CN108107474A - A kind of aliased data separation method and device based on sparse inversion - Google Patents
A kind of aliased data separation method and device based on sparse inversion Download PDFInfo
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Abstract
The application provides a kind of aliased data separation method and device based on sparse inversion.The described method includes：Aliased seismic data is split, obtains three-dimensional common detector gather data；According to the three-dimensional common detector gather data structure threshold contracting function, the threshold contracting function includes the relation between iterations and seismic data amplitude scope；Sparse constraint object function is built based on the aliased seismic data, the sparse constraint object function includes the functional relation between the aliased seismic data and useful signal data；According to the threshold contracting function, inverting solution is iterated to the sparse constraint object function using the three-dimensional space-time window that slides of structure, obtains the SNR estimation and compensation data of the aliased seismic data.Using each embodiment in the application, the separating effect of seismic data is improved, improves the efficiency of data processing.
Description
Technical field
The application belongs to seismic data processing technology field more particularly to a kind of aliased data separation based on sparse inversion
Method and device.
Background technology
Since traditional seismic acquisition efficiency is low, of high cost, it is impossible to meet the industry of high density earthquake data acquisition
Demand in the prior art, may be employed aliasing acquisition technique and improve earthquake-capturing day effect, reduce high-density seismic acquisition cost.
There is substantial amounts of adjacent big gun interference noise but since aliasing acquisition technique is by the way of continuous agitation, in aliasing gathered data,
Seriously reduce seismic data signal-to-noise ratio and image quality.Therefore, the SNR estimation and compensation of aliased data is the processing of aliasing gathered data
Necessary links.
In the prior art, aliasing gathered data separation method can be divided into three classes：Direct Denoising Algorithm, iterated denoising method and anti-
Drill partition method.Direct Denoising Algorithm and iterated denoising method are mainly made an uproar using random character of the adjacent big gun interference on non-big gun collection to suppress
Sound, they the shortcomings that be when seismic data aliasing degree is higher, these methods normally result in that serious noise is remaining and letter
Number damage, aliased data separating effect is bad, it is difficult to meet actual production demand.Relevant spy of the inverting partition method based on signal
Sign applies sparse constraint to seismic data to extract useful signal in transform domain, and utilizes can be predicted between signal and noise
Property realize SNR estimation and compensation, this kind of method depends critically upon degree of rarefication and used threshold contracting function of the signal in transform domain,
Calculating cost is higher, and aliased data separating effect is bad.The many invertion separation methods all Shortcomings proposed at present, are such as based on
FK (Frequency-Wavenumber) conversion, the separation method of linear Radon (Radon transform) conversion are in transform domain to bending
The characterization of lineups is not sparse, affects aliasing gathered data separating effect.Therefore, there is an urgent need for one kind in the industry can improve aliasing number
According to the embodiment of separating effect.
The content of the invention
The application is designed to provide a kind of aliased data separation method and device based on sparse inversion, sliding using three-dimensional
Dynamic space-time window can improve the local linear feature of seismic data, improve the separating effect of seismic data.Meanwhile it employs dilute
The constraint method of inversion and threshold contracting function are dredged, accelerates the convergence rate of iterative inversion, improves the efficiency of data processing.
On the one hand this application provides a kind of aliased data separation method based on sparse inversion, including：
Aliased seismic data is split, obtains three-dimensional common detector gather data；
According to the three-dimensional common detector gather data structure threshold contracting function, the threshold contracting function includes iteration
Relation between number and seismic data amplitude scope；
Sparse constraint object function is built based on the aliased seismic data, the sparse constraint object function includes described
Functional relation between aliased seismic data and useful signal data；
According to the threshold contracting function, using structure it is three-dimensional slide space-time window to the sparse constraint object function into
Row iteration inverting solves, and obtains the SNR estimation and compensation data of the aliased seismic data.
Further, it is described according to the threshold contracting function in another embodiment of the method, utilize structure
Three-dimensional slides space-time window and inverting solution is iterated to the sparse constraint object function, obtains the letter of the aliased seismic data
It makes an uproar mask data, including：
Perform the first processing step：
It is selected using the three-dimensional space-time window that slides from the currently active signal data in the sparse constraint object function
Take local earthquake's data；
Pretreatment useful signal is obtained into threshold trip processing to local earthquake's data according to the threshold contracting function
Data；
According to pretreatment useful signal data prediction neighbour's big gun interference noise；
The adjacent big gun interference noise is subtracted from the three-dimensional common detector gather data, obtains iteration useful signal number
According to；
Judge whether current iteration number is less than and preset total iterations, if being less than, by the iteration useful signal number
According to as the currently active signal data, first processing step is repeated, until the current iteration number is more than or equal to
During default total iterations, using the iteration useful signal data as the SNR estimation and compensation data.
Further, in another embodiment of the method, it is described according to the threshold contracting function to the part
Seismic data pre-processes useful signal data into threshold trip processing, acquisition, including：
Three dimensional fast Fourier direct transform is carried out to local earthquake's data, obtains direct transform Fourier data；
The corresponding threshold value of current iteration number is obtained according to the threshold contracting function, by the direct transform Fourier number
Seismic data less than the threshold value in is set to zero, obtains threshold processing data；
Threshold processing data are subjected to three dimensional fast Fourier inverse transformation, obtain the pretreatment useful signal number
According to.
Further, it is described that threshold processing data are subjected to three-dimensional quickly in another embodiment of the method
Fourier inversion obtains the pretreatment useful signal data, including：
Threshold processing data are subjected to three dimensional fast Fourier inverse transformation, the current three-dimensional space-time window that slides is obtained and corresponds to
Local pretreatment useful signal data；
Judge whether the seismic data in the currently active signal data is all selected, if it is not, then sliding described three
Dimension slides space-time window, obtains the corresponding local earthquake's data of next three-dimensional slip space-time window, threshold trip of going forward side by side processing, under acquisition
One three-dimensional corresponding part of space-time window of sliding pre-processes useful signal data；
If so, each three-dimensional corresponding part of space-time window of sliding is pre-processed useful signal data, integrated, will be integrated
Useful signal data afterwards, as the corresponding pretreatment useful signal data of the currently active signal data.
Further, in another embodiment of the method, the sparse constraint object function includes：
In above formula,Representing error term, d represents the aliased seismic data, and m represents useful signal data,
Γ represents aliasing operator,Represent bound term, the slip space-time of nx representation space X-directions
The window number of window, the window number of the slip space-time window of ny representation space Y-directions, nt represent the slip space-time in time t direction
The window number of window, F represent three dimensional fast Fourier direct transform operator, Wix,iy,itIt represents in space X, space Y, time T direction
On it is three-dimensional slide space-time window operator, | | FWix,iy,itm||0Expression takes L0 norms, and λ represents regularization parameter.
Further, it is described according to the three-dimensional common detector gather data structure in another embodiment of the method
Threshold contracting function is built, including：
Fast Fourier direct transform is carried out to the three-dimensional common detector gather data, obtains the three-dimensional common receiver road
Collect the peak swing value of data and minimum amplitude value；
According to the peak swing value and the minimum amplitude value, the threshold contracting function is built.
Further, in another embodiment of the method, the threshold contracting function includes：
In above formula, T (k) represents the threshold value of kth time iteration, and N represents total iterations.
On the other hand, this application provides a kind of aliased data separator based on sparse inversion, including：
Aliased data splits module, for being split to aliased seismic data, obtains three-dimensional common detector gather data；
Threshold function builds module, for according to the three-dimensional common detector gather data structure threshold contracting function；
Sparse object function builds module, for being based on the aliased seismic data structure sparse constraint object function, institute
Stating sparse constraint object function includes the functional relation between the aliased seismic data and useful signal data；
Alternate analysis module, for according to the threshold contracting function, space-time window to be slided to described using the three-dimensional of structure
Sparse constraint object function is iterated inverting solution, obtains the SNR estimation and compensation data of the aliased seismic data.
Further, in another embodiment of described device, the alternate analysis module is specifically used for：
Perform the first processing step：
It is selected using the three-dimensional space-time window that slides from the currently active signal data in the sparse constraint object function
Take local earthquake's data；
Pretreatment useful signal is obtained into threshold trip processing to local earthquake's data according to the threshold contracting function
Data；
According to pretreatment useful signal data prediction neighbour's big gun interference noise；
The adjacent big gun interference noise is subtracted from the three-dimensional common detector gather data, obtains iteration useful signal number
According to；
Judge whether current iteration number is less than and preset total iterations, if being less than, by the iteration useful signal number
According to as the currently active signal data, first processing step is repeated, until the current iteration number is more than or equal to
During default total iterations, using the iteration useful signal data as the SNR estimation and compensation data.
In another aspect, present invention also provides a kind of aliased data separator based on sparse inversion, including：Processor
And the memory for storing processor-executable instruction, the processor are realized above-mentioned based on sparse when performing described instruction
The aliased data separation method of inverting.
The aliased data separation method and device based on sparse inversion that the application provides split aliasing acquisition earthquake first
Data build threshold contracting function according to the three-dimensional common detector gather data after fractionation, data are provided for successive iterations inverting
Basis.Sparse-constrained inversion technology is recycled, the sparse constraint object function of aliased seismic data is built, and is slided using three-dimensional
Space-time window and threshold contracting function are iterated sparse constraint object function inverting solution, obtain three-dimensional common detector gather
The useful signal data of data complete the SNR estimation and compensation of aliased seismic data.Space-time window is slided using three-dimensional and chooses local earthquake
Data make use of the local linear feature of useful signal data, improve sparse degree of the signal in Fourier transform domain, improve
The effect of aliased seismic data SNR estimation and compensation.Meanwhile letter is shunk using sparse-constrained inversion, Fast Fourier Transform (FFT), threshold
Number etc., accelerates convergence rate, improves computational efficiency.
Description of the drawings
It in order to illustrate the technical solutions in the embodiments of the present application or in the prior art more clearly, below will be to embodiment or existing
There is attached drawing needed in technology description to be briefly described, it should be apparent that, the accompanying drawings in the following description is only this
Some embodiments described in application, for those of ordinary skill in the art, in the premise of not making the creative labor property
Under, it can also be obtained according to these attached drawings other attached drawings.
Fig. 1 is a kind of method stream of aliased data separation method one embodiment based on sparse inversion that the application provides
Journey schematic diagram；
Fig. 2 is the three-dimensional common detector gather schematic diagram split out in the embodiment of the present application in aliased seismic data；
Fig. 3 is the flow diagram of the aliased data separation method based on sparse inversion in another embodiment of the application；
Fig. 4 is the flow diagram of the aliased data separation method based on sparse inversion in the another embodiment of the application；
Fig. 5 is the useful signal of the three-dimensional common detector gather data separating of aliased seismic data one in the embodiment of the present application
Schematic diagram data；
Fig. 6 is that the adjacent big gun interference of three-dimensional common detector gather data separating in aliased seismic data in the embodiment of the present application is shown
It is intended to；
Fig. 7 is the stacked section schematic diagram before aliased seismic data separation in the embodiment of the present application；
Fig. 8 is the useful signal stacked section schematic diagram after aliased seismic data separation in the embodiment of the present application；
Fig. 9 is that the modular structure of aliased data separator one embodiment based on sparse inversion that the application provides is shown
It is intended to；
Figure 10 is the module knot for another aliased data separator embodiment based on sparse inversion that the application provides
Structure schematic diagram.
Specific embodiment
It is in order to make those skilled in the art better understand the technical solutions in the application, real below in conjunction with the application
The attached drawing in example is applied, the technical solution in the embodiment of the present application is clearly and completely described, it is clear that described implementation
Example is merely a part but not all of the embodiments of the present application.Based on the embodiment in the application, this field is common
Technical staff's all other embodiments obtained without creative efforts should all belong to the application protection
Scope.
The acquisition of seismic data is the basis of seismic prospecting, in order to improve the collecting efficiency of seismic data, can usually be adopted
With aliasing acquisition technique, you can different focus to be used to excite simultaneously, corresponding different wave detector receives different shakes simultaneously
The seismic signal that source generates.Aliasing acquisition technique can improve the collecting efficiency of seismic data, still, while by adjacent big gun when exciting
The interference noise needs brought are rejected from aliased seismic data, to obtain effective seismic data.
The embodiment of the present application can utilize three-dimensional slip space-time window, and aliased seismic data is carried out using sparse-constrained inversion
Separating treatment.Sparse-constrained inversion can essentially represent, using deconvolution principle, to calculate from noisy seismic channel
The amplitude of reflectance factor with sparse distribution feature and the method for time.Sparse-constrained inversion is nonlinear optimal problem, is led to
Nonlinear optimal problem can be often converted into linear optimization problem, then with linear optimization Algorithm for Solving.It is real using the application
The method for applying example improves the separating effect of seismic data, meanwhile, it employs sparse-constrained inversion method and threshold shrinks letter
Number accelerates the convergence rate of iterative inversion, improves the efficiency of data processing.
Specifically, Fig. 1 is a kind of aliased data separation method one embodiment based on sparse inversion that the application provides
Method flow schematic diagram, the application provide the aliased data separation method based on sparse inversion include：
S1, aliased seismic data is split, obtains three-dimensional common detector gather data.
It may include the seismic data that multiple wave detectors collect in aliased seismic data, the embodiment of the present application is to aliasing
It shakes data and carries out deconsolidation process, the seismic data of common receiver is splitted out, obtain three-dimensional common detector gather data.Example
Such as：Aliased seismic data can be multiplied by an aliasing operator, three-dimensional common detector gather data are splitted out, it specifically can be with
The fractionation of aliased seismic data is carried out with the following method：
m0=ΓHd (1)
In above formula, d can represent aliased seismic data, m0It can represent the three-dimensional common detector gather after splitting, Γ can
To represent aliasing operator, aliasing operator can include the firing time and location information of focus, ΓHIt can represent aliasing operator
Conjugation.
Fig. 2 is the three-dimensional common detector gather schematic diagram split out in the embodiment of the present application in aliased seismic data, such as Fig. 2
Shown, ordinate can represent the time in figure, and the first row can represent big gun wire size (can be understood as X-direction) in abscissa,
Two rows can represent useful signal data and adjacent big gun interference point in shot point pile No. (can be understood as Y-direction) aliased seismic data
Relevant and random feature is not shown.Useful signal data can represent effective seismic data in aliased seismic data, i.e.,
Except the seismic data of denoising.
S2, threshold contracting function is built according to the three-dimensional common detector gather data, the threshold contracting function includes
Relation between iterations and seismic data amplitude scope.
After obtaining three-dimensional common detector gather data, three-dimensional common detector gather data can be handled, according to three
The amplitude of common detector gather data is tieed up, determines threshold contracting function.Threshold contracting function can represent sparse-constrained inversion
In iterative process, each time during iteration in seismic data amplitude scope, i.e. threshold contracting function can represent iterations
With the correspondence between seismic data amplitude scope.It can be built by simulated experiment or the iterative data according to history
Threshold contracting function provides accurate data basis for follow-up sparse-constrained inversion, accelerates the convergence rate of iterative inversion.
In the application one embodiment, following method structure threshold contracting function may be employed：
Fast Fourier direct transform is carried out to the three-dimensional common detector gather data, obtains the three-dimensional common receiver road
Collect the peak swing value of data and minimum amplitude value；
According to the peak swing value and the minimum amplitude value, the threshold contracting function is built.
Three-dimensional Fourier's direct transform can be carried out to each three-dimensional common detector gather data, count each three-dimensional inspection altogether
Wave point trace gather data corresponding peak swing value Tmax and minimum amplitude value Tmin.Fast Fourier transform (FFT), is discrete Fourier
The fast algorithm of conversion, can be according to the characteristics such as odd, even, empty, real of discrete fourier transform, to the algorithm of Discrete Fourier Transform
It is improved acquisition.According to the corresponding peak swing value Tmax of each three-dimensional common detector gather data and minimum amplitude value
Tmin determines the amplitude scope of useful signal data during iterative inversion, further determines that out threshold contracting function.Threshold
Contracting function, that is, iterations can be according to reality with the physical relationship of the amplitude of corresponding seismic data during iteration each time
It needs to be configured, can be determined by modes such as numerical simulation, mathematical statisticses.
Different three-dimensional common detector gather data may correspond to different peak swing value Tmax and minimum amplitude value
Tmin, correspondingly, different three-dimensional common detector gather data may correspond to different threshold contracting functions.To aliased seismic
When data carry out the SNR estimation and compensation of sparse-constrained inversion, corresponding door can be used to different three-dimensional common detector gather data
Sill contracting function.
In the application one embodiment, equation below may be employed in threshold contracting function：
In above formula, T (k) can represent that the threshold of kth time iteration (can also represent shaking for seismic data during kth time iteration
The maximum or minimum value of amplitude), N can total iterations, can need to set according to actual iteration precision, the application one
N=50 can be taken in a embodiment.
S3, sparse constraint object function is built based on the aliased seismic data, the sparse constraint object function includes
Functional relation between the aliased seismic data and useful signal data.
It can include two parts in sparse constraint object function, a part is the constraint to noise, and a part is to anti-
The constraint of coefficient is penetrated, the constraint portions of norm structure reflectance factor may be employed.Useful signal data can represent aliased seismic
Effective seismic data is the seismic data except denoising in data.It can include aliased seismic number in sparse constraint object function
According to the functional relation between useful signal data.Iterative inversion can include：According to known geology, geophysical information, really
A fixed initial model, the then field-effect of forward modelling model are changed using the difference of calculated value and observation (remaining value)
Initial model, then forward modelling field is worth again, and model modification is remake according to comparative result.It so iterates, until calculated value
Reach preset precision with the difference (or mean square error) of observation or iterations reaches the iterations of threshold value, it is final to obtain
To inversion result.
Can using useful signal data as the variable of sparse constraint object function, by sparse constraint object function into
Row iteration inverting solves sparse constraint target letter, and by continuous iteration, it is optimal can to obtain the acquisition of sparse constraint object function
Corresponding useful signal data during solution.Specific construction method the embodiment of the present application of sparse constraint object function does not limit specifically
Fixed, the sparse-constrained inversion technology in the prior art that may be referred to is built.
In the application one embodiment, the sparse constraint object function can include：
In above formula,It can represent error term, d can represent aliased seismic data, and m can represent effective
Signal data, Γ can represent aliasing operator,It can represent bound term, nx can be with table
Show space X direction slip space-time window window number, ny can with representation space Y-direction slip space-time window window number,
Nt can represent the window number of the slip space-time window in time t direction, and F can represent three dimensional fast Fourier direct transform operator,
Wix ,iy,itIt can represent the three-dimensional slip space-time window operator on space X, space Y, time T direction, | | FWix,iy,itm||0It can be with
Expression takes L0Norm, λ can represent regularization parameter.
S4, space-time window is slided to the sparse constraint object function using the three-dimensional of structure according to the threshold contracting function
Inverting solution is iterated, obtains the SNR estimation and compensation data of the aliased seismic data.
Space-time window is slided based on three-dimensional and chooses corresponding useful signal data in sparse constraint object function, is received using threshold
Contracting function determines the amplitude range of seismic data during iteration, and further the seismic data of iteration is screened.To sparse constraint
Object function is iterated inverting, solves sparse constraint object function, obtains that sparse constraint object function optimal solution is corresponding to be had
Signal data is imitated, realizes the separation to aliased seismic data.It, can be by the three-dimensional common detector gather after fractionation during primary iteration
Data m0As initial useful signal data, iteration update is until the total iterations of arrival, obtains final effective letter successively
Number completes the inverting of aliased seismic data.
The three-dimensional common detector gather data split out in aliased seismic data include noise and useful signal data.This
The three-dimensional part number slided in the corresponding useful signal data of space-time window selection current iteration number may be employed in application embodiment
According to, using the local linear feature of useful signal data, inverting is iterated based on sparse constraint object function, solve it is sparse about
Beam object function.Specifically space-time window can be slided in space X, space Y, time T direction structure three-dimensional, from current iteration number pair
The corresponding part seismic data of the three-dimensional slip space-time window of selection successively in the useful signal data answered.Threshold can be utilized to shrink
Function controls the precision and convergence rate of iterative inversion, such as：Useful signal data of the threshold contracting function to selection can be utilized
It is further processed, as the basic data of iterative inversion, reduces calculation amount.Obtain the optimal of sparse constraint object function
Corresponding useful signal data during solution need until reaching the useful signal data that total iterations or iterative inversion obtain and having reached
The required precision wanted.Corresponding useful signal data when can be up to total iterations or reach required precision, as final
SNR estimation and compensation data, realize the SNR estimation and compensation of aliased seismic data.
Specific iterative inversion process may be referred to sparse-constrained inversion technology progress in the prior art, the embodiment of the present application
It is not especially limited.
In the embodiment of the present application when carrying out the inverting of sparse constraint object function based on three-dimensional slip space-time window, Ke Yiyi
Secondary multiple three-dimensional common detector gather data to being split out in aliased seismic data carry out sparse constraint iterative inversion respectively, will
Aliased data in each three-dimensional common detector gather data carries out SNR estimation and compensation, realizes the noise point of all aliased seismic datas
From.
Aliased data separation method provided by the embodiments of the present application based on sparse inversion slides space-time window pair using three-dimensional
The seismic data of sparse-constrained inversion process is screened, and can be improved the local linear feature of seismic data, be improved earthquake
The separating effect of data.Meanwhile sparse-constrained inversion method and threshold contracting function are employed, accelerate the convergence of iterative inversion
Speed improves the efficiency of data processing.
Fig. 3 is the flow diagram of the aliased data separation method based on sparse inversion in another embodiment of the application, such as
Shown in Fig. 3, the aliased data separation method based on sparse inversion includes in the embodiment of the present application：
The fractionation of aliased seismic data is being carried out, it, can after constructing threshold contracting function and sparse constraint object function
To carry out the iterative inversion of sparse constraint object function using following steps：
S20, space-time window is slided from the currently active signal data in the sparse constraint object function using the three-dimensional
Middle selection local earthquake data.
The currently active signal data can refer to the corresponding useful signal data of current iteration number, can be in space X, space
Y, time T directions structure is three-dimensional slides space-time window, is chosen from the corresponding the currently active signal of current iteration inverting number local
Seismic data.
S21, local earthquake's data into threshold trip are handled according to the threshold contracting function, it is effective obtains pretreatment
Signal data.
Local earthquake's data of selection are handled using threshold contracting function, filters out and meets iteration threshold requirement
Seismic data improves iteration precision and convergence rate as pretreatment useful signal data.
In the application one embodiment, it is described according to the threshold contracting function to local earthquake's data into threshold trip
Processing obtains pretreatment useful signal data, can include：
Three dimensional fast Fourier direct transform is carried out to local earthquake's data, obtains direct transform Fourier data；
The corresponding threshold value of current iteration number is obtained according to the threshold contracting function, by the direct transform Fourier number
Seismic data less than the threshold value in is set to zero, obtains threshold processing data；
Threshold processing data are subjected to three dimensional fast Fourier inverse transformation, obtain the pretreatment useful signal number
According to.
Specifically, according to current iteration number and threshold contracting function, the corresponding door of current iteration number can be obtained
Sill threshold value T.After carrying out three dimensional fast Fourier direct transform to local earthquake's data of selection, by the direct transform Fourier number of acquisition
Seismic data less than the corresponding threshold threshold value of current iteration number in is set to zero, obtains threshold processing data.It specifically can be with
Threshold processing data are obtained using equation below：
In above formula, f (m) can represent direct transform Fourier data, and T is the corresponding threshold value of current iteration number.
Above-mentioned formula (2) can be utilized, obtains the corresponding threshold value of current iteration number, such as：If current iteration number
It is 1, then k=1 can be substituted into above-mentioned formula (2), with reference to the maximum amplitude and minimum amplitude of three-dimensional common detector gather data,
It can determine the corresponding threshold value T of current iteration number.
After obtaining the corresponding threshold processing data of current iteration number, threshold processing data are subjected to three dimensional fast Fourier
Inverse transformation, you can to obtain the corresponding pretreatment useful signal data of current iteration number.
It is described that threshold processing data are carried out three in the application one embodiment on the basis of above-described embodiment
Fast Fourier Transform Inverse is tieed up, the pretreatment useful signal data is obtained, can include：
Threshold processing data are subjected to three dimensional fast Fourier inverse transformation, the current three-dimensional space-time window that slides is obtained and corresponds to
Local pretreatment useful signal data；
Judge whether the seismic data in the currently active signal data is all selected, if it is not, then sliding described three
Dimension slides space-time window, obtains the corresponding local earthquake's data of next three-dimensional slip space-time window, threshold trip of going forward side by side processing, under acquisition
One three-dimensional corresponding part of space-time window of sliding pre-processes useful signal data；
If so, each three-dimensional corresponding part of space-time window of sliding is pre-processed useful signal data, integrated, will be integrated
Useful signal data afterwards, as the corresponding pretreatment useful signal data of the currently active signal data.
Choose local earthquake's data in the currently active signal data successively using three-dimensional slip space-time window, and to selection
Local earthquake's data carry out Fast Fourier Transform (FFT) processing and threshold processing, obtain current three-dimensional and slide the corresponding part of space-time window
Pre-process useful signal data.Three-dimensional slip space-time window is slided again, from selection another part in the currently active signal data
Local earthquake's data carry out identical data processing, until the seismic data in the currently active signal data is all chosen simultaneously
Fast Fourier Transform (FFT) and threshold processing are carried out, obtaining different space-time positions, corresponding three-dimensional to slide the corresponding part of space-time window pre-
Handle useful signal data.The three-dimensional corresponding part of space-time window of sliding that each space-time position of acquisition is arrived pre-processes effectively letter
Number is integrated, you can with will treated that local pre-processing seismic data is put into is right in three-dimensional common detector gather data
At the position answered, the corresponding pretreatment useful signal data of the currently active signal data are obtained.
S22, useful signal data prediction neighbour's big gun interference noise is pre-processed according to described.
After obtaining the corresponding pretreatment useful signal data of current iteration number, pretreatment useful signal number can be based on
According to the adjacent big gun interference noise of prediction.The specific prediction that may be referred to noise prediction technology and carry out adjacent big gun noise, such as will pretreatment
Abnormal data in useful signal data is as adjacent big gun interference noise.In the application one embodiment, it is pre- to may be referred to formula (5)
Survey adjacent big gun interference noise：
N=(ΓHΓ-I)m (5)
In above formula, n can represent adjacent big gun interference noise, and Γ can represent aliasing operator, ΓHIt can represent aliasing operator
Conjugation, I can be with unit matrix.
S23, the adjacent big gun interference noise is subtracted from the three-dimensional common detector gather data, obtains iteration useful signal
Data.
After obtaining adjacent big gun interference noise, adjacent big gun interference noise can be subtracted from current three-dimensional common detector gather data
It goes, obtains iteration useful signal data, realize the iteration update of useful signal data.
S24, judge whether current iteration number is less than total iterations, if being less than, perform step S25, otherwise, perform
Step S26.Total iterations, that is, previously described default total iterations, is hereinafter properly termed as total iterations, total iteration
The size of number can be pre-set, and the embodiment of the present application is not especially limited.
S25, using the iteration useful signal data as the currently active signal data, repeat S20-S24,
S26, using the iteration useful signal data as the SNR estimation and compensation data.
Specifically, judge whether current iteration useful signal data are less than total iterations, if it is less, can will obtain
The currently active signal data of the iteration useful signal data obtained as next iteration inverting, repeats step S20-S24.I.e. pair
Updated iteration useful signal data choose local earthquake's data using the three-dimensional space-time window that slides, and to selecting partly
Shake data are handled, and obtain new iteration useful signal data, until iterations reaches total iterations.Work as iterations
When reaching total iterations, then using the iteration useful signal data of newest acquisition as current three-dimensional common detector gather data
SNR estimation and compensation data complete the SNR estimation and compensation processing of current three-dimensional common detector gather data.To other three-dimensional common receiver roads
Collect data and SNR estimation and compensation is carried out using identical method, until completing the SNR estimation and compensation of all three-dimensional common detector gather data
Processing.
Fig. 4 is the flow diagram of the aliased data separation method based on sparse inversion in the another embodiment of the application, such as
Shown in Fig. 4, the technical solution of the application is introduced with reference to specific example：
B1, aliased seismic data is split, the three-dimensional common detector gather data after being split.Specific fractionation side
Method may be referred to above-described embodiment, and details are not described herein again.
B2, threshold contracting function is built according to current three-dimensional common detector gather data.Specific construction method may be referred to
Above-described embodiment, details are not described herein again.
B3, the corresponding sparse constraint target letter of current three-dimensional common detector gather data is built based on aliased seismic data
Number.Specific construction method may be referred to above-described embodiment, and details are not described herein again.It can be by the three-dimensional common detector gather after fractionation
Data m0Initial useful signal data as sparse constraint object function iterative inversion.Different three-dimensional common detector gathers
The form of the corresponding sparse constraint object function of data can be identical, but initial effective letter in sparse constraint object function
Number may be different.
B4, current iteration number correspondence is calculated according to the corresponding threshold contracting function of current three-dimensional common detector gather data
Threshold value T.
B5, it space-time window slided using three-dimensional (when primary iteration, may be employed initial effective from the currently active signal data
Signal data is as the currently active signal data) in choose local earthquake's data successively, the embodiment of the present application can use space
X, the three-dimensional slip space-time window that space Y, time T direction sampling point number are 20 × 20 × 100.
B6, local earthquake's data of selection are done with three dimensional fast Fourier direct transform, obtains direct transform Fourier data.
B7, direct transform Fourier data into threshold trip is handled, threshold will be obtained less than the seismic data zero setting of threshold value
Handle data.The specific introduction that may be referred to above-described embodiment, details are not described herein again.
B8, three dimensional fast Fourier inverse transformation is done to threshold treated threshold processing data, obtains current three-dimensional slide
The corresponding local pretreatment useful signal data of space-time window；
B9, judge whether the seismic data in the currently active signal data is all selected, if it is not, then repeating step B5 extremely
Step B9, the next three-dimensional corresponding part of space-time window of sliding for obtaining the currently active signal model pre-process useful signal number
According to until to the processing for completing all seismic datas in the currently active signal data；If so, perform step B10.
B10, the corresponding three-dimensional local pretreatment useful signal data for sliding the acquisition of space-time window of different space-times are merged into
It is whole, obtain the corresponding pretreatment useful signal data of the currently active signal data.
B11, the corresponding pretreatment useful signal data of the currently active signal data using acquisition, predict that adjacent big gun interference is made an uproar
Sound n.
B12, the adjacent big gun interference noise that prediction is subtracted from current three-dimensional common detector gather data, update useful signal number
According to acquisition iteration useful signal data.
B13, judge whether iterations reaches total iterations, if so, B14 is performed, if it is not, then repeating step B4 extremely
Step B13, using iteration useful signal data as the currently active signal data of next iteration inverting.It carries out current three-dimensional common
The next iteration inversion procedure of geophone station trace gather data until reaching total iterations, completes current three-dimensional common receiver road
Collect the SNR estimation and compensation of data, obtain current three-dimensional common detector gather data SNR estimation and compensation data.
Fig. 5 is the useful signal of the three-dimensional common detector gather data separating of aliased seismic data one in the embodiment of the present application
Schematic diagram data, as shown in figure 5, ordinate can represent the time in figure, the first row can represent that big gun wire size (can be in abscissa
It is interpreted as X-direction), the second row can represent shot point pile No. (can be understood as Y-direction), and the adjacent big gun of random like has disturbed
The elimination of effect.Fig. 6 is the adjacent big gun interference of three-dimensional common detector gather data separating in aliased seismic data in the embodiment of the present application
Schematic diagram, as shown in fig. 6, ordinate can represent the time in figure, in abscissa the first row can represent big gun wire size (it is appreciated that
For X-direction), the second row can represent shot point pile No. (can be understood as Y-direction), and useful signal is not found in the noise of elimination
Damage.
B14, judge whether three-dimensional common detector gather data are disposed, if so, B15 is performed, if otherwise repeating to walk
Rapid B2 to step B14 carries out at the SNR estimation and compensation based on sparse inversion the three-dimensional common detector gather data after other fractionations
Reason.
B15, the corresponding SNR estimation and compensation data of each three-dimensional common detector gather data are integrated, obtains aliased seismic
The SNR estimation and compensation data of data complete the SNR estimation and compensation of entire aliasing acquisition seismic data.Fig. 7 is aliasing in the embodiment of the present application
Stacked section schematic diagram before seismic data separation, abscissa can represent Taoist monastic name in figure, and ordinate can represent the time, such as scheme
Shown in 7, substantial amounts of neighbour's big gun serious interference reduces earthquake signal-to-noise ratio and image quality.Fig. 8 is aliasing in the embodiment of the present application
The useful signal stacked section schematic diagram after data separating is shaken, abscissa can represent Taoist monastic name in figure, when ordinate can represent
Between, as shown in figure 8, the method in the embodiment of the present application, after carrying out SNR estimation and compensation processing to aliased seismic data, eliminates adjacent big gun
Interference, useful signal are highlighted, and lineups continuity enhancing, signal-to-noise ratio significantly improves.
The aliased data separation method based on sparse inversion that the application provides splits aliasing acquisition seismic data first,
Three dimensional fast Fourier direct transform is done to common detector gather, determines threshold contracting function.Then useful signal data are carried out
Three-dimensional sliding window Fourier direct transform, the processing of transform domain data threshold, it is three-dimensional slide space-time window Fast Fourier Transform Inverse and
Useful signal data are pre-processed to merge.Useful signal data prediction neighbour's big gun interference noise is pre-processed according to obtaining, and from three-dimensional altogether
It is subtracted in geophone station trace gather, updates useful signal data.Finally to all three-dimensional common detector gather iteration refutation processes,
Complete aliasing gathered data SNR estimation and compensation.Space-time window is slided using three-dimensional and chooses local earthquake's data, make use of useful signal number
According to local linear feature, improve sparse degree of the signal in Fourier transform domain, improve aliased seismic data noise point
From effect.Meanwhile using sparse-constrained inversion, Fast Fourier Transform (FFT), threshold contracting function etc., convergence rate is accelerated,
Improve computational efficiency.
Based on the aliased data separation method described above based on sparse inversion, this specification one or more embodiment
A kind of aliased data separator based on sparse inversion is also provided.The device can include the use of this specification implementation
The example system (including distributed system) of the method, software (application), module, component, server, client etc. and with reference to must
The device for the implementation hardware wanted.Based on same innovation thinking, in one or more embodiments that this specification embodiment provides
Device is as described in the following examples.Since the implementation that device solves the problems, such as is similar to method, this specification is implemented
The implementation of the specific device of example may refer to the implementation of preceding method, and overlaps will not be repeated.It is used below, term
" unit " or " module " can realize the combination of the software and/or hardware of predetermined function.Although following embodiment is described
Device is preferably realized with software, but the realization of the combination of hardware or software and hardware is also what may and be contemplated.
Specifically, Fig. 9 is the mould of aliased data separator one embodiment based on sparse inversion that the application provides
Block structure schematic diagram, as shown in figure 9, the aliased data separator provided herein based on sparse inversion includes：Aliasing
Data split module 91, threshold function structure module 92, and sparse object function builds module 93, alternate analysis module 94.
Aliased data splits module 91, can be used for splitting aliased seismic data, obtains three-dimensional common receiver road
Collect data；
Threshold function builds module 92, can be used for shrinking letter according to the three-dimensional common detector gather data structure threshold
Number；
Sparse object function builds module 93, can be used for building sparse constraint target letter based on the aliased seismic data
Number, the sparse constraint object function include the functional relation between the aliased seismic data and useful signal data；
Alternate analysis module 94 can be used for according to the threshold contracting function, and three-dimensional using structure slides space-time window
Inverting solution is iterated to the sparse constraint object function, obtains the SNR estimation and compensation data of the aliased seismic data.
The aliased data separator based on sparse inversion that the application provides, it is provided by the embodiments of the present application based on sparse
The aliased data separation method of inverting employs sparse-constrained inversion method and threshold contracting function, accelerates iterative inversion
Convergence rate improves the efficiency of data processing.Meanwhile the local line of seismic data can be improved using the three-dimensional space-time window that slides
Property feature improves the separating effect of seismic data.
On the basis of above-described embodiment, the alternate analysis module is specifically used for：
Perform the first processing step：
It is selected using the three-dimensional space-time window that slides from the currently active signal data in the sparse constraint object function
Take local earthquake's data；
Pretreatment useful signal is obtained into threshold trip processing to local earthquake's data according to the threshold contracting function
Data；
According to pretreatment useful signal data prediction neighbour's big gun interference noise；
According to the three-dimensional common detector gather data and the adjacent big gun interference noise, iteration useful signal data are obtained；
Judge whether current iteration number is less than and preset total iterations, if being less than, by the iteration useful signal number
According to as the currently active signal data, first processing step is repeated, until the current iteration number is more than or equal to
During default total iterations, using the iteration useful signal data as the SNR estimation and compensation data.
The aliased data separator based on sparse inversion that the application provides slides space-time window using three-dimensional and chooses effectively
Local earthquake's data in signal with reference to Fast Fourier Transform (FFT) and threshold contracting function, accelerate the speed of iteration convergence, carry
High computational efficiency.The local linear feature of useful signal is make use of, sliding space-time window by three-dimensional is handled, and is improved signal and is existed
The sparse degree of Fourier transform domain, significantly improves the separating effect of aliased seismic data, improves signal-to-noise ratio, improve
Image quality.
Need what is illustrated, device described above can also include other embodiment party according to the description of embodiment of the method
Formula, concrete implementation mode are referred to the description of related method embodiment, do not repeat one by one herein.
It is above-mentioned that this specification specific embodiment is described.Other embodiments are in the scope of the appended claims
It is interior.In some cases, the action recorded in detail in the claims or step can be come according to different from the order in embodiment
It performs and still can realize desired result.In addition, the process described in the accompanying drawings not necessarily require show it is specific suitable
Sequence or consecutive order could realize desired result.In some embodiments, multitasking and parallel processing be also can
With or it may be advantageous.
Above-mentioned the aliased data separation method or device based on sparse inversion that this specification embodiment provides can counted
Corresponding program instruction is performed to realize by processor in calculation machine, it is such as real at PC ends using the c++ language of windows operating systems
Existing, Linux system realize or other for example realized using android, iOS system programming language in intelligent terminal and
Processing logic realization based on quantum computer etc..A kind of aliased data separation dress based on sparse inversion that this specification provides
In another embodiment put, Figure 10 is that another aliased data separator based on sparse inversion that the application provides is implemented
The modular structure schematic diagram of example, as shown in Figure 10, the aliased data based on sparse inversion point that another embodiment of the application provides
It can include processor 101 and memory 102 for storing processor-executable instruction from device,
Processor 101 and memory 102 complete mutual communication by bus 103；
The processor 101 is used to call the program instruction in the memory 102, above-mentioned respectively based on sparse anti-to perform
The method that the aliased data separation method embodiment drilled is provided, such as including：Aliased seismic data is split, obtains three
Tie up common detector gather data；According to the three-dimensional common detector gather data structure threshold contracting function, the threshold is shunk
Function includes the relation between iterations and seismic data amplitude scope；It is sparse about based on aliased seismic data structure
Beam object function, the function that the sparse constraint object function is included between the aliased seismic data and useful signal data close
System；According to the threshold contracting function, changed using the three-dimensional space-time window that slides of structure to the sparse constraint object function
For inverting, the SNR estimation and compensation data of the aliased seismic data are obtained.
It should be noted that specification device described above can also include it according to the description of related method embodiment
His embodiment, concrete implementation mode are referred to the description of embodiment of the method, do not repeat one by one herein.In the application
Each embodiment described by the way of progressive, just to refer each other for identical similar part between each embodiment, often
What a embodiment stressed is all difference from other examples.For hardware+program class embodiment,
Since it is substantially similar to embodiment of the method, so description is fairly simple, related part is said referring to the part of embodiment of the method
It is bright.
This specification embodiment is not limited to meet industry communication standard, standard computer data processing sum number
According to storage rule or the described situation of this specification one or more embodiment.The right way of conduct is made in some professional standards or use by oneself
In formula or the practice processes of embodiment description embodiment amended slightly can also realize above-described embodiment it is identical, it is equivalent or
The implementation result being anticipated that after close or deformation.Using these modifications or deformed data acquisition, storage, judgement, processing side
The embodiment of the acquisitions such as formula still may belong within the scope of the optional embodiment of this specification embodiment.
In the 1990s, can clearly be distinguished for the improvement of a technology be on hardware improvement (for example,
Improvement to circuit structures such as diode, transistor, switches) or software on improvement (improvement for method flow).So
And with the development of technology, the improvement of current many method flows can be considered as directly improving for hardware circuit.
Improved method flow nearly all by being programmed into hardware circuit to obtain corresponding hardware circuit by designer.Cause
This, it cannot be said that the improvement of a method flow cannot be realized with hardware entities module.For example, programmable logic device
(Programmable Logic Device, PLD) (such as field programmable gate array (Field Programmable Gate
Array, FPGA)) it is exactly such a integrated circuit, logic function determines device programming by user.By designer
Voluntarily programming comes a digital display circuit " integrated " on a piece of PLD, without chip maker is asked to design and make
Dedicated IC chip.Moreover, nowadays, substitution manually makes IC chip, this programming is also used instead mostly " patrols
Volume compiler (logic compiler) " software realizes that software compiler used is similar when it writes with program development,
And the source code before compiling also write by handy specific programming language, this is referred to as hardware description language
(Hardware Description Language, HDL), and HDL is also not only a kind of, but there are many kind, such as ABEL
(Advanced Boolean Expression Language)、AHDL(Altera Hardware Description
Language)、Confluence、CUPL(Cornell University Programming Language)、HDCal、JHDL
(Java Hardware Description Language)、Lava、Lola、MyHDL、PALASM、RHDL(Ruby
Hardware Description Language) etc., VHDL (Very-High-Speed are most generally used at present
Integrated Circuit Hardware Description Language) and Verilog.Those skilled in the art also should
This understands, it is only necessary to method flow slightly programming in logic and is programmed into integrated circuit with above-mentioned several hardware description languages,
The hardware circuit for realizing the logical method flow can be readily available.
Controller can be implemented in any suitable manner, for example, controller can take such as microprocessor or processing
The computer for the computer readable program code (such as software or firmware) that device and storage can be performed by (micro-) processor can
Read medium, logic gate, switch, application-specific integrated circuit (Application Specific Integrated Circuit,
ASIC), the form of programmable logic controller (PLC) and embedded microcontroller, the example of controller include but not limited to following microcontroller
Device：ARC 625D, Atmel AT91SAM, Microchip PIC18F26K20 and Silicone Labs C8051F320, are deposited
Memory controller is also implemented as a part for the control logic of memory.It is also known in the art that except with
Pure computer readable program code mode is realized beyond controller, can be made completely by the way that method and step is carried out programming in logic
Controller is obtained in the form of logic gate, switch, application-specific integrated circuit, programmable logic controller (PLC) and embedded microcontroller etc. to come in fact
Existing identical function.Therefore this controller is considered a kind of hardware component, and various to being used to implement for including in it
The device of function can also be considered as the structure in hardware component.Or even, the device for being used to implement various functions can be regarded
For either the software module of implementation method can be the structure in hardware component again.
System, device, module or the unit that above-described embodiment illustrates can specifically realize by computer chip or entity,
Or it is realized by having the function of certain product.A kind of typical realization equipment is computer.Specifically, computer for example may be used
Think personal computer, laptop computer, vehicle-mounted human-computer interaction device, cellular phone, camera phone, smart phone, individual
Digital assistants, media player, navigation equipment, electronic mail equipment, game console, tablet computer, wearable device or
The combination of any equipment in these equipment of person.
Although this specification one or more embodiment provides the method operating procedure as described in embodiment or flow chart,
But either it can include more or less operating procedures without creative means based on conventional.The step of being enumerated in embodiment
Order is only a kind of mode in numerous step execution sequences, does not represent unique execution sequence.Device in practice or
When end product performs, can according to embodiment either method shown in the drawings order perform or it is parallel perform it is (such as parallel
The environment of processor or multiple threads, even distributed data processing environment).Term " comprising ", "comprising" or its
Any other variant is intended to non-exclusive inclusion so that process, method, product including a series of elements or
Equipment not only include those elements, but also including other elements that are not explicitly listed or further include for this process,
Method, product or the intrinsic element of equipment.In the absence of more restrictions, it is not precluded from including the element
Also there are other identical or equivalent elements in process, method, product or equipment.The first, the second grade words are used for representing name
Claim, and do not represent any particular order.
For convenience of description, it is divided into various modules during description apparatus above with function to describe respectively.Certainly, this is being implemented
The function of each module is realized can in the same or multiple software and or hardware during specification one or more, it can also
The module for realizing same function is realized by the combination of multiple submodule or subelement etc..Device embodiment described above is only
It is only illustrative, for example, the division of the unit, is only a kind of division of logic function, can have in actual implementation in addition
Dividing mode, such as multiple units or component may be combined or can be integrated into another system or some features can be with
Ignore or do not perform.Another, shown or discussed mutual coupling, direct-coupling or communication connection can be logical
Some interfaces are crossed, the INDIRECT COUPLING or communication connection of device or unit can be electrical, machinery or other forms.
The present invention be with reference to according to the method for the embodiment of the present invention, the flow of device (system) and computer program product
Figure and/or block diagram describe.It should be understood that it can be realized by computer program instructions every first-class in flowchart and/or the block diagram
The combination of flow and/or box in journey and/or box and flowchart and/or the block diagram.These computer programs can be provided
The processor of all-purpose computer, special purpose computer, Embedded Processor or other programmable data processing devices is instructed to produce
A raw machine so that the instruction performed by computer or the processor of other programmable data processing devices is generated for real
The device for the function of being specified in present one flow of flow chart or one box of multiple flows and/or block diagram or multiple boxes.
These computer program instructions, which may also be stored in, can guide computer or other programmable data processing devices with spy
Determine in the computer-readable memory that mode works so that the instruction generation being stored in the computer-readable memory includes referring to
Make the manufacture of device, the command device realize in one flow of flow chart or multiple flows and/or one box of block diagram or
The function of being specified in multiple boxes.
These computer program instructions can be also loaded into computer or other programmable data processing devices so that counted
Series of operation steps is performed on calculation machine or other programmable devices to generate computer implemented processing, so as in computer or
The instruction offer performed on other programmable devices is used to implement in one flow of flow chart or multiple flows and/or block diagram one
The step of function of being specified in a box or multiple boxes.
In a typical configuration, computing device includes one or more processors (CPU), input/output interface, net
Network interface and memory.
Memory may include computer-readable medium in volatile memory, random access memory (RAM) and/or
The forms such as Nonvolatile memory, such as read-only memory (ROM) or flash memory (flash RAM).Memory is computer-readable medium
Example.
Computer-readable medium includes permanent and non-permanent, removable and non-removable media can be by any method
Or technology come realize information store.Information can be computer-readable instruction, data structure, the module of program or other data.
The example of the storage medium of computer includes, but are not limited to phase transition internal memory (PRAM), static RAM (SRAM), moves
State random access memory (DRAM), other kinds of random access memory (RAM), read-only memory (ROM), electric erasable
Programmable read only memory (EEPROM), fast flash memory bank or other memory techniques, read-only optical disc read-only memory (CD-ROM),
Digital versatile disc (DVD) or other optical storages, magnetic tape cassette, the storage of tape magnetic rigid disk, graphene stores or other
Magnetic storage apparatus or any other non-transmission medium, the information that can be accessed by a computing device available for storage.According to herein
In define, computer-readable medium does not include the data of temporary computer readable media (transitory media), such as modulation
Signal and carrier wave.
It will be understood by those skilled in the art that this specification one or more embodiment can be provided as method, system or calculating
Machine program product.Therefore, this specification one or more embodiment can be used complete hardware embodiment, complete software embodiment or
With reference to the form of the embodiment in terms of software and hardware.Moreover, this specification one or more embodiment can be used at one or
It is multiple wherein include computer usable program code computer-usable storage medium (include but not limited to magnetic disk storage,
CD-ROM, optical memory etc.) on the form of computer program product implemented.
Each embodiment in this specification is described by the way of progressive, identical similar portion between each embodiment
Point just to refer each other, and the highlights of each of the examples are difference from other examples.It is real especially for system
For applying example, since it is substantially similar to embodiment of the method, so description is fairly simple, related part is referring to embodiment of the method
Part explanation.In the description of this specification, reference term " one embodiment ", " some embodiments ", " example ",
The description of " specific example " or " some examples " etc. means to combine specific features, structure, material that the embodiment or example describe
Or feature is contained at least one embodiment or example of this specification.In the present specification, to the signal of above-mentioned term
Property statement be necessarily directed to identical embodiment or example.Moreover, particular features, structures, materials, or characteristics described
It may be combined in any suitable manner in any one or more of the embodiments or examples.In addition, without conflicting with each other, this
The technical staff in field can be by the different embodiments described in this specification or example and different embodiments or exemplary spy
Sign is combined and combines.
The foregoing is merely the embodiments of this specification one or more embodiment, are not limited to book explanation
Book one or more embodiment.To those skilled in the art, this specification one or more embodiment can have various
Change and variation.All any modifications, equivalent replacements and improvements are made within spirit herein and principle, should all include
Within right.
Claims (10)
1. a kind of aliased data separation method based on sparse inversion, which is characterized in that including：
Aliased seismic data is split, obtains three-dimensional common detector gather data；
According to the three-dimensional common detector gather data structure threshold contracting function, the threshold contracting function includes iterations
With the relation between seismic data amplitude scope；
Sparse constraint object function is built based on the aliased seismic data, the sparse constraint object function includes the aliasing
Functional relation between seismic data and useful signal data；
According to the threshold contracting function, changed using the three-dimensional space-time window that slides of structure to the sparse constraint object function
It is solved for inverting, obtains the SNR estimation and compensation data of the aliased seismic data.
A kind of 2. aliased data separation method based on sparse inversion as described in claim 1, which is characterized in that the basis
The threshold contracting function is iterated inverting to the sparse constraint object function using the three-dimensional slip space-time window of structure and asks
Solution obtains the SNR estimation and compensation data of the aliased seismic data, including：
Perform the first processing step：
Utilize three-dimensional slip space-time window selection office from the currently active signal data in the sparse constraint object function
Portion's seismic data；
Pretreatment useful signal number is obtained into threshold trip processing to local earthquake's data according to the threshold contracting function
According to；
According to pretreatment useful signal data prediction neighbour's big gun interference noise；
The adjacent big gun interference noise is subtracted from the three-dimensional common detector gather data, obtains iteration useful signal data；
Judge whether current iteration number is less than and preset total iterations, if being less than, the iteration useful signal data are made
For the currently active signal data, first processing step is repeated, until the current iteration number is more than or equal to described
When presetting total iterations, using the iteration useful signal data as the SNR estimation and compensation data.
A kind of 3. aliased data separation method based on sparse inversion as claimed in claim 2, which is characterized in that the basis
For the threshold contracting function to local earthquake's data into threshold trip processing, acquisition pre-processes useful signal data, including：
Three dimensional fast Fourier direct transform is carried out to local earthquake's data, obtains direct transform Fourier data；
The corresponding threshold value of current iteration number is obtained according to the threshold contracting function, it will be in the direct transform Fourier data
Seismic data less than the threshold value is set to zero, obtains threshold processing data；
Threshold processing data are subjected to three dimensional fast Fourier inverse transformation, obtain the pretreatment useful signal data.
4. a kind of aliased data separation method based on sparse inversion as claimed in claim 3, which is characterized in that described by institute
It states threshold processing data and carries out three dimensional fast Fourier inverse transformation, obtain the pretreatment useful signal data, including：
Threshold processing data are subjected to three dimensional fast Fourier inverse transformation, current three-dimensional is obtained and slides the corresponding office of space-time window
Portion pre-processes useful signal data；
Judge whether the seismic data in the currently active signal data is all selected, if it is not, then sliding described three-dimensional sliding
Dynamic space-time window, obtains the corresponding local earthquake's data of next three-dimensional slip space-time window, and threshold trip of going forward side by side processing obtains next
Three-dimensional slides the corresponding local pretreatment useful signal data of space-time window；
If so, each three-dimensional corresponding part of space-time window of sliding is pre-processed useful signal data, integrated, after integration
Useful signal data, as the corresponding pretreatment useful signal data of the currently active signal data.
5. a kind of aliased data separation method based on sparse inversion as described in claim 1, which is characterized in that described sparse
Constrained objective function includes：
<mrow>
<mi>J</mi>
<mrow>
<mo>(</mo>
<mi>m</mi>
<mo>)</mo>
</mrow>
<mo>=</mo>
<mfrac>
<mn>1</mn>
<mn>2</mn>
</mfrac>
<mo>|</mo>
<mo>|</mo>
<mi>d</mi>
<mo>-</mo>
<mi>&Gamma;</mi>
<mi>m</mi>
<mo>|</mo>
<msubsup>
<mo>|</mo>
<mn>2</mn>
<mn>2</mn>
</msubsup>
<mo>+</mo>
<mi>&lambda;</mi>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>i</mi>
<mi>x</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<mrow>
<mi>n</mi>
<mi>x</mi>
</mrow>
</munderover>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>i</mi>
<mi>y</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<mrow>
<mi>n</mi>
<mi>y</mi>
</mrow>
</munderover>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>i</mi>
<mi>t</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<mrow>
<mi>n</mi>
<mi>t</mi>
</mrow>
</munderover>
<mo>|</mo>
<mo>|</mo>
<msub>
<mi>FW</mi>
<mrow>
<mi>i</mi>
<mi>x</mi>
<mo>,</mo>
<mi>i</mi>
<mi>y</mi>
<mo>,</mo>
<mi>i</mi>
<mi>t</mi>
</mrow>
</msub>
<mi>m</mi>
<mo>|</mo>
<msub>
<mo>|</mo>
<mn>0</mn>
</msub>
</mrow>
In above formula,Represent error term, d represents the aliased seismic data, and m represents useful signal data, Γ tables
Show aliasing operator,Represent bound term, the slip space-time window of nx representation space X-directions
Window number, the window number of the slip space-time window of ny representation space Y-directions, nt represent the slip space-time window in time t direction
Window number, F represent three dimensional fast Fourier direct transform operator, Wix,iy,itIt represents on space X, space Y, time T direction
Three-dimensional slides space-time window operator, | | FWix,iy,itm||0Expression takes L0Norm, λ represent regularization parameter.
A kind of 6. aliased data separation method based on sparse inversion as described in claim 1, which is characterized in that the basis
The three-dimensional common detector gather data structure threshold contracting function, including：
Fast Fourier direct transform is carried out to the three-dimensional common detector gather data, obtains the three-dimensional common detector gather number
According to peak swing value and minimum amplitude value；
According to the peak swing value and the minimum amplitude value, the threshold contracting function is built.
A kind of 7. aliased data separation method based on sparse inversion as claimed in claim 6, which is characterized in that the threshold
Contracting function includes：
<mrow>
<mi>T</mi>
<mrow>
<mo>(</mo>
<mi>k</mi>
<mo>)</mo>
</mrow>
<mo>=</mo>
<mi>T</mi>
<mi>m</mi>
<mi>a</mi>
<mi>x</mi>
<mo>*</mo>
<msup>
<mrow>
<mo>(</mo>
<mfrac>
<mrow>
<mi>T</mi>
<mi>m</mi>
<mi>i</mi>
<mi>n</mi>
</mrow>
<mrow>
<mi>T</mi>
<mi>m</mi>
<mi>a</mi>
<mi>x</mi>
</mrow>
</mfrac>
<mo>)</mo>
</mrow>
<mfrac>
<mi>k</mi>
<mi>N</mi>
</mfrac>
</msup>
<mo>,</mo>
<mi>k</mi>
<mo>=</mo>
<mn>1</mn>
<mo>,</mo>
<mn>2</mn>
<mo>,</mo>
<mo>...</mo>
<mo>,</mo>
<mi>N</mi>
</mrow>
In above formula, T (k) represents the threshold value of kth time iteration, and N represents total iterations.
8. a kind of aliased data separator based on sparse inversion, which is characterized in that including：
Aliased data splits module, for being split to aliased seismic data, obtains three-dimensional common detector gather data；
Threshold function builds module, for according to the three-dimensional common detector gather data structure threshold contracting function；
Sparse object function builds module, described dilute for being based on the aliased seismic data structure sparse constraint object function
Dredging constrained objective function includes the functional relation between the aliased seismic data and useful signal data；
Alternate analysis module, for according to the threshold contracting function, space-time window to be slided to described sparse using the three-dimensional of structure
Constrained objective function is iterated inverting solution, obtains the SNR estimation and compensation data of the aliased seismic data.
A kind of 9. aliased data separator based on sparse inversion as claimed in claim 8, which is characterized in that the iteration
Separation module is specifically used for：
Perform the first processing step：
Utilize three-dimensional slip space-time window selection office from the currently active signal data in the sparse constraint object function
Portion's seismic data；
Pretreatment useful signal number is obtained into threshold trip processing to local earthquake's data according to the threshold contracting function
According to；
According to pretreatment useful signal data prediction neighbour's big gun interference noise；
The adjacent big gun interference noise is subtracted from the three-dimensional common detector gather data, obtains iteration useful signal data；
Judge whether current iteration number is less than and preset total iterations, if being less than, the iteration useful signal data are made
For the currently active signal data, first processing step is repeated, until the current iteration number is more than or equal to described
When presetting total iterations, using the iteration useful signal data as the SNR estimation and compensation data.
10. a kind of aliased data separator based on sparse inversion, which is characterized in that at including processor and for storage
The memory of device executable instruction is managed, the processor is realized when performing described instruction such as any one institute in claim 1 to 7
The step of stating method.
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| CN109521456A (en) * | 2018-09-25 | 2019-03-26 | 中国辐射防护研究院 | A kind of gamma emitter item inversion method and system based on regularization least square method |
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| CN111273353A (en) * | 2020-02-12 | 2020-06-12 | 同济大学 | Intelligent seismic data de-aliasing method and system based on U-Net network |
| CN113568033A (en) * | 2020-04-28 | 2021-10-29 | 中国石油天然气集团有限公司 | Design method and device of three-dimensional irregular sampling seismic acquisition observation system |
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| CN111399057B (en) * | 2020-05-14 | 2021-06-22 | 中国海洋石油集团有限公司 | Seismic data noise suppression method based on non-convex sparse constraint |
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