset incident angle;

[0159] A second determining unit is configured to superimpose the partial derivatives of the error functions of the actual seismic records and the simulation seismic records to obtain the partial derivatives of the constraint error function with respect to the anisotropy parameter.

[0160] A third determining unit is configured to obtain the parameter sensitivity matrix of the anisotropy parameter based on the partial derivatives of the constraint error function with respect to the anisotropy parameter.

[0161] In some embodiments, the second determining unit further includes:

[0162] The second determining sub-unit is configured to superimpose each of the actual seismic records and the partial derivative of the error function of the simulated seismic record in the order of the first incident angle and the second azimuth angle.

[0163] It should be noted that, in the embodiments of the present application, if the above-mentioned equivalent matrix modulus determination method is implemented in the form of a software function module and sold or used as an independent product, it can also be stored in a computer-readable storage medium. Based on this understanding, the technical solutions of the embodiments of the present application can be embodied in the form of a software product, which is stored in a storage medium and includes a number of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the methods described in the embodiments of the present application. The aforementioned storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM), a magnetic disk or an optical disk, and various program code storage media. Thus, the embodiments of the present application are not limited to any specific hardware and software combination.

[0164] Correspondingly, the embodiments of the present application provide a storage medium having a computer program stored thereon, characterized by comprising computer program instructions, wherein when the computer program instructions are executed by a processor, the steps of the equivalent matrix modulus determination method provided in the above embodiments are implemented.

[0165] Embodiment six

[0166] The embodiments of the present application provide an anisotropy parameter sensitivity matrix determination device; Figure 10 The composition structure diagram of the anisotropy parameter sensitivity matrix determination device provided in the embodiments of the present application is shown in Figure 10 The anisotropy parameter sensitivity matrix determination device 1100 includes a processor 1101, at least one communication bus 1102, a user interface 1103, at least one external communication interface 1104, and a memory 1105. The communication bus 1102 is configured to realize the connection and communication between the components. The user interface 1103 can include a display screen, and the external communication interface 1104 can include a standard wired interface and a wireless interface. The processor 1101 is configured to execute the program of the anisotropy parameter sensitivity matrix determination method stored in the memory to realize the steps of the anisotropy parameter sensitivity matrix determination method provided in the above embodiments.

[0167] The above anisotropy parameter sensitivity matrix determination device and storage medium embodiments are similar to the description of the above method embodiments, and have similar beneficial effects to the method embodiments. For technical details not disclosed in the computer device and storage medium embodiments of the present application, please refer to the description of the method embodiments of the present application for understanding.

[0168] It should be noted that the description of the storage medium and device embodiments above is similar to the description of the method embodiments above, and has similar beneficial effects as the method embodiments. For technical details not disclosed in the storage medium and device embodiments of the present application, please refer to the description of the method embodiments of the present application for understanding.

[0169] It should be understood that the "one embodiment" or "an embodiment" mentioned throughout the specification means that the specific features, structures or characteristics related to the embodiment are included in at least one embodiment of the present application. Therefore, "in one embodiment" or "in an embodiment" appearing throughout the specification does not necessarily refer to the same embodiment. In addition, these specific features, structures or characteristics can be combined in one or more embodiments in any suitable manner. It should be understood that the size of the sequence number of the above processes in various embodiments of the present application does not mean the order of execution, and the execution order of the processes should be determined according to its function and inherent logic, and should not constitute any limitation on the implementation process of the embodiments of the present application. The sequence number of the above embodiments of the present application is only for description, not representing the advantages and disadvantages of the embodiments.

[0170] It should be noted that in this document, the terms "comprising", "containing", or any other variant thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements not only includes those elements, but also includes other elements not explicitly listed or inherent to such a process, method, article or device. Without more limitations, the element defined by the statement "including a" does not exclude the presence of additional identical elements in the process, method, article or device including the element.

[0171] In several embodiments provided by the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are only schematic. For example, the division of the units is only a logical function division, and actual implementation can have another division manner, such as: multiple units or components can be combined, or can be integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the displayed or discussed components can be through some interface, indirect coupling or communication connection between devices or units, which can be electrical, mechanical or other forms.

[0172] The units described above as separate components can or can not be physically separated, and the components displayed as units can or can not be physical units; they can be located in one place or distributed on multiple network units; some or all of the units can be selected according to actual needs to achieve the purpose of the embodiment scheme.

[0173] In addition, each of the functional units in the embodiments of the present application can be integrated into one processing unit, each unit can be separately implemented as a single unit, or two or more units can be integrated into one unit; the integrated unit can be implemented in the form of hardware, or in the form of hardware plus software function unit.

[0174] Those skilled in the art can understand that all or part of the steps of the above-mentioned method embodiments can be completed by relevant hardware instructed by programs. The aforementioned programs can be stored in a computer readable storage medium, and when the programs are executed, the steps of the method embodiments are executed. The aforementioned storage medium includes mobile storage devices, read-only memory (ROM), magnetic discs or optical discs, and various storage media that can store program codes.

[0175] Alternatively, when the integrated units of the present application are implemented in the form of software function modules and sold or used as independent products, they can also be stored in a computer readable storage medium. Based on this understanding, the technical solutions of the embodiments of the present application can be embodied in the form of software products, and the computer software products are stored in a storage medium, including a number of instructions for making a controller execute all or part of the methods described in the embodiments of the present application. The aforementioned storage medium includes mobile storage devices, ROM, magnetic discs or optical discs, and various storage media that can store program codes.

[0176] The above is only an embodiment of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art can easily think of changes or replacements within the technical scope disclosed in the present application, which should be covered in the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A method of determining an anisotropic parameter sensitivity matrix, characterized in that, The method comprises the following steps: obtaining an actual pre-stack azimuth angle gather, a longitudinal wave impedance, a transverse wave impedance, a density and an initial model of anisotropy parameters; constructing a simulated pre-stack azimuth angle gather based on the initial model of the longitudinal wave impedance, the transverse wave impedance, the density and the anisotropy parameters; obtaining an error function of a plurality of actual seismic records and simulated seismic records with a preset azimuth angle and a preset incidence angle according to the actual pre-stack azimuth angle gather and the simulated pre-stack azimuth angle gather; constructing a constraint error function of the actual pre-stack azimuth angle gather and the simulated pre-stack azimuth angle gather based on the error function of each actual seismic record and simulated seismic record; determining an anisotropy parameter sensitivity matrix according to a partial derivative of the constraint error function with respect to the anisotropy parameters.

2. The method of claim 1, wherein, The method of constructing the simulated pre-stack azimuth angle gather based on the initial model of the longitudinal wave impedance, the transverse wave impedance, the density and the anisotropy parameters comprises the following steps: establishing a functional relationship between a longitudinal wave reflection coefficient and the longitudinal wave impedance, the transverse wave impedance, the density and the anisotropy parameters; generating the simulated pre-stack azimuth angle gather by using the functional relationship and a seismic wavelet based on a convolution principle.

3. The method of claim 1, wherein, The method of constructing the constraint error function of the actual pre-stack azimuth angle gather and the simulated pre-stack azimuth angle gather based on the error function of each actual seismic record and simulated seismic record comprises the following steps: accumulating the error functions of a plurality of actual seismic records and simulated seismic records corresponding to different azimuth angles and different incidence angles to obtain a matching item of simulated data and actual data; calculating a constraint item of the initial model of the anisotropy parameters; obtaining the constraint error function of the actual pre-stack azimuth angle gather and the simulated pre-stack azimuth angle gather based on the matching item of the simulated data and the actual data and the constraint item of the initial model of the anisotropy parameters.

4. The method of claim 3, wherein, The constraint item of the initial model of the anisotropy parameters comprises constraint items of initial models of anisotropy parameters in three different directions.

5. The method of claim 1, wherein, The method of determining the anisotropy parameter sensitivity matrix according to the partial derivative of the constraint error function with respect to the anisotropy parameters comprises the following steps: calculating a partial derivative of the error function of the actual seismic record and the simulated seismic record under the preset azimuth angle and the preset incidence angle; superimposing the partial derivatives of the error functions of each actual seismic record and simulated seismic record to obtain the partial derivative of the constraint error function with respect to the anisotropy parameters; obtaining the anisotropy parameter sensitivity matrix based on the partial derivative of the constraint error function with respect to the anisotropy parameters.

6. The method of claim 5, wherein, The method of superimposing the partial derivatives of the error functions of each actual seismic record and simulated seismic record comprises the following steps: superimposing the partial derivatives of the error functions of each actual seismic record and simulated seismic record in the order of incidence angle first and azimuth angle second.

7. The method of claim 1, wherein, The preset azimuth angle has a first angle range, and the difference between adjacent azimuth angles is 1 degree; the preset incidence angle has a second angle range, and the difference between adjacent incidence angles is 1 degree.

8. An apparatus for determining an anisotropic parameter sensitivity matrix, characterized in that The method comprises the following steps: obtaining an actual pre-stack azimuth angle gather, a longitudinal wave impedance, a transverse wave impedance, a density and an initial model of anisotropy parameters; The first construction module is configured to construct a simulated prestack azimuth angle gather based on an initial model of the P-wave impedance, the S-wave impedance, the density and the anisotropy parameter; The second construction module is configured to obtain an error function of a plurality of actual seismic records and simulated seismic records with a preset azimuth angle and a preset incident angle according to the actual prestack azimuth angle gather and the simulated prestack azimuth angle gather; The third construction module is configured to construct a constraint error function of the actual prestack azimuth angle gather and the simulated prestack azimuth angle gather based on the error function of each actual seismic record and simulated seismic record; The determination module is configured to determine the anisotropy parameter sensitivity matrix according to the partial derivative of the constraint error function with respect to the anisotropy parameter.

9. An apparatus for determining an anisotropic parameter sensitivity matrix, characterized in that The memory and the processor are included, and the memory stores a computer program which is executed by the processor to perform the method for determining the anisotropy parameter sensitivity matrix according to any one of claims 1 to 7.

10. A storage medium, characterized by The computer program stored in the storage medium can be executed by one or more processors, and can be used to implement the method for determining the anisotropy parameter sensitivity matrix according to any one of claims 1 to 7.

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