CN114994762A - Sparse domain seismic diffracted wave separation method - Google Patents
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Abstract
The invention relates to the technical field of seismic exploration multiple suppression, in particular to a sparse domain seismic diffracted wave separation method. And then, iterative decomposition is carried out on the diffracted wave signals by utilizing a matching tracking algorithm to obtain sparse diffracted wave signal atoms, finally, the least square technology is adopted to solve atomic coefficients of the diffracted wave signals obtained by decomposition, and separated diffracted wave data are obtained by weighted superposition of the diffracted wave signal atoms and the coefficients thereof. The method is simple, high in calculation efficiency, good in noise immunity, good in application effect on low signal-to-noise ratio data, and capable of solving the problem of separation integrity of the top point and the two wings of the diffracted wave better, and the diffracted wave signal is decomposed more thoroughly, so that the method is one of conventional processes for seismic data processing, wide in application range and high in popularization value.
Description
Technical Field
The invention relates to the technical field of seismic exploration multiple suppression, in particular to a sparse domain seismic diffracted wave separation method.
Background
With the depth of exploration and development, the significance of small-scale and high-resolution seismic imaging in high-precision seismic exploration is increasingly important. The seismic exploration focuses on researching information related to transverse inhomogeneous bodies such as faults, river channels, cracks, pinch-off points, erosion hole type reservoirs and the like, the target geologic bodies have the characteristics of small size, irregular shape, strong spatial heterogeneity and the like, and unlike reflected waves, seismic waves meet the small-size geologic bodies in the propagation process to form a secondary seismic source to generate a large number of diffracted waves, and compared with the reflected waves, the diffracted waves have obvious difference in dynamics and kinematics. Therefore, the imaging by utilizing the good diffracted waves has very important significance for the exploration of the transverse inhomogeneous body, and meanwhile, the structural development zone can be better explored to search for favorable trapping. Since the amplitude of the diffracted wave is much weaker than that of the reflected wave and is usually buried in the reflected wave information and difficult to recognize, conventional seismic processing mainly targets the primary reflected wave and usually causes some damage to diffracted waves other than the continuous reflection in the noise suppression process, and thus a separate imaging technique for diffracted waves has been developed.
Diffracted wave separation imaging can be divided into direct method and indirect method, wherein the direct method is used for directly imaging diffracted waves in the process of shifting or after shifting according to the characteristic difference between reflected waves and diffracted waves, and the indirect method is used for separating diffracted waves from a gather wave field before shifting and then performing shift imaging on the separated diffracted waves. The direct method has the characteristic of high calculation efficiency, while the migration front-track set diffracted wave separation technology mostly adopts an iterative inversion method, the data volume of wave field separation is very large, the diffracted wave separation time is very long, and the calculation efficiency is low. In addition, diffracted wave energy separated by diffracted waves of a trace set before deviation is weak, diffracted wave signals are often difficult to identify in a low signal-to-noise ratio area, and how to separate reliable weak diffracted wave signals from submerged strong reflection data is a technical difficulty of diffracted wave separation imaging.
The method for separating diffracted waves of a trace gather before offset mainly utilizes the difference of kinematics and dynamic characteristics of reflected waves and diffracted waves, and the commonly used technology mainly utilizes a singular value filtering technology utilizing the difference of amplitude energy of the reflected waves and the diffracted waves, and an inclination angle filtering technology utilizing the difference of travel time of seismic waves or a Radon transform filtering technology, which are difficult to better solve the problem of simultaneous separation of a diffracted wave vertex and two wings, and in addition, for low signal-to-noise ratio data, the effect of diffracted wave separation is influenced by noise, and the effect of diffracted wave separation is not ideal.
For example, the prior art discloses a diffracted wave separation method based on near-path flanged sparse Radon transform, which utilizes high-efficiency sparse Radon transform to perform wave field separation on a pre-stack channel set containing diffracted waves to obtain separated reflected waves and diffracted waves.
Disclosure of Invention
The invention provides a sparse domain seismic diffracted wave separation method which has high noise immunity and thorough diffracted wave signal separation, aiming at overcoming the technical problems that the diffracted wave separation technology in the prior art is influenced by noise and the diffracted wave separation effect is not ideal.
In order to solve the technical problems, the invention adopts the technical scheme that: a sparse domain seismic diffracted wave separation method, the method comprising:
the method comprises the following steps: constructing diffracted wave signals with different curvatures by using the theory that a time-distance curve of diffracted waves is a hyperbolic curve and amplitude energy and propagation distance are in inverse proportion to generate a diffracted wave signal atom library;
step two: performing iterative decomposition on the signal atoms in the diffracted wave signal atom library obtained in the step one by using a matching pursuit algorithm to obtain sparse diffracted wave signal atoms; in the matching pursuit decomposition process, each iteration adopts a least square method to solve the coefficient of sparse signal atoms;
step three: and D, performing weighted superposition on the diffracted wave signal atoms obtained in the step two and the coefficients thereof to obtain separated diffracted wave data.
The invention adopts the complete diffracted wave signal atom library to carry out diffracted wave decomposition in the sparse domain, has better noise immunity, has obvious application effect on low signal-to-noise ratio data, and can better solve the problem of separation integrity of the diffracted wave vertex and two wings.
Further, in the first step, before generating the diffracted wave signal atom library, data needs to be input and rearranged, specifically: inputting a shot gather or a common-center-point gather, and rearranging the input shot gather or the common-center-point gather according to the offset distance to obtain a common-offset-distance gather d; simultaneous input of root mean square velocity field v rms 。
Further, in the first step, after the data is input and rearranged, parameters in the diffracted wave separation process are set, including the curvature range [ sigma ] of diffracted wave signal atoms 1 ～σ 2 ]Curvature interval delta sigma, damping coefficient epsilon of least square solution, minimum acceptable correlation coefficient threshold alpha of diffracted wave signal atoms and actual data acp Maximum acceptable residual percentage ζ acp And matching and tracking the maximum iteration number N.
Further, in the first step, a diffracted wave signal Atom library Atom (σ, t) is generated 0 And x), wherein,
the time-distance curve calculation formula of the diffracted wave signal adopts a hyperbolic formula,
wherein t is 0 Is the time of the two-way reflection of the vertex of the diffracted wave, and x is the distance between the horizontal direction and the vertex of the hyperbolaI is a curvature index, i is 1, 2.
Further, in the first step, a diffracted wave signal Atom library Atom (σ, t) is generated 0 And x), wherein,
the amplitude of the diffracted wave is calculated by using the formula
Wherein A is 0 V is the seismic amplitude and the root mean square velocity at the vertex of the hyperbola, x is the distance between the horizontal direction and the vertex of the hyperbola, and a and b are undetermined coefficients related to the amplitude.
Further, in the first step, a diffracted wave signal Atom library Atom (σ, t) is generated 0 X) further comprises the following operations:
performing least square fitting according to the searched diffracted wave signals, namely | | A (x) -A real (x)||→min，A real (x) Is the amplitude value of the actual diffracted wave data.
Further, the specific operations of searching for diffracted wave signal atoms in the second step are as follows:
(I) setting input data d;
initializing residual data r 0 D, outputting diffracted wave seismic data d s 0, the searched diffracted wave Atom library Atom searched Phi, the iteration number k is 0;
circularly processing time sampling points;
circularly processing the number of seismic channels;
(II) matching and tracking circulation: k is less than or equal to N;
(III) calculating Atom library Atom (sigma, t) of diffracted wave signals 0 X) and data residual r k Correlation coefficient of (2)
(iv) calculating an index value m with the largest correlation coefficient C (σ) as argmax (C (σ) i ) 1,2,.., N, if C (σ) m )>α acp Entering the step (V), otherwise ending the matching tracking loop;
(V) diffraction to be searchedAdding wave signal atoms to the searched Atom pool, Atom searched ＝Atom searched ∪Atom(σ m ,t 0 X) while excluding from the atom pool of the next iteration,
representing a remove atom operation.
Furthermore, the coefficient for solving the sparse signal atoms in the second step is a global optimization coefficient for solving diffracted wave atoms, and the adopted equation is an overdetermined equation.
Further, the solving of the coefficients of the sparse signal atoms in the second step is specifically operated as follows:
let L be Atom searched The global optimization coefficient y of the searched diffracted wave atoms is solved by adopting a least square method searched ＝(L T L+εI) -1 L T d, T represents matrix transposition, I represents a unit diagonal matrix, epsilon represents a least square solution damping coefficient, and d represents a common offset gather.
Further, the specific operation of the third step is as follows:
reconstructing diffracted wave seismic data d s ＝Ly searched ；
Updating residual r k+1 ＝d-d s Calculating the percentage coefficient of the residual
If ζ is>ζ acp If k is k +1, then step (III) is entered, otherwise, the matching tracking loop is ended;
after the matching tracking cycle is finished;
finishing the seismic channel number cycle processing;
finishing the time sampling point cycle processing;
outputting diffracted wave seismic data d s 。
Compared with the prior art, the invention has the beneficial effects that:
1) according to the invention, the complete diffracted wave signal atom library is adopted to carry out diffracted wave decomposition in a sparse domain, so that the noise immunity is very good, the application effect on low signal-to-noise ratio data is obvious, and the problem of the separation integrity of the top point and the two wings of the diffracted wave can be better solved;
2) compared with the traditional matching pursuit technology, the method adopts iterative matching pursuit to solve the coefficient of the diffracted wave signal atoms, and diffracted wave signals are decomposed more thoroughly;
3) the method is simple in overall method and high in calculation efficiency, is used as one of conventional processes for seismic data processing, is wide in application range, and is worthy of popularization and application.
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FIG. 1 is a flow chart of the sparse domain seismic diffracted wave separation method of the present invention;
FIG. 2 is a detailed flow chart of the sparse domain seismic diffracted wave separation method of the present invention;
FIG. 3 is a graph of the effect of the noise-free data separation of the sparse domain seismic diffracted wave separation method of the present invention;
FIG. 4 is a diagram of the separation effect of the sparse domain seismic diffracted wave separation method when the signal-to-noise ratio of the diffracted wave signals to noise is-6 db;
FIG. 5 is a diagram of the effect of the sparse domain seismic diffracted wave separation method of the present invention when the signal-to-noise ratio of the diffracted wave signal to noise is-20 db.
Detailed Description
The drawings are for illustrative purposes only and are not to be construed as limiting the patent; for the purpose of better illustrating the embodiments, certain features of the drawings may be omitted, enlarged or reduced, and do not represent the size of an actual product; it will be understood by those skilled in the art that certain well-known structures in the drawings and descriptions thereof may be omitted. The positional relationships depicted in the drawings are for illustrative purposes only and are not to be construed as limiting the present patent.
The same or similar reference numerals in the drawings of the embodiments of the present invention correspond to the same or similar components; in the description of the present invention, it should be understood that if there are terms such as "upper", "lower", "left", "right", "long", "short", etc., indicating orientations or positional relationships based on the orientations or positional relationships shown in the drawings, it is only for convenience of description and simplicity of description, but does not indicate or imply that the device or element referred to must have a specific orientation, be constructed in a specific orientation, and be operated, and therefore, the terms describing the positional relationships in the drawings are only used for illustrative purposes and are not to be construed as limitations of the present patent, and specific meanings of the terms may be understood by those skilled in the art according to specific situations.
The technical scheme of the invention is further described in detail by the following specific embodiments in combination with the attached drawings:
example 1
As shown in fig. 1-2, a sparse domain seismic diffracted wave separation method includes:
the method comprises the following steps: constructing diffracted wave signals with different curvatures by using the theory that a time-distance curve of diffracted waves is a hyperbolic curve and amplitude energy and propagation distance are in inverse proportion to generate a diffracted wave signal atom library;
step two: performing iterative decomposition on searching signal atoms in the diffracted wave signal atom library obtained in the step one by using a matching pursuit algorithm to obtain sparse diffracted wave signal atoms; in the matching pursuit decomposition process, each iteration adopts a least square method to solve the coefficient of sparse signal atoms;
step three: and D, performing weighted superposition on the diffracted wave signal atoms obtained in the step two and the coefficients thereof to obtain separated diffracted wave data.
The specific operation of the first step is as follows: input data and data rearrangement: rearranging the input shot gathers or common-center gather according to the offset distance to obtain a common-offset gather d, wherein the shot gathers and the common-center gather are all the prior professional names and are not repeated herein; simultaneous input of root mean square velocity field v rms (ii) a The main purpose of data rearrangement is to fully utilize good hyperbolic characteristic of the diffracted wave signals in a common offset range, so that matching, tracking and decomposition are conveniently carried out by utilizing a hyperbolic diffracted wave signal atom library, and a root mean square velocity field is used for amplitude fitting of a subsequent diffracted wave signal atom library;
setting parameters in the diffracted wave separation process: curvature range [ sigma ] of diffracted wave signal atom 1 ～σ 2 ]Curvature interval delta sigma, damping coefficient epsilon of least square solution, minimum acceptable correlation coefficient threshold alpha of diffracted wave signal atoms and actual data acp Maximum acceptable residual percentage ζ acp Because of being influenced by the absolute magnitude of the amplitude, the residual error definition of the invention adopts relative percentage with wider adaptability to measure the magnitude of the residual error energy, and the maximum iteration number N of matching pursuit is realized;
generating a diffracted wave signal Atom library Atom (sigma, t) 0 X), each atom in the atomic library of diffracted wave signals consists of a hyperbolic travel time and corresponding amplitude, and only has a value at the position of the hyperbolic curve, wherein the calculation formula of the time distance curve of the diffracted wave signals adopts a hyperbolic formula,
wherein t is 0 The two-pass reflection time of the vertex of the diffracted wave is shown, x is the distance between the horizontal direction and the vertex of the hyperbola, i is a curvature index, and i is 1, 2. Because the energy of diffracted wave signals is obviously attenuated along with the increase of the transverse distance from a diffracted point, the transverse change of amplitude is generally not considered in the traditional diffracted wave separation technology based on hyperbolic Radon transformation, and the diffracted wave energy separation has a certain degree of residue
Wherein A is 0 V is the seismic amplitude and the root mean square velocity at the vertex of the hyperbolic curve respectively, a and b are coefficients to be determined related to the amplitude, and least square fitting is carried out according to the searched diffracted wave signals, namely: | A (x) -A real (x)||→min，A real (x) The amplitude value of the actual diffracted wave data is obtained;
the specific operation of searching the diffracted wave signal atoms in the second step is as follows:
(I) setting initial parameters:
initializing residual data r 0 D, output data d s 0, the searched diffracted wave Atom library Atom searched Phi, the iteration number k is 0;
circularly processing time sampling points;
circularly processing the number of seismic channels;
(II) matching and tracking circulation: k is less than or equal to N;
(III) calculating a diffracted wave signal Atom library Atom (sigma, t) 0 X) and data residual r k Correlation coefficient of
(iv) calculating an index value m with the largest correlation coefficient as argmax (C (σ) i ) 1,2,.., N, if C (σ) m )>α acp Entering the step (V), otherwise ending the matching tracking loop;
(V) adding the searched diffracted wave signal atoms into the searched Atom library, Atom searched ＝Atom searched ∪Atom(σ m ,t 0 X) while excluding from the atom pool of the next iteration,
representing a remove atom operation, each atom is not utilized by repeated searches.
The specific operation of solving the coefficients of the sparse signal atoms in the second step is as follows:
let L be Atom searched For sparse diffracted wave atoms, the sampling points of diffracted wave data are far larger than the number of the diffracted wave atoms, so that an equation for solving the global optimization coefficient of the diffracted wave atoms is an overdetermined equation, and the solution of the global optimization coefficient of the searched diffracted wave atoms is obtained by adopting a least square method and expressed as follows: y is searched ＝(L T L+εI) -1 L T d, T represents matrix transposition, I represents unit diagonal matrix, epsilon represents least square solving damping coefficient, d represents common deviationShifting a distance gather;
the third step comprises the following specific operations:
reconstructing diffracted wave seismic data d s ＝Ly searched ；
Updating residual r k+1 ＝d-d s Calculating the percentage coefficient of the residual
If ζ>ζ acp If k is k +1, then step (III) is entered, otherwise, the matching tracking loop is ended;
the matching pursuit cycle ends;
finishing the seismic channel number cycle processing;
the time sample point loop processing ends.
Output diffracted wave seismic data d s 。
The diffraction wave signal decomposition method adopts the complete diffraction wave signal atom library to carry out diffraction wave decomposition in a sparse domain, has better noise immunity, has a remarkable application effect on low signal-to-noise ratio data, and can better solve the problem of the separation integrity of the top point and the two wings of the diffraction wave, so that the diffraction wave signal separation is more complete. The method is simple in overall method and high in calculation efficiency, is used as one of conventional processes for seismic data processing, is wide in application range, and is worthy of application and popularization.
The superiority of the method of the invention is illustrated by the following specific data tests, which are carried out in the following specific operations: the test data of the invention adopts synthetic seismic data, the track pitch of the data is 12.5m, the data comprises 8 groups of diffraction waves with certain adjacent pitches, and the variation of the diffraction pitches is 12.5m, 25m, 37.5m, 50m, 62.5m, 75m, 87.5m and 100m respectively. The reflection coefficient at the vertex of the left diffracted wave is 0.0023, the reflection coefficient at the vertex of the right diffracted wave is 0.0028, and the data further comprises an upper horizontal layered interface and a lower horizontal layered interface, wherein the reflection coefficients of the upper horizontal layered interface and the lower horizontal layered interface are 0.01 and 0.012 respectively.
In order to test the diffracted wave separation effect of the present invention, the present example was tested using noiseless data. The test result comprises four subgraphs (A), (B), (C) and (D), and the data are respectively as follows: the graph (a) is an input data graph, the graph (B) is a separated diffracted wave data graph, the graph (C) is a graph of data other than diffracted waves, and the graph (D) is a difference graph between a separated diffracted wave and a real diffracted wave.
As can be seen from FIG. 3, the reflected wave signal is completely separated from the diffracted wave signal, the separated diffracted wave signal is complete and thorough, and the difference from the real diffracted wave signal is very small and difficult to be identified by naked eyes.
Example 2
The embodiment is an embodiment 2 of a sparse domain seismic diffracted wave separation method, and the difference between the embodiment and the embodiment 1 is as follows: in this embodiment, the test data is synthetic seismic data, the track pitch of the data is 12.5m, the data includes 8 groups of diffracted waves with a certain adjacent pitch, and the variation of the diffracted pitch is 12.5m, 25m, 37.5m, 50m, 62.5m, 75m, 87.5m, and 100m, respectively. The reflection coefficient at the vertex of the left diffracted wave is 0.0023, the reflection coefficient at the vertex of the right diffracted wave is 0.0028, and the data also comprises an upper horizontal layered interface and a lower horizontal layered interface, wherein the reflection coefficients are 0.01 and 0.012 respectively.
In order to test the diffracted wave separation effect of the present invention, the present embodiment uses data with respective snr of 12db for testing. The test result comprises four subgraphs (A), (B), (C) and (D), and the data are respectively as follows: the graph (a) is an input data graph, the graph (B) is a separated diffracted wave data graph, the graph (C) is a graph of data other than diffracted waves, and the graph (D) is a difference graph between a separated diffracted wave and a real diffracted wave.
As can be seen from fig. 4, since the amplitude values of the diffracted waves gradually attenuate as the distance increases, the diffracted wave signals become difficult to identify with respect to the peaks of the diffracted waves, and if separation is performed based on the slope, the diffracted wave signals tend to be difficult to separate well because the signal-to-noise ratio is low. The diffracted wave signal separation of the method of the present invention is still complete, and the difference between the diffracted wave separated from the actual diffracted wave in fig. 4(D) can be seen, and the difference between the diffracted wave and the actual diffracted wave is only slightly different.
Example 3
The embodiment is an embodiment 3 of a sparse domain seismic diffracted wave separation method, and is different from the embodiment 1 in that: in this embodiment, the test data is synthetic seismic data, the track pitch of the data is 12.5m, the data includes 8 groups of diffracted waves with a certain adjacent pitch, and the variation of the diffracted pitch is 12.5m, 25m, 37.5m, 50m, 62.5m, 75m, 87.5m, and 100m, respectively. The reflection coefficient at the vertex of the left diffracted wave is 0.0023, the reflection coefficient at the vertex of the right diffracted wave is 0.0028, and the data further comprises an upper horizontal layered interface and a lower horizontal layered interface, wherein the reflection coefficients of the upper horizontal layered interface and the lower horizontal layered interface are 0.01 and 0.012 respectively.
In order to test the diffracted wave separation effect of the present invention, the present example uses data with signal-to-noise ratios of 6db respectively for testing. The test result comprises four subgraphs (A), (B), (C) and (D), and the data are respectively as follows: the graph (a) is an input data graph, the graph (B) is a separated diffracted wave data graph, the graph (C) is a graph of data other than diffracted waves, and the graph (D) is a difference graph between a separated diffracted wave and a real diffracted wave.
As can be seen from fig. 5, since the noise energy is further strengthened, the signals of both wings of the diffracted wave are not recognizable, and only near the vertex of the diffracted wave, a clear diffracted wave signal can be seen, and from the separation result, the diffracted wave separation effect is still ideal, and although the difference between the real diffracted wave and the separated diffracted wave is strengthened, the energy value is still weak compared with the real diffracted wave energy.
It should be understood that the above-described embodiments of the present invention are merely examples for clearly illustrating the present invention, and are not intended to limit the embodiments of the present invention. Other variations and modifications will be apparent to persons skilled in the art in light of the above description. And are neither required nor exhaustive of all embodiments. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present invention should be included in the protection scope of the claims of the present invention.
Claims (10)
1. A sparse domain seismic diffracted wave separation method is characterized by comprising the following steps:
the method comprises the following steps: constructing diffracted wave signals with different curvatures by using the theory that a time-distance curve of diffracted waves is a hyperbolic curve and amplitude energy and propagation distance are in inverse proportion to generate a diffracted wave signal atom library;
step two: performing iterative decomposition on searching signal atoms in the diffracted wave signal atom library obtained in the step one by using a matching pursuit algorithm to obtain sparse diffracted wave signal atoms; in the matching pursuit decomposition process, each iteration adopts a least square method to solve the coefficient of sparse signal atoms;
step three: and D, performing weighted superposition on the diffracted wave signal atoms obtained in the step two and the coefficients thereof to obtain separated diffracted wave data.
2. The sparse-domain seismic diffracted wave separation method of claim 1, wherein: in the first step, before generating the diffracted wave signal atom library, data needs to be input and rearranged, specifically: inputting a shot gather or a common-center-point gather, and rearranging the input shot gather or the common-center-point gather according to the offset distance to obtain a common-offset-distance gather d; simultaneous input of root mean square velocity field v rms 。
3. The sparse domain seismic diffracted wave separation method of claim 2, wherein: in the first step, after data is input and rearranged, parameters in the diffracted wave separation process are set, including the curvature range [ sigma ] of diffracted wave signal atoms 1 ～σ 2 ]Curvature interval delta sigma, damping coefficient epsilon of least square solution, minimum acceptable correlation coefficient threshold alpha of diffracted wave signal atoms and actual data acp Maximum acceptable residual percentage ζ acp The maximum number of iterations N is matched and tracked.
4. A sparse domain seismic diffracted wave separation method as claimed in claim 3, wherein: generating a diffracted wave signal Atom library Atom (sigma, t) in the first step 0 And x), wherein,
the time-distance curve calculation formula of the diffracted wave signal adopts a hyperbolic formula,
wherein t is 0 For the two-way reflection time of the vertex of the diffracted wave, x is the distance from the horizontal to the vertex of the hyperbola, i is the curvature index, and i is 1, 2.
5. The sparse-domain seismic diffracted wave separation method of claim 4, wherein: generating a diffracted wave signal Atom library Atom (sigma, t) in the first step 0 And x), wherein,
the amplitude of the diffracted wave is calculated by using the formula
Wherein A is 0 V is the seismic amplitude and the root mean square velocity at the vertex of the hyperbola, x is the distance between the horizontal direction and the vertex of the hyperbola, and a and b are undetermined coefficients related to the amplitude.
6. The sparse-domain seismic diffracted wave separation method of claim 5, wherein: generating a diffracted wave signal Atom library Atom (sigma, t) in the first step 0 X) further comprises the following operations:
performing least square fitting according to the searched diffracted wave signals, namely | | A (x) -A real (x)||→min，A real (x) Is the amplitude value of the actual diffracted wave data.
7. The sparse-domain seismic diffracted wave separation method of claim 1, wherein: the specific operations of searching for diffracted wave signal atoms in the second step are as follows:
(I) setting initial parameters:
initializing residual data r 0 D, outputting diffracted wave seismic data d s 0, the searched diffracted wave Atom library Atom searched Phi, the iteration number k is 0;
circularly processing time sampling points;
circularly processing the number of seismic channels;
(II) matching and tracking circulation: k is less than or equal to N;
(III) calculating Atom library Atom (sigma, t) of diffracted wave signals 0 X) and data residual r k Correlation coefficient of
(iv) calculating an index value m with the largest correlation coefficient C (σ) as argmax (C (σ) i ) 1,2,.., N, if C (σ) m )>α acp If not, ending the matching tracking cycle;
(V) adding the searched diffracted wave signal atoms into the searched Atom library, Atom searched ＝Atom searched ∪Atom(σ m ,t 0 X) while excluding from the atom pool of the next iteration,
representing a remove atom operation.
8. The sparse-domain seismic diffracted wave separation method of claim 7, wherein: and in the second step, the coefficient for solving the sparse signal atoms is a global optimization coefficient for solving diffracted wave atoms, and the adopted equation is an overdetermined equation.
9. The sparse-domain seismic diffracted wave separation method of claim 8, wherein: the second step of solving the coefficients of the sparse signal atoms is specifically operated as follows:
let L be Atom searched The global optimization coefficient y of the searched diffracted wave atoms is solved by adopting a least square method searched ＝(L T L+εI) -1 L T d, T denotes a matrix transpose, I denotes a unitAnd (3) a diagonal matrix, wherein epsilon represents a least square solution damping coefficient, and d represents a common offset gather.
10. The sparse-domain seismic diffracted wave separation method of claim 9, wherein: the third step comprises the following specific operations:
reconstructing diffracted wave seismic data d s ＝Ly searched ；
Updating residual r k+1 ＝d-d s Calculating the percentage coefficient of the residual
If ζ>ζ acp If k is k +1, then step (III) is entered, otherwise, the matching tracking loop is ended;
the matching pursuit cycle ends;
finishing the seismic channel number cycle processing;
finishing the time sampling point cycle processing;
output diffracted wave seismic data d s 。
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