CN106199715B - Strong reflection separation method and device based on model - Google Patents
Strong reflection separation method and device based on model Download PDFInfo
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Abstract
The invention discloses a kind of strong reflection separation method and device based on model, which comprises strong reflection model is established according to real well data；For strong reflection lineups three wink of progress Parameter analysis, initial wavelet control parameter is obtained；The control parameter is optimized, is obtained and strong reflection lineups best match wavelet；Best match wavelet is subtracted from original earthquake data, the data after obtaining strong reflection separation obtain model test conclusion；Conclusion (of pressure testing) is used for real data analysis, carries out strong reflection separation；Carry out the analysis of well bypass road, adjusting parameter；It determines final matching Wavelet parameter, obtains whole district's strong reflection separating resulting.Strongly reflecting layer can be separated by this method, prominent reservoir weak signal improves the precision of reservoir prediction.
Description
Technical field
The present invention relates to the explanatory process fields of seismic signal, and in particular to a kind of strong reflection separation method based on model
And device.
Background technique
When handling seismic signal, there are problems that strong reflection lineups shield reservoir weak signal, surveyed in earthquake
In spy, as Modern seismic exploration targets is from structural oil pool to elusive reservoirs such as small sand body, narrow river, thin interbed, microcracks
Transfer, the seismic response energy of reservoir targets is weaker, is often submerged among background information even background noise, waveform is also often sent out
Raw distortion.Therefore, how the weak variable signal of weak signal or space effectively detects as a problem, expands in the prior art
Including High-resolution Processing, attributive analysis, prestack post-stack inversion, and strongly reflecting layer separation method for rising recently etc. is ground
Study carefully.
Matching pursuit algorithm (Matching Pursuit) is proposed that the algorithm can resolve into original signal by Mallat etc.
The linear combination of multiple atoms, these atoms are determined by one group of control parameter: center delay time, centre frequency, phase, ruler
Spend the factor and amplitude.By selecting the combination of different parameters atom, original signal is reconstructed, to reach denoising, frequency dividing etc.
Purpose.Aiming at the problem that strong reflection lineups shield reservoir weak signal, matching pursuit algorithm is a kind of relatively new method, but
It is that in the actual operation process, the selection of control parameter is a very crucial problem, the selection of parameter seriously constrains this
Effective application of method.
Summary of the invention
For the defects in the prior art, the present invention provides a kind of strong reflection separation method and device based on model,
This method can separate strongly reflecting layer using match tracing technology in conjunction with real data feature, the prominent weak letter of reservoir
Number, improve the precision of reservoir prediction.
According to the present invention on one side, a kind of strong reflection separation method based on model is provided, which is characterized in that described
Method the following steps are included:
(1) strong reflection model is established according to real well data；
(2) for strong reflection lineups three wink of progress Parameter analysis, initial control parameter is obtained；Wherein, the control ginseng
Number is γ={ u, f, φ, k }, and u, f, φ and k respectively represent wavelet center delay time, centre frequency, phase and scale factor；
(3) control parameter is optimized, is obtained and strong reflection lineups best match wavelet；
(4) best match wavelet is subtracted from original earthquake data, the data after obtaining strong reflection separation obtain model
Conclusion (of pressure testing)；
(5) experiment conclusion is used for real data analysis, carries out strong reflection separation；
(6) analysis of well bypass road is carried out, enters step (7) if meeting the requirements, (5) is otherwise entered step and carries out parameter adjustment；
(7) it determines final matching Wavelet parameter, obtains whole district's strong reflection separating resulting.
Optionally, described for strong reflection lineups three wink of progress Parameter analysis, obtaining initial matching parameter includes:
The three winks Parameter analysis includes: using the time at instantaneous amplitude largest enveloping as wavelet center delay time
un, by frequency f centered on the instantaneous frequency at instantaneous amplitude largest envelopingnWith by the instantaneous phase at instantaneous amplitude largest enveloping
Position is used as sub-wave phase φn, obtain initial control parameter { un,fn,φn}；And
Determine that scale factor k, the scale factor k are calculated by the following formula to obtain:
Wherein, hereIt is small echo redundant dictionary, is over-complete dictionary of atoms；<f, g>represent the interior of f and g
Product,It is by waveletIt is normalized.
Optionally, described that Wavelet parameter is optimized, obtain include: with strong reflection lineups best match wavelet
According to formulaWhen optimizing the delay of wavelet center in searching for dictionary
Between un, centre frequency fn, phasen, then disturbed near initial value, obtain search range [un-Δu,un+ Δ u], [fn-Δ
f,fn+ Δ f], [φn-Δφ,φn+ Δ φ], [kn-Δk,kn+ Δ k], Δ u is time interval, and Δ f is frequency interval, Δ φ
It is phase intervals, Δ k is scale parameter interval.
Optionally, described that Wavelet parameter is optimized, obtain include: with strong reflection lineups best match wavelet
According to model test result and real data feature, optimization obtains the wavelet with the strong reflection best match.
Optionally, the control parameter further includes wavelet amplitude an, and wavelet amplitude is obtained by following formula:
According to the present invention on the other hand, a kind of strong reflection separator based on model is provided, which is characterized in that described
Device include the following:
Model building module, for establishing strong reflection model according to real well data；
Parameter initialization module, for obtaining initial control parameter for strong reflection lineups three wink of progress Parameter analysis；
Wherein, the control parameter be γ={ u, f, φ, k }, u, f, φ and k respectively represent wavelet center delay time, centre frequency,
Phase and scale factor；
Parameter optimization module obtains and strong reflection lineups best match for optimizing to the control parameter
Wave；
Data computation module, for subtracting best match wavelet from original earthquake data, after obtaining strong reflection separation
Data, obtain model test conclusion；
Experiment conclusion is used for real data analysis, carries out strong reflection separation by strong reflection separation module；
Analysis module, for carrying out the analysis of real data well bypass road；
Determining module obtains whole district's strong reflection separating resulting for determining final matching Wavelet parameter.
Optionally, in the parameter initialization module, the three winks Parameter analysis includes: will be at instantaneous amplitude largest enveloping
Time as wavelet center delay time un, by frequency f centered on the instantaneous frequency at instantaneous amplitude largest envelopingnAnd it will
Instantaneous phase at instantaneous amplitude largest enveloping is as sub-wave phase φn, obtain initial control parameter { un,fn,φn}；And
Determine that scale factor k, the scale factor k are calculated by the following formula to obtain:
Wherein, hereIt is small echo redundant dictionary, is over-complete dictionary of atoms；<f, g>represent the interior of f and g
Product,It is by waveletIt is normalized.
Optionally, in the parameter optimization module, according to formulaIn search dictionary
Middle optimization wavelet center delay time un, centre frequency fn, phasen, then disturbed near initial value, obtain search model
Enclose [un-Δu,un+ Δ u], [fn-Δf,fn+ Δ f], [φn-Δφ,φn+ Δ φ], [kn-Δk,kn+ Δ k], Δ u is the time
Interval, Δ f is frequency interval, and Δ φ is phase intervals, and Δ k is scale parameter interval.
Optionally, the parameter optimization module, according to model test result and real data feature, optimization obtains and institute
State the wavelet of strong reflection best match.
Optionally, device according to claim 6, the control parameter further include wavelet amplitude an, and pass through
Following formula obtains wavelet amplitude:
As shown from the above technical solution, the strong reflection separation method and device provided by the invention based on model, to matching
The control parameter of wavelet, which optimizes, to be sought, and preferably to separate to strongly reflecting layer, the weak reflection of the prominent reservoir that underlies is special
Sign.The application of real data shows that seismic signature and well data after strong reflection separation have the higher goodness of fit.
Detailed description of the invention
Fig. 1 is the flow chart of the strong reflection separation method based on model provided according to embodiments of the present invention；
Fig. 2 is the two dimensional model schematic diagram of embodiment according to the present invention；
Fig. 3 is the forward modeling sectional view of embodiment according to the present invention；
Fig. 4 is the strong reflection separation sectional view of embodiment according to the present invention；
Fig. 5 is the separation front and back RMS amplitude curve comparison figure of embodiment according to the present invention；
Fig. 6 is the separation front and back energy growth rate curve comparison figure of embodiment according to the present invention；
Fig. 7 is that the wavelet of embodiment according to the present invention subtracts comparative bid parameter；
Fig. 8 is the frequency disturbance comparison diagram of embodiment according to the present invention；
Fig. 9 is that well profile comparison diagram is crossed in the separation front and back of embodiment according to the present invention.
Specific embodiment
With reference to the accompanying drawing, the specific embodiment of invention is further described.Following embodiment is only used for more clear
Illustrate to Chu technical solution of the present invention, and not intended to limit the protection scope of the present invention.
Matching pursuit algorithm (Matching Pursuit) is by propositions such as Mallat, which is a kind of effective letter
Signal decomposition can be the linear combination of multiple atoms by number sparse decomposition method, right by selecting the combination of different parameters atom
Original signal is reconstructed, special to achieve the purpose that.Algorithm fundamental formular expression formula are as follows:
Wherein f be Hilbert space in arbitrary signal,For the residual error and the 1st after the 1st iteration
The inner product of selected basic function, R when secondary iteration1F is residual error caused by first time iteration, while R1F is also that f existsIt is upper close
Residual error like after, and R1F andIt is orthogonal, satisfaction:
After m iteration, obtain:
RmF is last residual error item.
In order to makeIndicate most preferably approaching for signal f, it is necessary to so that residual error item is small as far as possible, then inner product
?It should be big as far as possible.Just need to find one and the immediate atom of f, this process clearly elaborates
Meaning with tracking.M iteration is remaining at the residue after the combination and the m times iteration of m atom signal decomposition.It is changing every time
During generation, be all find out first with the maximally related atom of original signal, then carry out next step decomposition.Repeat, until surplus
Remaining residual values meet given threshold or the number of iterations reaches the maximum of setting.WaveletIt can be by γn={ un,fn,φn,kn}
It portrays, un、fn、φnAnd knReferred to as wavelet control parameter respectively indicates required waveletCenter delay time, center frequency
Rate, phase and scale factor.
The present invention seeks the control parameter of matching wavelet using three-step approach.First using Morlet small echo as ground atom,
Matching wavelet, four controls of Morlet small echo are characterized by wavelet center delay time, centre frequency, phase and scale factor
Parameter group processed becomes parameter array γ, and γ={ u, f, φ, k } respectively represents wavelet center delay time, centre frequency, phase
And scale factor.
Morlet Wavelet temporal domain expression formula is
fmIt is wavelet centre frequency, u is center delay time, and k is scale factor, and φ is phase.Here is wavelet control
The specific acquiring method of parameter.
The first step, using complex seismic trace analytical technology calculate three wink attribute, at instantaneous amplitude largest enveloping when
Between centered on delay time un, using at the time point instantaneous frequency and instantaneous phase equally as initial value fnAnd φn, obtain
To three parameter { u of preresearch estimatesn,fn,φn}.For Morlet wavelet, it is also understood that scale factor k, just can determine that in this way
One unique Morlet wavelet, scale factor are calculated by formula (5),
HereIt is small echo redundant dictionary, is over-complete dictionary of atoms.The inner product of<f, g>represent f and g,It is by waveletIt is normalized.Utilize three originally determined parameter un, fnAnd φn, with public affairs
Formula (5) carries out traversal search to parameter k, finds out optimal value.
Second step seeks the most optimized parameter with the matched wavelet of determinationIt is optimized in search dictionary with formula (5)
This four parameters, then disturb near initial value, obtain search range [un-Δu,un+ Δ u], [fn-Δf,fn+ Δ f],
[φn-Δφ,φn+ Δ φ], [kn-Δk,kn+ Δ k], Δ u is time interval, and Δ f is frequency interval, and Δ φ is phasetophase
Every Δ k is scale parameter interval.
Third step estimates amplitude parameter an, wavelet amplitude is obtained using formula (6)；
For the separation of strong reflection lineups, which only needs iteration primary, and in second step, should be according to mould
Type test result and real data feature, optimization obtain the wavelet with the strong reflection best match, then will matching wavelet from
It is subtracted in original seismic data, the record after obtaining removal strong reflection, and then next step analysis can be carried out.
For the selection of match parameter, the present invention provides certain borrow by model test, to the correct selection of parameter
Mirror effect, effectively improves the effect of this method in practical applications.Specific step is as follows for model test:
1) strong reflection model is established.
2) to strong reflection lineups three wink of progress Parameter analysis, initial match parameter is obtained.
3) optimize Wavelet parameter, obtain the wavelet with strong reflection lineups best match.
4) matching wavelet is subtracted from original seismic data, the record after obtaining strong reflection separation obtains model test
Conclusion.
5) experiment conclusion is used for real data analysis, carries out strong reflection separation；
6) analysis of well bypass road is carried out, according to analytical effect, (7) or entrance the 5th can be entered step) step progress parameter tune
It is whole.
7) it determines final matching Wavelet parameter, obtains reasonable strong reflection separating resulting, carry out reservoir prediction analysis etc..
Strong reflection separation method flow chart based on model is as shown in Figure 1.
The present invention is for the first time discussed the selection of wavelet control parameter, and mainly frequency and wavelet subtract begging for for ratio
By.Analysis of experiments shows separating effect best in order to obtain, should all subtract matching wavelet, and original frequency should be strong anti-
It penetrates near lineups dominant frequency, and range of disturbance is smaller.
According to one embodiment of present invention, a kind of strong reflection separation method based on model is provided, which is characterized in that
It the described method comprises the following steps:
Strong reflection model is established according to real well data；Having made following strong reflection model in the present embodiment, (model shows
It is intended to as shown in Fig. 2, the forward modeling sectional view of the model is as shown in figure 3, white line is the strong reflection axis picked up), upper layer represents low speed
Stratum, speed 1000m/s, density 1.65g/cm3；Underlie for mudstone stratum, setting speed 2500m/s, density is
2.2g/cm3；Centre is sandstone, setting speed 3500m/s, density 2.275g/cm3；Sandstone formation is located next to resistance above
Anti- interface.Three mouthfuls of well points well Well1, Well2 and Well3 position cumulative sand thickness is respectively 18m, 5.4m and 13.7m.Such as figure
4 show strong reflection separation sectional view, extract lineups up 10ms, down 40ms when window in RMS amplitude attribute, lead to
It crosses analysis to find, which shows more consistent feature on RMS amplitude curve.In order to further analyze curve
Changing rule, the change rate of RMS amplitude before and after the processing is statisticallyd analyze, will be without sand body seismic channel RMS amplitude
As background value RmsAmp, the RMS amplitude value of other seismic channels is denoted as variable R msAmp (x), x=1,2, and 3 ..., if energy
Growth rate is Ratio (x).
Ratio (x)=(RmsAmp (x)-RmsAmp)/RmsAmp (7)
The reflection of this parameter is situation of change of the root mean square energy relative to background value, can intuitively show that strong reflection separates
The attributive character of the seismic data of front and back, as shown in Figure 5.Apparent variation has occurred in growth rate before and after the processing, increases after processing
Long rate becomes larger, this explanation is for background strong reflection, and response of the Sandstone Section on amplitude attribute is more obvious, this is to reality
The application of data plays positive directive function.
It is discussed in addition, emphasis of the present invention subtracts ratio to frequency disturbance and wavelet.The present invention is fixed in frequency
Under the conditions of, 0.6,0.8 times, 1 times (all subtracting) that matching wavelet is individually subtracted compares, comparing result such as Fig. 6.Thus may be used
Know, in the case where wavelet all subtracts, energy growth rate is maximum.
Under conditions of matching wavelet all subtracts, after setpoint frequency range of disturbance, algorithm is sought in disturbance section automatically
Look for Optimum Matching wavelet, such as Fig. 7.It follows that the spectral change feature of real data is directed to, in order to accurately reflect preliminary wavelet
Feature and lineups energy variations rule enhance the opposite variation of this energy to greatest extent, in relatively stable strong reflection area,
It is recommended that given compared with microvariations range, 1-2Hz or so.
For real data feature, interval of interest seismic data is analyzed, determines data dominant frequency in 25Hz or so.
It is combined with the theoretical analysis of, passed through well profile parameter testing, final to determine that wavelet control parameter frequency is 24Hz-25Hz, zero phase,
Scale parameter selects k=0.17, and initial wavelet center delay time is T6c layer position time (strong reflection wave crest) explained, perturbing area
Between 2ms.Whole district's separation is carried out to the shale strong reflection of the work area beach Zhang Jia, the data volume after obtaining strong reflection separation, so as to subsequent point
Analysis.
The present invention has chosen the comparison and analysis that two mouthfuls of typical cases well W1 and W2 cross well profile, such as Fig. 8.Strongly reflecting layer
Before separation, two mouthfuls of wells have apparent strong reflection at T6c, and feature differentiation is more difficult.It is separated by strong reflection, Ke Yiqing
Clear sees, apparent amplitude-frequency response (shown in ellipse) occurs under strongly reflecting layer in W1 well, and W2 well amplitude-frequency response is faint.By two
The log data of mouth well is it is found that the long 8 sections of sand body overall thickness of W1 well reach 31.6m, and the long 8 sections of sand body overall thickness of W2 well are only
6.6m, section has consistency well with treated.
The core of matching pursuit algorithm is to match accurately seeking for wavelet, so seeking control parameter asking as most critical
Topic.Tradition application lacks the processes such as model verifying and detail parameters analysis, lacks reliability, application effect is unobvious.The present invention
Based on model test, the control parameter of matching wavelet is sought having carried out more detailed discussion, more accurately seeks matching
Wavelet, and optimal separation, the weak reflectance signature of the prominent reservoir that underlies are carried out to strong reflection lineups.Real data applies table
Bright, seismic signature and well data after strong reflection separation have the higher goodness of fit, and application effect is obvious.
In specification of the invention, numerous specific details are set forth.It is to be appreciated, however, that the embodiment of the present invention can be with
It practices without these specific details.In some instances, well known method, structure and skill is not been shown in detail
Art, so as not to obscure the understanding of this specification.
Similarly, it should be understood that disclose to simplify the present invention and help to understand one or more in each inventive aspect
A, in the above description of the exemplary embodiment of the present invention, each feature of the invention is grouped together into individually sometimes
In embodiment, figure or descriptions thereof.However, should not explain the method for the disclosure is in reflect an intention that be wanted
Ask protection the present invention claims features more more than feature expressly recited in each claim.More precisely, such as
As following claims reflect, inventive aspect is all features less than single embodiment disclosed above.
Therefore, it then follows thus claims of specific embodiment are expressly incorporated in the specific embodiment, wherein each right is wanted
Ask itself all as a separate embodiment of the present invention.
It will be understood by those skilled in the art that can be adaptively changed to the module in the equipment in embodiment
And they are provided in the different one or more equipment of the embodiment.Can in embodiment module or unit or
Component is combined into a module or unit or component, and furthermore they can be divided into multiple submodule or subelement or subgroups
Part.In addition to such feature and/or at least some of process or unit are mutually exclusive places, any combination can be used
To all features disclosed in this specification (including adjoint claim, abstract and attached drawing) and so disclosed any side
All process or units of method or equipment are combined.Unless expressly stated otherwise, this specification (is wanted including adjoint right
Ask, make a summary and attached drawing) disclosed in each feature can be replaced with an alternative feature that provides the same, equivalent, or similar purpose.
In addition, it will be appreciated by those of skill in the art that although some embodiments described herein include other embodiments
In included certain features rather than other feature, but the combination of the feature of different embodiments mean it is of the invention
Within the scope of and form different embodiments.For example, in the following claims, embodiment claimed is appointed
Meaning one of can in any combination mode come using.
Various component embodiments of the invention can be implemented in hardware, or to run on one or more processors
Software module realize, or be implemented in a combination thereof.It will be understood by those of skill in the art that can be used in practice
In the equipment of microprocessor or digital signal processor (DSP) to realize a kind of browser terminal according to an embodiment of the present invention
Some or all components some or all functions.The present invention is also implemented as executing side as described herein
Some or all device or device programs (for example, computer program and computer program product) of method.It is such
It realizes that program of the invention can store on a computer-readable medium, or can have the shape of one or more signal
Formula.Such signal can be downloaded from an internet website to obtain, and perhaps be provided on the carrier signal or with any other shape
Formula provides.
It should be noted that the above-mentioned embodiments illustrate rather than limit the invention, and ability
Field technique personnel can be designed alternative embodiment without departing from the scope of the appended claims.In the claims,
Any reference symbol between parentheses should not be configured to limitations on claims.Word "comprising" does not exclude the presence of not
Element or step listed in the claims.Word "a" or "an" located in front of the element does not exclude the presence of multiple such
Element.The present invention can be by means of including the hardware of several different elements and being come by means of properly programmed computer real
It is existing.In the unit claims listing several devices, several in these devices can be through the same hardware branch
To embody.The use of word first, second, and third does not indicate any sequence.These words can be explained and be run after fame
Claim.
Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention., rather than its limitations；To the greatest extent
Pipe present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that: its according to
So be possible to modify the technical solutions described in the foregoing embodiments, or to some or all of the technical features into
Row equivalent replacement；And these are modified or replaceed, various embodiments of the present invention technology that it does not separate the essence of the corresponding technical solution
The range of scheme should all cover within the scope of the claims and the description of the invention.
Claims (10)
1. a kind of strong reflection separation method based on model, which is characterized in that the described method comprises the following steps:
(1) strong reflection model is established according to real well data；
(2) for strong reflection lineups three wink of progress Parameter analysis, initial control parameter is obtained；Wherein, the control parameter is
γ={ u, f, φ, k }, u, f, φ and k respectively represent wavelet center delay time, centre frequency, phase and scale factor；
(3) control parameter is optimized, is obtained and strong reflection lineups best match wavelet；
(4) best match wavelet is subtracted from original earthquake data, the data after obtaining strong reflection separation obtain model test
Conclusion is based on strong reflection mask data, carries out Parameter analysis to best match wavelet using energy growth rate, fixed in frequency
Under the conditions of, 0.6 times, 0.8 times of matching wavelet is individually subtracted and all subtracts, and compares, in the feelings that wavelet all subtracts
Under condition, energy growth rate is maximum；Under conditions of matching wavelet all subtracts, after setpoint frequency range of disturbance, algorithm exists automatically
It disturbs and finds Optimum Matching wavelet in section, given for the spectral change feature of real data in relatively stable strong reflection area
Determine the range of disturbance of 1-2Hz, to accurately reflect preliminary wavelet feature and lineups energy variation rule, enhances energy to greatest extent
Opposite variation；
Wherein, energy growth rate are as follows:
Ratio (x)=(RmsAmp (x)-RmsAmp)/RmsAmp
Ratio is energy growth rate, and RmsAmp is no sand body seismic channel RMS amplitude, and RmsAmp (x) is that remaining seismic channel is equal
Root mean square amplitude value, x=1,2,3 ...；
(5) experiment conclusion is used for real data analysis, carries out strong reflection separation；
(6) analysis of well bypass road is carried out, enters step (7) if meeting the requirements, (5) is otherwise entered step and carries out parameter adjustment；
(7) it determines final matching Wavelet parameter, obtains whole district's strong reflection separating resulting.
2. the method according to claim 1, wherein described carry out three wink parameters point for strong reflection lineups
Analysis, obtaining initial matching parameter includes:
The three winks Parameter analysis includes: using the time at instantaneous amplitude largest enveloping as wavelet center delay time un, by wink
When amplitude largest enveloping at instantaneous frequency centered on frequency fnWith using the instantaneous phase at instantaneous amplitude largest enveloping as
Sub-wave phase φn, obtain initial control parameter { un,fn,φn}；And
Determine that scale factor k, the scale factor k are calculated by the following formula to obtain:
Wherein, hereIt is small echo redundant dictionary, is over-complete dictionary of atoms；The inner product of<f, g>represent f and g,It is by waveletIt is normalized.
3. the method according to claim 1, wherein described optimize control parameter, obtain and strong reflection
Lineups best match wavelet includes:
According to formulaWavelet center delay time u is optimized in search dictionaryn、
Centre frequency fn, phasen, then disturbed near initial value, obtain search range [un-Δu,un+ Δ u], [fn-Δf,fn+
Δ f], [φn-Δφ,φn+ Δ φ], [kn-Δk,kn+ Δ k], Δ u is time interval, and Δ f is frequency interval, and Δ φ is phase
Bit interval, Δ k are scale parameter intervals.
4. method according to claim 1 or 3, which is characterized in that it is described that control parameter is optimized, it obtains and strong anti-
Penetrating lineups best match wavelet includes:
According to model test result and real data feature, optimization obtains the wavelet with the strong reflection best match.
5. according to the method described in claim 2, it is characterized in that, the control parameter further includes wavelet amplitude an, and pass through
Following formula obtains wavelet amplitude:
6. a kind of strong reflection separator based on model, which is characterized in that described device include the following:
Model building module, for establishing strong reflection model according to real well data；
Parameter initialization module, for obtaining initial control parameter for strong reflection lineups three wink of progress Parameter analysis；Its
In, the control parameter is γ={ u, f, φ, k }, and u, f, φ and k respectively represent wavelet center delay time, centre frequency, phase
Position and scale factor；
Parameter optimization module obtains and strong reflection lineups best match wavelet for optimizing to the control parameter；
Data computation module, for best match wavelet to be subtracted from original earthquake data, the number after obtaining strong reflection separation
According to obtaining model test conclusion, be based on strong reflection mask data, carry out parameter point to best match wavelet using energy growth rate
Analysis is individually subtracted 0.6 times, 0.8 times of matching wavelet and all subtracts, and compare, in son under conditions of frequency is fixed
In the case that wave all subtracts, energy growth rate is maximum；Under conditions of matching wavelet all subtracts, setpoint frequency range of disturbance
Afterwards, algorithm finds Optimum Matching wavelet in disturbance section automatically, for the spectral change feature of real data, relatively stable
Strong reflection area, give the range of disturbance of 1-2Hz, to accurately reflect preliminary wavelet feature and lineups energy variations rule, most
Limits enhance the opposite variation of energy；
Wherein, energy growth rate are as follows:
Ratio (x)=(RmsAmp (x)-RmsAmp)/RmsAmp
Ratio is energy growth rate, and RmsAmp is no sand body seismic channel RMS amplitude, and RmsAmp (x) is that remaining seismic channel is equal
Root mean square amplitude value, x=1,2,3 ...；
Experiment conclusion is used for real data analysis, carries out strong reflection separation by strong reflection separation module；
Analysis module, for carrying out the analysis of real data well bypass road；
Determining module obtains whole district's strong reflection separating resulting for determining final matching Wavelet parameter.
7. device according to claim 6, which is characterized in that in the parameter initialization module, the three winks parameter point
Analysis includes: using the time at instantaneous amplitude largest enveloping as wavelet center delay time un, at instantaneous amplitude largest enveloping
Instantaneous frequency centered on frequency fnWith using the instantaneous phase at instantaneous amplitude largest enveloping as sub-wave phase φn, obtain just
Beginning control parameter { un,fn,φn}；And
Determine that scale factor k, the scale factor k are calculated by the following formula to obtain:
Wherein, hereIt is small echo redundant dictionary, is over-complete dictionary of atoms；The inner product of<f, g>represent f and g,It is by waveletIt is normalized.
8. device according to claim 6, which is characterized in that in the parameter optimization module, according to formulaWavelet center delay time u is optimized in search dictionaryn, centre frequency fn, phase
φn, then disturbed near initial value, obtain search range [un-Δu,un+ Δ u], [fn-Δf,fn+ Δ f], [φn-Δφ,
φn+ Δ φ], [kn-Δk,kn+ Δ k], Δ u is time interval, and Δ f is frequency interval, and Δ φ is phase intervals, and Δ k is scale
Parameter space.
9. the device according to claim 6 or 8, which is characterized in that the parameter optimization module, according to model test result
With real data feature, optimization obtains the wavelet with the strong reflection best match.
10. device according to claim 6, the control parameter further includes wavelet amplitude an, and obtained by following formula
Obtain wavelet amplitude:
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| CN112305584B (en) * | 2019-07-24 | 2022-10-14 | 中国石油化工股份有限公司 | Phase shift wavelet-based strong reflection separation method for thin coal seam |
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