CN112578440A - Extremum constrained three-parameter scanning wavelet decomposition method and system - Google Patents
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Abstract
The invention provides an extremum constrained three-parameter scanning wavelet decomposition method and a system, wherein the method comprises the following steps: s1, performing complex seismic trace analysis on the current seismic signal, and calculating the instantaneous attribute; s2, calculating initial parameters of the local optimal atoms according to the instantaneous attributes; s3, searching the phase, frequency and scale of the local optimal atom according to the initial parameters and extracting the time shift of the local optimal atom; s4, obtaining the residual error of the local optimal atoms and the seismic signals, recording the residual error of the seismic signals as the current seismic signals, and repeating the steps S1-S4 until preset conditions are met to obtain a series of wavelet combinations. The invention fully considers the relationship among wavelet control parameters and the influence of phase extreme values in a local range on the optimal matching parameters, improves the calculation efficiency and can obtain more accurate local optimal time-frequency atoms, thereby realizing high-precision and high-efficiency seismic wavelet decomposition.
Description
Technical Field
The invention belongs to the field of geophysical exploration, and particularly relates to an extremum constrained three-parameter scanning wavelet decomposition method and system.
Background
The spectrum imaging technology is a reservoir prediction characteristic interpretation technology based on seismic spectrum decomposition developed in recent years, and is an important component in seismic attribute analysis. The method becomes a valuable post-processing technology for researching complex oil and gas areas, the technology mainly utilizes the frequency spectrum tuning principle to describe the thickness and distribution of a reservoir stratum, and can also be used for describing sedimentary facies and sedimentary environment, detecting river channels and sand bodies, extracting various time-frequency attributes and the like.
The core of seismic spectrum decomposition is a time-frequency analysis technology of signals, and the time-frequency analysis is a conventional method for analyzing non-stationary signals. Common time-frequency analysis methods include linear time-frequency analysis methods, bilinear time-frequency analysis methods, parametric time-frequency analysis methods, and the like. The traditional STFT, CWT and GST are typical linear time-frequency analysis methods, which are restricted by uncertainty principle, and the time-frequency channel set can not reach higher time-frequency resolution at the same time. The Wigner-Ville distribution is a typical bilinear time frequency analysis method, and a single-component stable signal is decomposed, so that the time frequency resolution is high; however, WVD is bilinear and can exhibit severe cross terms when decomposing multi-component non-stationary signals.
Matching pursuit (also called wavelet decomposition) is a typical parameterized time-frequency analysis method, which is proposed in 1993 by s.mallat and z.zhang, and can decompose seismic signals into a set of a series of wavelets, and when a single wavelet is used for calculating a time-frequency spectrum by using WVD, decomposition of non-stationary signals can also obtain higher time-frequency resolution. The technology is applied to various aspects in the geophysical field since the proposal, such as reflection coefficient inversion, resolution enhancement processing, noise removal, strong reflection removal, thin sand body prediction, seismic inversion, seismic sediment interpretation, geologic body detection and the like. However, the technology realizes the decomposition of the seismic signals by continuously searching for local optimal atoms, and has low calculation efficiency. In order to improve the calculation efficiency, YangHua Wang (2007) researches a matching tracking method which combines global coarse grain prediction and local optimum in an iteration process, the calculation efficiency is improved, but the relation between parameters is not considered in the local optimum wavelet searching process, and the decomposition precision cannot be guaranteed; zhang Guangchang (2010) provides a double-parameter dynamic scanning technology, which improves the decomposition efficiency, but does not consider the influence of wavelet scale, and the wavelet scale is a fixed value and is not in line with the actual situation.
Therefore, the problem of local optimal atom search efficiency and precision in wavelet decomposition still needs to be solved.
Disclosure of Invention
Features and advantages of the invention will be set forth in part in the description which follows, or may be obvious from the description, or may be learned by practice of the invention.
In order to overcome the problems of the prior art, the invention provides an extremum constrained three-parameter scanning wavelet decomposition method, which comprises the following steps:
s1, performing complex seismic trace analysis on the current seismic signal, and calculating the instantaneous attribute;
s2, calculating initial parameters of the local optimal atoms according to the instantaneous attributes;
s3, searching the phase, frequency and scale of the local optimal atom according to the initial parameters and extracting the time shift of the local optimal atom;
s4, obtaining residual error x of local optimal atoms and seismic signalsi+1(t) and comparing the residual x of said seismic signali+1And (t) recording the signals as current seismic signals, and repeating the steps S1 to S4 until preset conditions are met to obtain a series of wavelet combinations.
Alternatively,the instantaneous properties include instantaneous amplitude, instantaneous frequency and instantaneous phase, and the initial parameters include an initial time shift
Initial frequency
Initial phase
Initial dimension
The step S2 includes:
searching for a maximum of said instantaneous amplitude, said initial time shift
The initial frequency being the time corresponding to the maximum of the instantaneous amplitude
For the instantaneous frequency corresponding to that time, the initial phase
The instantaneous phase corresponding to the time;
using initial time shift
Initial phase
Initial frequency
Obtaining initial scale by maximum matching projection principle
Optionally, the step S3 includes:
searching the phase phi of the local optimum atom in the given parameter variation range according to the maximum matching projection principleiFrequency fiSum scale σi；
Searching a monotonous interval of the instantaneous phase in a given time-shifting search interval, and searching a local optimal phase phi in the monotonous intervaliThe position corresponding to the closest phase is taken as the local optimum time shift ui。
Optionally, the step S4 includes:
obtaining the amplitude a of the local optimal atom according to the phase, frequency, scale and time shift of the optimal atomiResidual x of said seismic signali+1(t) is a seismic signal xi(t) subtracting the local optimum atom and amplitude aiThe product of (a). Alternatively, the locally optimal atom M is calculated by the following formula, respectivelyi(t) and amplitude of local optimum atom ai：
Wherein the content of the first and second substances,
for the optimal atom from the ith iteration, R(i)And X is the seismic signal of the ith iteration.
Optionally, the preset conditions in step S4 are: the iteration number reaches a preset threshold value or the residual error x of the seismic signali+1The energy of (t) is less than P% of the energy of the original signal x (t).
Optionally, the preset threshold is less than 1/3% of the seismic signal length, and the P% is less than 20%.
The invention provides an extremum constrained three-parameter scanning wavelet decomposition system, comprising:
the analysis unit is used for carrying out complex seismic channel analysis on the current seismic signal and calculating the instantaneous attribute;
the initial parameter calculation unit is used for calculating the initial parameters of the local optimal atoms according to the instantaneous attributes;
the optimal parameter calculation unit is used for searching the phase, frequency and scale of the local optimal atom according to the initial parameters and extracting the time shift of the local optimal atom;
a local optimal atom obtaining unit for obtaining a local optimal atom;
an iterative calculation unit for calculating residual x of the seismic signali+1(t) and comparing the residual x of said seismic signali+1(t) recording as current seismic signals;
and the iteration judging unit is used for judging whether the preset conditions are met or not, if so, terminating the iteration calculation and acquiring a series of combinations of wavelets.
Optionally, the optimal parameter calculation unit is specifically configured to: searching the phase phi of the local optimum atom in the given parameter variation range according to the maximum matching projection principleiFrequency fiAnd the scale parameter σi(ii) a Searching a monotonous interval of the instantaneous phase in a given time-shifting search interval, and searching a local optimal phase phi in the monotonous intervaliThe position corresponding to the closest phase is taken as the local optimum time shift ui。
The present invention provides a computer-readable storage medium storing at least one program executable by a computer, the at least one program, when executed by the computer, causing the computer to perform the steps of a method provided by any of the embodiments of the present invention.
The extreme value constrained three-parameter scanning wavelet decomposition method and system provided by the invention fully consider the relationship among wavelet control parameters and the influence of the phase extreme value in a local range on the optimal matching parameter, improve the calculation efficiency and simultaneously obtain more accurate local optimal time-frequency atoms, thereby realizing high-precision and high-efficiency seismic wavelet decomposition.
Drawings
FIG. 1 is a flowchart illustrating the steps of an extremum constrained three-parameter wavelet decomposition method according to an embodiment of the present invention.
FIG. 2 is a flowchart illustrating the steps of an extremum-constrained three-parameter wavelet decomposition method according to an embodiment of the present invention.
FIG. 3 is a schematic structural diagram of an extremum constrained three-parameter scanning wavelet decomposition system according to an embodiment of the present invention.
FIG. 4 is a diagram of an actual seismic signal.
FIG. 5 shows wavelets decomposed by the atomic wave decomposition technique.
FIG. 6 is a time-frequency trace set of seismic signals obtained by atomic wave decomposition techniques.
FIG. 7 is a graph of wavelets decomposed using the present invention.
FIG. 8 is a time-frequency trace set of seismic signals calculated using the present invention.
Detailed Description
The invention is described in further detail below with reference to the accompanying drawings:
as shown in FIG. 1, the present invention provides an extremum constrained three-parameter wavelet decomposition method, comprising:
s1, performing complex seismic trace analysis on the current seismic signal, and calculating the instantaneous attribute;
transient properties include instantaneous amplitude, instantaneous frequency and instantaneous phase. Inputting seismic signal x (t), and comparing the current seismic signal xiAnd (t) performing complex seismic trace analysis to calculate three curves of instantaneous amplitude, instantaneous phase and instantaneous frequency. x is the number ofi(t) is the signal of the ith iteration, which is the original input seismic signal x (t). Complex seismic trace analysis of digital signals is a well-known common technology and is often used in three-transient attribute analysis, and the calculation process and the three-transient attribute extraction are described in detail in well-known textbooks and are not described in detail herein.
S2, calculating initial parameters of the local optimal atoms according to the instantaneous attributes;
more specifically, the maximum of the instantaneous amplitude is searched, the initial time shift
I.e. the time corresponding to the maximum of the instantaneous amplitude, the initial frequency
I.e. the instantaneous frequency, the initial phase, corresponding to the time
I.e. the instantaneous phase corresponding to that time.
Using initial time shift
Initial phase
Initial frequency
Obtaining initial scale by maximum matching projection principle
S3, searching the phase, frequency and scale of the local optimal atom according to the initial parameters and extracting the time shift of the local optimal atom;
searching local optimum phase phi in given parameter variation range according to maximum matching projection principleiFrequency fiAnd the scale parameter σi。
Searching a monotonous interval of the instantaneous phase in a given time-shifting search interval, and searching a local optimal phase phi in the monotonous intervaliThe position corresponding to the closest phase is taken as the local optimum time shift ui。
In practice, the initial dimension
Is fixed in a group
Then, the method is obtained by calculating an optimization formula (1);
wherein D ═ { M ═r(t)}r∈ΓIs a dictionary of time-frequency atoms,
is a function R(i)X and
is internally accumulated, and
R(i)x represents the residual signal of the ith iteration, the 1 st iteration is X (t), and Mr(t) is a time-frequency atom determined by a parameter r, the time-frequency atom is obtained by formula (2), ri＝{ui,σi,fi,φiAnd i represents the number of iterations.
At the initial time shift
Under the fixed condition, searching the local optimal phase phi in the given parameter variation range according to the maximum matching projection principleiFrequency fiAnd the scale parameter σi。
In this embodiment, the local optimization of the three parameters of phase, frequency and scale is to find r in a local areai＝{ui0,σi,fi,φiH, the initial time shift ui0Fixed and constant, search range is [ r ]i-Δr,ri+Δr]Where Δ r is (Δ u, Δ σ, Δ f, Δ Φ), that is, Δ u is 0 as a time offset, Δ σ is 0.1 as a scale offset, Δ f is 5Hz as a frequency offset, and Δ Φ is 50 as a phase offset. In specific implementation, different values are arbitrarily selected within the range given by each parameter, a group of time-frequency atoms are obtained by the formula (2), and the corresponding parameter is the local optimal phi when the formula (1) reaches the maximumi、fiAnd σi。
The locally optimal time shift is obtained from the relationship of the locally optimal phase and the instantaneous phase profile. More specifically, at a given time-shifted search interval
Inner search effective monotonic interval of instantaneous phase
The instantaneous phase is monotonically increasing or monotonically decreasing in the interval, and the local optimum phase phi is searched in the intervaliThe phase position with the minimum difference is the local optimum time shift u of the searchi。
S4, obtaining the local optimal atoms and the residual error of the seismic signal, and calculating the residual error x of the seismic signali+1And (t) recording the signals as current seismic signals, and repeating the steps S1 to S4 to carry out iterative decomposition until preset conditions are met to obtain a series of wavelet combinations.
Obtaining the amplitude a of the local optimal atom according to the phase, frequency, scale and time shift of the optimal atomi(ii) a And then obtaining residual error x of the seismic signal according to the phase, frequency, scale, time shift and amplitude of the optimal atomi+1(t) of (d). Residual x of seismic signali+1(t) is a seismic signal xi(t) subtracting the local optimum atom and amplitude aiThe product of (a).
More specifically, according to the phase phi of the locally optimal atomiFrequency fiDimension σiAnd time shift uiObtaining the amplitude a of the locally optimal atom in combination with the formula (3)i. Equation (3) is as follows:
wherein the content of the first and second substances,
for the optimal parameter r from the ith iterationi＝{ui,σi,fi,φiAnd the locally optimal atom, R, determined by equation (2)(i)X is seismic signal of ith iteration, R of 1 st iteration(i)X is the original seismic signal X (t).
Phase phi of locally optimal atomiFrequency fiDimension σiAnd time shift uiSubstituting the parameters into formula (2) to obtain the locally optimal atom Mi(t) of (d). Seismic signal xi(t) subtracting the local optimum atom and amplitude aiObtaining a residual x of the seismic signali+1(t) of (d). For calculating the residual xi+1The formula of (t) is as follows:
xi+1(t)＝xi(t)-aiMi(t) (4)
the preset condition comprises that the iteration number reaches a preset threshold value or the residual error x of the seismic signali+1The energy of (t) is less than P% of the energy of the original signal x (t). Wherein the preset threshold is less than 1/3 of the seismic signal length, and P is not more than 20. In this embodiment, the exit condition is 167 predetermined iterations or the residual xi+1The energy of (t) is less than 10% of the energy of the original signal x (t).
The final raw seismic signal is decomposed into a combination of a series of wavelets, as shown in equation (5):
referring to fig. 2, the present invention provides an extremum constrained three-parameter wavelet decomposition method, comprising:
101. and starting.
102. Inputting a current seismic signal;
103. analyzing the complex seismic channel;
for the current seismic signal xi(t) performing complex seismic trace analysis, and calculating instantaneous amplitude, instantaneous phase and instantaneous frequency. Obtaining an initial time shift, an initial frequency and an initial phase according to the instantaneous amplitude; more specifically, the maximum of the instantaneous amplitude is searched, the initial time shift
I.e. the time corresponding to the maximum of the instantaneous amplitude, the initial frequency
I.e. the instantaneous frequency, the initial phase, corresponding to the time
I.e. the instantaneous phase corresponding to that time.
104. Matching an initial scale;
obtaining an initial scale on the basis of the initial time shift, the initial frequency and the initial phase; in this embodiment, initial time shifting is utilized
Initial phase
Initial frequency
And the above equations (1) and (2) to obtain the initial scale
105. Local dynamic scanning;
at the initial time shift
In the fixed case, according to the mostSearching local optimum phase phi in given parameter variation range by large matching projection principleiFrequency fiAnd the scale parameter σi
106. Extracting the time shift of the local optimal atom;
and extracting the time shift of the local optimal atom by using the instantaneous phase attribute calculated in the complex seismic channel analysis and the local optimal phase obtained by the local dynamic scanning. More specifically, at a given time-shifted search interval
Inner search effective monotonic interval of instantaneous phase
The instantaneous phase is monotonically increasing or monotonically decreasing in the interval, and the local optimum phase phi is searched in the intervaliThe phase position with the minimum difference is the local optimum time shift u of the searchi。
107. Calculating local optimal atoms;
phase phi of locally optimal atomiFrequency fiDimension σiAnd time shift uiSubstituting the parameters into formula (2) to obtain the locally optimal atom Mi(t)。
108. Judging whether a preset condition is met, if so, entering a step 11, and ending the process; if not, go to step 109;
109. removing local optimal atoms to obtain a residual error;
obtaining the amplitude a of the local optimal atom according to the phase, frequency, scale and time shift of the optimal atom and the formula (3)i(ii) a And then obtaining residual error x of the seismic signal according to the phase, frequency, scale, time shift and amplitude of the optimal atomi+1(t) of (d). Residual x of seismic signali+1(t) is a seismic signal xi(t) subtracting the local optimum atom and amplitude aiThe product of (a).
The preset condition comprises that the iteration number reaches a preset threshold value or the residual error x of the seismic signali+1(t) is low in energyP% of the energy of the original signal x (t). Wherein the preset threshold is less than 1/3 of the seismic signal length, and P is not more than 20. In this embodiment, the exit condition is 167 predetermined iterations or the residual xi+1The energy of (t) is less than 10% of the energy of the original signal x (t).
110. The residual is recorded as the current seismic signal and returns to step 102.
111. And ending the process.
The final raw seismic signal is decomposed into a combination of a series of wavelets as shown in equation (5).
The present invention provides a computer-readable storage medium storing at least one program executable by a computer, the at least one program, when executed by the computer, causing the computer to perform the steps of a method provided by any of the embodiments of the present invention.
As shown in FIG. 3, the present invention provides an extremum constrained three-parameter scanning wavelet decomposition system, comprising: the system comprises an analysis unit 10, an initial parameter calculation unit 20, an optimal parameter calculation unit 30, a local optimal atom acquisition unit 40, an iterative calculation unit 50 and an iterative judgment unit 60. Wherein:
the analysis unit 10 is used for performing complex seismic channel analysis on the current seismic signal and calculating the instantaneous attribute; more specifically, the analyzing unit is used to implement step S1, and is not described herein again.
The initial parameter calculation unit 20 is connected to the analysis unit 10 and configured to calculate an initial parameter of the locally optimal atom according to the transient property; more specifically, the initial parameter calculation unit is used to implement step S2, and is not described herein again.
The optimal parameter calculation unit 30 is connected to the analysis unit 10 and the initial parameter calculation unit 20, and the optimal parameter calculation unit 30 is configured to search for a phase, a frequency, and a scale of a local optimal atom according to the initial parameter and extract a time shift of the local optimal atom; more specifically, the optimum parameter calculation unit is used to implement step S30, and will not be described herein.
The local optimal atom obtaining unit 40 is configured to obtain a local optimal atom; phase of locally optimal atomφiFrequency fiDimension σiAnd time shift uiSubstituting the parameters into formula (2) to obtain the locally optimal atom Mi(t)。
The iterative computation unit 50 is connected to the local optimal atom acquisition unit 40 for computing a residual x of the seismic signali+1(t) and comparing the residual x of said seismic signali+1(t) is recorded as the current seismic signal. Residual x of seismic signali+1(t) is a seismic signal xi(t) subtracting the local optimum atom and amplitude aiThe product of (a); obtaining the amplitude a of the local optimal atom according to the phase, frequency, scale and time shift of the optimal atom and the formula (3)i。
The iteration judging unit 60 is connected to the iteration calculating unit 50, and is configured to judge whether a preset condition is satisfied, and if so, terminate the iteration calculation, and obtain a series of combinations of wavelets. The preset condition comprises that the iteration number reaches a preset threshold value or the residual error x of the seismic signali+1The energy of (t) is less than P% of the energy of the original signal x (t). Wherein the preset threshold is less than 1/3 of the seismic signal length, and P is not more than 20. In this embodiment, the exit condition is 167 predetermined iterations or the residual xi+1The energy of (t) is less than 10% of the energy of the original signal x (t).
The advantageous effects of the embodiments of the present invention are explained below by a specific example.
Fig. 4 shows an actual seismic signal, from which it can be seen that the maximum and minimum values of the seismic waveform are between 800ms and 1000ms, and the maximum energy of the calculated time spectrum should also be between 800ms and 1000 ms.
Fig. 5 shows the wavelets decomposed by the original four-parameter dynamic scanning wavelet decomposition method, and the wavelets output by each step of iteration are sequentially from left to right, the iteration time is 80 times, and the iteration time is 381 seconds. It can be seen from the solid line circle in the figure that a plurality of wavelets appear at the same position, the polarity is opposite, and the energy of the next wavelet is greater than that of the previous wavelet, and this phenomenon appears because the wavelet deviates from the position of the maximum value of the instantaneous amplitude during searching time shift, and the root cause is that when the time shift parameter of the local optimal atom is searched, the instantaneous phase jumps in the time shift disturbance range, namely, pi suddenly changes to-pi, the phase size of the searched local optimal atom has no problem, but the time shift has a difference and deviates from the maximum position of the instantaneous amplitude, so that the local optimal atom of the iteration is incorrect, and the calculated residual signal is incorrect and directly influences the subsequent iteration process. Meanwhile, as can be seen from the figure, such a situation generally occurs in pairs, because the instantaneous amplitude energy of the position is the largest at the ith iteration, but the deviation occurs when the locally optimal atom is picked up, and the energy of the residual signal is strengthened near the position, so that the wavelet energy of the next iteration search is higher than that of the previous iteration, and the iteration logic is not satisfied.
FIG. 6 shows the time spectrum of the wavelet computation decomposed by the original four-parameter dynamic scanning wavelet decomposition method. As shown in FIG. 5 of the original seismic signal, the maximum energy of the seismic signal should be between 800ms and 1000ms, and according to the time-frequency analysis principle, the maximum energy mass of the time-frequency analysis should also be between 800ms and 1000ms, but the maximum energy (the darkest part) in FIG. 6 is below 1400ms, which is consistent with the maximum energy wavelet in the first black circle shown in FIG. 5; strong energy clusters below 1000ms are related to wavelets in the rightmost circle in fig. 5, and three wavelets (with opposite polarities) appear at the same position, which directly causes the energy of the energy clusters in the time spectrum to have problems. Because the influence of the phase is not considered in the decomposition process, the decomposition wavelet is incorrect, so the calculated time frequency spectrum is also incorrect, and the subsequent application of the time frequency spectrum is directly influenced.
FIG. 7 shows the wavelet decomposed by the extremum-constrained three-parameter wavelet decomposition method of the present invention, with an iteration count of 60 and an iteration time of 19 seconds. It can be seen from the figure that the energy of the wavelet is continuously reduced, which is consistent with the practical iterative decomposition idea, and the situation that two wavelets are at the same position does not exist, and the constraint of the phase extremum proposed by the invention is benefited. The energy of the first wavelet is the largest and appears between 800ms and 1000ms, the time frequency spectrum calculated by the method is shown in figure 8, and the energy relation of the time frequency spectrum can also show that the maximum energy of the time frequency spectrum also appears between 800ms and 1000ms and is consistent with the maximum energy position of the seismic signal. The iteration times are not very different, but the calculation time is greatly reduced.
In a word, compared with the existing wavelet decomposition technology, the method fully considers the relation among the time-frequency atom decision parameters, reduces the existing four-parameter dynamic search into three-parameter dynamic search, and improves the calculation efficiency; meanwhile, the influence of phase mutation on local optimal time shift is considered, the optimal phase is searched in the monotonous interval of the instantaneous phase, the local optimal time shift is determined by the local optimal phase, and the accuracy of wavelet decomposition is improved.
The invention provides an extremum constrained three-parameter scanning wavelet decomposition method and system, which can realize wavelet decomposition with higher precision and improve the calculation efficiency. The invention fully considers the relation between the time-frequency atom decision parameters, reduces the prior four-parameter dynamic search into three-parameter dynamic search, and improves the calculation efficiency; meanwhile, the influence of phase mutation on local optimal time shift is considered, the optimal phase is searched in the monotonous interval of the instantaneous phase, the local optimal time shift is determined by the local optimal phase, and the accuracy of wavelet decomposition is improved.
The above-described embodiment is only one embodiment of the present invention, and it will be apparent to those skilled in the art that various modifications and variations can be easily made based on the application and principle of the present invention disclosed in the present application, and the present invention is not limited to the method described in the above-described embodiment of the present invention, so that the above-described embodiment is only preferred, and not restrictive.
Claims (10)
1. An extremum constrained three-parameter scanning wavelet decomposition method, comprising:
s1, performing complex seismic trace analysis on the current seismic signal, and calculating the instantaneous attribute;
s2, calculating initial parameters of the local optimal atoms according to the instantaneous attributes;
s3, searching the phase, frequency and scale of the local optimal atom according to the initial parameters, and extracting the time shift of the local optimal atom;
s4, obtaining residual error x of local optimal atoms and seismic signalsi+1(t) and comparing the residual x of said seismic signali+1And (t) recording the signals as current seismic signals, and repeating the steps S1 to S4 until preset conditions are met to obtain a series of wavelet combinations.
2. The extremum-constrained three-parameter swept wavelet decomposition method of claim 1, wherein the instantaneous attributes comprise instantaneous amplitude, instantaneous frequency and instantaneous phase, and the initial parameters comprise an initial time shift
Initial frequency
Initial phase
Initial dimension
The step S2 includes:
searching for a maximum of said instantaneous amplitude, said initial time shift
The initial frequency being the time corresponding to the maximum of the instantaneous amplitude
For the instantaneous frequency corresponding to that time, the initial phase
The instantaneous phase corresponding to the time;
using initial time shift
Initial phase
Initial frequency
Obtaining initial scale by maximum matching projection principle
3. The extremum-constrained three-parameter scanning wavelet decomposition method of claim 1, wherein said step S3 comprises:
searching the phase phi of the local optimum atom in the given parameter variation range according to the maximum matching projection principleiFrequency fiSum scale σi；
Searching a monotonous interval of the instantaneous phase in a given time-shifting search interval, and searching a local optimal phase phi in the monotonous intervaliThe position corresponding to the closest phase is taken as the local optimum time shift ui。
4. The extremum-constrained three-parameter scanning wavelet decomposition method of claim 1, wherein said step S4 comprises: obtaining the amplitude a of the local optimal atom according to the phase, frequency, scale and time shift of the optimal atomiResidual x of said seismic signali+1(t) is a seismic signal xi(t) subtracting the local optimum atom and amplitude aiThe product of (a).
5. The extremum-constrained three-parameter scanning wavelet decomposition method of claim 4, wherein the locally optimal atom M is calculated by the following formulai(t) and amplitude of local optimum atom ai：
Wherein the content of the first and second substances,
for the optimal atom from the ith iteration, R(i)And X is the seismic signal of the ith iteration.
6. The extremum-constrained three-parameter scanning wavelet decomposition method of claim 1, wherein the preset conditions in step S4 are: the iteration number reaches a preset threshold value or the residual error x of the seismic signali+1The energy of (t) is less than P% of the energy of the original signal x (t).
7. The extremum-constrained three-parameter swept wavelet decomposition method of claim 6, wherein said predetermined threshold is less than 1/3% of the seismic signal length, and said P% is less than 20%.
8. An extremum constrained three-parameter scanning wavelet decomposition system, comprising:
the analysis unit is used for carrying out complex seismic channel analysis on the current seismic signal and calculating the instantaneous attribute;
the initial parameter calculation unit is used for calculating the initial parameters of the local optimal atoms according to the instantaneous attributes;
the optimal parameter calculation unit is used for searching the phase, frequency and scale of the local optimal atom according to the initial parameters and extracting the time shift of the local optimal atom;
a local optimal atom obtaining unit for obtaining a local optimal atom;
an iterative calculation unit for calculating residual x of the seismic signali+1(t) and removing residuals of said seismic signalsDifference xi+1(t) recording as current seismic signals;
and the iteration judging unit is used for judging whether the preset conditions are met or not, if so, terminating the iteration calculation and acquiring a series of combinations of wavelets.
9. The extremum-constrained three-parameter scanning wavelet decomposition system of claim 1, wherein the optimal parameter computing unit is specifically configured to: searching the phase phi of the local optimum atom in the given parameter variation range according to the maximum matching projection principleiFrequency fiAnd the scale parameter σi(ii) a Searching a monotonous interval of the instantaneous phase in a given time-shifting search interval, and searching a local optimal phase phi in the monotonous intervaliThe position corresponding to the closest phase is taken as the local optimum time shift ui。
10. A computer-readable storage medium storing at least one program executable by a computer, the at least one program, when executed by the computer, causing the computer to perform the steps of the method of any one of claims 1 to 7.
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Citations (15)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6188964B1 (en) * | 1999-09-14 | 2001-02-13 | Ut-Battelle, Llc | Method for using global optimization to the estimation of surface-consistent residual statics |
| EP1094338A1 (en) * | 1999-10-22 | 2001-04-25 | Jason Geosystems B.V. | Method of estimating elastic parameters and rock composition of underground formations using seismic data |
| US20040078160A1 (en) * | 2002-10-11 | 2004-04-22 | Frei Mark G. | Method, computer program, and system for intrinsic timescale decomposition, filtering, and automated analysis of signals of arbitrary origin or timescale |
| GB0421346D0 (en) * | 2004-09-24 | 2004-10-27 | Smith Jonathan S R | Product representations of amplitude and frequency modulated signals |
| CN102116868A (en) * | 2009-12-31 | 2011-07-06 | 中国石油化工股份有限公司 | Seismic wave decomposition method |
| CN102804771A (en) * | 2009-06-22 | 2012-11-28 | 汤姆森特许公司 | Process For Matching Pursuit Based Coding Of Video Data For A Sequence Of Images |
| CN103558635A (en) * | 2013-10-30 | 2014-02-05 | 北京诺克斯达石油科技有限公司 | Method and device for estimating film thickness based on even function seismic response |
| CN103728660A (en) * | 2012-10-12 | 2014-04-16 | 中国石油化工股份有限公司 | Multi-channel matching tracking method based on seismic data |
| CN104298863A (en) * | 2014-09-28 | 2015-01-21 | 江南大学 | Method for quickly searching for three-parameter Chirp time-frequency atoms |
| CN105277973A (en) * | 2014-05-26 | 2016-01-27 | 中国石油化工股份有限公司 | Matching pursuit based wavelet decomposition optimization method |
| 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 |
| CN106483561A (en) * | 2015-08-24 | 2017-03-08 | 中国石油化工股份有限公司 | A kind of wavelet decomposition method of frequency domain |
| CN106842298A (en) * | 2015-12-04 | 2017-06-13 | 中国石油化工股份有限公司 | A kind of unconformity strong reflection auto-adaptive separating method based on match tracing |
| CN108061916A (en) * | 2016-11-09 | 2018-05-22 | 中国石油化工股份有限公司 | A kind of seismic reflection recognition methods of multiple tracks constraint |
| CN109861721A (en) * | 2019-03-06 | 2019-06-07 | 重庆邮电大学 | A kind of compressed sensing based Frequency Hopping Signal sparse decomposition method |
-
2019
- 2019-09-30 CN CN201910937317.0A patent/CN112578440A/en active Pending
Patent Citations (15)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6188964B1 (en) * | 1999-09-14 | 2001-02-13 | Ut-Battelle, Llc | Method for using global optimization to the estimation of surface-consistent residual statics |
| EP1094338A1 (en) * | 1999-10-22 | 2001-04-25 | Jason Geosystems B.V. | Method of estimating elastic parameters and rock composition of underground formations using seismic data |
| US20040078160A1 (en) * | 2002-10-11 | 2004-04-22 | Frei Mark G. | Method, computer program, and system for intrinsic timescale decomposition, filtering, and automated analysis of signals of arbitrary origin or timescale |
| GB0421346D0 (en) * | 2004-09-24 | 2004-10-27 | Smith Jonathan S R | Product representations of amplitude and frequency modulated signals |
| CN102804771A (en) * | 2009-06-22 | 2012-11-28 | 汤姆森特许公司 | Process For Matching Pursuit Based Coding Of Video Data For A Sequence Of Images |
| CN102116868A (en) * | 2009-12-31 | 2011-07-06 | 中国石油化工股份有限公司 | Seismic wave decomposition method |
| CN103728660A (en) * | 2012-10-12 | 2014-04-16 | 中国石油化工股份有限公司 | Multi-channel matching tracking method based on seismic data |
| CN103558635A (en) * | 2013-10-30 | 2014-02-05 | 北京诺克斯达石油科技有限公司 | Method and device for estimating film thickness based on even function seismic response |
| CN105277973A (en) * | 2014-05-26 | 2016-01-27 | 中国石油化工股份有限公司 | Matching pursuit based wavelet decomposition optimization method |
| CN104298863A (en) * | 2014-09-28 | 2015-01-21 | 江南大学 | Method for quickly searching for three-parameter Chirp time-frequency atoms |
| CN106483561A (en) * | 2015-08-24 | 2017-03-08 | 中国石油化工股份有限公司 | A kind of wavelet decomposition method of frequency domain |
| 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 |
| CN106842298A (en) * | 2015-12-04 | 2017-06-13 | 中国石油化工股份有限公司 | A kind of unconformity strong reflection auto-adaptive separating method based on match tracing |
| CN108061916A (en) * | 2016-11-09 | 2018-05-22 | 中国石油化工股份有限公司 | A kind of seismic reflection recognition methods of multiple tracks constraint |
| CN109861721A (en) * | 2019-03-06 | 2019-06-07 | 重庆邮电大学 | A kind of compressed sensing based Frequency Hopping Signal sparse decomposition method |
Non-Patent Citations (7)
| Title |
|---|
| 刘汉卿 等: "《动态匹配追踪中利用连续相位求取瞬时频率》", 《物探与化探》, vol. 39, no. 1, pages 211 - 216 * |
| 宋炜 等: "《快速匹配追踪三参数时频特征滤波》", 《石油地球物理勘探》, vol. 48, no. 4, pages 519 - 528 * |
| 张雪冰 等: "《基于局部均值分解的地震信号时频分解方法》", 《吉林大学学报(地球科学版)》, vol. 47, no. 5, pages 1562 - 1571 * |
| 蔡涵鹏 等: "《基于混合优化算法的地震数据匹配追踪分解》", 《中南大学学报(自然科学版)》, vol. 44, no. 2, pages 687 - 694 * |
| 陈双全 等: "《应用局部频率属性检测天然气藏》", 《石油地球物理勘探》, vol. 47, no. 5, pages 754 - 757 * |
| 高静怀 等: "《小波变换域地震资料瞬时频率分析方法》", 《石油物探》, vol. 46, no. 6, pages 532 - 540 * |
| 黄跃 等: "《多子波分解与重构中子波的优选》", 《石油物探》, vol. 52, no. 1, 31 January 2013 (2013-01-31), pages 17 - 23 * |
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