CN112904426A - Decoupling elastic wave reverse time migration method, system and application - Google Patents

Abstract

The invention belongs to the technical field of exploration seismology data processing, and discloses a decoupling elastic wave reverse time migration method, a system and application, wherein an input seismic record, seismic wavelets, a density model and a velocity model are obtained; obtaining a seismic source and wave detection point continuation wave field by solving an elastic medium wave equation; elastic wave field separation is carried out by using vector Helmholtz decomposition, and separated amplitude-preserving pure longitudinal wave and transverse wave vector wave fields are obtained; calculating imaging conditions by using an elastic wave impedance sensitive kernel function to obtain high signal-to-noise ratio and high precision longitudinal wave-longitudinal wave (PP) and longitudinal wave-transverse wave (PS) imaging results; and superposing all shot integrated image results to obtain a final offset imaging section. The invention can obtain the separation result of pure longitudinal wave and pure transverse wave vector wave fields with true amplitude, improve the fidelity of imaging amplitude, automatically avoid low-frequency noise generated by cross-correlation of double-pass wave fields, improve the signal-to-noise ratio and resolution of imaging, and assist in high-precision longitudinal and transverse wave combined seismic interpretation.

Description

A decoupled elastic wave reverse time migration method, system and application

technical field

The invention belongs to the technical field of exploration seismology data processing, and in particular relates to a method, system and application of decoupling elastic wave reverse time migration.

Background technique

At present, in the multi-wave and multi-component exploration seismic data processing, elastic wave reverse time migration is the migration method with the highest imaging accuracy. However, due to the use of two-way wave information for wave field continuation, strong low-frequency noise and migration artifacts are often generated in complex areas such as salt domes, fault blocks, and thrust faults, which reduce the spatial resolution and imaging of migration results. The signal-to-noise ratio seriously affects the accuracy of subsequent seismic interpretation. In addition, traditional elastic wave imaging methods usually do not use the separation of longitudinal and transverse wave fields, but directly use the extended transverse and vertical wave field components for cross-correlation imaging, which makes the physical meaning of the imaging results ambiguous, and it is easy to cause serious longitudinal and transverse waves. crosstalk noise.

Through the above analysis, the existing problems and defects in the prior art are:

(1) The existing multi-wave and multi-component elastic wave reverse-time migration methods often generate strong low-frequency noise and noise in complex areas such as salt domes, fault blocks, and thrust faults due to the wave field continuation by solving the two-way wave equation. Migration artifacts reduce imaging resolution and signal-to-noise ratio, and seriously affect the accuracy of subsequent seismic interpretation.

(2) The traditional elastic wave imaging method usually does not separate the longitudinal and transverse wave fields, and directly uses the transverse and vertical elastic wave field components after extension to perform cross-correlation imaging, which makes the physical meaning of the imaging results unclear, and it is easy to cause serious longitudinal and transverse waves. wave crosstalk noise.

The difficulty of solving the above problems and defects is as follows:

(1) For the low-frequency noise in the elastic wave reverse time migration, the conventional processing method is to first use the elastic wave reverse time migration to obtain the imaging result with low frequency noise, and then use the post-stack Laplacian high-pass filter to filter the low-frequency noise. In addition to low-frequency noise, this processing flow is likely to cause phase distortion of the filtered imaging results and inaccurate imaging amplitudes. However, there are few researches on imaging processing methods to remove these low-frequency noises directly in wavefield continuation and applied imaging conditions.

(2) In order to reduce the crosstalk noise of longitudinal and shear waves in elastic wave imaging, it is necessary to separate the longitudinal and shear waves of the source and detection point wavefields after the extension before applying the imaging conditions. Although simple Helmholtz decomposition can be used to extract pure longitudinal waves and pure shear wave field, but also caused the phase and amplitude of the separated wave field to be inconsistent with the original wave field, resulting in inaccurate final imaging amplitude.

The significance of solving the above problems and defects is:

(1) Aiming at the problem of elastic wave reverse-time migration of low-frequency noise, the patent of the present invention will construct a brand-new impedance sensitive kernel function through the linear combination of the source and the detection point wave field, and use the sensitive kernel function to calculate the zero-delay cross-correlation The imaging conditions can be directly removed to achieve the effect of removing low-frequency noise during the imaging process. This technical method can greatly improve the imaging signal-to-noise ratio and spatial resolution of the elastic wave reverse time migration results.

(2) In addition, the present invention proposes a new true-amplitude vector wave Helmholtz wave field decomposition method. Compared with the conventional simple scalar Helmholtz decomposition, this method first obtains the auxiliary wave field by solving the Poisson equation, Then two divergence and curl operations are applied to the auxiliary wavefield to obtain the separated true amplitude vector pure longitudinal wave and pure shear wave field. This technique can significantly improve the fidelity of the elastic wave reverse time migration imaging amplitude.

SUMMARY OF THE INVENTION

Aiming at the problems existing in the prior art, the present invention provides a theoretical method, processing algorithm and technical process of decoupling elastic wave reverse time migration, and in particular relates to a solution based on vector Helmholtz decomposition and impedance-sensitive nuclear imaging conditions The theoretical method, efficient algorithm and processing flow of coupled elastic wave reverse time migration are designed to solve the problems of low frequency noise and longitudinal and shear wave crosstalk artifacts in elastic wave reverse time migration.

The present invention is realized in this way, a method for decoupling elastic wave reverse time migration, the method for decoupling elastic wave reverse time migration includes: acquiring input seismic records, seismic wavelets, density and velocity models; Wave Equation, to obtain source and receiver extension wavefields; use vector Helmholtz decomposition for wavefield separation to obtain separated true-amplitude pure longitudinal (P) waves and pure transverse (S) wave vector wavefields; use elastic The wave impedance sensitive kernel function calculates the imaging conditions, and obtains high-precision PP and PS imaging results; superimposes the imaging results of all shot sets to obtain the final migration imaging section.

Further, the method for decoupling elastic wave reverse time migration includes the following steps:

Step 1: Obtain input data; wherein, the input data includes: longitudinal wave migration velocity model v _p (x), shear wave migration velocity model v _s (x), density model ρ (x), source function wavelet f ( t), multi-wave and multi-component observation data d(x _r , t), providing model and seismic data basis for subsequent wave field continuation;

Step 2: According to the input source wavelet f(t), density model ρ(x), longitudinal wave velocity model v _p (x) and shear wave velocity model v _s (x), by solving the first-order velocity-stress elastic wave equation, Calculate the vector wavefield u _s (x,t) extended on the source side to provide the required source wavefield for subsequent wavefield separation and application of imaging conditions;

Step 3: Calculate the detection point by solving the elastic wave equation according to the input density model ρ(x), longitudinal wave velocity model v _p (x), shear wave velocity model v _s (x) and observation data d(x _r , t). The vector continuation wavefield ur (x, _t ) provides the wavefield of the detection point required for subsequent wavefield separation and application of imaging conditions;

Step 4: Use the vector Helmholtz decomposition to separate the longitudinal and shear waves of the extended source and detection point wave fields, and extract the vector pure longitudinal and pure shear wave fields. This innovative processing step can eliminate the compression and shear waves in the imaging results. crosstalk noise, improve imaging quality, and make imaging results have clear physical meaning;

Step 5: After obtaining the separated source and receiver wavefields, perform cross-correlation imaging using elastic impedance sensitive nuclear imaging conditions to obtain PP and PS imaging results. This innovative processing step can automatically remove imaging results when imaging conditions are applied. Low-frequency noise in the medium, improve the signal-to-noise ratio and resolution of imaging;

In step 6, the imaging results of all shot sets are added to obtain the final migrated imaging section, and source illumination is used to improve the balance of deep imaging amplitudes.

Further, in step 2, the form of the first-order velocity-stress elastic wave equation is:

Among them, x is the imaging space position, x _s is the source position, t is the wave field propagation time, u _s =[u _s,x u _s,y u _s,z ] ^T is the source polarization velocity wave field, σ _s =[ σ _s,xx σ _s,yy σ _s,zz σ _s,xy σ _s,xz σ _s,yz ] ^T is the source stress wave field, T is the transpose symbol, and δ is the Kronecker function. L is the partial derivative matrix, and C(x) is the parameter matrix, with the following expression:

Further, in step 3, the expression of the elastic wave equation is:

Among them, x _r is the position of the detection point, L is the partial derivative matrix, C(x) is the parameter matrix, and the expression is:

Further, in step 4, the vector Helmholtz decomposition is used to separate the longitudinal and transverse waves of the source and the detection point wave field, which has the following expression:

为梯度运算，

为散度运算，

为旋度运算，

为分离后的纵波震源波场，

为的横波震源波场，

为的纵波检波点波场，

为的横波检波点波场。w_s和w_r为辅助矢量波场，可通过求解如下泊松方程获得：in,

is the gradient operation,

is the divergence operation,

is the curl operation,

is the separated longitudinal wave source wavefield,

is the shear wave source wavefield of

is the longitudinal wave detection point wave field,

is the wavefield of the shear wave detection point. w _s and w _r are auxiliary vector wave fields, which can be obtained by solving the following Poisson equation:

where Δ is the Laplace operator.

Further, in step 5, after obtaining the separated source and receiver wavefields, cross-correlation imaging is performed using elastic impedance sensitive nuclear imaging conditions to obtain PP and PS imaging results, which have the following expressions:

为剪切模量，

为体积模量，

I为单位矩阵。in,

is the shear modulus,

is the bulk modulus,

I is the identity matrix.

Another object of the present invention is to provide a decoupled elastic wave reverse time migration system applying the decoupled elastic wave reverse time migration method, the decoupled elastic wave reverse time migration system comprising:

Input data acquisition module, used for acquiring input data; wherein, the input data includes: longitudinal wave migration velocity model v _p (x), shear wave migration velocity model v _s (x), density model ρ (x), source function Wavelet f(t), multi-wave and multi-component observation data d(x _r ,t);

The source vector continuation wave field _{calculation module} is used to solve a Order velocity-stress elastic wave equation, calculate the source vector continuation wave field u _s (x,t);

The wave field calculation module of the detection point vector continuation is used for according to the input density model ρ(x), longitudinal wave velocity model v _p (x), shear wave velocity model v _s (x) and observation data d (x _r , t), By solving the elastic wave equation, the vector continuation wave field ur (x, _t ) of the detection point is calculated;

The compression and shear wave separation module is used to separate the compression and shear waves of the source and receiver wave fields by using the vector Helmholtz decomposition;

The imaging result acquisition module is used to perform cross-correlation imaging using elastic impedance sensitive nuclear imaging conditions after obtaining the separated source and receiver wave fields to obtain PP and PS imaging results;

The migration imaging profile acquisition module is used to add the imaging results of all the shots to obtain the final migration imaging profile, and use the source illumination to improve the balance of the deep imaging amplitude.

Another object of the present invention is to provide a computer device, the computer device includes a memory and a processor, the memory stores a computer program, and when the computer program is executed by the processor, the processor executes the following step:

Obtain the input seismic records, seismic wavelets, density and velocity models; obtain the source and detection point extension wavefields by solving the elastic wave wave equation; use the vector Helmholtz decomposition to separate the wavefields to obtain the separated amplitude-preserving pure Longitudinal (P) wave and pure transverse (S) wave vector wave field; use elastic wave impedance sensitive kernel function to calculate imaging conditions to obtain high-precision PP and PS imaging results; superimpose all shot integration imaging results to obtain the final migration imaging section .

Another object of the present invention is to provide a computer-readable storage medium, which stores a computer program, and when the computer program is executed by a processor, causes the processor to perform the following steps:

Obtain the input seismic records, seismic wavelets, density and velocity models; obtain the source and detection point extension wavefields by solving the elastic wave wave equation; use the vector Helmholtz decomposition to separate the wavefields to obtain the separated amplitude-preserving pure Longitudinal (P) wave and pure transverse (S) wave vector wave field; use elastic wave impedance sensitive kernel function to calculate imaging conditions to obtain high-precision PP and PS imaging results; superimpose all shot integration imaging results to obtain the final migration imaging section .

Another object of the present invention is to provide an information data processing terminal for implementing the decoupled elastic wave reverse time migration system.

Combined with all the above technical solutions, the advantages and positive effects of the present invention are as follows: the method for decoupling elastic wave reverse time migration provided by the present invention first uses the vector Helmholtz decomposition to separate the wave fields, and obtains pure amplitude-preserving waves. Longitudinal (P) wave and pure transverse (S) wave vector wave field, and then use elastic wave impedance sensitive kernel function to calculate imaging conditions to obtain high-precision PP and PS imaging results.

Based on the solution of the present invention, after acquiring the input seismic data, source wavelet and model parameters, the extended source and detection point vector wavefields are obtained by solving the elastic wavefield equation, and then the vertical and horizontal wavefields are separated by vector Helmholtz decomposition. , obtain the P-wave and S-wave vector wave fields of the source and detection point, and finally use the imaging conditions based on the elastic impedance sensitive nucleus to perform cross-correlation imaging to obtain the final imaging result. Compared with the existing elastic wave reverse time migration imaging technology, the technical method of the present invention adopts the vector Helmholtz decomposition to obtain the separation result of the pure P wave field and the S wave field of the true amplitude, thereby avoiding the occurrence of Crosstalk noise, improve imaging quality; in addition, this technical method uses elastic impedance sensitive kernel function to calculate imaging conditions, which can well avoid background noise in reverse time migration, improve imaging resolution and signal-to-noise ratio, to assist high precision Combined seismic interpretation of longitudinal and shear waves.

Description of drawings

In order to illustrate the technical solutions of the embodiments of the present invention more clearly, the following will briefly introduce the accompanying drawings that need to be used in the embodiments of the present invention. Obviously, the drawings described below are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can also be obtained from these drawings without creative effort.

FIG. 1 is a flowchart of a method for decoupling elastic wave reverse time migration provided by an embodiment of the present invention.

FIG. 2 is a schematic diagram of a method for decoupling elastic wave reverse time migration provided by an embodiment of the present invention.

3 is a structural block diagram of a decoupled elastic wave reverse time migration system provided by an embodiment of the present invention;

In the figure: 1. Input data acquisition module; 2. Source vector continuation wavefield calculation module; 3. Receiver point vector continuation wavefield calculation module; 4. P&S wave separation module; 5. Imaging result acquisition module; Move the imaging profile acquisition module.

FIG. 4 is a schematic diagram of a longitudinal wave velocity model v _p (x) provided by an embodiment of the present invention.

FIG. 5 is a schematic diagram of a shear wave velocity model vs ( _x ) provided by an embodiment of the present invention.

FIG. 6 is a schematic diagram of a conventional elastic wave reverse time migration PP imaging result based on divergence and curl wavefield separation and conventional cross-correlation imaging conditions provided by an embodiment of the present invention.

FIG. 7 is a schematic diagram of a conventional elastic wave reverse time migration PS imaging result based on divergence and curl wavefield separation and conventional cross-correlation imaging conditions provided by an embodiment of the present invention.

FIG. 8 is a schematic diagram of an elastic wave reverse time migration PP imaging result based on vector Helmholtz decomposition and traditional cross-correlation imaging conditions provided by an embodiment of the present invention.

FIG. 9 is a schematic diagram of an elastic wave reverse time migration PS imaging result based on vector Helmholtz decomposition and traditional cross-correlation imaging conditions provided by an embodiment of the present invention.

FIG. 10 is a schematic diagram of a decoupled elastic wave reverse time migration PP imaging result based on vector Helmholtz decomposition and impedance-sensitive nuclear imaging conditions provided by an embodiment of the present invention.

11 is a schematic diagram of a PS imaging result of decoupled elastic wave reverse time migration based on vector Helmholtz decomposition and impedance-sensitive nuclear imaging conditions provided by an embodiment of the present invention.

Detailed ways

In order to make the objectives, technical solutions and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention, but not to limit the present invention.

Aiming at the problems existing in the prior art, the present invention provides a method for decoupling elastic wave reverse time migration, an efficient algorithm and a processing flow. The present invention is described in detail below with reference to the accompanying drawings.

As shown in FIG. 1 , the method for decoupling elastic wave reverse time migration provided by an embodiment of the present invention includes the following steps:

S101, acquiring input seismic records, seismic wavelets, density and velocity models;

S102, by solving the elastic wave wave equation, the continuation wave field of the source and the detection point is obtained;

S103, use vector Helmholtz decomposition to obtain separated true amplitude pure longitudinal wave and pure shear wave field;

S104, performing migration imaging using elastic impedance sensitive nuclear imaging conditions;

S105, superimpose all the imaging results of the shot set to obtain the final offset imaging section.

A schematic diagram of the method for decoupling elastic wave reverse time migration provided by the embodiment of the present invention is shown in FIG. 2 .

As shown in FIG. 3 , the decoupled elastic wave reverse time migration system provided by the embodiment of the present invention includes:

Input data acquisition module 1, for acquiring input data; wherein, the input data includes: longitudinal wave migration velocity model v _p (x), shear wave migration velocity model v _s (x), density model ρ (x), hypocenter Function wavelet f(t), multi-wave and multi-component observation data d(x _r , t), these inputs improve the model and data basis for subsequent wave field calculation and migration imaging;

The source vector continuation wave field calculation module 2 is used to adopt the point according to the input source wavelet f(t), density model ρ(x), longitudinal wave velocity model v _p (x) and shear wave velocity model v _s (x). source excitation mode, the source vector continuation wave field u _s (x, t) is calculated by solving the first-order velocity-stress elastic wave equation;

The wave field calculation module 3 of the wave field vector continuation of the detection point is used for inputting the density model ρ(x), the longitudinal wave velocity model v _p (x), the shear wave velocity model v _s (x) and the observation data d (x _r , t) , by solving the elastic wave equation, the vector continuation wave field ur (x, _t ) of the detection point is calculated;

The compression and shear wave separation module 4 adopts the vector Helmholtz decomposition to separate the compression and shear waves of the source and receiver point wave fields. This innovative technical step can obtain true amplitude pure compression waves and pure shear wave vector wave fields to ensure the amplitude validity of the imaging results. And avoid longitudinal and transverse wave crosstalk noise;

The imaging result acquisition module 5 is used to perform cross-correlation imaging using elastic impedance sensitive nuclear imaging conditions after obtaining the separated source and receiver wavefields. This innovative processing step can automatically remove low-frequency noise when the imaging conditions are applied, and obtain High signal-to-noise ratio and high resolution PP and PS imaging results;

The migration imaging profile acquisition module 6 is used for adding the imaging results of all the shot sets to obtain the final migration imaging profile, and using the source illumination to improve the balance of the deep imaging amplitude.

The technical solutions of the present invention will be further described below in conjunction with the embodiments.

Example 1

In order to solve the problem of low-frequency noise and crosstalk artifacts in elastic wave reverse time migration, the invention proposes a decoupled elastic reverse time migration imaging method based on vector Helmholtz decomposition and impedance sensitive nuclear imaging conditions. The invention first uses the vector Helmholtz decomposition to separate the wave field to obtain amplitude-preserving pure longitudinal (P) wave and pure transverse (S) wave vector wave field, and then uses the elastic wave impedance sensitive kernel function to calculate the imaging conditions to obtain high Precision PP and PS imaging results.

The decoupling elastic reverse time migration imaging method based on the impedance sensitive core of the present invention includes:

(1) Obtain input data, the input data includes: longitudinal wave migration velocity model v _p (x), shear wave migration velocity model v _s (x), density model ρ (x), source function wavelet f (t) , multi-wave multi-component observation data d(x _r ,t).

(2) According to the input source wavelet f(t), density model ρ(x), longitudinal wave velocity model v _p (x) and shear wave velocity model v _s (x), by solving the first-order velocity-stress elastic wave equation, To calculate the source vector continuation wave field u _s (x,t), the form of the first-order velocity-stress elastic wave equation is:

Where, x is the imaging space position, x _s is the source position, t is the wave field propagation time, u _s =[u _s,x u _{s,y u s,y} u _s,z ] ^T is the polarization velocity wave field, σ _s =[σ _s,xx σ _s,yy σ _s,zz σ _s,xy σ _s,xz σ _s,yz ] ^T is the stress wave field, T is the transpose symbol, and δ is the Kronecker function. L is the partial derivative matrix, and C(x) is the parameter matrix, with the following expression:

(3) According to the input density model ρ(x), longitudinal wave velocity model v _p (x), shear wave velocity model v _s (x) and observation data d (x _r ,t), calculate the detection point by solving the elastic wave equation The vector continuation wave field ur (x, _t ), the expression of the elastic wave equation is:

where x _r is the location of the detection point, and L and C(x) have the same expressions as equations (2) and (3).

(4) Use the vector Helmholtz decomposition to separate the longitudinal and shear waves of the source and receiver wave fields, the specific expression is as follows:

为梯度运算，

为散度运算，

为旋度运算，

为分离后的纵波震源波场，

为的横波震源波场，

为的纵波检波点波场，

为的横波检波点波场。w_s和w_r为辅助矢量波场，可通过求解如下的泊松方程获得：in,

is the gradient operation,

is the divergence operation,

is the curl operation,

is the separated longitudinal wave source wavefield,

is the shear wave source wavefield of

is the longitudinal wave detection point wave field,

is the wavefield of the shear wave detection point. w _s and w _r are auxiliary vector wavefields, which can be obtained by solving the following Poisson equation:

where Δ is the Laplace operator.

(5) After obtaining the separated source and receiver wavefields, perform cross-correlation imaging using elastic impedance sensitive nuclear imaging conditions to obtain PP and PS imaging results. The specific expressions are as follows:

为剪切模量，

为体积模量，

I为单位矩阵。in,

is the shear modulus,

is the bulk modulus,

I is the identity matrix.

(6) Add the imaging results of all shot sets to obtain the final migrated imaging profile, and use source illumination to improve the balance of deep imaging amplitudes.

The above-mentioned at least one technical solution adopted in the embodiment of the present invention can achieve the following beneficial effects:

Based on the solution of the present invention, after acquiring the input seismic data, source wavelet and model parameters, the extended source and detection point vector wavefields are obtained by solving the elastic wavefield equation, and then the vertical and horizontal wavefields are separated by vector Helmholtz decomposition. , obtain the P-wave and S-wave vector wave fields of the source and detection point, and finally use the imaging conditions based on the elastic impedance sensitive nucleus to perform cross-correlation imaging to obtain the final imaging result. Compared with the existing elastic wave reverse time migration imaging technology, this technical method adopts the vector Helmholtz decomposition, which can obtain the wave field separation result of preserving the amplitude, thereby avoiding the crosstalk noise in the migration profile and improving the imaging quality; , this technical method uses elastic impedance sensitive kernel function to calculate imaging conditions, which can well avoid background noise in reverse time migration, improve imaging resolution and signal-to-noise ratio, and assist high-precision compression and shear wave joint seismic interpretation.

Example 2

The description given below is the description of the actual effect of the embodiment in the model.

The method provided by the present invention is applied to the international standard Marmousi model imaging, and ideal PP and PS imaging results are obtained. The longitudinal wave velocity model (as shown in Figure 4) and the shear wave velocity model (as shown in Figure 5); the observation aperture of 3km is used, and the real velocity model is used for full-waveform forward modeling, and the observed seismic records are obtained, with a total of 103 shot collections data; input the source wavelet and the migration model to carry out the source wavefield continuation, and back-propagate the observational seismic records to obtain the wavefield continuation wavefield at the detection point, and apply the sensitive kernel function imaging conditions to obtain the imaging results (as shown in Figure 10 and Figure 11) . To compare the imaging effects, the imaging results obtained using the conventional elastic wave reverse time migration method based on curl and divergence wavefield decomposition and conventional cross-correlation imaging conditions are shown in Figures 6-7, using vector Helmholtz decomposition The imaging results obtained by the elastic wave reverse time migration method under the conventional cross-correlation imaging conditions are shown in Fig. 8-Fig. 9. Compared with the imaging results of conventional elastic wave reverse time migration (as shown in Figures 6-9), the solution in the embodiments of this specification adopts elastic wave reverse time migration based on vector Helmholtz decomposition and impedance-sensitive nuclear imaging conditions, It can automatically eliminate low-frequency noise in reverse time migration, improve imaging section resolution and signal-to-noise ratio (as shown in Figures 10 and 11), and can greatly improve the accuracy of subsequent seismic interpretation. In the foregoing schematic diagram, Distance corresponds to the abscissa x, and Depth corresponds to the ordinate z.

In the above-mentioned embodiments, it may be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented in whole or in part in the form of a computer program product, the computer program product includes one or more computer instructions. When the computer program instructions are loaded or executed on a computer, all or part of the processes or functions described in the embodiments of the present invention are generated. The computer may be a general purpose computer, special purpose computer, computer network, or other programmable device. The computer instructions may be stored in or transmitted from one computer readable storage medium to another computer readable storage medium, for example, the computer instructions may be downloaded from a website site, computer, server or data center Transmission to another website site, computer, server, or data center by wire (eg, coaxial cable, fiber optic, digital subscriber line (DSL), or wireless (eg, infrared, wireless, microwave, etc.)). The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server, a data center, or the like that includes an integration of one or more available media. The usable media may be magnetic media (eg, floppy disks, hard disks, magnetic tapes), optical media (eg, DVD), or semiconductor media (eg, Solid State Disk (SSD)), among others.

The above are only specific embodiments of the present invention, but the protection scope of the present invention is not limited to this. Any person skilled in the art is within the technical scope disclosed by the present invention, and all within the spirit and principle of the present invention Any modifications, equivalent replacements and improvements made within the scope of the present invention should be included within the protection scope of the present invention.

Claims (10)

1. A decoupling elastic wave reverse time migration method is characterized in that the elastic wave reverse time migration method of vector wave field decoupling comprises the following steps: obtaining input seismic records, seismic wavelets, density and longitudinal and transverse wave velocity models; obtaining a seismic source and wave detection point continuation wave field by solving an elastic medium wave equation; elastic wave field separation is carried out by using vector Helmholtz decomposition, and separated true-amplitude pure longitudinal (P) wave and pure transverse (S) wave vector wave fields are obtained; calculating imaging conditions by using an elastic wave impedance sensitive kernel function to obtain high-precision longitudinal wave-longitudinal wave (PP) and longitudinal wave-transverse wave (PS) imaging results; and superposing all the single-shot imaging results to obtain a final offset imaging section.

2. A decoupled elastic wave reverse time migration method according to claim 1, wherein said vector wavefield decoupled elastic wave reverse time migration method comprises the steps of:

step one, acquiring input data; wherein the input data comprises: longitudinal wave offset velocity model v_p(x) Transverse wave migration velocity model v_s(x) Density model rho (x), source function wavelet f (t), multi-wave multi-componentObserved data d (x)_r,t)；

Secondly, according to the input seismic source wavelet f (t), the density model rho (x) and the longitudinal wave velocity model v_p(x) And transverse wave velocity model v_s(x) Calculating an elastic vector wave field u extended at one side of the seismic source by solving a first-order velocity-stress elastic medium wave equation in a point source excitation mode_s(x,t)；

Thirdly, according to the input density model rho (x) and the longitudinal wave velocity model v_p(x) Transverse wave velocity model v_s(x) Using the observed data d (x)_rT) as boundary condition, calculating extended elastic vector wave field u at one side of detection point by solving elastic wave equation_r(x,t)；

Step four, performing vertical and horizontal wave field separation on the coupling elastic wave fields at the seismic source side and the wave detection point side by adopting vector Helmholtz decomposition;

step five, after the separated seismic source and wave detection point wave fields are obtained, performing zero-delay cross-correlation imaging by using elastic impedance sensitive nuclear imaging conditions to obtain PP and PS imaging results;

and step six, adding the imaging results of all shot gathers to obtain a final offset imaging section, and improving the balance of deep imaging amplitude by using seismic source illumination as a preconditioner.

3. The method for decoupling reverse time migration of an elastic wave according to claim 2, wherein in the second step, the first order velocity-stress elastic wave equation is in the form of:

where x is the imaging spatial position, x_sFor the seismic source location, t is the wavefield travel time, u_s＝[u_s,x u_s,y u_s,z]^TFor the seismic source side deflection velocity wave field, σ_s＝[σ_s,xx σ_s,yy σ_s,zz σ_s,xy σ_s,xz σ_s,yz]^TAs seismic sourceA side stress wave field, T is a transposition symbol, and delta is a kronecker function; l is a first order partial derivative matrix, C (x) is a model parameter matrix, having the following expression:

4. the method for decoupling reverse time migration of an elastic wave according to claim 2, wherein in step three, the expression of the elastic wave equation is:

wherein x is_rFor the position of the detection point, L is a partial derivative matrix, C (x) is a rigidity matrix formed by model parameters, and the specific expression is as follows:

5. the method for de-coupling elastic wave reverse time migration according to claim 2, wherein in step four, the source and demodulator point wavefields are separated by using vector Helmholtz decomposition, and the method has the following expression:

wherein,

in order to perform the gradient operation, the method comprises the following steps,

in order to calculate the divergence, the method comprises the following steps,

in order to calculate the rotation degree,

for the separated longitudinal wave source wavefield,

for the separated shear wave source wavefield,

for the separated longitudinal geophone point wavefield,

the separated transverse wave detection point wave field is obtained; w is a_sAnd w_rTo assist the vector wavefield, it can be obtained by solving the following poisson equation:

where Δ is the laplace operator.

6. The method for decoupling elastic wave reverse time migration according to claim 2, wherein in step five, after the separated source and demodulator wave fields are obtained, cross-correlation imaging is performed by using elastic impedance sensitive nuclear imaging conditions, and PP and PS imaging results are obtained, wherein the expression is as follows:

wherein,

in order to be able to obtain a shear modulus,

in order to be the bulk modulus,

and I is an identity matrix.

7. An elastic wave reverse time migration system for implementing the vector wave field decoupling elastic wave reverse time migration method according to any one of claims 1 to 6, wherein the vector wave field decoupling elastic wave reverse time migration method comprises the following steps:

the input data acquisition module is used for acquiring input data; wherein the input data comprises: longitudinal wave offset velocity model v_p(x) Transverse wave migration velocity model v_s(x) Density model rho (x), source function wavelet f (t), and multi-wave multi-component observation data d (x)_r,t)；

A seismic source vector continuation wave field calculation module for calculating the vector continuation wave field of the seismic source according to the input seismic source wavelets f (t), the density model rho (x) and the longitudinal wave velocity model v_p(x) And transverse wave velocity model v_s(x) Calculating a seismic source vector continuation wave field u by solving a first-order velocity-stress elastic wave equation in a point source excitation mode_s(x,t)；

A wave detection point vector continuation wave field calculation module for calculating the wave field according to the input density model rho (x) and the longitudinal wave velocity model v_p(x) Transverse wave velocity model v_s(x) Using the observed data d (x)_rT) as boundary condition, calculating the extended wave field u of the wave detection point vector by solving the elastic wave equation_r(x,t)；

The longitudinal and transverse wave field separation module is used for performing longitudinal and transverse wave separation on wave fields of the seismic source and the wave detection point by adopting vector Helmholtz decomposition;

the imaging result acquisition module is used for performing cross-correlation imaging by using elastic impedance sensitive nuclear imaging conditions after acquiring the separated seismic source and wave detection point wave fields to acquire PP and PS imaging results;

and the offset imaging section acquisition module is used for adding all the single-shot imaging results to obtain a final offset imaging section, and using the seismic source illumination as a preconditioner to improve the balance of the deep imaging amplitude.

8. A computer device, characterized in that the computer device comprises a memory and a processor, the memory storing a computer program which, when executed by the processor, causes the processor to carry out the steps of:

obtaining input seismic records, seismic wavelets, density and velocity models; obtaining a seismic source and wave detection point continuation wave field by solving an elastic wave fluctuation equation; performing vertical and horizontal wave field separation by using vector Helmholtz decomposition to obtain separated true-amplitude pure longitudinal (P) wave and pure transverse (S) wave vector wave fields; calculating imaging conditions by using an elastic wave impedance sensitive kernel function to obtain high-precision PP and PS imaging results; and superposing all shot integrated image results to obtain a final offset imaging section.

9. A computer-readable storage medium storing a computer program which, when executed by a processor, causes the processor to perform the steps of:

obtaining input seismic records, seismic wavelets, density and velocity models; obtaining a seismic source and wave detection point continuation wave field by solving an elastic wave fluctuation equation; performing wave field separation by using vector Helmholtz decomposition to obtain separated pure longitudinal (P) wave and pure transverse (S) wave vector wave fields with amplitude preserved; calculating imaging conditions by using an elastic wave impedance sensitive kernel function to obtain high-precision PP and PS imaging results; and superposing all shot integrated image results to obtain a final offset imaging section.

10. An information data processing terminal, characterized in that the information data processing terminal is used for implementing the decoupled elastic wave reverse time migration system according to claim 7.

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