Global space-variant scatter function calculation method and device, electronic equipment and medium

Abstract

The application discloses a global space-varying scattering function calculation method and device, electronic equipment and medium. The method can include: establishing a scattering point model; according to the velocity model and the real-time scattering point model, performing three-dimensional seismic wave field simulation on the two-way wave equation and its inverse migration equation to obtain inverse migration data; and according to the velocity model and the inverse migration data, performing reverse-time migration to obtain the global space-varying scattering function. The application performs sparse optimization sampling on the scattering point model, avoids interference of wave fields of adjacent scattering points while ensuring the density of point scattering functions, realizes efficient calculation of the global space-varying scattering function by using the calculation cost of the space-invariant scattering function, and finally provides an accurate and effective Hessian approximation operator to promote the practicalization process of the imaging domain least square reverse-time migration.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of seismic wave imaging, and more particularly to a global space-variable scattering function calculation method and device, an electronic equipment and a medium. BACKGROUND

[0002] The least squares reverse-time migration method is currently the most accurate imaging method, but the data domain least squares reverse-time migration needs to match the observed seismic data through multiple reverse migration / migration iterations in theory, so that the influence of factors such as unknown seismic wavelet, amplitude mismatch, insufficient initial model accuracy on imaging effect is very large. At the same time, in the implementation of reverse migration / migration process, a large number of three-dimensional seismic wave field forward calculation is needed, and the data converges slowly, which all lead to great problems in the actual data application.

[0003] The imaging domain least squares reverse-time migration directly obtains the least squares reverse-time migration result by estimating the Hessian inverse operator and preconditioning the reverse-time migration image. However, due to the fact that the Hessian operator is too large and seriously ill-conditioned, it cannot be stored and inverted, so a reasonable approximation is needed. Diagonal Hessian only extracts elements near the diagonal, which can effectively consider the illumination of the observation system, and is convenient for inversion and regularization, so it is widely used. However, this operator only uses a small part of the information of the Hessian, so the improvement of imaging resolution is very limited. The scattering function can accurately consider the Hessian effect of a single scattering point on the underground space. However, when using this space-invariant scattering function for imaging domain least squares migration, only the neighborhood of the scattering point can get accurate inversion. On the contrary, according to the definition of Hessian, the space-invariant scattering function of any point in the underground needs to be calculated, which needs to simulate the wave field for millions of times in three-dimensional case, which is obviously impractical and very redundant.

[0004] Therefore, it is necessary to develop a global space-variable scattering function calculation method and device based on sparse optimization, an electronic equipment and a medium.

[0005] The information disclosed in the background section of the present application is only intended to deepen the understanding of the general background of the present application, and should not be regarded as acknowledging or implying in any form that the information constitutes prior art known to those skilled in the art. SUMMARY

[0006] In view of the fact that the imaging domain least square reverse time migration technology lacks a global space variable scattering function which takes into account imaging accuracy and calculation efficiency, the present application provides a global space variable scattering function calculation method and device, electronic equipment and medium. The scattering point model is sparsely optimized and sampled, the density of the point scattering function is ensured, and interference of wave fields of adjacent scattering points is avoided, so as to realize efficient calculation of the global space variable scattering function by using the calculation cost of the space invariant scattering function, and finally provide an accurate and effective Hessian approximation operator to promote the practical process of the imaging domain least square reverse time migration.

[0007] In the first aspect, the embodiments of the present application provide a global space variable scattering function calculation method, comprising:

[0008] establishing a scattering point model;

[0009] performing three-dimensional seismic wave field simulation on a two-way wave equation and its reverse migration equation according to a velocity model and a real-time scattering point model, and obtaining reverse migration data;

[0010] performing reverse time migration according to the velocity model and the reverse migration data, and obtaining a global space variable scattering function.

[0011] Preferably, the establishment of the scattering point model comprises:

[0012] determining a sampling interval and an initial position, and then establishing the scattering point model.

[0013] Preferably, the sampling interval is determined by formula (1):

[0014]

[0015] wherein r is the sampling interval, w is the weight, v max is the maximum velocity, and f is the main frequency.

[0016] Preferably, the numerical calculation of the two-way wave equation and its reverse migration equation is realized by acoustic high-order finite difference and optimal matching layer, and the reverse migration data is obtained.

[0017] Preferably, the two-way wave equation is:

[0018]

[0019] wherein v is the velocity, p represents the seismic wave field, s represents the source function, is the Laplace operator, t is the time, and x, y and z respectively represent three spatial directions.

[0020] Preferably, the reverse migration equation is:

[0021]

[0022] wherein v is velocity, p represents seismic wave field, s represents source function, is Laplace operator, and δ is perturbation field.

[0023] As a specific implementation manner of the embodiments of the present disclosure,

[0024] In a second aspect, the embodiments of the present disclosure further provide a global space-variable scattering function calculation device, comprising:

[0025] a modeling module, which establishes a scattering point model;

[0026] a reverse migration data acquisition module, which performs three-dimensional seismic wave field simulation on a two-way wave equation and a reverse migration equation thereof according to a velocity model and a real-time scattering point model, and acquires reverse migration data;

[0027] a global space-variable scattering function acquisition module, which performs reverse time migration according to the velocity model and the reverse migration data, and acquires a global space-variable scattering function.

[0028] Preferably, the establishment of the scattering point model comprises:

[0029] determining a sampling interval and an initial position, and then establishing the scattering point model.

[0030] Preferably, the sampling interval is determined by formula (1):

[0031]

[0032] wherein r is the sampling interval, w is weight, v max is the maximum velocity, and f is the main frequency.

[0033] Preferably, numerical calculation of the two-way wave equation and the reverse migration equation thereof is realized by acoustic high-order finite difference and optimal matching layer, and the reverse migration data is acquired.

[0034] Preferably, the two-way wave equation is:

[0035]

[0036] wherein v is velocity, p represents seismic wave field, s represents source function, is Laplace operator, t is time, and x, y and z respectively represent three spatial directions.

[0037] Preferably, the reverse migration equation is:

[0038]

[0039] wherein v is velocity, p represents seismic wave field, s represents source function, for the Laplace operator, δ is a perturbation field.

[0040] In a third aspect, the embodiments of the present disclosure further provide an electronic device, which comprises:

[0041] a memory, which stores executable instructions;

[0042] a processor, which runs the executable instructions in the memory to implement the global space-variant scattering function calculation method.

[0043] In a fourth aspect, the embodiments of the present disclosure further provide a computer readable storage medium, which stores a computer program, and the computer program is executed by a processor to implement the global space-variant scattering function calculation method.

[0044] The global space-variant scattering function calculation method based on sparse optimization can reduce the calculation amount of the global space-variant scattering function to an acceptable range of actual three-dimensional seismic data processing while ensuring the approximation accuracy, solve the problem of low precision of the imaging domain least square reverse-time migration using the space-invariant scattering function, and thus promote the practicalization of the imaging domain least square reverse-time migration.

[0045] The method and apparatus have other characteristics and advantages that will be apparent from or will be elucidated with regard to the drawings and the detailed description that follows, which together form an integral part of the present disclosure and are intended to explain the principles of the application. BRIEF DESCRIPTION OF DRAWINGS

[0046] The above and other objects, features and advantages of the present application will become more apparent from the following detailed description when taken in conjunction with the accompanying drawings, in which like reference characters refer to like parts throughout the figures, and in which:

[0047] Figure 1 A flow chart showing the steps of the global space-variant scattering function calculation method according to one embodiment of the present application is shown.

[0048] Figure 2 A schematic diagram showing a recess model according to one embodiment of the present application is shown.

[0049] Figure 3 A schematic diagram showing a scattering point model designed according to one embodiment of the present application is shown. Figure 2 A schematic diagram showing a scattering point model designed according to one embodiment of the present application is shown.

[0050] Figure 4 A schematic diagram showing a scattering point model designed according to one embodiment of the present application is shown. Figure 3A schematic diagram of the de-migrated data generated by the model.

[0051] Figure 5 A schematic diagram of the global point scatter function results obtained by de-migrating the data is shown. Figure 4

[0052] Figure 6 A schematic diagram of the global space-variant point scatter function 2D results according to an embodiment of the present application is shown.

[0053] Figure 7 A schematic diagram of the 1D binning results for the data is shown. Figure 6

[0054] A schematic diagram of the sparse optimized global space-variant point scatter function 2D results according to an embodiment of the present application is shown. Figure 8

[0055] A schematic diagram of the 1D binning results for the data is shown. Figure 9 Figure 8 A block diagram of a global space-variant scatter function computing device according to an embodiment of the present application is shown.

[0056] Figure 10 BRIEF DESCRIPTION OF DRAWINGS

[0057] BRIEF DESCRIPTION OF DRAWINGS

[0058] 201, modeling module; 202, de-migrated data acquisition module; 203, global space-variant scatter function acquisition module. DETAILED DESCRIPTION

[0059] Preferred embodiments of the present application will be described in more detail below. Although the preferred embodiments of the present application are described below, it is understood that the present application can be implemented in various forms and should not be limited by the embodiments set forth herein.

[0060] The present application provides a global space-variant scatter function computing method, comprising:

[0061] establishing a scatter point model;

[0062] performing 3D seismic wave field simulation on a two-way wave equation and its de-migration equation according to the velocity model and the real-time scatter point model, and acquiring de-migrated data;

[0063] performing reverse-time migration according to the velocity model and the de-migrated data, and acquiring a global space-variant scatter function.

[0064] In one example, establishing a scatter point model comprises:

[0065] determining a sampling interval and an initial position, and then establishing a scatter point model. ​​

[0066] In one example, the sampling interval is determined by formula (1):

[0067]

[0068] Wherein, r is the sampling interval, w is the weight, generally 1.5, v max is the maximum velocity, and f is the dominant frequency.

[0069] In one example, the numerical calculation of the two-way wave equation and its reverse migration equation is realized by the high-order finite difference of acoustic wave and the best matching layer, and the reverse migration data is obtained.

[0070] In one example, the two-way wave equation is:

[0071]

[0072] Wherein, v is the velocity, p represents the seismic wave field, s represents the source function, is the Laplacian operator, t is the time, x, y and z respectively represent three directions of space.

[0073] In one example, the reverse migration equation is:

[0074]

[0075] Wherein, v is the velocity, p represents the seismic wave field, s represents the source function, is the Laplacian operator, δ is the perturbation field.

[0076] Specifically, the velocity model and the dominant frequency are read; the sampling interval and the initial position are determined by formula (1), and the initial position is generally taken as The scattering point model is established;

[0077] The three-dimensional seismic wave field simulation is carried out on the two-way wave equation and its reverse migration equation, and the reverse migration data is obtained, wherein the two-way wave equation is formula (2), and the reverse migration equation is formula (3);

[0078] The reverse time migration is carried out according to the velocity model and the reverse migration data, and the global space-varying scattering function is obtained.

[0079] The numerical calculation of the two-way wave equation and its reverse migration equation is realized by the high-order finite difference of acoustic wave and the best matching layer, and the reverse migration data d dem is obtained.

[0080] The application also provides a global space-varying scattering function calculation device, which comprises:

[0081] The modeling module establishes a scattering point model;

[0082] a reverse migration data acquisition module, which acquires reverse migration data by simulating three-dimensional seismic wave field on a two-way wave equation and a reverse migration equation thereof according to a velocity model and a real-time scattering point model;

[0083] a global space-variable scattering function acquisition module, which acquires a global space-variable scattering function by reverse time migration according to the velocity model and the reverse migration data.

[0084] In one example, establishing the scattering point model comprises:

[0085] determining a sampling interval and an initial position, and then establishing the scattering point model.

[0086] In one example, the sampling interval is determined by formula (1):

[0087]

[0088] wherein r is the sampling interval, w is a weight, generally 1.5, v is a maximum velocity, and f is a main frequency. max

[0089] In one example, the numerical calculation of the two-way wave equation and the reverse migration equation thereof is implemented by a sound wave high-order finite difference and an optimal matching layer to acquire the reverse migration data.

[0090] In one example, the two-way wave equation is:

[0091]

[0092] wherein v is a velocity, p represents a seismic wave field, s represents a source function, and is a Laplace operator, t is time, and x, y and z respectively represent three spatial directions.

[0093] In one example, the reverse migration equation is:

[0094]

[0095] wherein v is a velocity, p represents a seismic wave field, s represents a source function, and is a Laplace operator, δ is a perturbation field.

[0096] Specifically, the velocity model and the main frequency are read; the sampling interval and the initial position are determined by formula (1), and the initial position is generally taken as to establish the scattering point model;

[0097] three-dimensional seismic wave field simulation is performed on the two-way wave equation and the reverse migration equation thereof to acquire the reverse migration data, wherein the two-way wave equation is formula (2), and the reverse migration equation is formula (3).​

[0098] According to the velocity model and the reverse migration data, reverse time migration is performed to obtain the global space-varying scattering function.

[0099] The application further provides an electronic device, which comprises a memory storing executable instructions and a processor running the executable instructions in the memory to implement the global space-varying scattering function calculation method.

[0100] The application further provides a computer readable storage medium storing a computer program, which is executed by a processor to implement the global space-varying scattering function calculation method.

[0101] In order to understand the scheme and effects of the embodiments of the application, four specific application examples are given below. Those skilled in the art should understand that the examples are only for the convenience of understanding the application, and any specific details of the examples are not intended to limit the application in any way.

[0102] Example 1

[0103] Figure 1 A flow chart showing the steps of the global space-varying scattering function calculation method according to an embodiment of the application is shown.

[0104] As shown in Figure 1 , the global space-varying scattering function calculation method comprises: step 101, establishing a scattering point model; step 102, according to the velocity model and the real-time scattering point model, performing three-dimensional seismic wave field simulation on a two-way wave equation and its reverse migration equation to obtain reverse migration data; and step 103, according to the velocity model and the reverse migration data, performing reverse time migration to obtain the global space-varying scattering function.

[0105] Figure 2 A schematic diagram showing a recess model according to an embodiment of the application is shown.

[0106] Using the recess model as an example, as shown in Figure 2 , a velocity model v is read, the maximum velocity is 4000 m / s, and the main frequency f is 20 Hz.

[0107] Figure 3 A schematic diagram showing a scattering point model designed according to Figure 2 is shown.

[0108] The sampling interval r is calculated to be 300 m and the initial position b is [200 m, 200 m, 200 m], the scattering point model m is generated, and a two-dimensional cross section of the central survey line is shown as Figure 3 .

[0109] Figure 4 A schematic diagram showing the scattering point model m is shown. Figure 3A schematic diagram of the inverse offset data generated by the model.

[0110] Using velocity model Figure 2 and scattering point model Figure 3 Wavefield simulations were performed on the two-way wave equation and its inverse migration equation to obtain inverse migration data d. dem ,like Figure 4 As shown;

[0111] Figure 5 It shows the Figure 4 A schematic diagram of the global point scattering function obtained by reverse time migration of data.

[0112] Using velocity model Figure 2 and inverse offset data Figure 4 Perform reverse time migration to obtain the global space-varying scattering function, such as Figure 5 As shown.

[0113] Figure 6 A schematic diagram of a two-dimensional result of the global spatially variable point scattering function under oversampling according to an embodiment of the present invention is shown.

[0114] Figure 7 It shows as Figure 6 A schematic diagram of the one-dimensional line drawing results of the data.

[0115] Figure 8 A schematic diagram of a two-dimensional result of a sparsely optimized global spatially variable point scattering function according to an embodiment of the present invention is shown.

[0116] Figure 9 It shows as Figure 8 A schematic diagram of the one-dimensional line drawing results of the data.

[0117] Traditional single-point scattering functions can only calculate Hessian information at a specific location underground, which obviously cannot accurately reflect global velocity changes and lighting differences in the model. Conversely, if a reasonable sampling interval cannot be found, such as Figure 6 As shown, the two scattering points are too close together, causing the scattered energy to interfere with each other, as... Figure 7 As shown, this can also lead to serious errors in imaging inversion based on point scattering functions. Point scattering functions based on sparse optimization, such as... Figure 8 The diagram shows how to solve the problem of global spatial variation characteristics and avoid interference artifacts caused by excessively close point scattering functions, such as... Figure 9 As shown.

[0118] Example 2

[0119] Figure 10 A block diagram of a global space-varying scattering function calculation device according to an embodiment of the present invention is shown.

[0120] likeFigure 10 The global space-varying scattering function calculation device comprises:

[0121] The modeling module 201 establishes a scattering point model.

[0122] The reverse migration data acquisition module 202 performs three-dimensional seismic wave field simulation on the two-way wave equation and its reverse migration equation according to the velocity model and the real-time scattering point model, and acquires reverse migration data.

[0123] The global space-varying scattering function acquisition module 203 performs reverse time migration according to the velocity model and the reverse migration data, and acquires the global space-varying scattering function.

[0124] As an optional solution, the establishment of the scattering point model comprises:

[0125] The sampling interval and the initial position are determined, and then the scattering point model is established.

[0126] As an optional solution, the sampling interval is determined by formula (1):

[0127]

[0128] wherein r is the sampling interval, w is the weight, v is the maximum velocity, and f is the main frequency. max

[0129] As an optional solution, the numerical calculation of the two-way wave equation and its reverse migration equation is realized by acoustic high-order finite difference and optimal matching layer, and the reverse migration data is acquired.

[0130] As an optional solution, the two-way wave equation is:

[0131]

[0132] wherein v is the velocity, p represents the seismic wave field, s represents the source function, and Laplacian is the Laplace operator. t is the time, and x, y and z represent three spatial directions.

[0133] As an optional solution, the reverse migration equation is:

[0134]

[0135] wherein v is the velocity, p represents the seismic wave field, s represents the source function, and Laplacian is the Laplace operator. t is the time, and x, y and z represent three spatial directions. δ is the perturbation field.

[0136] Example 3

[0137] ​​The electronic device includes a memory storing executable instructions, and a processor running the executable instructions in the memory to implement the global space-varying scattering function calculation method.

[0138] The electronic device according to an embodiment of the present disclosure includes a memory and a processor.

[0139] The memory is configured to store non-transitory computer-readable instructions. Specifically, the memory can include one or more computer program products that can include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may, for example, include random access memory (RAM), cache memory, and / or the like. The non-volatile memory may, for example, include read-only memory (ROM), hard disk, flash memory, and / or the like.

[0140] The processor can be a central processing unit (CPU) or other form of processing unit having data processing and / or instruction execution capabilities, and can control other components in the electronic device to perform desired functions. In an embodiment of the present disclosure, the processor is configured to run the computer-readable instructions stored in the memory.

[0141] Those skilled in the art will understand that, in order to solve the technical problem of how to obtain a good user experience effect, the present embodiment can also include well-known structures such as a communication bus, an interface, and the like, which should also be included in the protection scope of the present disclosure.

[0142] Detailed descriptions of the present embodiment can refer to the corresponding descriptions in the foregoing embodiments, which will not be repeated here.

[0143] Example 4

[0144] The present embodiment of the present disclosure provides a computer-readable storage medium storing a computer program, which is executed by a processor to implement the global space-varying scattering function calculation method.

[0145] The computer-readable storage medium according to an embodiment of the present disclosure stores non-transitory computer-readable instructions. When the non-transitory computer-readable instructions are run by a processor, all or part of the steps of the method according to the embodiments of the present disclosure are performed.

[0146] The above computer readable storage medium includes, but is not limited to, an optical storage medium (for example, a CD-ROM and a DVD), a magneto-optical storage medium (for example, an MO), a magnetic storage medium (for example, a magnetic tape or a magnetic hard disk), a medium having a built-in rewritable nonvolatile memory (for example, a memory card), and a medium having a built-in ROM (for example, a ROM cartridge).

[0147] Those skilled in the art will understand that the above description of the embodiments of the present application is given for the purpose of exemplarily illustrating the advantageous effects of the embodiments of the present application, and is not intended to limit the embodiments of the present application to any of the examples given.

[0148] The above has described the embodiments of the present application, and the above description is exemplary, is not exhaustive, and is not limited to the disclosed embodiments. Many modifications and changes are apparent to those skilled in the art without departing from the scope and spirit of the described embodiments.

Claims

1. A method for global space-variable scattering function calculation for imaging-domain least-squares reverse-time migration, characterized in that, The method comprises: establishing a scatter point model; performing three-dimensional seismic wave field simulation on a two-way wave equation and its reverse migration equation according to a velocity model and a real-time scatter point model to obtain reverse migration data; performing reverse time migration according to the velocity model and the reverse migration data to obtain a global space-varying scatter function; wherein the establishment of the scatter point model comprises: determining a sampling interval and an initial position, and then establishing the scatter point model; wherein the sampling interval is determined by formula (1): （1） where r is the sampling interval, w is the weight, v max is the maximum velocity, and f is the fundamental frequency.

2. The method for global space-variable scattering function calculation for imaging-domain least-squares reverse time migration according to claim 1, wherein, the numerical calculation of the two-way wave equation and its reverse migration equation is realized by acoustic high-order finite difference and optimal matching layer to obtain the reverse migration data.

3. The method for global space-variable scattering function calculation for imaging-domain least-squares reverse time migration of claim 1, wherein, The two-way wave equation is: （2） where v is velocity, p representing a seismic wavefield, s representing a source function, is a Laplacian operator, t is time, and x, y, z represent three spatial directions.

4. The method for global space-variable scattering function calculation for imaging-domain least squares reverse time migration according to claim 1, wherein, The reverse migration equation is: （3） where v is the velocity, p representing the seismic wavefield, s representing the source function, is the Laplacian operator, , δ is the perturbation field, and t is time.

5. An apparatus for global space-variable scattering function computation for imaging-domain least-squares reverse-time migration, characterized in that, The method comprises: a modeling module for establishing a scatter point model; a reverse migration data obtaining module for performing three-dimensional seismic wave field simulation on a two-way wave equation and its reverse migration equation according to a velocity model and a real-time scatter point model to obtain reverse migration data; a global space-varying scatter function obtaining module for performing reverse time migration according to the velocity model and the reverse migration data to obtain a global space-varying scatter function; wherein the establishment of the scatter point model comprises: determining a sampling interval and an initial position, and then establishing the scatter point model; wherein the sampling interval is determined by formula (1): （1） where r is the sampling interval, w is the weight, v max is the maximum velocity, and f is the fundamental frequency.

6. An electronic device, comprising: The electronic device comprises: a memory storing executable instructions; a processor running the executable instructions in the memory to implement the global space-varying scatter function calculation method for imaging domain least square reverse time migration according to any one of claims 1-4.

7. A computer-readable storage medium, characterized in that, The computer readable storage medium stores a computer program which, when executed by a processor, implements the global space-varying scatter function calculation method for imaging domain least square reverse time migration according to any one of claims 1-4.

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