CN109471172B - Surface wave purification method and device based on same-phase axis morphological difference - Google Patents
Surface wave purification method and device based on same-phase axis morphological difference Download PDFInfo
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- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
- G01V1/28—Processing seismic data, e.g. analysis, for interpretation, for correction
- G01V1/32—Transforming one recording into another or one representation into another
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- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
- G01V1/28—Processing seismic data, e.g. analysis, for interpretation, for correction
- G01V1/36—Effecting static or dynamic corrections on records, e.g. correcting spread; Correlating seismic signals; Eliminating effects of unwanted energy
- G01V1/362—Effecting static or dynamic corrections; Stacking
Abstract
The invention provides a surface wave purification method and device based on the morphological difference of the same phase axis, and relates to the technical field of seismic data processing. By means of the reflected waveData yrCarrying out initialization; according to the original seismic data y and the reflected wave data yrObtaining sparse representation coefficient of the surface wave in the frequency domain high resolution LRT transform domain, and reconstructing the surface wave data yg(ii) a According to the original seismic data y and the reconstructed surface wave data ygObtaining sparse representation coefficient of the reflected wave in time domain high resolution HRT transform domain, and reconstructing reflected wave data yr(ii) a And iterating the reconstruction calculation step to solve the sparse optimization problem under the MCA framework and obtain a surface wave purification result. By carrying out multiple times of transformation and reconstruction on the surface wave and the reflected wave, when the frequency and the visual speed of the surface wave and the reflected wave are close, the surface wave can still be effectively extracted, the interference of the reflected wave on a frequency dispersion energy spectrum of the surface wave is reduced, and high-precision surface wave data are provided for frequency dispersion analysis.
Description
Technical Field
The invention relates to the technical field of seismic data processing, in particular to a surface wave purification method and device based on the morphological difference of the same phase axis.
Background
The surface wave detection reflects the change of a shallow transverse wave velocity structure by virtue of the characteristics of small attenuation, high signal-to-noise ratio and nondestructive detection, and the frequency dispersion characteristic of the surface wave detection is widely applied to the aspects of surface geological structure detection, engineering detection and the like. In order to accurately extract the surface wave dispersion curve, wave fields are separated by a signal processing method according to the characteristic difference of surface waves and interference waves, and different from a method for suppressing the surface waves in reflected wave exploration, the surface wave dispersion information cannot be influenced before and after the surface wave exploration is required to be processed. The existing surface wave purification method is only based on some mathematical transformation to carry out wave field separation in a transformation domain, but because the representation coefficients of the surface waves and the interference waves in the transformation domain are not sparse enough, the wave field separation effect is poor, and the like.
Disclosure of Invention
In view of the above, the present invention provides a method and an apparatus for surface wave purification based on the morphological difference of the same phase axis, so as to improve the above-mentioned problems.
The technical scheme adopted by the invention is as follows:
the embodiment of the invention provides a surface wave purification method based on the morphological difference of the same phase axis, which comprises the following steps,
s10: for seismic reflection wave data yrCarrying out initialization;
s20: according to the original seismic data y and the reflected wave data yrObtaining sparse representation coefficient of the surface wave in the frequency domain high resolution LRT transform domain, and reconstructing the surface wave data ygThe method comprises the following steps:
based on the original seismic data y and the reflected wave data yrCalculating to obtain first residual error data delta y1Wherein, Δ y1＝y-yr；
For the first residual data Δ y1Performing frequency domain high resolution LRT transform to obtain a first transform coefficient zg；
For the obtained first transform coefficient zgUsing a first threshold value sigmagCarrying out hard threshold processing to obtain a sparse representation coefficient z of the surface wave in a frequency domain high-resolution LRT (linear LRT transform) domaing'；
Sparse representation coefficient z of surface waveg' inverse LRT transform in frequency domain to reconstruct surface wave data yg；
S30: according to the original seismic data y and the reconstructed surface wave data ygObtaining sparse representation coefficient of the reflected wave in time domain high resolution HRT transform domain, and reconstructing reflected wave data yr；
And (5) iteratively performing the step S20 and the step S30 to obtain a surface wave purification result.
Further, the method is based on the original seismic data y and the reconstructed surface wave data ygObtaining sparse representation coefficient of the reflected wave in time domain high resolution HRT transform domain, and reconstructing reflected wave data yrComprises the following steps:
according to the original seismic data y and the reconstructed surface wave data ygCalculating to obtain second residual error data delta y2Wherein Δ y2＝y-yg；
For second residual data Δ y2Performing time domain high resolution HRT transformation to obtain a second transformation coefficient zr；
For the obtained second transform coefficient zrUsing a second threshold value sigmarThe reflected wave is obtained by performing hard threshold processingSparse representation coefficient z of time domain high resolution HRT transform domainr'；
Sparse representation of coefficient z for reflected wavesr' time domain inverse HRT transform is carried out to reconstruct reflected wave data yr。
Further, a loop variable K is set, the initial value K of the loop variable K is 0, and before the step S20, the method further includes:
let the loop variable k be k + 1.
Further, during each iteration, the first threshold σ is updatedgSecond threshold value σrThe values of (a) specifically include:
Further, the pair of seismic reflection wave data yrThe initialization includes:
setting the initial value of the reflected wave data as yr＝0；
Further, the step of iteratively performing the steps S20 and S30 to obtain the surface wave purification result includes:
when the loop variable K is less than or equal to the iteration number K, the steps S20 to S30 are repeatedly performed to obtain a surface wave purification result.
Further, the method further comprises:
and when the loop variable K is greater than the iteration times K, stopping iteration and outputting the surface wave purified data.
Further, on the wavelet data ygReflected wave data yrBefore performing initialization, the method further comprises:
raw seismic data y is acquired.
The invention also provides a surface wave purification device based on the same phase axis morphological difference, which is characterized in that the device is used for executing the surface wave purification method based on the same phase axis morphological difference, and the device comprises:
an initialization unit for initializing the reflected wave data yrCarrying out initialization;
a first reconstruction unit for reconstructing seismic data y from the original seismic data y and the reflected wave data yrObtaining sparse representation coefficient of the surface wave in the frequency domain high resolution LRT transform domain, and reconstructing the surface wave data yg；
A second reconstruction unit for reconstructing the surface wave data y from the original seismic data ygObtaining sparse representation coefficient of the reflected wave in time domain high resolution HRT transform domain, and reconstructing reflected wave data yr；
The first reconstruction unit and the second reconstruction unit are further used for carrying out repeated iterative reconstruction for multiple times to obtain a surface wave purification result.
Compared with the prior art, the invention has the following beneficial effects:
the invention provides a surface wave purification method and device based on the same-phase axis morphological difference, which are used for purifying reflected wave data yrCarrying out initialization; according to the original seismic data y and the reflected wave data yrObtaining sparse representation coefficient of the surface wave in the frequency domain high resolution LRT transform domain, and reconstructing the surface wave data yg(ii) a According to the original seismic data y and the reconstructed surface wave data ygObtaining sparse representation coefficient of the reflected wave in time domain high resolution HRT transform domain, and reconstructing reflected wave data yr(ii) a And iterating the reconstruction calculation step to solve the sparse optimization problem under the MCA framework and obtain a surface wave purification result. By carrying out multiple times of transformation and reconstruction on the surface wave and the reflected wave, when the frequency and the visual speed of the surface wave and the reflected wave are close, the surface wave can still be effectively extracted, the interference of the reflected wave on a frequency dispersion energy spectrum of the surface wave is reduced, and high-precision surface wave data are provided for frequency dispersion analysis.
In order to make the aforementioned and other objects, features and advantages of the present invention comprehensible, preferred embodiments accompanied with figures are described in detail below.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are required to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained according to the drawings without inventive efforts.
FIG. 1 shows a schematic diagram of a seismic data computing device provided by the present invention.
FIG. 2 shows a flow chart of a surface wave purification method based on the morphological differences of the same phase axes.
Fig. 3 shows a flow chart of sub-steps of step S20 in fig. 2.
Fig. 4 shows a flow chart of sub-steps of step S30 in fig. 2.
FIG. 5 is a schematic diagram of functional modules of a surface wave refining device based on the morphological differences of the same phase axes.
Icon: 100-a seismic data computing device; 101-a memory; 102-a memory controller; 103-a processor; 104-peripheral interfaces; 105-a display unit; 106-input-output unit; 200-a surface wave purification device based on the morphological difference of the same phase axis; 210-an obtaining unit; 220-an initialization unit; 230-a first reconstruction unit; 240-a second reconstruction unit; 250-a judgment unit; 260-output unit.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. The components of embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the present invention, presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the present invention without making any creative effort, shall fall within the protection scope of the present invention.
It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures.
In the description of the present invention, it should also be noted that relational terms such as first and second, and the like, may be used solely herein to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. The terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element. The specific meanings of the above terms in the present invention can be understood in specific cases to those skilled in the art.
Some embodiments of the invention are described in detail below with reference to the accompanying drawings. The embodiments described below and the features of the embodiments can be combined with each other without conflict.
FIG. 1 shows a block schematic diagram of a seismic data computing device 100 provided by a preferred embodiment of the present invention. The seismic data computing device 100 may be a desktop computer, a laptop computer, a tablet computer, a smart phone, a Personal Digital Assistant (PDA), or the like. The seismic data computing equipment 100 comprises a surface wave refining device 200 based on the morphological difference of the same phase axis, a memory 101, a storage controller 102, a processor 103, a peripheral interface 104, a display unit 105 and an input/output unit 106.
The memory 101, the memory controller 102, the processor 103, the peripheral interface 104, the display unit 105, and the input/output unit 106 are electrically connected to each other directly or indirectly to implement data transmission or interaction. For example, the components may be electrically connected to each other via one or more communication buses or signal lines. The surface wave refining apparatus 200 based on the morphological difference of the same phase axis includes at least one software function module which can be stored in the memory 101 in the form of software or firmware (firmware) or solidified in an Operating System (OS) of the seismic data computing device 100. The processor 103 is configured to execute an executable module stored in the memory 101, such as a software functional module or a computer program included in the device 200 for surface wave refining based on the morphological difference of the same phase axis.
The Memory 101 may be, but is not limited to, a Random Access Memory (RAM), a Read Only Memory (ROM), a Programmable Read-Only Memory (PROM), an Erasable Read-Only Memory (EPROM), an electrically Erasable Read-Only Memory (EEPROM), and the like. The memory 101 is used for storing a program, and the processor 103 executes the program after receiving an execution instruction, and the method executed by the process-defined server disclosed by any embodiment of the invention can be applied to the processor 103, or implemented by the processor 103.
The processor 103 may be an integrated circuit chip having signal processing capabilities. The Processor 103 may be a general-purpose Processor, and includes a Central Processing Unit (CPU), a Network Processor (NP), and the like; but may also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other programmable logic device, discrete gate or transistor logic device, discrete hardware components. The various methods, steps and logic blocks disclosed in the embodiments of the present invention may be implemented or performed. A general purpose processor may be a microprocessor or the processor 103 may be any conventional processor 103 or the like.
The peripheral interface 104 couples various input/output devices to the processor 103 as well as to the memory 101. In some embodiments, the peripheral interface 104, the processor 103, and the memory controller 102 may be implemented in a single chip. In other examples, they may be implemented separately from the individual chips.
The display unit 105 provides an interactive interface (e.g., a user interface) between the seismic data computing device 100 and a user or for displaying image data to a user reference. In this embodiment, the display unit 105 may be a liquid crystal display or a touch display. In the case of a touch display, the display can be a capacitive touch screen or a resistive touch screen, which supports single-point and multi-point touch operations. Supporting single-point and multi-point touch operations means that the touch display can sense touch operations simultaneously generated from one or more positions on the touch display, and the sensed touch operations are sent to the processor 103 for calculation and processing.
The input output unit 106 is used to provide user input data to enable user interaction with the seismic data computing device 100. For example, it may be used to set the number of iterations, set a threshold value, and so on.
The surface wave has the characteristics of small transverse propagation attenuation, high signal-to-noise ratio and the like, and the frequency dispersion characteristic reflects the change of a shallow transverse wave velocity structure, so that the surface wave is widely applied to the aspects of shell mantle velocity structure detection, engineering detection and the like. In petroleum earthquake, a shallow transverse wave velocity structure is also researched and inverted by utilizing a fundamental surface wave frequency dispersion curve on a Z component, and the shallow transverse wave velocity structure is used for calculating a PS wave static correction value. In recent years, based on different response characteristics of high-order and fundamental-order surface waves to formation parameters, joint inversion is performed by using fundamental-order and high-order surface wave dispersion curves, the stability of inversion is improved, and the inversion accuracy is improved, so that the method becomes one of research hotspots in the field.
In multi-component seismic acquisition, fundamental surface waves have stronger energy on a Z component, and high-order surface waves often develop on an X component; because the wave above the X component is generally interfered by the reflected wave, the continuity of the frequency dispersion energy spectrum is poor, and an accurate frequency dispersion curve is difficult to extract, so that uncertainty exists in the process of inverting a fine transverse wave velocity structure by using a high-order surface wave. In order to accurately extract the surface wave dispersion curve, a relatively pure surface wave needs to be extracted according to the characteristic difference between the surface wave and the interference wave. Since the frequency and apparent velocity of the PS reflected wave are close to those of the higher-order surface wave, it is difficult to extract the surface wave efficiently only depending on the difference between the frequency and apparent velocity.
Therefore, in order to utilize the surface wave of the X component, a high-precision surface wave extraction method is essential.
First embodiment
Referring to fig. 2, the present embodiment provides a surface wave purification method based on the morphological difference of the same phase axis, and the method includes steps S01 to S50.
Step S01: raw seismic data is acquired.
Raw seismic data y is obtained, which in this embodiment refers to recorded single shot seismic data y. Typically, the single shot seismic data y includes reflected wave data and surface wave data.
Step S10: for seismic reflection wave data yrInitialization is performed.
The pair of seismic reflection wave data yrInitialization is performed, i.e. for the reflected wave data yrGiving an initial value, in this embodiment, let the reflected wave data yr＝0。
Before the step S20, the method further includes a step S101.
Step S101: let the loop variable k be k + 1.
Since the loop calculation needs to be performed for a plurality of iterations, in this embodiment, a loop variable K is set, the given iteration number K is given, the initial value K of the loop variable K is 0, and the loop variable K is K + 1. That is, during the first iteration, K +1 is 0+1, and the number of iterations may be set arbitrarily, and in this embodiment, K is 3.
Sparse surface waves and reflected waves are sparsely represented by adopting a frequency domain high-resolution Linear Radon Transform (LRT) and a time domain high-resolution Hyperbolic Radon Transform (HRT), and a sparse optimization problem is constructed under a Morphological Component Analysis (MCA) framework; solving by using an improved block coordinate relaxation algorithm of Stark and the like.
Step S20: according to the original seismic data y and the reflected wave data yrObtaining sparse representation coefficient of the surface wave in the frequency domain high resolution LRT transform domain, and reconstructing the surface wave data yg。
Referring to fig. 3, in the present embodiment, step S20 includes substeps S201-step S204.
Step S201: based on the original seismic data y and the reflected wave data yrCalculating to obtain first residual error data delta y1Wherein, Δ y1＝y-yr。
The raw seismic data y includes reflected wave data yrAnd surface wave data ygUsing y-yrAnd removing the influence of reflected wave data in the original seismic data, and obtaining the rest surface wave data.
Step S202: for the first residual data Δ y1Performing frequency domain high resolution LRT transform to obtain a first transform coefficient zg。
For the first residual data Δ y1Performing frequency domain LRT to obtain a first transform coefficient zgThen, the frequency dispersion spectrum is obtained.
Step S203: for the obtained first transform coefficient zgUsing a first threshold value sigmagCarrying out hard threshold processing to obtain a sparse representation coefficient z of the surface wave in a frequency domain high-resolution LRT (linear LRT transform) domaing'。
For the obtained first transform coefficient zgUsing a first threshold value sigmagCarrying out hard threshold processing to obtain a sparse representation coefficient z of the surface wave in a frequency domain high-resolution LRT (linear LRT transform) domaing'. Generally, the first threshold σgThe initial value of (A) is set to 0.4-0.5, and in each iteration process,
wherein K is a loop variable and K is the number of iterations. For the obtained first transform coefficient zgUsing a first threshold value sigmagPerforming hard threshold processing to obtain the first transform coefficient zgTo leave values smaller than the first threshold value sigma larger than the first threshold valuegTo obtain the height of the surface wave in the frequency domainSparse representation coefficient z of resolution LRT transform domaing'。
Step S204: sparse representation coefficient z of surface waveg' inverse LRT transform in frequency domain to reconstruct surface wave data yg。
Thresholding the first transform coefficient zg' inverse LRT transform in frequency domain, and the wavelet data ygReconstructing, wherein the frequency domain inverse LRT formula is d (f) ═ L (f) m (f); in the formula: d (f) is a Fourier coefficient vector of a time-space domain seismic channel with a specified frequency f, and the length is nx multiplied by 1; m (f) is a Fourier coefficient vector of Radon domain seismic traces with a specified frequency f, and the length is np multiplied by 1; l (f) is a complex matrix of nx × np orders
Wherein v isi(i ═ 1, 2.., np) is the apparent velocity, xjThe offset is (j ═ 1, 2.., nx), and nx and np are the number of traces of seismic data and the number of velocity parameters, respectively. The frequency domain high resolution LRT satisfies the equation:
wherein the content of the first and second substances,
diagonal matrix WdWeighting the matrix diag (W) for datad)i＝|(d-Lm)i|-1/2Reflecting the standard deviation of the data; diagonal matrix WmWeighting the matrix diag (W) for Radon coefficientsm)i＝|mi|-1/2Determining the sparsity of the transform coefficients; i is an identity matrix; the parameter lambda balances the proportion of time-space domain data errors and the sparsity of Radon transform coefficients; l isHIs the conjugate transpose of L. This equation is solved using an iterative reweighted least squares algorithm.
Step S30: according to the original seismic data y and the reconstructed surface wave data ygObtaining sparse representation coefficient of the reflected wave in time domain high resolution HRT transform domain, and reconstructing reflected wave numberAccording to yr。
Referring to fig. 4, in the present embodiment, the step S30 includes sub-steps S301 to S304. Reconstructing reflected wave data yrThe steps of (1) are similar to those of reconstructing surface wave data and will not be described in detail.
Step S301: according to the original seismic data y and the reconstructed surface wave data ygCalculating to obtain second residual error data delta y2Wherein Δ y2＝y-yg。
Step S302: for second residual data Δ y2Performing time domain high resolution HRT transformation to obtain a second transformation coefficient zr。
Step S303: for the obtained second transform coefficient zrUsing a second threshold value sigmarCarrying out hard threshold processing to obtain a sparse representation coefficient z of the reflected wave in a time domain high-resolution HRT transform domainr'。
For the obtained second transform coefficient zrUsing a second threshold value sigmarCarrying out hard threshold processing to obtain a sparse representation coefficient z of the reflected wave in a time domain high-resolution HRT transform domainr'. In general, the second threshold σrThe initial value of (A) is set to 0.1-0.2, and in each iteration process,
wherein K is a loop variable and K is the number of iterations. For the obtained second transform coefficient zrUsing a second threshold value sigmarPerforming hard threshold processing to obtain second transform coefficient zrIs smaller than the second threshold value sigmarIs truncated and remains greater than a second threshold value sigmarTo obtain a sparse representation coefficient z of the reflected wave in the time domain high resolution HRT transform domainr'。
Step S304: sparse representation of coefficient z for reflected wavesr' time domain inverse HRT transform is carried out to reconstruct reflected wave data yr。
Time domain inverse HRT formula is
Wherein d (t, x) is time-space domain seismic data, x is offset, t is seismic wave two-way travel time, m (tau, v) is Radon transformation coefficient, v is root-mean-square velocity, tau is time intercept, and the data are written into a matrix-vector form
d＝Lm，
d is a vector rearranged by the seismic data according to the track, and the length (nx multiplied by nt) multiplied by 1; m is a vector formed by rearranging hyperbolic Radon coefficients according to speed, the length (nv multiplied by n tau) multiplied by 1, and nx, nt, nv and n tau are the track number of data, the number of sampling points of each track, the number of speed parameters and the number of intercept parameters respectively; the operator L is not accessed in a matrix form, and only represents the amplitude superposition algorithm in the Radon coefficient domain as shown by the formula d ═ Lm. Solving the equations satisfied by the time-domain HRT in the constrained space proposed by sabdione and Sacchi:
seismic data d in the formula are integrally normalized and limited in space
Is defined as
Wherein T is a threshold value, and the value range is 0< T < 1. The equation is solved by adopting a left preconditioned regular equation conjugate gradient algorithm.
Step S40: it is determined whether the loop variable K is less than or equal to the number of iterations K.
And determining whether the iteration number reaches the set iteration number K. Since the value of the loop variable may represent the number of iterations in each iteration calculation process, the value of the loop variable is compared with the iteration number K, and if the loop variable K is less than or equal to the iteration number K, that is, the preset iteration number is not reached, step S10 is executed. If the preset iteration number has been reached, i.e. when the loop variable K is greater than the iteration number K, step S50 is executed.
Step S50: stopping iterative operation, and outputting the surface wave purified data.
Second embodiment
The present embodiment provides a surface wave purifying apparatus 200 based on the morphological difference of the same phase axis, and the surface wave purifying apparatus 200 based on the morphological difference of the same phase axis is used for executing the surface wave purifying method based on the morphological difference of the same phase axis provided in the first embodiment.
It should be noted that the basic principle and technical effect of the surface wave refining apparatus 200 based on the shape difference of the same phase axis provided in this embodiment are substantially the same as those of the surface wave refining method based on the shape difference of the same phase axis provided in the first embodiment, and for the sake of brief description, this embodiment will not be described in detail, and the related contents in the first embodiment are referred to in this embodiment without detailed description.
Referring to fig. 5, fig. 5 is a schematic diagram illustrating functional units of a surface wave refining apparatus 200 based on the morphological differences of the same phase axes according to the present embodiment.
The surface wave refining apparatus 200 based on the morphological difference of the same phase axis includes an obtaining unit 210, an initializing unit 220, a first reconstructing unit 230, a second reconstructing unit 240, a determining unit 250, and an outputting unit 260.
The obtaining unit 210 is configured to obtain raw seismic data.
It is to be understood that, in a preferred embodiment, the obtaining unit 210 may be configured to execute step S01.
An initialization unit 220 for initializing the reflected wave data yrInitialization is performed.
It is to be understood that, in a preferred embodiment, the initialization unit 220 may be configured to perform step S10.
A first reconstruction unit 230 for reconstructing a seismic data set from the original seismic data y and the reflected wave data yrObtaining sparse representation coefficient of the surface wave in the frequency domain high resolution LRT transform domain, and reconstructing the surface wave data yg。
It is to be understood that in a preferred embodiment, the first reconstruction unit 230 may be configured to perform step S20.
A second reconstruction unit 240 forThe original seismic data y and the reconstructed surface wave data ygObtaining sparse representation coefficient of the reflected wave in time domain high resolution HRT transform domain, and reconstructing reflected wave data yr。
It is to be understood that, in a preferred embodiment, the second reconstruction unit 240 may be configured to perform step S30.
A judging unit 250, configured to judge whether the confirmation loop variable is less than or equal to the iteration number.
It is to be understood that, in a preferred embodiment, the determining unit 250 may be configured to execute the step S40.
The first reconstruction unit 230 and the second reconstruction unit 240 are further configured to perform multiple iterative reconstructions when the loop variable is less than or equal to the iteration number to obtain a surface wave purification result.
And the output unit 260 is used for outputting the surface wave purification result when the loop variable is greater than the iteration times.
It is to be understood that, in a preferred embodiment, the output unit 260 may be used to perform step S50.
In summary, the present invention provides a method and an apparatus for surface wave purification based on the morphological differences of the same phase axes. By applying to the reflected wave data yrCarrying out initialization; according to the original seismic data y and the reflected wave data yrObtaining sparse representation coefficient of the surface wave in the frequency domain high resolution LRT transform domain, and reconstructing the surface wave data yg(ii) a According to the original seismic data y and the reconstructed surface wave data ygObtaining sparse representation coefficient of the reflected wave in time domain high resolution HRT transform domain, and reconstructing reflected wave data yr(ii) a And iterating the reconstruction calculation step to solve the sparse optimization problem under the MCA framework and obtain a surface wave purification result. By carrying out multiple times of transformation and reconstruction on the surface wave and the reflected wave, when the frequency and the visual speed of the surface wave and the reflected wave are close, the surface wave can still be effectively extracted, the interference of the reflected wave on a frequency dispersion energy spectrum of the surface wave is reduced, and high-precision surface wave data are provided for frequency dispersion analysis.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus and method can be implemented in other ways. The apparatus embodiments described above are merely illustrative, and for example, the flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
In addition, the functional modules in the embodiments of the present invention may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.
The functions, if implemented in the form of software functional modules and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention. It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures.
The above description is only for the specific embodiments of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present invention, and all the changes or substitutions should be covered within the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (9)
1. A surface wave purification method based on the morphological difference of the same phase axis is characterized in that the method comprises the following steps,
s10: for seismic reflection wave data yrCarrying out initialization;
s20: according to the original seismic data y and the reflected wave data yrObtaining sparse representation coefficient of the surface wave in the frequency domain high resolution LRT transform domain, and reconstructing the surface wave data ygThe method comprises the following steps:
based on the original seismic data y and the reflected wave data yrCalculating to obtain first residual error data delta y1Wherein, Δ y1＝y-yr；
For the first residual data Δ y1Performing frequency domain high resolution LRT transform to obtain a first transform coefficient zg；
For the obtained first transform coefficient zgUsing a first threshold value sigmagCarrying out hard threshold processing to obtain a sparse representation coefficient z of the surface wave in a frequency domain high-resolution LRT (linear LRT transform) domaing'；
Sparse representation coefficient z of surface waveg' inverse LRT transform in frequency domain to reconstruct surface wave data yg；
S30: according to the original seismic data y and the reconstructed surface wave data ygObtaining sparse representation coefficient of the reflected wave in time domain high resolution HRT transform domain, and reconstructing reflected wave data yr；
And (5) iteratively performing the step S20 and the step S30 to obtain a surface wave purification result.
2. The method of claim 1, wherein the original seismic data y and the reconstructed surface wave data y are used as basis for surface wave refininggObtaining sparse representation coefficient of the reflected wave in time domain high resolution HRT transform domain, and reconstructing reflected wave data yrComprises the following steps:
according to the original seismic data y and the reconstructed surface wave data ygCalculating to obtain second residual error data delta y2Wherein Δ y2＝y-yg；
For second residual data Δ y2Performing time domain high resolution HRT transformation to obtain a second transformation coefficient zr；
For the obtained second transform coefficient zrUsing a second threshold value sigmarCarrying out hard threshold processing to obtain a sparse representation coefficient z of the reflected wave in a time domain high-resolution HRT transform domainr'；
Sparse representation of coefficient z for reflected wavesr' time domain inverse HRT transform is carried out to reconstruct reflected wave data yr。
3. The method according to claim 2, wherein a loop variable K is set, the given number of iterations K is set, and an initial value K of the loop variable K is 0, and before the step S20, the method further comprises:
let the loop variable k be k + 1.
4. The method of claim 3, wherein the first threshold σ is updated during each iterationgSecond threshold value σrThe values of (a) specifically include:
5. The method of claim 1, wherein the seismic reflection wave data y are processed by a surface wave refining method based on morphological differences of the same phase axesrThe initialization includes:
let the initial value of the reflected wave data be yr＝0。
6. The method of claim 5, wherein the step of iteratively performing the steps S20 and S30 to obtain the result of surface wave purification comprises:
when the loop variable K is less than or equal to the iteration number K, the steps S20 to S30 are repeatedly performed to obtain a surface wave purification result.
7. The method of surface wave purification based on morphological differences in the same phase axis as defined in claim 5 further comprising:
and when the loop variable K is greater than the iteration times K, stopping iteration and outputting the surface wave purified data.
8. The method of claim 1, wherein the surface wave data y is obtained by a surface wave refining method based on morphological differences of the same phase axesgReflected wave data yrBefore performing initialization, the method further comprises:
raw seismic data y is acquired.
9. A surface wave purification device based on the same phase axis morphological difference is characterized in that the device is used for executing the surface wave purification method based on the same phase axis morphological difference as any one of claims 1 to 8, and the device comprises:
an initialization unit for initializing the reflected wave data yrCarrying out initialization;
a first reconstruction unit for reconstructing seismic data y from the original seismic data y and the reflected wave data yrObtaining sparse representation coefficient of the surface wave in the frequency domain high resolution LRT transform domain, and reconstructing the surface wave data yg；
A second reconstruction unit for reconstructing the surface wave data y from the original seismic data ygObtaining sparse representation coefficient of the reflected wave in time domain high resolution HRT transform domain, and reconstructing reflected wave data yr；
The first reconstruction unit and the second reconstruction unit are further used for carrying out repeated iterative reconstruction for multiple times to obtain a surface wave purification result.
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