CN106855638A - Matching pursuit seismic spectrum decomposition method and device - Google Patents
Matching pursuit seismic spectrum decomposition method and device Download PDFInfo
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- G01V1/28—Processing seismic data, e.g. for interpretation or for event detection
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Abstract
The embodiment of the application provides a matching pursuit seismic spectrum decomposition method and device. Wherein the method comprises the following steps: (1) acquiring a seismic signal, and taking the seismic signal as a current signal; (2) determining the center frequency of the atom to be searched according to the current signal; (3) searching atoms meeting a first preset condition in a preset overcomplete library by using a matching pursuit algorithm, selecting the atom most relevant to the current signal, acquiring the corresponding projection component of the current signal at the most relevant atom, and acquiring the signal residual error of the current signal and the corresponding projection component; (4) taking the signal residual error as a new current signal, and repeating the steps (2) to (4) until the currently obtained signal residual error is smaller than a preset threshold value; (5) and obtaining a seismic spectrum decomposition result of the seismic data according to all the corresponding projection components. The method and the device can improve the calculation efficiency, the decomposition precision and the adaptability of the matching pursuit algorithm for seismic spectrum decomposition.
Description
Technical field
The application is related to Seismic Data Processing Technique field, more particularly, to a kind of match tracing earthquake spectral factorization method and
Device.
Background technology
With deepening continuously for oil-gas exploration and development, craven fault, thin reservoir and lithology are closed the identification of circle and are explained as ground
The emphasis of shake data Fine structural interpretation.Earthquake Spectral Decomposition Technique can not only improve explanation and prediction energy of the seismic data to thin reservoir
Power, and the geological information of more horn of plenty can be obtained from geological data, just cause industry extensive concern once releasing, and obtain
Fast development.Extensive use is obtained at the aspect such as stratum or sedimentary facies explanation, oil and gas detection.Its general principle is selection one
Group, by observing projection of the signal to be analyzed on basic function, obtains signal in the limited basic function of time-domain and frequency domain
In time-domain and the Joint Distribution of frequency domain.
Initial earthquake spectral factorization is mainly realized by Short Time Fourier Transform (STFT), later to have engendered base again
In the earthquake spectral factorization method of wavelet transformation, S-transformation and matching pursuit algorithm (MP) etc..Wherein, based on matching pursuit algorithm
(MP) earthquake spectral factorization method in signal Time-frequency Decomposition, with it is simple, direct and effective the characteristics of, in seismic data interpretation
Field has obtained extensive utilization.The appearance of matching pursuit algorithm causes that utilizing complete storehouse exists realizing the rarefaction representation of signal
In most cases it is possibly realized.But because match tracing method is a kind of greedy algorithm, and excessively complete storehouse is general very huge,
It is computationally very expensive and unpractical to find real best match.In in most cases selecting complete storehouse at present
The current atomic time of correlation maximum, using the way for traveling through that maximum atom of all atom selection inner products, its shortcoming
It is the seismic signal for not adapting to different characteristic, and computational efficiency and Decomposition Accuracy be not high.
The content of the invention
The purpose of the embodiment of the present application is to provide a kind of match tracing earthquake spectral factorization method and device, can be improved
It is used for computational efficiency, Decomposition Accuracy and the adaptability of earthquake spectral factorization with tracing algorithm.
To reach above-mentioned purpose, the embodiment of the present application provides a kind of match tracing earthquake spectral factorization method, methods described
Including：
(1) seismic signal is obtained, and using the seismic signal as current demand signal；
(2) according to the current demand signal, the centre frequency of atom to be searched is determined；
(3) searched for using matching pursuit algorithm and preset the first pre-conditioned atom of satisfaction in complete storehouse, selection is described
Meet in the first pre-conditioned atom with the maximally related atom of the current demand signal, obtain the current demand signal in the most phase
Corresponding projection components at the atom of pass, and obtain the signal residual error of the current demand signal and the corresponding projection components；It is described
The first pre-conditioned centre frequency for the atom is equal to the centre frequency of the atom to be searched；
(4) using the signal residual error as new current demand signal, repeat step (2) to (4), until currently available is described
Signal residual error is less than untill predetermined threshold value；
(5) according to all correspondence projection components, the earthquake spectral factorization result of the geological data is obtained.
It is that, up to above-mentioned purpose, the embodiment of the present application additionally provides a kind of match tracing earthquake spectral factorization device, described device
Including：
Acquisition module, for obtaining seismic signal, and using the seismic signal as current demand signal；
Centre frequency determining module, for according to the current demand signal, determining the centre frequency of atom to be searched；
Search module, the first pre-conditioned original is met in complete storehouse for searching for preset using matching pursuit algorithm
Son, with the maximally related atom of the current demand signal in selection the first pre-conditioned atom of the satisfaction, obtains the current letter
Corresponding projection components number at the maximally related atom, and obtain the letter of the current demand signal and the corresponding projection components
Number residual error；The described first pre-conditioned centre frequency for the atom is equal to the centre frequency of the atom to be searched；
Replicated blocks, determine for the signal residual error as new current demand signal, to be repeated the centre frequency
Module to the replicated blocks, untill the currently available signal residual error is less than predetermined threshold value；
Result obtains module, for according to all correspondence projection components, obtaining the earthquake spectrum point of the geological data
Solution result.
The technical scheme provided from above-mentioned the embodiment of the present application, the embodiment of the present application is using matching pursuit algorithm
When carrying out earthquake spectral factorization, the centre frequency of the atom that search is needed in complete storehouse was determined by current demand signal, was different from
The way of all atoms of search of prior art, improves computational efficiency.On the other hand, the embodiment of the present application is only searched for and preset
The first pre-conditioned atom is met in complete storehouse, the atom for representing seismic signal is therefrom determined, what is finally given is used for
Express and more matched between the excessively complete storehouse of seismic signal and seismic signal, improve dividing for matching pursuit algorithm earthquake spectral factorization
Solution precision and the adaptability to different earthquake signal.
Brief description of the drawings
Accompanying drawing described herein is used for providing further understanding the embodiment of the present application, constitutes the embodiment of the present application
A part, does not constitute the restriction to the embodiment of the present application.In the accompanying drawings：
Fig. 1 is a kind of match tracing earthquake spectral factorization method schematic diagram of the embodiment of the present application；
Fig. 2 is the Ricker wavelet schematic diagrames of 30HZ for the dominant frequency of the embodiment of the present application；
Fig. 3 is the result schematic diagram of the wavelet transformation Time-frequency Decomposition of the embodiment of the present application；
Fig. 4 is the result schematic diagram of the S-transformation Time-frequency Decomposition of the embodiment of the present application；
Fig. 5 is the result schematic diagram of the ordinary matches tracing algorithm Time-frequency Decomposition of the embodiment of the present application；
Fig. 6 is the result schematic diagram of the improvement matching pursuit algorithm Time-frequency Decomposition of the embodiment of the present application；
Fig. 7 is the seismic signal schematic diagram of a certain road seismic channel of the embodiment of the present application；
Fig. 8 is the result schematic diagram decomposed using CWT to the seismic signal shown in Fig. 7 of the embodiment of the present application；
Fig. 9 is followed the trail of the result decomposed using ordinary matches and illustrated for the embodiment of the present application to the seismic signal shown in Fig. 7
Figure；
Figure 10 is the result decomposed using the match tracing after improving to the seismic signal shown in Fig. 7 of the embodiment of the present application
Schematic diagram；
Figure 11 is the 10HZ frequency sections that matching pursuit algorithm is produced that improve of the embodiment of the present application；
Figure 12 is the 30HZ frequency sections that matching pursuit algorithm is produced that improve of the embodiment of the present application；
Figure 13 is the 50HZ frequency sections that matching pursuit algorithm is produced that improve of the embodiment of the present application；
Figure 14 decomposes 10Hz, 30Hz and 50Hz horizon slice for obtaining for the matching pursuit algorithm that improves of the embodiment of the present application
Multispectral image composite result；
Figure 15 decomposes 10Hz, 30Hz and 50Hz for obtaining for the short term Fourier transform (FFT) of the embodiment of the present application
Horizon slice multispectral image composite result；
Figure 16 for improved in the case of single CPU of the embodiment of the present application matching pursuit algorithm and short time-window fft algorithm take it is right
Than figure；
Figure 17 for improved under the CPU multithreadings of the embodiment of the present application matching pursuit algorithm and short time-window fft algorithm take it is right
Than figure；
Figure 18 is a kind of match tracing earthquake spectral factorization schematic device of the embodiment of the present application.
Specific embodiment
For the purpose, technical scheme and advantage for making the embodiment of the present application become more apparent, with reference to embodiment and attached
Figure, is described in further details to the embodiment of the present application.Here, the schematic description and description of the embodiment of the present application is used for
The embodiment of the present application is explained, but is not intended as the restriction to the embodiment of the present application.
The technical scheme that the embodiment of the present application is provided is introduced in order to clearer, first herein to matching pursuit algorithm
Do an introduction.Matching pursuit algorithm is a kind of mode of signal sparse expression, is substantially that signal is carried out on excessively complete storehouse
Decompose.
Give an excessively complete storehouse D ∈ Rn×k, wherein its each column represents a kind of atom of prototype signal.A given letter
Number y, it can be expressed as the sparse linear combination of these atoms.That is, signal y can be expressed as：Y=Dx, or y ≈ Dx.
The mistake completeness for crossing complete storehouse refers to the number of atom and is far longer than the length of signal y.The basic ideas of matching pursuit algorithm
For：From excessively complete storehouse D, one sparse bayesian learning of an atomic building most matched with signal y is selected, and obtains signal residual error,
Then proceed to the atom that is most matched with signal residual error of selection, iterate, signal y can by these atoms come it is linear and, then plus
Last residual values are gone up to represent.It will be apparent that if residual values are in negligible scope, signal y is approximately just these
The linear combination of atom.
In said process, in the atomic time that selection is most matched with signal y, signal y can be calculated each with excessively complete storehouse
The inner product of individual atom, selects an atom of inner product maximum absolute value, and it is exactly most to be matched in current iteration computing with signal y
's.The process formula is expressed：Signal y ∈ H (H represents Hilbert space) is made, one is selected from excessively complete storehouse
The atom for most matching, meetsWherein, r0Represent an excessively complete storehouse matrix column index.This
Sample signal y is just broken down into most matched atomsTwo parts of upright projection component and residual error, i.e.,：
To residual error R1F carries out same decomposition, and to the residual error for subsequently obtaining each time carries out same decomposition successively, then
Kth step can be obtained：WhereinMeet
Visible signal y by being after K+1 step decomposition：
Above-mentioned RiF represents residual error, i=1,2,3 ...
Above-mentioned is exactly the simple introduction of ordinary matches tracing algorithm, below in conjunction with the accompanying drawings, to the specific of the embodiment of the present application
Implementation method is described in further detail.
With reference to shown in Fig. 1, a kind of match tracing earthquake spectral factorization method that the embodiment of the present application is provided can include following
Step.The method can be used for the Time-frequency Decomposition of seismic signal.
Step S101, obtains seismic signal, and using the seismic signal as current demand signal.
Wherein, the original time domain seismic signal that the seismic signal can be obtained for earthquake data acquisition.In order that score
The result of frequency is more smoothed, and in one embodiment of the application, the seismic signal can be by the earthquake of smoothing processing
Signal, can thus mitigate influence of the noise to decomposition result.
Step S102, according to the current demand signal, determines the centre frequency of atom to be searched.
Because the improvement match tracing method described in the present embodiment is the process that a circulation is performed, perform each time
A current demand signal is required for during loop body.Specifically, the current demand signal can be obtain earthquake primary signal or
After circulation each time having been performed according to matching pursuit algorithm, the signal residual error for obtaining.The centre frequency of the atom to be searched can
Think the current demand signal in the instantaneous frequency corresponding to the instantaneous energy highest moment.In one embodiment of the application, can
With the analytic signal by being calculated current demand signal, and instantaneous energy highest moment, the moment are obtained by analytic signal
Instantaneous frequency can be as the centre frequency of atom to be searched.Specifically, if current demand signal is c (t), analytic signal is c
T ()+iH [c (t)], the centre frequency of atom to be searched is obtained further according to below equation.
First, the analytic signal instantaneous energy highest moment is obtained according to below equation.
tn=argmax | | c (t)+iH [c (t)] | | (1)
In formula, tnThe instantaneous energy highest moment is represented, c (t) represents current demand signal, and H [] represents Hilbert transform；
Current demand signal is in tnThe instantaneous frequency at place is the centre frequency of atom to be searched.
In formula, ωnRepresent the centre frequency of atom to be searched.
Step S103, is searched for using matching pursuit algorithm and preset the first pre-conditioned atom of satisfaction, choosing in complete storehouse
Select in the first pre-conditioned atom of the satisfaction with the maximally related atom of the current demand signal, obtain the current demand signal in institute
The corresponding projection components at maximally related atom are stated, and it is residual with the signal of the corresponding projection components to obtain the current demand signal
Difference；The described first pre-conditioned centre frequency for the atom is equal to the centre frequency of the atom to be searched.
It is described to preset the matrix that complete storehouse be for a kind of columns more than line number, complete dictionary was can be described as again.If
Can determine the center of the atom for needing search, it is possible to greatly reduce the atomic quantity for needing search, determine to be searched
The centre frequency of atom is substantially that the atom that will be preset in complete storehouse has carried out one and deletes choosing, and deleting the atom that choosing obtains all is
Meet the first pre-conditioned atom, obtain and work as according to matching pursuit algorithm in these first pre-conditioned atoms of satisfaction
The maximally related atom of front signal, the circulation each time of match tracing is obtained for a maximally related atom, these most related originals
Son can be used to represent seismic signal.With the maximally related original of the current demand signal in selection the first pre-conditioned atom of satisfaction
Son, can be that maximum atom with the inner product of current demand signal in finding out the first pre-conditioned atom of all satisfactions.
In one embodiment of the application, excessively complete storehouse is expressed as：G={ gn(t) }, gnT () represents atom, wherein n
=0,1,2,3 ...
Corresponding projection components of the current demand signal at the maximally related atom can be current demand signal most related
Atom on upright projection an, can specifically be expressed as：<c(t),gn(t)>gnT (), wherein c (t) are current demand signal.Currently
Signal is the signal residual error with the difference signal of the projection components.
Step S104, using the signal residual error as new current demand signal, repeat step S102 to S104, until current obtain
To the signal residual error less than predetermined threshold value.
The purpose of match tracing Time-frequency Decomposition is that signal is expressed as the sparse linear combination of atom.Iterative process each time
In, all there is certain residual error between the linear combination of atom and primary signal, when residual error can be ignored, we just can be with
Think that seismic signal Time-frequency Decomposition is completed.The predetermined threshold value can be a negligible boundary set in advance
Limit, when signal residual error is less than this boundary, it is believed that seismic signal can be represented by the linear combination of each atom.
Step S105, according to all correspondence projection components, obtains the earthquake spectral factorization result of the geological data.
The earthquake spectral factorization result can be the sum of seismic signal projection components on each atom, the process formula
Expressing to be：
In formula, s (t) represents original seismic signal, anRepresent projected length of the original seismic signal on each atom.
Embodiment as shown in Figure 1 understand, the embodiment of the present application when earthquake spectral factorization is carried out using matching pursuit algorithm,
The centre frequency of the atom that search is needed in complete storehouse was determined by current demand signal, the search different from prior art is owned
The way of atom, improves computational efficiency.On the other hand, satisfaction first is pre- during the embodiment of the present application is only searched for and preset complete storehouse
If the atom of condition, therefrom determine the atom for representing seismic signal, finally give for expressing the excessively complete of seismic signal
It is standby more to be matched between storehouse and seismic signal, improve the Decomposition Accuracy of matching pursuit algorithm earthquake spectral factorization and to different earthquake
The adaptability of signal.
During time frequency analysis, the atom in excessively complete storehouse is typically all the atom that the small echo based on form known builds, specifically
Can be including Ricker wavelet (Ricker wavelets) and Morlet wavelets etc..In one embodiment of the application, rake is used
Wavelet (Ricker wavelets) built complete storehouse.The general expression of atom can be：
In formula, LnRepresent scale parameter, tnThe displacement parameter of small echo is represented,Represent the morther wavelet of constituting atom.
If morther wavelet is：
So, formula (5) substitution formula (4) can be obtained into atomic expression is：
The frequency spectrum of atom is shown in formula (6)：
The form of known Ricker wavelets is：
In formula, f0Represent the crest frequency of Ricker wavelets, ω0=2 π f0。
The corresponding frequency spectrum of Ricker wavelets is：
In formula, f represents frequency.
It can be seen from above formula, the atomic expression built using Ricker wavelets is：
Make ωn=ω0/LnIt is the centre frequency of small echo, then：
Its frequency spectrum is：
From formula (12), the phase of such atomic spectrum by small echo center tnIt is determined that, its amplitude is in small echo
Frequency of heart ωnPlace is maximum.In the present embodiment, after atomic expression is determined according to above formula, can be according to shown in Fig. 1
Flow chart, carries out earthquake spectral factorization.
Ricker wavelets have form simple, the advantages of zero phase, in the present embodiment, as the mother for building atom
Small echo, calculating process is simpler, also closer to blast wavelet.
In one embodiment of the application, in order to avoid for the spacing mistake between each atom for representing seismic signal
It is small, introduce a new parameter --- minimum atomic distance, the variable is defined between the atom for expressing seismic signal
Admissible minimum spacing, so it is determined that in atom with the current demand signal maximally related atomic time, except inner product to be selected most
Big atom, in addition it is also necessary to meet the atom and all before selected for the location interval between the atom for representing seismic signal
More than or equal to default minimum atomic separation.
Specifically, selecting the first pre-conditioned original of the satisfaction in one embodiment of the application, described in S103
With the maximally related atom of the current demand signal in son, following two steps can be included.
(1) original with the inner product maximum absolute value of the current demand signal in the first pre-conditioned atom of the satisfaction is determined
Son.
(2) judge the atom of the inner product maximum absolute value and whether the spacing between the maximally related atom that determines before is big
In equal to default minimum atomic separation, if the determination result is YES, then the atom of the inner product maximum absolute value is described maximally related
Atom, if being judged as NO, the atom of the inner product maximum absolute value is rejected from the first pre-conditioned atom of the satisfaction,
Above step (1)~(2) are repeated, until judged result for untill being.
In a specific embodiment of the application, before according to flow shown in Fig. 1, and between the minimum atom of consideration simultaneously
Every having obtained for representing the atom g of seismic signal1(t)、g2(t) and g3T (), now, determines further according to step in S102
This time circulate that the atom to be searched for should meet first is pre-conditioned, it is assumed that preset in complete storehouse, and met first and preset
The atom of condition is g4(t)、g5(t) and g6(t).When now performing S103, it is first determined g4(t)、g5(t)、g6In (t) with it is current
The maximally related atom of signal, it is assumed that be g4(t), then judge g4(t) and each atom g for determining before1(t)、g2(t) and g3
Whether the interval between (t) is more than or equal to minimum atomic separation, if it is not, then giving up g4(t), again in remaining atom g5(t)
And g6One is determined between (t) with the maximally related current atom of current demand signal, repetition above step, until it is former to be met minimum
The current atom at son interval.
Research shows that atomic distance is to influence match tracing computational efficiency and decompose the key of quality, but regrettably normal
During rule calculate, this factor is not considered, in the above-mentioned several embodiments for considering atomic separation of the application, by minimum atom
It is spaced to take into account and is conducive to improving Decomposition Accuracy.
In a specific embodiment of the application, it is 10 to preset minimum atomic separation, i.e., being carried according to the flow of Fig. 1 is carried out
During earthquake spectral factorization, the atom maximum with current demand signal inner product selected in only S103 meets and all most phases for obtaining before
When closing the interval between atom more than or equal to 10, the maximum atom of the inner product can be just left, as most relevant atomic, for table
Up to seismic signal.
In one embodiment of the application, in order to verify the improvement matching pursuit algorithm that above the embodiment of the present application is carried
Validity, carried out the experiment of corresponding Numerical Validation.One dominant frequency of design is 30HZ, and continuity length is 200ms, wavelet peak value
Ricker wavelets at 70ms, then use wavelet transformation CWT, S-transformation, shown in ordinary matches tracing algorithm and Fig. 1 respectively
The improvement matching pursuit algorithm that embodiment is provided carries out time frequency analysis to test each decomposition algorithm to the Ricker wavelets
Whether whether time-frequency locality is good and has temporal frequency domain resolution ratio higher.Fig. 2 is that previously described dominant frequency is
The Ricker wavelets of 30HZ, Fig. 3 to Fig. 6 is respectively wavelet transformation CWT, S-transformation, ordinary matches tracing algorithm and the application reality
Applying the improvement matching pursuit algorithm that example carried carries out the result of Time-frequency Decomposition.Ordinate is the time in Fig. 3 to Fig. 6, and unit is
ms.Be can be seen that from Fig. 3 to Fig. 6 in the image after decomposing, the result that two kinds of matching pursuit algorithms are obtained is in time and frequency domain
Resolution ratio wavelet transformation CWT and S-transformation will be high, time-frequency locality is preferable.
Although due to having merely entered a Ricker wavelet in the present embodiment, the atom number of rarefaction representation is less, and
, all than larger, improved matching pursuit algorithm is similar with ordinary matches tracing algorithm result, but Fig. 3 to Fig. 6 still may be used for spacing
To show, improved matching pursuit algorithm time-frequency locality is good.
Geological data, can accurately to storage with reference to technologies such as graphics, three-dimensional visualizations by after high accuracy Time-frequency Decomposition
The special geology such as layer, oil gas phenomenon carries out Fine structural interpretation.Matching pursuit algorithm after the improvement that the embodiment of the present application is proposed
Apply in coming from certain exploratory area carbonate reservoir, seismic signal sample rate 1ms, dominant frequency about 35HZ, frequency bandwidth about 7-
85HZ.Fig. 7 is the seismic signal of a certain road seismic channel, and abscissa is the time (unit ms), and ordinate is amplitude.Fig. 8 is to Fig. 7
The result that shown seismic signal is decomposed using CWT, Fig. 9 is to use ordinary matches to follow the trail of the seismic signal shown in Fig. 7 to decompose
Result, Figure 10 be to shown in Fig. 7 seismic signal using improve after match tracing decompose result, in Fig. 8 to Figure 10 show
Different reflectivity are shown, single reflectance target can be accurately recognized in time-frequency domain.In Fig. 8 to 10, abscissa is the time, single
Position ms, ordinate is frequency.Comparison diagram 8-10 sees can draw the matching pursuit algorithm after improving compared with CWT methods, ordinary matches
Following the trail of has Decomposition Accuracy higher.
In one embodiment of the application, Figure 11-13 is with the frequency that matching pursuit algorithm is produced that improves as shown in Figure 1
Rate section, abscissa represents the recording mechanism in seismic profile in Figure 11-13, and ordinate represents time, unit s.Figure 11-13 distinguishes
Correspondence 10Hz frequencies section, 30Hz frequencies section and 50Hz frequency sections.The reflected amplitude at 1.85s, 2.25s in Figure 11-13
Gradually strengthen from 10HZ to 50HZ and then weaken, 30HZ or so is most strong.The appearance of this phenomenon will sum up in the point that reservoir gas-bearing is special
Levy, after reservoir gas-bearing, resonant frequency is migrated towards energy side higher, when these resonant frequencies are illuminated, be just easy to know
Not.This example demonstrates that, improved match tracing method as shown in Figure 1 can help realize differentiate single target in frequency domain
Reflection.
In another embodiment of the application, recognize that some are special using improved match tracing method as shown in Figure 1
Different geologic objective, such as river course, lithologic anomalous body, low frequency shadow, and can be based on further with the development of Time-frequency Decomposition result
The multispectral image synthesis of iconology, it is latent that the spectral decomposition data of discrete type can also show that the personnel that help explain understand by animation
Geologic objective, and explanation is analyzed to these potential targets.This can be solved using single spectrum point on partial extent
Amount can not show the defect of full detail, improve Explanation Accuracy, greatly excavate effective information.Figure 14 and Figure 15 be 10Hz,
30Hz and 50Hz horizon slice multispectral image composite results.Wherein, Figure 14 is improved carried using the embodiment of the present application
The result for obtaining is decomposed with method for tracing, Figure 15 is that the result for obtaining is decomposed using short term Fourier transform (FFT).Synthesis
Reservoir obtains further meticulous depiction in figure afterwards, can be very good to carry out explication de texte with reference to various data to its local feature.
Comparison diagram 14 and Figure 15 understood, the anisotropism on stratum is portrayed and become apparent from right regions in Figure 14, can finely be recognized many
Individual solution cavity, in addition it can be seen that the early fracture in northwest (NW) east southeast direction is cut by the NE trending fault that the later stage develops, fault system
System becomes apparent from, and feature is obvious, advantageously in Fine structural interpretation.
Relative to other decomposition algorithms, matching pursuit algorithm extremely takes, and how to improve computational efficiency, decomposition efficiency sum
There is substantial connection according to amount, in order to further improve computational efficiency, in one embodiment of the application, using such as Fig. 1 institutes
On the basis of showing improved matching pursuit algorithm, the characteristics of for matching pursuit algorithm, using CPU multithreading strategies, greatly
Improve computational efficiency.By taking Xeon series E5-2670 processors as an example, its dominant frequency 2.30Hz, using CPU multithreading strategies, pole
The earth improves computational efficiency.Figure 16 is improved matching pursuit algorithm shown in comparison diagram 1 and short time-window FFT in the case of list CPU
Algorithm, the two carries out spectral factorization using single thread to different number of samples simultaneously, in the case where CPU frequency is certain, with ginseng
All increase in approximately linear with calculating number of samples and increasing the time-consuming of FFT and this method, but the embodiment of the present application carried it is improved
Faster, the FFT that compares more takes the time-consuming speed increase of the calculating of matching pursuit algorithm in more number of samples, this be due to
This method is influenceed when calculating using bulk redundancy operator.
In the case where CPU frequency is certain, the fixed number of samples for participating in calculating, is transformed parallel by CPU multithreadings,
Two kinds of algorithms are carried out with time-consuming contrast, as shown in figure 17, increasing with the thread for participating in computing, two kinds as we can see from the figure
The computational efficiency of algorithm is improved significantly, but increases time-consuming performance boost speed relative reduction with thread.The application
The improved matching pursuit algorithm and fft algorithm that embodiment is carried all have preferable parallelization feature, by multi-threaded parallel
Accelerating can be up to 5-6 times of acceleration effect, and the number of samples of computing is more, and parallel acceleration effect is more obvious.
A kind of match tracing earthquake spectral factorization device is additionally provided in the embodiment of the present application, as described in the following examples.
Because the principle of the device solve problem is similar to a kind of match tracing earthquake spectral factorization method, therefore the implementation of the device can be with
Implement referring to a kind of match tracing earthquake spectral factorization method, repeat part and repeat no more.
As shown in figure 18, a kind of match tracing earthquake spectral factorization device that the embodiment of the present application is provided, can include with
Under several modules.
Acquisition module 1801, for obtaining seismic signal, and using the seismic signal as current demand signal.
Centre frequency determining module 1802, for according to the current demand signal, determining the centre frequency of atom to be searched.
Search module 1803, to preset that meet in complete storehouse first pre-conditioned for being searched for using matching pursuit algorithm
Atom, with the maximally related atom of the current demand signal in selection the first pre-conditioned atom of the satisfaction, obtains described current
Corresponding projection components of the signal at the maximally related atom, and the current demand signal is obtained with the corresponding projection components
Signal residual error；The described first pre-conditioned centre frequency for the atom is equal to the centre frequency of the atom to be searched.
Replicated blocks 1804, as new current demand signal, the centre frequency is repeated for using the signal residual error
Determining module to the replicated blocks, untill the currently available signal residual error is less than predetermined threshold value.
Result obtains module 1805, for according to all correspondence projection components, obtaining the earthquake of the geological data
Spectral factorization result.
From the embodiment of above-mentioned the application device, the embodiment of the present application is carrying out earthquake spectrum using matching pursuit algorithm
During decomposition, center and the centre frequency of the atom that search is needed in complete storehouse were determined by current demand signal, were different from
The way of all atoms of traversal of prior art, improves computational efficiency.On the other hand, the embodiment of the present application has only been used in advance
The first pre-conditioned atom is met in the excessively complete storehouse set up to go to represent seismic signal, is obtained again equivalent to according to seismic signal
To the new excessively complete storehouse matched with the signal, the adaptability and Decomposition Accuracy of matching pursuit algorithm are improve.
The step of method described in the embodiment of the present application, can be directly embedded into the software mould of hardware, computing device
Block or the combination of both.Software module can be stored in RAM memory, flash memory, ROM memory, eprom memory,
In eeprom memory, register, hard disk, moveable magnetic disc, CD-ROM or this area in other any form of storage media.
Exemplarily, storage medium can be connected with processor, to allow that processor reads information from storage medium, it is possible to
Write information is deposited to storage medium.Alternatively, storage medium can also be integrated into processor.Processor and storage medium can set
It is placed in ASIC, ASIC can be arranged in user terminal.Alternatively, processor and storage medium can also be arranged at user's end
In different part in end.
In one or more exemplary designs, above-mentioned functions described by the embodiment of the present application can be in hardware, soft
Any combination of part, firmware or this three is realized.If realized in software, these functions can be stored and computer-readable
On medium, or it is transmitted on the medium of computer-readable with one or more instructions or code form.Computer readable medium includes electricity
Brain stores medium and is easy to so that allowing computer program to be transferred to other local telecommunication medias from a place.Storage medium can be with
It is that any general or special computer can be with the useable medium of access.For example, such computer readable media can include but
RAM, ROM, EEPROM, CD-ROM or other optical disc storages, disk storage or other magnetic storage devices are not limited to, or other are appointed
What can be used for carrying or store with instruct or data structure and other can be by general or special computer or general or specially treated
Device reads the medium of the program code of form.Additionally, any connection can be properly termed computer readable medium, example
Such as, if software is by a coaxial cable, fiber optic cables, double from web-site, server or other remote resources
Twisted wire, Digital Subscriber Line (DSL) or with the wireless way for transmitting such as example infrared, wireless and microwave be also contained in it is defined
In computer readable medium.Described disk (disk) and disk (disc) include Zip disk, radium-shine disk, CD, DVD, floppy disk
And Blu-ray Disc, disk is generally with magnetic duplication data, and disk generally carries out optical reproduction data with laser.Combinations of the above
Can also be included in computer readable medium.
Particular embodiments described above, purpose, technical scheme and beneficial effect to the application have been carried out further in detail
Describe in detail bright, should be understood that the specific embodiment that the foregoing is only the embodiment of the present application, be not used to limit this Shen
Protection domain please, all any modification, equivalent substitution and improvements within spirit herein and principle, done etc., all should wrap
It is contained within the protection domain of the application.
Claims (12)
1. a kind of match tracing earthquake spectral factorization method, it is characterised in that comprise the following steps：
(1) seismic signal is obtained, and using the seismic signal as current demand signal；
(2) according to the current demand signal, the centre frequency of atom to be searched is determined；
(3) searched for using matching pursuit algorithm and preset the first pre-conditioned atom of satisfaction in complete storehouse, select the satisfaction
With the maximally related atom of the current demand signal in first pre-conditioned atom, the current demand signal is obtained described maximally related
Corresponding projection components at atom, and obtain the signal residual error of the current demand signal and the corresponding projection components；Described first
The pre-conditioned centre frequency for the atom is equal to the centre frequency of the atom to be searched；
(4) using the signal residual error as new current demand signal, repeat step (2) to (4), until the currently available signal
Residual error is less than untill predetermined threshold value；
(5) according to all correspondence projection components, the earthquake spectral factorization result of the geological data is obtained.
2. the method for claim 1, it is characterised in that described according to the current demand signal, determines atom to be searched
Centre frequency, specifically includes：
According to the current demand signal, the analytic signal of the current demand signal is obtained；
The analytic signal instantaneous energy highest moment is obtained, instantaneous frequency of the current demand signal at the moment is treated for described
Search for the centre frequency of atom.
3. method as claimed in claim 2, it is characterised in that described when obtaining the analytic signal instantaneous energy highest
Carve, instantaneous frequency of the current demand signal at the moment is the centre frequency of the atom to be searched, specially：
The analytic signal instantaneous energy highest moment is obtained according to below equation,
tn=argmax | | c (t)+iH [c (t)] | |
In formula, tnThe expression instantaneous energy highest moment, c (t) expression current demand signals, H [] expression Hilbert transforms, c (t)+
IH [c (t)] represents analytic signal；
The instantaneous frequency is obtained by below equation,
In formula, ωnRepresent the centre frequency of atom to be searched.
4. method as claimed in claim 3, it is characterised in that the atom preset in complete storehouse is based on Ricker wavelet
Build.
5. method as claimed in claim 4, it is characterised in that the selection is described meet in the first pre-conditioned atom with
The maximally related atom of current demand signal, including：
Determine atom with the inner product maximum absolute value of the current demand signal in the first pre-conditioned atom of the satisfaction；And
Judge the atom of the inner product maximum absolute value and whether the spacing between the maximally related atom that determines before is more than or equal to
Default minimum atomic separation, if the determination result is YES, then the atom of the inner product maximum absolute value is the maximally related atom, if
Be judged as NO, then by the atom of the inner product maximum absolute value from it is described satisfaction the first pre-conditioned atom in reject, repeat with
Upper step, until judged result for untill being.
6. the method as described in any in claim 1 to 5, it is characterised in that the seismic signal is by smoothing processing
Seismic signal.
7. a kind of match tracing earthquake spectral factorization device, it is characterised in that described device includes：
Acquisition module, for obtaining seismic signal, and using the seismic signal as current demand signal；
Centre frequency determining module, for according to the current demand signal, determining the centre frequency of atom to be searched；
Search module, meets the first pre-conditioned atom in complete storehouse, choosing for searching for preset using matching pursuit algorithm
Select in the first pre-conditioned atom of the satisfaction with the maximally related atom of the current demand signal, obtain the current demand signal in institute
The corresponding projection components at maximally related atom are stated, and it is residual with the signal of the corresponding projection components to obtain the current demand signal
Difference；The described first pre-conditioned centre frequency for the atom is equal to the centre frequency of the atom to be searched；
Replicated blocks, as new current demand signal, the centre frequency determining module is repeated for using the signal residual error
To the replicated blocks, untill the currently available signal residual error is less than predetermined threshold value；
Result obtains module, for according to all correspondence projection components, obtaining the earthquake spectral factorization knot of the geological data
Really.
8. device as claimed in claim 7, it is characterised in that the centre frequency determining module includes：
Analytic signal acquisition submodule, for according to the current demand signal, obtaining the analytic signal of the current demand signal；
Centre frequency obtains submodule, and for obtaining the analytic signal instantaneous energy highest moment, the current demand signal exists
The instantaneous frequency at the moment is the centre frequency of the atom to be searched.
9. device as claimed in claim 8, it is characterised in that the centre frequency obtain submodule specifically for：
The analytic signal instantaneous energy highest moment is obtained according to below equation,
tn=argmax | | c (t)+iH [c (t)] | |
In formula, tnThe expression instantaneous energy highest moment, c (t) expression current demand signals, H [] expression Hilbert transforms, c (t)+
IH [c (t)] represents analytic signal；
The instantaneous frequency is obtained by below equation,
In formula, ωnRepresent the centre frequency of atom to be searched.
10. device as claimed in claim 9, it is characterised in that the atom preset in complete storehouse is based on rake
What ripple built.
11. devices as claimed in claim 10, it is characterised in that the search module includes：
Atom determination sub-module, for determine it is described satisfaction the first pre-conditioned atom in it is exhausted with the inner product of the current demand signal
To the atom that value is maximum；
Cyclic submodule block, between the maximally related atom that judges the atom of the inner product maximum absolute value and determine before
Whether away from more than or equal to default minimum atomic separation, if the determination result is YES, then the atom of the inner product maximum absolute value is described
Maximally related atom, if being judged as NO, by the atom of the inner product maximum absolute value from the first pre-conditioned original of the satisfaction
Rejected in son, repeat above step, until judged result for untill being.
12. device as described in claim 7 to 11 is any, it is characterised in that the seismic signal is by smoothing processing
Seismic signal.
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109344847A (en) * | 2017-12-07 | 2019-02-15 | 太原理工大学 | Mining XLPE cable insulation electric branch growth phase recognition methods based on sparse decomposition |
| CN109375265A (en) * | 2018-08-22 | 2019-02-22 | 中国地质大学（武汉） | A kind of ideal earthquake spectral factorization method based on changeable phases Ricker wavelet match tracing |
| CN109752758A (en) * | 2019-01-16 | 2019-05-14 | 中国石油大学(华东) | A kind of seismic data decomposition method, system and storage medium and terminal |
| CN111239808A (en) * | 2018-11-28 | 2020-06-05 | 中国石油天然气股份有限公司 | Seismic inversion spectrum decomposition method and device, electronic equipment and storage medium |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5963507A (en) * | 1998-05-13 | 1999-10-05 | Western Atlas International, Inc. | Method for improving the accuracy of ocean bottom reflectivity estimations using the inverse backus filter |
| CN104422960A (en) * | 2013-09-02 | 2015-03-18 | 中国石油化工股份有限公司 | Seismic data fluid identification method based on self-adaption extraction of signal low-frequency intense anomaly |
| CN104570081A (en) * | 2013-10-29 | 2015-04-29 | 中国石油化工股份有限公司 | Pre-stack reverse time migration seismic data processing method and system by integral method |
| CN104570107A (en) * | 2013-10-29 | 2015-04-29 | 中国石油化工股份有限公司 | Time-frequency analysis method based on improved matching pursuit algorithm |
| CN105353408A (en) * | 2015-11-20 | 2016-02-24 | 电子科技大学 | Wigner higher-order spectrum seismic signal spectral decomposition method based on matching pursuit |
| CN105607122A (en) * | 2015-12-23 | 2016-05-25 | 西南科技大学 | Seismic texture extraction and enhancement method based on total variation seismic data decomposition model |
-
2016
- 2016-12-19 CN CN201611176693.5A patent/CN106855638A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5963507A (en) * | 1998-05-13 | 1999-10-05 | Western Atlas International, Inc. | Method for improving the accuracy of ocean bottom reflectivity estimations using the inverse backus filter |
| CN104422960A (en) * | 2013-09-02 | 2015-03-18 | 中国石油化工股份有限公司 | Seismic data fluid identification method based on self-adaption extraction of signal low-frequency intense anomaly |
| CN104570081A (en) * | 2013-10-29 | 2015-04-29 | 中国石油化工股份有限公司 | Pre-stack reverse time migration seismic data processing method and system by integral method |
| CN104570107A (en) * | 2013-10-29 | 2015-04-29 | 中国石油化工股份有限公司 | Time-frequency analysis method based on improved matching pursuit algorithm |
| CN105353408A (en) * | 2015-11-20 | 2016-02-24 | 电子科技大学 | Wigner higher-order spectrum seismic signal spectral decomposition method based on matching pursuit |
| CN105607122A (en) * | 2015-12-23 | 2016-05-25 | 西南科技大学 | Seismic texture extraction and enhancement method based on total variation seismic data decomposition model |
Non-Patent Citations (1)
| Title |
|---|
| 李传辉: "地震信号快速匹配追踪分解及瞬时谱分析", 《中国优秀硕士学位论文全文数据库 基础科学辑》 * |
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109344847A (en) * | 2017-12-07 | 2019-02-15 | 太原理工大学 | Mining XLPE cable insulation electric branch growth phase recognition methods based on sparse decomposition |
| CN109344847B (en) * | 2017-12-07 | 2022-03-15 | 太原理工大学 | Mining XLPE cable insulation electric branch growth stage identification method based on sparse decomposition |
| CN109375265A (en) * | 2018-08-22 | 2019-02-22 | 中国地质大学（武汉） | A kind of ideal earthquake spectral factorization method based on changeable phases Ricker wavelet match tracing |
| CN111239808A (en) * | 2018-11-28 | 2020-06-05 | 中国石油天然气股份有限公司 | Seismic inversion spectrum decomposition method and device, electronic equipment and storage medium |
| CN111239808B (en) * | 2018-11-28 | 2022-06-03 | 中国石油天然气股份有限公司 | Seismic inversion spectrum decomposition method and device, electronic equipment and storage medium |
| CN109752758A (en) * | 2019-01-16 | 2019-05-14 | 中国石油大学(华东) | A kind of seismic data decomposition method, system and storage medium and terminal |
| CN109752758B (en) * | 2019-01-16 | 2019-08-27 | 中国石油大学(华东) | A kind of seismic data decomposition method, system and storage medium and terminal |
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