CN110174702A - A kind of method and system that marine seismic data low frequency weak signal is restored - Google Patents
A kind of method and system that marine seismic data low frequency weak signal is restored Download PDFInfo
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Abstract
The application discloses a kind of method and system that marine seismic data low frequency weak signal is restored, this method comprises: obtaining seismic channel data seeks primary reflection coefficient, convolution obtains the first earthquake record data；The first residual error of the first earthquake record data and seismic channel data is calculated, modification reflection coefficient obtains the first intensive reflection coefficient sequence；The second earthquake record data are obtained using the first intensive reflection coefficient sequence and the far-field wavelet phase convolution of Yu wavelet spectrum constraint；The second residual error of the second earthquake record data and seismic channel data is calculated, modification reflection coefficient obtains the second intensive reflection coefficient sequence；Iterative calculation obtains the reflection coefficient of low frequency weak signal recovery；Constrain far-field wavelet, the broadband wavelet for the low frequency weak signal that is restored；Convolution obtains the seismic data after low frequency restoration.The present invention realizes that frequency domain seeks low frequency end weighted factor, to restore the low frequency signal of seismic energy source.
Description
Technical field
The present invention relates to the technical fields in Seismic Exploration Data Processing, more particularly, to a kind of marine seismic data
The method and system that low frequency weak signal is restored.
Background technique
With the requirement of the increasingly complicated and marine fining exploration of exploitation Oil-gas Accumulation Types, low frequency signal is due to penetrability
By force, the slow feature that decays meets such demand just and receives extensive attention and utilize.Theory and practice shows enhancing
Low frequency restores low frequency end weak signal, can greatly improve the resolution ratio of seismic data, improve the subsequent inverting of seismic data
Stability and reliability.The recovery of low frequency weak signal is one of the important research content of Modern seismic data processing, and currently grinds
The hot and difficult issue studied carefully.
At sea in seismic data acquisition process, due to the influence of ghosting, there are trap effect, especially low frequency to signal
End, the low frequency signal of 0-10Hz, which will receive, to be seriously affected, cause signal extremely faint, seismic data recording arrive almost be also-
24DB signal below, therefore by going ghosting that low frequency end weak signal can be improved in seism processing；Compressed sensing
It is another technology for restoring weak signal, compressive sensing theory is as a kind of new sampling theory, using non-adaptive linear throwing
Shadow keeps the prototype structure of signal, by developing the sparse characteristic of signal, under conditions of being much smaller than Nyquist sample rate, and benefit
The discrete sample of signal is obtained with stochastical sampling, then passes through the complete reconstruction signal of non-linear algorithm for reconstructing.Its method flow master
To include stochastical sampling, sparse signal representation, signal reconstruction, Combined Treatment is perceived by Local Contraction perception and area compresses,
Local homogenization and region homogenization noise can be suppressed, weaker useful signal is enhanced.
And in practical applications, low frequency end weak signal can be improved by ghosting compacting, but since ghosting is primary
" tail " of wave, is difficult to separate with significant wave, after the ghosting that decayed, significant wave is caused largely also to incur loss,
After ghosting is suppressed, phase polarity is also changed, and is unfavorable for explaining；Pass through the low frequency signal enhanced after compressed sensing
It is current research hotspot and difficult point, but it becomes unstable characteristic and affected by noise because of the space-time by seismic wavelet,
The effect of inverting is not fine, easily generates noise while restoring low frequency weak signal, cause restore low frequency after signal because
Noise is too big and is difficult to be widely applied, and time-consuming serious.Therefore it provides a kind of undistorted and simple marine seismic data is low
The scheme that frequency weak signal is restored is this field technical problem urgently to be resolved.
Summary of the invention
In view of this, being solved the present invention provides the method and system that a kind of marine seismic data low frequency weak signal is restored
Marine seismic data low frequency weak signal restores distortion and time-consuming serious technical problem in the prior art.
In order to solve the above-mentioned technical problem, the present invention proposes a kind of method that marine seismic data low frequency weak signal is restored,
Include:
Seismic channel data is obtained, primary reflection coefficient is sought using mixing norm Sparse Pulse Inversion, it will be described original anti-
It penetrates coefficient and the far-field wavelet phase convolution of Yu wavelet spectrum constraint obtains the first earthquake record data；
The first residual error of the first earthquake record data Yu the seismic channel data is calculated, and utilizes first residual error
It modifies the reflection coefficient and obtains the first intensive reflection coefficient sequence；
It is obtained using the described first intensive reflection coefficient sequence and the far-field wavelet phase convolution of Yu wavelet spectrum constraint
Second earthquake record data；The second residual error of the second earthquake record data Yu the seismic channel data is calculated, and utilizes institute
It states reflection coefficient described in the second residual modification and obtains the second intensive reflection coefficient sequence；Iterative calculation obtains the recovery of low frequency weak signal
Reflection coefficient；
Constraint far-field wavelet, the broadband wavelet for the low frequency weak signal that is restored are composed using Yu wavelet；
The reflection coefficient and the broadband wavelet convolution restored using the low frequency weak signal obtains the ground after low frequency restoration
Shake data.
Optionally, wherein it is described that primary reflection coefficient is sought using mixing norm Sparse Pulse Inversion, further comprise:
The seismic channel data convolution synthetic seismogram data are written as Matrix-Vector form: D=WR+N, wherein
The D is earthquake record data；The W is the correspondence Wavelet Martrix of seismic wavelet construction；The R is discrete seismic reflection system
Number；The N is the noise of addition；Using method of regularization solve above-mentioned matrix-vector equation obtain the primary reflection coefficient and
The noise of addition.
Optionally, wherein it is extensive that the reflection coefficient and far-field wavelet convolution restored using the low frequency weak signal obtains low frequency
Seismic data after multiple, are as follows:
The far-field wavelet of the reflection coefficient and acquisition focal shock parameter simulation that are restored using the low frequency weak signal, and/or it is real
The far-field wavelet convolution of survey obtains the seismic data after low frequency restoration.
Optionally, wherein seismic channel data is obtained, primary reflection coefficient is sought using mixing norm Sparse Pulse Inversion,
Further are as follows:
Seismic channel data is obtained, composes constraint far-field wavelet, the cummerbund for the low frequency weak signal that is restored using Yu wavelet
Wave；
Analysis obtains road number of the seismic channel data in spatial frequency domain in spatial window, using intermediate value, mean value or intermediate value
Estimate to obtain mixing norm sparse model with the form of mean value combination；
It seeks obtaining primary reflection coefficient using mixing norm sparse model and seismic channel data.
Optionally, wherein the first intensive reflection coefficient sequence and the second intensive reflection coefficient sequence, all in accordance with first
Residual error or the second residual error size are obtained using conjugate gradient algorithms and determination.
On the other hand, the present invention also provides the systems that a kind of marine seismic data low frequency weak signal is restored, comprising: the first ground
Shake record data processor, the first intensive reflection coefficient sequence processor, reflection coefficient processor, broadband wavelet processor and low
Frequently extensive seismic data process device；Wherein,
The first earthquake record data processor is connected with the described first intensive reflection coefficient sequence processor, obtains
Seismic channel data is taken, primary reflection coefficient is sought using mixing norm Sparse Pulse Inversion, by the primary reflection coefficient and Yu
The far-field wavelet phase convolution of family name's wavelet spectrum constraint obtains the first earthquake record data；
The first intensive reflection coefficient sequence processor, with the first earthquake record data processor and reflection coefficient
Processor is connected, and calculates the first residual error of the first earthquake record data and the seismic channel data, and utilization described the
Reflection coefficient described in one residual modification obtains the first intensive reflection coefficient sequence；
At the reflection coefficient processor, with the described first intensive reflection coefficient sequence processor and the extensive seismic data of low frequency
Reason device is connected, and is obtained using the described first intensive reflection coefficient sequence and the far-field wavelet phase convolution of Yu wavelet spectrum constraint
To the second earthquake record data；The second residual error of the second earthquake record data Yu the seismic channel data is calculated, and is utilized
Reflection coefficient described in second residual modification obtains the second intensive reflection coefficient sequence；It is extensive that iterative calculation obtains low frequency weak signal
Multiple reflection coefficient；
The broadband wavelet processor is connected with the extensive seismic data process device of the low frequency, about using Yu wavelet spectrum
Beam far-field wavelet, the broadband wavelet for the low frequency weak signal that is restored；
The extensive seismic data process device of low frequency, is connected with the reflection coefficient processor and broadband wavelet processor,
The reflection coefficient and the broadband wavelet convolution restored using the low frequency weak signal obtains the seismic data after low frequency restoration.
Optionally, wherein the first earthquake record data processor further comprises: matrix-vector synthesis unit and
Reflection coefficient processing unit；Wherein,
The matrix-vector synthesis unit, for the seismic channel data convolution synthetic seismogram data to be written as square
Battle array-vector form: D=WR+N, wherein the D is earthquake record data；The W is the correspondence wavelet of seismic wavelet construction
Matrix；The R is discrete fractal；The N is the noise of addition；
The reflection coefficient processing unit obtains the original for solving above-mentioned matrix-vector equation using method of regularization
Beginning reflection coefficient and the noise of addition.
Optionally, wherein the extensive seismic data process device of low frequency further comprises: reflection coefficient and far-field wavelet number
According to acquiring unit and low frequency restoration seismic data process unit；Wherein,
The reflection coefficient and far-field wavelet data capture unit, the reflection system restored for obtaining the low frequency weak signal
Number and the far-field wavelet of acquisition focal shock parameter simulation, and/or the far-field wavelet of actual measurement；
The low frequency restoration seismic data process unit is used for the reflection coefficient and far-field wavelet in convolution model
Convolution obtains the seismic data after low frequency restoration.
Optionally, wherein the first earthquake record data processor, comprising: broadband wavelet processing unit, mixing norm
Sparse model optimizes unit and primary reflection coefficient processing unit；Wherein,
The broadband wavelet processing unit is composed constraint far-field wavelet using Yu wavelet, is obtained for obtaining seismic channel data
To the broadband wavelet for restoring low frequency weak signal；
The mixing norm sparse model optimizes unit, obtains seismic channel data space in spatial frequency domain for analyzing
Road number in window is estimated to obtain mixing norm sparse model in the form of intermediate value, mean value or intermediate value and mean value combination；
The primary reflection coefficient processing unit, for seeking obtaining using mixing norm sparse model and seismic channel data
Primary reflection coefficient.
Optionally, wherein the first intensive reflection coefficient sequence and the second intensive reflection coefficient sequence, all in accordance with first
Residual error or the second residual error size are obtained using conjugate gradient algorithms and determination.
Compared with prior art, the method and system that marine seismic data low frequency weak signal provided by the invention is restored, until
One of following beneficial effect is realized less:
(1) method and system that marine seismic data low frequency weak signal of the present invention is restored, based at seismic data
Convolution model is managed, reflection coefficient is sought using mixing norm Sparse Pulse Inversion first, after the influence for eliminating seismic wavelet, then with
The far-field wavelet phase convolution of Yu wavelet spectrum constraint, optimizes far-field wavelet under the premise of composing constraint, and it is low to realize that frequency domain is sought
Frequency end weighted factor, to restore the low frequency signal of seismic energy source.
(2) method and system that marine seismic data low frequency weak signal of the present invention is restored, based at seismic data
Convolution model is managed, reflection coefficient is sought using mixing norm Sparse Pulse Inversion first, after the influence for eliminating seismic wavelet, then with
The far-field wavelet phase convolution of Yu wavelet spectrum constraint, it is adaptable, it, can be with other than it can be good at being applied to horizontal cable
It is suitble to varying depth cable, OBC and OBN data；Signal-to-noise ratio retentivity is good, when expanding low frequency, will not raise low-frequency noise；Hi-fi of amplitude
Degree is high.
(3) method and system that marine seismic data low frequency weak signal of the present invention is restored uses mixing norm
The far-field wavelet being more of practical significance is utilized in inverting reflection coefficient, algorithmic stability, and effect has better fidelity, leads to
It crosses Yu wavelet spectrum constraint and restores low frequency weak signal and optimization phase, keep wavelet secondary lobe smaller, resolution ratio is higher, has stronger
It is explanatory.
Detailed description of the invention
It is combined in the description and the attached drawing for constituting part of specification shows the embodiment of the present invention, and even
With its explanation together principle for explaining the present invention.By reading referring to made by the following drawings to non-limiting embodiment institute
The detailed description of work, other features, objects and advantages will become more apparent upon:
Fig. 1 shows for the process for a kind of method that marine seismic data low frequency weak signal is restored described in the embodiment of the present invention
It is intended to；
Fig. 2 is that Yu wavelet filter described in the embodiment of the present invention responds schematic diagram；
Fig. 3 is the schematic diagram of the original seismic data data before low-frequency compensation described in the embodiment of the present invention；
Fig. 4 is the schematic diagram of the earthquake record data after low-frequency compensation by the method for the invention；
Fig. 5 is the process for the method that another marine seismic data low frequency weak signal is restored described in the embodiment of the present invention
Schematic diagram；
Fig. 6 is the process for the method that another marine seismic data low frequency weak signal described in the embodiment of the present invention is restored
Schematic diagram；
Fig. 7 shows for a kind of structure for the system that marine seismic data low frequency weak signal is restored described in the embodiment of the present invention
It is intended to；
Fig. 8 is the structure for the system that another marine seismic data low frequency weak signal is restored described in the embodiment of the present invention
Schematic diagram；
Fig. 9 is the structure for the system that another marine seismic data low frequency weak signal described in the embodiment of the present invention is restored
Schematic diagram；
Figure 10 is the knot for the system that another marine seismic data low frequency weak signal described in the embodiment of the present invention is restored
Structure schematic diagram.
Specific embodiment
The application is described in further detail with reference to the accompanying drawings and examples.It is understood that this place is retouched
The specific embodiment stated is used only for explaining related application, rather than the restriction to this application.It also should be noted that in order to
Convenient for description, part relevant to the application is illustrated only in attached drawing.
It should be noted that in the absence of conflict, the features in the embodiments and the embodiments of the present application can phase
Mutually combination.The application is described in detail below with reference to the accompanying drawings and in conjunction with the embodiments.
As shown in FIG. 1, FIG. 1 is the processes of the method for the marine seismic data low frequency weak signal recovery described in the present embodiment to show
It is intended to.Present embodiment discloses a kind of method for marine seismic data low frequency weak signal recovery technology, using far-field wavelet and pass through Yu Shi
Wavelet spectrum constraint obtains low frequency weighted factor and restores low frequency weak signal, rather than uses above two technology, after can effectively avoid
The two because of the ghosting factor is difficult to that standard or wavelet time-varying space-variant in azimuth is asked to cause statistical difference or strong noise that distortion is caused not protect width
The problem of, algorithm is simple, and parameter is readily selected.
The method that marine seismic data low frequency weak signal described in the present embodiment is restored, comprises the following steps that
Step 101 obtains seismic channel data, seeks primary reflection coefficient using mixing norm Sparse Pulse Inversion, will be former
Beginning reflection coefficient and the far-field wavelet phase convolution of Yu wavelet spectrum constraint obtain the first earthquake record data.
Convolution model is most basic, most classic theory in seism processing, is differentiated with this theory for the raising of guidance
Rate processing (widening low frequency end signal is the important component for improving resolution processes) is still current seismic data and improves and divides
The theoretical basis of resolution processing.This technology is based on seism processing convolution model, anti-using mixing norm Sparse Pulse first
It drills and seeks reflection coefficient, then the far-field wavelet phase convolution with Yu wavelet spectrum constraint, in the process of spectrum constraint shaping far-field wavelet
In, realize that frequency domain seeks low frequency weighted factor, to restore the low frequency signal information of signal source.
Step 102, the first residual error for calculating the first earthquake record data and seismic channel data, and utilize the first residual modification
Reflection coefficient obtains the first intensive reflection coefficient sequence.
Reflection coefficient is extracted from seismic channel according to sparse principle, and generates synthetic seismogram after wavelet convolution, benefit
With the size modification reflection coefficient of synthetic seismogram and the residual error of original seismic data, new more dense reflection coefficient is obtained
Sequence, then composite traces is done, such iteration obtains the reflection coefficient sequence that can most preferably approach seismic traces.Earthquake is cutd open
Face obtains reflection coefficient section via seismic wavelet effect is eliminated after mixing norm inverting.
And utilize the size modification reflection coefficient of the residual error of synthetic seismogram and original seismic data, then it can be according to altogether
The principle and residual error size of yoke gradient algorithm determine that cloth length obtains new intensive reflection coefficient sequence, then are made into composite traces, such as
This iteration is most preferably approached the reflection coefficient sequence of seismic traces.
Step 103 is obtained using the first intensive reflection coefficient sequence and the far-field wavelet phase convolution of Yu wavelet spectrum constraint
Second earthquake record data；The second residual error of the second earthquake record data and seismic channel data is calculated, and is repaired using the second residual error
Change reflection coefficient and obtains the second intensive reflection coefficient sequence；Iterative calculation obtains the reflection coefficient of low frequency weak signal recovery.
Optionally, the described first intensive reflection coefficient sequence and the second intensive reflection coefficient sequence, all in accordance with the first residual error
Or second residual error size using conjugate gradient algorithms and determination obtain.
Optionally, it is as follows to seek reflection coefficient method for mixing norm Sparse Pulse Inversion:
Based on convolution model, earthquake record d (t) is expressed as the relationship of seismic wavelet w (t) He reflection coefficient r (t) are as follows:
D (t)=w (t) * r (t)+n (t) (1.1)
Wherein n (t) is the noise of addition.R, D, N is enabled to respectively indicate discrete stratum reflection coefficient, earthquake record, addition
Noise, W be seismic wavelet w construction correspondence Wavelet Martrix, convolution model synthesis earthquake record be written as Matrix-Vector shape
Formula:
D=WR+N (1.2)
Directly equation (1.2) are solved with the solution by generation to noise and its reflection coefficient, it is therefore desirable to utilize regularization side
Method stable solution.Such as Linear Least Square problem:
In optimization problem, first item is observation data item, and the model of inversion result is made accordingly to approach reality as far as possible
Earthquake record, Section 2 are the instable regularization term of measurement solution, and c is referred to as regularizing operator, and α is regularization parameter.By
Noise complexity in real seismic record, be usually unsatisfactory for Gaussian noise it is assumed that so when data set has big residual error
Data even wrong data when, be based on l2The least-square inversion algorithm of norm will generate unstable even wrong knot
Fruit.Therefore, data fit term and regularization term are obtained using L1-L2 norm constraint:
Due to objective function be it is non-smooth, the solution of problem (1.4) uses linear programming algorithm, is calculated using conjugate gradient
Method and interior-point algohnhm are solved.
Step 104 composes constraint far-field wavelet, the broadband wavelet for the low frequency weak signal that is restored using Yu wavelet.
In seismic prospecting, the interpretation of seismic wavelet is mainly by the phase of wavelet, amplitude and the big factor shadow of frequency spectrum three
It rings.Finally if it is zero phase, bandwidth, low frequency is abundant, secondary lobe is small wavelet, then interpretation is strong for seismic profile.
The final purpose of Yu wavelet spectrum constraint far-field wavelet deconvolution is that seismic wavelet is made to obtain better interpretation,
Resolution ratio reaches higher.It selects different wavelets extremely important as desired output, is influenced by acquisition condition and geologic(al) factor, ground
Shake wavelet is the weak narrow-band wavelet of low-frequency pole, and the wavelet generally selected is band logical wavelet, Ricker wavelet, the former perdurabgility
Long, secondary lobe waveform is complicated, and the latter's sidelobe magnitudes are big, and frequency range is narrow, and are both theoretical wavelets, cannot parse reality well
Border data spectral characteristic, therefore we select a kind of new wavelet --- far-field wavelet, far-field wavelet is according to actual observation system
The seismic wavelet that system simulation or actual measurement obtain, but its phase characteristic is often minimum phase or mixed-phase, is unfavorable for solving
It releases, needs to carry out shaping to it, constraint far-field wavelet is composed using Yu wavelet, makes it that there is better phase characteristic.Then I
Using famous Geophysicist Yu Shoupeng professor research achievement, Yu wavelet is substantially Ricker wavelet in a certain range
Integral, expression formula are as follows:
Its frequency domain expression formula are as follows:
In above-mentioned expression formula, r (t) is Ricker wavelet, and q and p are the limits of integration of crest frequency in Yu wavelet parameter,
Qf、PfIt is the frequency domain transformation of q, p respectively, f is Ricker wavelet frequency.
Yu wavelet filter responds schematic diagram as shown in 2 institute of Figure of description, by adjusting PfParameter reconstruction low frequency is weak
Signal.Wherein, AMP is amplitude kurtosis, PfIt is frequency domain transformation respectively, FREQ is frequency.
(3) Yu wavelet spectrum constraint far-field wavelet, output restore the broadband wavelet of low frequency weak signal.Others can be increased
Optimization processing, such as the frequency domain of model trace is smooth, spatial domain is smooth, to obtain more stable, ideal model trace.To Mr. Yu
Seismic channel gives the road number in the spatial window in its spatial frequency domain, estimates the seismic channel in the model trace of the spatial window, model
The estimation mode in road can use intermediate value, mean value or intermediate value and the algorithm combination of mean value etc..Each seismic channel is all in accordance with above-mentioned
Mode estimates corresponding model trace automatically, is not necessarily to manual intervention.Further optimization processing, such as mould can also be increased to model trace
The frequency domain in type road is smooth, spatial domain is smooth etc., to obtain more stable, ideal model trace.
The amplitude of seismic wavelet, frequency spectrum, phase directly influence the interpretation of seismic inversion, and far-field wavelet is often root
The air gun source parameter simulation that observation system is acquired factually is surveyed to obtain.
Step 105, the reflection coefficient restored using low frequency weak signal and broadband wavelet convolution obtain the ground after low frequency restoration
Shake data.
As shown in Figure 3 and Figure 4, Fig. 3 is the schematic diagram of the original seismic data data before low-frequency compensation；Fig. 4 is to pass through this
The schematic diagram of earthquake record data after embodiment method low-frequency compensation.
In some alternative embodiments, the reflection coefficient and far-field wavelet convolution restored using the low frequency weak signal is obtained
Seismic data after to low frequency restoration, are as follows: the reflection coefficient and acquisition focal shock parameter restored using the low frequency weak signal is simulated
Far-field wavelet, and/or actual measurement far-field wavelet convolution obtain the seismic data after low frequency restoration.
Input acquisition air gun source parameter simulation far-field wavelet, or actual measurement far-field wavelet, the same analog submodule of actual measurement known to practice
Wave difference very little, actual production substantially uses Simulation of far-field wavelet, to reduce cost.
Marine seismic data low frequency weak signal restoration methods described in the present embodiment, it is anti-using mixing norm Sparse Pulse
It drills and seeks reflection coefficient, after the influence for eliminating seismic wavelet, then the far-field wavelet phase convolution with Yu wavelet spectrum constraint, it is composing about
Optimize far-field wavelet under the premise of beam, realizes that frequency domain seeks low frequency end weighted factor, to restore the low frequency signal of signal source.
It effectively prevents being difficult to ask quasi- because of the ghosting factor or wavelet time-varying space-variant in azimuth causes statistical difference or strong noise to cause to be distorted
The problem of not protecting width, algorithm is simple, adaptable, parameter is readily selected.
In some alternative embodiments, as shown in figure 5, for the weak letter of another marine seismic data low frequency in the present embodiment
Number restore method flow diagram, from method in Fig. 1 unlike, using mix norm Sparse Pulse Inversion seek it is original
Reflection coefficient further comprises:
The seismic channel data convolution synthetic seismogram data are written as Matrix-Vector form: D=WR by step 501
+ N, wherein the D is earthquake record data；The W is the correspondence Wavelet Martrix of seismic wavelet construction；The R is discrete ground
Shake reflection coefficient；The N is the noise of addition；
Step 502 is solved above-mentioned matrix-vector equation using method of regularization and obtains the primary reflection coefficient and addition
Noise.
In some alternative embodiments, as shown in fig. 6, for another weak letter of marine seismic data low frequency in the present embodiment
Number restore method flow diagram, from method in Fig. 1 unlike, obtain seismic channel data, using mix norm it is sparse
Pulse Inversion seeks primary reflection coefficient, further includes:
Step 601 obtains seismic channel data, composes constraint far-field wavelet using Yu wavelet, be restored low frequency weak signal
Broadband wavelet.
Step 602, analysis obtain road number of the seismic channel data in spatial frequency domain in spatial window, using intermediate value, mean value
Or intermediate value and the form of mean value combination are estimated to obtain mixing norm sparse model.
Step 603 is sought obtaining primary reflection coefficient using mixing norm sparse model and seismic channel data.
As shown in fig. 7, the structure for the system 700 of marine seismic data low frequency weak signal recovery a kind of in the present embodiment is shown
It is intended to, which is used to implement the method that the marine seismic data low frequency weak signal in above-described embodiment is restored, which includes:
First earthquake record data processor 701, the first intensive reflection coefficient sequence processor 702, reflection coefficient processor 703, width
Band wavelet processor 704 and the extensive seismic data process device 705 of low frequency.
Wherein, the first earthquake record data processor 701 is connected with the first intensive reflection coefficient sequence processor 702,
Seismic channel data is obtained, primary reflection coefficient is sought using mixing norm Sparse Pulse Inversion, by primary reflection coefficient and Yu Shi
The far-field wavelet phase convolution of wavelet spectrum constraint obtains the first earthquake record data.
First intensive reflection coefficient sequence processor 702, at the first earthquake record data processor 701 and reflection coefficient
Reason device 703 is connected, and calculates the first residual error of the first earthquake record data and seismic channel data, and anti-using the first residual modification
It penetrates coefficient and obtains the first intensive reflection coefficient sequence.
Reflection coefficient processor 703, with the first intensive reflection coefficient sequence processor 702 and the extensive seismic data process of low frequency
Device 705 is connected, and obtains second using the first intensive reflection coefficient sequence and the far-field wavelet phase convolution of Yu wavelet spectrum constraint
Earthquake record data；The second residual error of the second earthquake record data and seismic channel data is calculated, and anti-using the second residual modification
It penetrates coefficient and obtains the second intensive reflection coefficient sequence；Iterative calculation obtains the reflection coefficient of low frequency weak signal recovery.
Broadband wavelet processor 704 is connected with the extensive seismic data process device 705 of low frequency, is composed and is constrained using Yu wavelet
Far-field wavelet, the broadband wavelet for the low frequency weak signal that is restored.
The extensive seismic data process device 705 of low frequency, is connected with reflection coefficient processor 703 and broadband wavelet processor 704,
The reflection coefficient and broadband wavelet convolution restored using low frequency weak signal obtains the seismic data after low frequency restoration.
In some alternative embodiments, as shown in figure 8, for another weak letter of marine seismic data low frequency in the present embodiment
Number restore system 800 structural schematic diagram, unlike system in Fig. 7, the first earthquake record data processor
701, further comprise: matrix-vector synthesis unit 711 and reflection coefficient processing unit 712.Wherein, matrix-vector synthesis unit
711, for seismic channel data convolution synthetic seismogram data to be written as Matrix-Vector form: D=WR+N, wherein D is
Earthquake record data；W is the correspondence Wavelet Martrix of seismic wavelet construction；R is discrete fractal；N is making an uproar for addition
Sound.
Reflection coefficient processing unit 712 obtains primary reflection for solving above-mentioned matrix-vector equation using method of regularization
Coefficient and the noise of addition.
In some alternative embodiments, as shown in figure 9, for another weak letter of marine seismic data low frequency in the present embodiment
Number restore system 900 structural schematic diagram, unlike system in Fig. 7, the extensive seismic data process device 705 of low frequency,
Further comprise: reflection coefficient and far-field wavelet data capture unit 751 and low frequency restoration seismic data process unit 752.
Wherein, reflection coefficient and far-field wavelet data capture unit 751, for obtaining the reflection system of low frequency weak signal recovery
Number and the far-field wavelet of acquisition focal shock parameter simulation, and/or the far-field wavelet of actual measurement；Low frequency restoration seismic data process unit
752, for by reflection coefficient and far-field wavelet, convolution to obtain the seismic data after low frequency restoration in convolution model.
In some alternative embodiments, as shown in Figure 10, weak for another marine seismic data low frequency in the present embodiment
The structural schematic diagram for the system 1000 that signal restores, unlike system in Fig. 7, the first earthquake record data processor
701, comprising: broadband wavelet processing unit 713, mixing norm sparse model optimization unit 714 and primary reflection coefficient processing list
Member 715.
Wherein, broadband wavelet processing unit 713 composes constraint far field using Yu wavelet for obtaining seismic channel data
Wave, the broadband wavelet for the low frequency weak signal that is restored；It mixes norm sparse model and optimizes unit 714, obtain earthquake for analyzing
Road number of the track data in spatial frequency domain in spatial window is estimated in the form of intermediate value, mean value or intermediate value and mean value combination
Obtain mixing norm sparse model；Primary reflection coefficient processing unit 715, for utilizing mixing norm sparse model and seismic channel
Data are sought obtaining primary reflection coefficient.
Optionally, in above system, the first intensive reflection coefficient sequence and the second intensive reflection coefficient sequence, all in accordance with
First residual error or the second residual error size are obtained using conjugate gradient algorithms and determination.
Through the foregoing embodiment it is found that the method and system that marine seismic data low frequency weak signal of the invention is restored, reaches
Arrived it is following the utility model has the advantages that
(1) method and system that marine seismic data low frequency weak signal of the present invention is restored, based at seismic data
Convolution model is managed, reflection coefficient is sought using mixing norm Sparse Pulse Inversion first, after the influence for eliminating seismic wavelet, then with
The far-field wavelet phase convolution of Yu wavelet spectrum constraint, optimizes far-field wavelet under the premise of composing constraint, and it is low to realize that frequency domain is sought
Frequency end weighted factor, to restore the low frequency signal of seismic energy source.
(2) method and system that marine seismic data low frequency weak signal of the present invention is restored, based at seismic data
Convolution model is managed, reflection coefficient is sought using mixing norm Sparse Pulse Inversion first, after the influence for eliminating seismic wavelet, then with
The far-field wavelet phase convolution of Yu wavelet spectrum constraint, it is adaptable, it, can be with other than it can be good at being applied to horizontal cable
It is suitble to varying depth cable, OBC and OBN data；Signal-to-noise ratio retentivity is good, when expanding low frequency, will not raise low-frequency noise；Hi-fi of amplitude
Degree is high.
(3) method and system that marine seismic data low frequency weak signal of the present invention is restored uses mixing norm
The far-field wavelet being more of practical significance is utilized in inverting reflection coefficient, algorithmic stability, and effect has better fidelity, leads to
It crosses Yu wavelet spectrum constraint and restores low frequency weak signal and optimization phase, keep wavelet secondary lobe smaller, resolution ratio is higher, has stronger
It is explanatory.
Although some specific embodiments of the invention are described in detail by example, the skill of this field
Art personnel it should be understood that example above merely to being illustrated, the range being not intended to be limiting of the invention.The skill of this field
Art personnel are it should be understood that can without departing from the scope and spirit of the present invention modify to above embodiments.This hair
Bright range is defined by the following claims.
Claims (10)
1. a kind of method that marine seismic data low frequency weak signal is restored characterized by comprising
Seismic channel data is obtained, primary reflection coefficient is sought using mixing norm Sparse Pulse Inversion, by the primary reflection system
Several far-field wavelet phase convolutions with Yu wavelet spectrum constraint obtain the first earthquake record data；
The first residual error of the first earthquake record data Yu the seismic channel data is calculated, and utilizes first residual modification
The reflection coefficient obtains the first intensive reflection coefficient sequence；
Second is obtained using the described first intensive reflection coefficient sequence and the far-field wavelet phase convolution of Yu wavelet spectrum constraint
Earthquake record data；It calculates the second residual error of the second earthquake record data Yu the seismic channel data, and utilizes described the
Reflection coefficient described in two residual modifications obtains the second intensive reflection coefficient sequence；Iterative calculation obtains the anti-of low frequency weak signal recovery
Penetrate coefficient；
Constraint far-field wavelet, the broadband wavelet for the low frequency weak signal that is restored are composed using Yu wavelet；
The reflection coefficient and the broadband wavelet convolution restored using the low frequency weak signal obtains the earthquake number after low frequency restoration
According to.
2. the method that marine seismic data low frequency weak signal according to claim 1 is restored, which is characterized in that the use
Mixing norm Sparse Pulse Inversion seeks primary reflection coefficient, further comprises:
The seismic channel data convolution synthetic seismogram data are written as Matrix-Vector form: D=WR+N, wherein described
D is earthquake record data；The W is the correspondence Wavelet Martrix of seismic wavelet construction；The R is discrete fractal；
The N is the noise of addition；Above-mentioned matrix-vector equation, which is solved, using method of regularization obtains the primary reflection coefficient and addition
Noise.
3. the method that marine seismic data low frequency weak signal according to claim 1 is restored, which is characterized in that described in utilization
The reflection coefficient and far-field wavelet convolution that low frequency weak signal is restored obtain the seismic data after low frequency restoration, are as follows:
The far-field wavelet of the reflection coefficient and acquisition focal shock parameter simulation that are restored using the low frequency weak signal, and/or actual measurement
Far-field wavelet convolution obtains the seismic data after low frequency restoration.
4. the method that marine seismic data low frequency weak signal according to claim 1 is restored, which is characterized in that obtain earthquake
Track data seeks primary reflection coefficient using mixing norm Sparse Pulse Inversion, further are as follows:
Seismic channel data is obtained, composes constraint far-field wavelet, the broadband wavelet for the low frequency weak signal that is restored using Yu wavelet；
Analysis obtains road number of the seismic channel data in spatial frequency domain in spatial window, using intermediate value, mean value or intermediate value and
The form of value combination is estimated to obtain mixing norm sparse model；
It seeks obtaining primary reflection coefficient using mixing norm sparse model and seismic channel data.
5. the method that marine seismic data low frequency weak signal according to claim 1 is restored, which is characterized in that described first
Intensive reflection coefficient sequence and the second intensive reflection coefficient sequence utilize conjugation ladder all in accordance with the first residual error or the second residual error size
Degree algorithm and determination obtain.
6. the system that a kind of marine seismic data low frequency weak signal is restored characterized by comprising at the first earthquake record data
Manage device, the first intensive reflection coefficient sequence processor, reflection coefficient processor, broadband wavelet processor and the extensive seismic data of low frequency
Processor；Wherein,
The first earthquake record data processor is connected with the described first intensive reflection coefficient sequence processor, obtains ground
Track data is shaken, primary reflection coefficient is sought using mixing norm Sparse Pulse Inversion, by the primary reflection coefficient and Yu Shi
The far-field wavelet phase convolution of wave spectrum constraint obtains the first earthquake record data；
The first intensive reflection coefficient sequence processor is handled with the first earthquake record data processor and reflection coefficient
Device is connected, and calculates the first residual error of the first earthquake record data and the seismic channel data, and residual using described first
Difference modifies the reflection coefficient and obtains the first intensive reflection coefficient sequence；
The reflection coefficient processor, with the described first intensive reflection coefficient sequence processor and the extensive seismic data process device of low frequency
It is connected, obtains the using the far-field wavelet phase convolution of the described first intensive reflection coefficient sequence and Yu wavelet spectrum constraint
Two earthquake record data；The second residual error of the second earthquake record data Yu the seismic channel data is calculated, and described in utilization
Reflection coefficient described in second residual modification obtains the second intensive reflection coefficient sequence；Iterative calculation obtains the recovery of low frequency weak signal
Reflection coefficient；
The broadband wavelet processor is connected with the extensive seismic data process device of the low frequency, remote using Yu wavelet spectrum constraint
Ground wave, the broadband wavelet for the low frequency weak signal that is restored；
The extensive seismic data process device of low frequency, is connected with the reflection coefficient processor and broadband wavelet processor, utilizes
The reflection coefficient and the broadband wavelet convolution that the low frequency weak signal is restored obtain the seismic data after low frequency restoration.
7. the system that marine seismic data low frequency weak signal according to claim 6 is restored, which is characterized in that described first
Earthquake record data processor further comprises: matrix-vector synthesis unit and reflection coefficient processing unit；Wherein,
The matrix-vector synthesis unit, for by the seismic channel data convolution synthetic seismogram data be written as matrix-to
Amount form: D=WR+N, wherein the D is earthquake record data；The W is the correspondence Wavelet Martrix of seismic wavelet construction；
The R is discrete fractal；The N is the noise of addition；
The reflection coefficient processing unit, it is described original anti-for being obtained using the above-mentioned matrix-vector equation of method of regularization solution
Penetrate the noise of coefficient and addition.
8. the system that marine seismic data low frequency weak signal according to claim 6 is restored, which is characterized in that the low frequency
Extensive seismic data process device further comprises: reflection coefficient and far-field wavelet data capture unit and low frequency restoration seismic data
Processing unit；Wherein,
The reflection coefficient and far-field wavelet data capture unit, for obtain reflection coefficient that the low frequency weak signal is restored and
Acquire the far-field wavelet of focal shock parameter simulation, and/or the far-field wavelet of actual measurement；
The low frequency restoration seismic data process unit, for by the reflection coefficient and far-field wavelet in convolution model convolution
Seismic data after obtaining low frequency restoration.
9. the system that marine seismic data low frequency weak signal according to claim 6 is restored, which is characterized in that described first
Earthquake record data processor, comprising: broadband wavelet processing unit, mixing norm sparse model optimization unit and primary reflection system
Number processing unit；Wherein,
The broadband wavelet processing unit is composed constraint far-field wavelet using Yu wavelet, is obtained extensive for obtaining seismic channel data
The broadband wavelet of multiple low frequency weak signal；
The mixing norm sparse model optimizes unit, obtains seismic channel data in spatial frequency domain in spatial window for analyzing
Road number, estimate to obtain mixing norm sparse model in the form of intermediate value, mean value or intermediate value and mean value combination；
The primary reflection coefficient processing unit, it is original for seeking obtaining using mixing norm sparse model and seismic channel data
Reflection coefficient.
10. the system that marine seismic data low frequency weak signal according to claim 6 is restored, which is characterized in that described the
One intensive reflection coefficient sequence and the second intensive reflection coefficient sequence utilize conjugation all in accordance with the first residual error or the second residual error size
Gradient algorithm and determination obtain.
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