CN109270574A - A kind of joint the Method of Deconvolution based on a variety of vibroseis acquisition data - Google Patents
A kind of joint the Method of Deconvolution based on a variety of vibroseis acquisition data Download PDFInfo
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Abstract
The invention discloses a kind of joint the Method of Deconvolution based on a variety of vibroseis acquisition data.Earthquake data acquisition is carried out in areal using different focus, the seismic signal that different focus are excited has different effective frequency belt widths, and the different obtained earthquake records of epicenter excitation require to correspond to identical subsurface reflective path;Joint deconvolution will be carried out after all data in-phase stackings;Since the source wavelet that different focus are excited is mutually advantageous in respective effective band range, carrying out joint deconvolution after combining different wavelets using method of the invention can be realized mutual supplement with each other's advantages, the weak area of frequency band that the obtained seismic data of single epicenter excitation can be filled up, realizes the Broad band data processing of deconvolution.
Description
Technical field
The invention belongs to marine seismic prospectiong fields, and in particular to a kind of anti-pleat of joint based on a variety of vibroseis acquisition data
Product method.
Background technique
The power generator that focus is acquired as seismic signal directly determines the quality of acquired seismic data, to rear
Continuous data process and interpretation has important influence.It can be used for exciting the focus of seismic signal many kinds of at present, difference shake
The wavelet frequency band that source is excited often has differences.As air gun source effective frequency belt width common in marine seismic prospectiong is usual
In 2-250Hz, and spark source can then excite the wavelet of 20-400Hz bandwidth, then have the focus of energy converter mode that can swash
The wide source wavelet in the section 300-3500Hz of hair band.
The height of source signal frequency has directly with wavelet penetration capacity and for identification of formation ability (resolution ratio)
Relationship, low frequency energy is compared to high-frequency energy to be influenced small by Earth's absorption and attenuation, therefore can penetrate deeper stratum, still
Resolution ratio is poorer than radio-frequency component.In order to overcome the problems, such as this, it has been proposed that being compensated using the thinking of source wavelet deconvolution
Low frequency or radio-frequency component, it is desirable to which acquisition is similar to Pulse Source stimulation effect, realizes double guarantees of penetration depth and resolution ratio.
But due to the presence of noise, being directed to will when the weaker region of signal band energy of a certain epicenter excitation carries out deconvolution
The amplification (in practical application, deconvolution is carried out just in special frequency channel) for causing noise, to reduce signal-to-noise ratio, affects
The quality of seismic data.For this purpose, it is proposed that the method that the earthquake record that different epicenter excitations obtain carries out joint deconvolution,
Noise method problem caused by frequency missing in single epicenter excitation earthquake record is effectively avoided, frequency bandwidth is being widened, is improving
While resolution ratio, signal-to-noise ratio ensure that.
The earthquake record x that focus i is excitedi(t) it can be expressed from the next:
xi(t)=si(t)*r(t)+ni(t) (1)
Wherein si(t) time series for being source wavelet i, r (t) are stratum impulse response, niWhen (t) being excited for focus i
Environmental noise.
If ignoring environmental noise, while Fourier transform is done to formula (1), can be obtained:
Xi(w)=Si(w)·R(w) (2)
Wherein, Xi(w)、Si(w), R (w) corresponds respectively to xi(t)、si(t) and the Fourier transform results of r (t).
In order to eliminate the influence of source wavelet, the true reflection coefficient sequence on stratum is obtained, earthquake record need to usually be done
Deconvolution processing:
Due to SiIt (w) is band-limited signal, calculated R (w) will be very big outside frequency band, or even tends to be infinite, therefore
In practical solution procedure, often in Si(w) white noise coefficient is added, or w is limited in SiEffective band range wiIt is interior.But
After such consequence is exactly deconvolution, frequency band is compensated but very limited (resolution ratio improves limited).
Summary of the invention
It is an object of the invention to overcome the deficiencies of the prior art and provide a kind of connection based on a variety of vibroseis acquisition data
Close the Method of Deconvolution.
Technical scheme is as follows:
Joint the Method of Deconvolution based on a variety of vibroseis acquisition data of the invention, includes the following steps:
Earthquake data acquisition is carried out in areal using different focus, the seismic signal that different focus are excited has not
Same effective band range, and the different obtained earthquake records of epicenter excitation require to correspond to identical subsurface reflective path;
Assuming that there is n kind focus, wherein n >=2, signal receiver then will record n sets of data, and all data are carried out in-phase stacking (such as
After dephasing processing, as need can the compacting of advanced Row noise) obtain superimposed seismic data x (t):
Wherein, si(t) time series for being source wavelet i, riIt (t) is stratum impulse response, ni(t) for corresponding to focus
The environmental noise of wavelet i;It is compared to single vibroseis acquisition, later earthquake record is superimposed and contains the frequency band of different wavelets, because
This frequency spectrum is more abundant, complete;
In view of focal point is identical in collection process for different focus, therefore corresponding stratum impulse response is also identical
, ignore environmental noise (noise removal), formula (1) can be rewritten are as follows:
X (t)=s (t) * r (t) (2)
Found out by formula (3), more source datas, which are superimposed later result and can be regarded as source wavelet s (t), excites it
The earthquake record arrived afterwards;
Formula (2) is transformed into frequency domain, is obtained:
X (w)=S (w) R (w) (4)
X (w), S (w), R (w) correspond respectively to the Fourier transform results of x (t), s (t) and r (t);
It is directed to and is superimposed later earthquake record X (w) progress deconvolution, obtain:
Wherein, w1、w2And wnThe effective band range of 1,2 and n of focus is respectively indicated, w indicates having for joint deconvolution processing
Frequency band is imitated, is the union of all source wavelet dominant frequency bands, U indicates union;Effective band corresponding to some source wavelet
Range, effective band range w corresponding to the result after more source patterns are obviously broader;1/S (w) is deconvolution filter
It can be returned time-domain by inverse fourier transform and earthquake record carries out direct convolution and obtains deconvolution by frequency domain expression formula
As a result.
As a kind of currently preferred embodiment, a variety of focus for carrying out data acquisition in areal exist
Identical or approximately uniform position excitation, the signal receiver for recording data are fixed position in different vibroseis acquisitions.
As the optional another embodiment of the present invention, the different focus that data acquisition is carried out in areal
Signal receiver corresponding with its position can change, but by making different shakes after time shift, correction or dephasing processing
Source-signal receiver reflected path is identical.
As a kind of currently preferred embodiment, source wavelet si(t) it can use well-log information synthesis or logical
It crosses earthquake record inverting to obtain, for air gun and spark source, wavelet can then pass through simulation or the actual measurement based near field
Signal solves to obtain.
It further include carrying out noise pressure before all data are carried out in-phase stacking as a kind of currently preferred embodiment
The step of system or removal noise.
In addition, same type focus causes dominant frequency band difference that should also be considered for different focus due to mode of excitation difference
Or (i.e. hair mode, air gun shake a variety of focus in present subject matter under the conditions of such as dynamite source is filled the water in desert and do not filled the water
Place depth difference etc. in source);
Compared with prior art, the present invention is excited using a variety of focus and joint deconvolution solution is in the prior art
Problem.Since the frequency band that different focus are recorded is mutually advantageous, advantage is realized mutually after being combined using method of the invention
It mends, so as to fill up the weak area of frequency band of the obtained seismic data of single epicenter excitation, realizes the Broad band data processing of deconvolution.
Detailed description of the invention
Fig. 1 difference dominant frequency Ricker wavelet and combined result comparison, left figure are son after different dominant frequency Ricker wavelets and combination
Wave morphology, right figure are the curve of amplitude spectrum of corresponding wavelet;
Fig. 2 difference dominant frequency Ricker wavelet and combined result normalization comparison, left figure are different dominant frequency Ricker wavelets and combination
Later wavelet normalizes form, and right figure is the normalized amplitude spectral curve of corresponding wavelet;
Fig. 3 40Hz dominant frequency wavelet is with wavelet (40Hz and 160Hz dominant frequency wavelet) deconvolution Comparative result, left figure is combined
Time-domain wavelet form, right figure are curve of amplitude spectrum;
Fig. 4 acquires schematic diagram based on the seismic data joint deconvolution of more vibroseis acquisitions.
Specific embodiment
The present invention is described further with reference to the accompanying drawings and detailed description.
Joint the Method of Deconvolution based on a variety of vibroseis acquisition data of the invention, includes the following steps:
Earthquake data acquisition is carried out in areal using different focus, the seismic signal that different focus are excited has not
Same effective frequency belt width, and the different obtained earthquake records of epicenter excitation require to correspond to identical subsurface reflective path;
Assuming that there is n kind focus, wherein n >=2, signal receiver then will record n sets of data, and all data are carried out in-phase stacking (such as
After dephasing processing, as need can the compacting of advanced Row noise) obtain superimposed seismic data x (t):
Wherein, si(t) time series for being source wavelet i, riIt (t) is stratum impulse response, ni(t) for corresponding to focus
The environmental noise of wavelet i;It is compared to single vibroseis acquisition, later earthquake record is superimposed and contains the frequency band of different wavelets, because
This frequency spectrum is more abundant, complete;
In view of focal point is identical in collection process for different focus, therefore corresponding stratum impulse response is also identical
, ignore environmental noise (noise removal), formula (1) can be rewritten are as follows:
X (t)=s (t) * r (t) (2)
Found out by formula (3), more source datas, which are superimposed later result and can be regarded as source wavelet s (t), excites it
The earthquake record arrived afterwards;
Formula (2) is transformed into frequency domain, is obtained:
X (w)=S (w) R (w) (4)
X (w), S (w), R (w) correspond respectively to the Fourier transform results of x (t), s (t) and r (t);
It is directed to and is superimposed later earthquake record X (w) progress deconvolution, obtain:
Wherein, w1、w2And wnThe effective band range of 1,2 and n of focus is respectively indicated, w indicates having for joint deconvolution processing
Frequency band is imitated, is the union of all source wavelet frequency bands;Corresponding to the effective band range of some source wavelet, more source patterns
Effective band range w corresponding to result afterwards is obviously broader;1/S (w) is deconvolution filter frequency domain expression formula, can
Deconvolution result is obtained with the direct convolution of earthquake record progress so that it is returned time-domain by inverse fourier transform.
The present embodiment verifies effect of the invention using the Ricker wavelet of different dominant frequency.Fig. 1 gives dominant frequency
It spreads, while is illustrated two kinds of wavelets for 40Hz (solid line), the wavelet form of two kinds of Ricker wavelets of 160Hz (long dotted line) and amplitude
Directly it is superimposed later result (short dash line).By comparison it can be found that individually a certain kind wavelet frequency band is relatively narrow, combination
Later advantage realizes complementation, and frequency bandwidth obtains widening greatly very much.For more intuitive comparison, Fig. 2 by wavelet and amplitude spectrum into
It has gone normalization, it can be seen that the later result secondary lobe of combination becomes smaller from wavelet form, has been more nearly ideal pulse wavelet,
The increase of frequency domain different frequency bands useful signal, then ensure that the stability of deconvolution process.
Fig. 3 compared the result after 40Hz dominant frequency Ricker wavelet and combined result deconvolution.Single dominant frequency wavelet is due to having
It is relatively narrow to imitate frequency band, therefore narrow-band compensation (in figure shown in dotted line) can only be carried out during deconvolution, after corresponding deconvolution
Wavelet secondary lobe is larger, and the frequency band advantage of two kinds of data, anti-pleat is then preferably utilized in the deconvolution result based on combined result
Widening for low frequency and high frequency may be implemented in the thick frequency band of product.Wavelet is also more nearly pulse wavelet.Desired output is designed as in Fig. 3
Complete band logical wavelet, secondary lobe shake the Gibbs' effect introduced from inverse fourier transform.
Fig. 4 gives a set of land multi-source acquisition scheme, and after focus s1 excitation, signal to be reflected is detected device and connects
It receives, explosive source s2 is received again, and since focus is identical with detector position, signal corresponds to identical reflection
Layer position, can be overlapped and joint deconvolution.
Claims (5)
1. a kind of joint the Method of Deconvolution based on a variety of vibroseis acquisition data, it is characterised in that include the following steps:
Earthquake data acquisition is carried out in areal using different focus, the seismic signal that different focus are excited has different
Effective frequency belt width, and the different obtained earthquake records of epicenter excitation require to correspond to identical subsurface reflective path;Assuming that
There is n kind focus, wherein n >=2, signal receiver then will record n sets of data, and all data progress in-phase stacking is superimposed
Seismic data x (t) afterwards:
Wherein, si(t) time series for being source wavelet i, riIt (t) is stratum impulse response, ni(t) for corresponding to source wavelet i
Environmental noise;It is compared to single vibroseis acquisition, later earthquake record is superimposed and contains the frequency band of different wavelets;
In view of focal point is identical in collection process for different focus, thus corresponding stratum impulse response be also it is identical,
Ignore environmental noise (noise removal), formula (1) can be rewritten are as follows:
X (t)=s (t) * r (t) (2)
Found out by formula (3), more source datas be superimposed later result can be regarded as source wavelet s (t) excitation after
The earthquake record arrived:
Formula (2) is transformed into frequency domain, is obtained:
X (w)=S (w) R (w) (4)
X (w), S (w), R (w) correspond respectively to the Fourier transform results of x (t), s (t) and r (t);
It is directed to and is superimposed later earthquake record X (w) progress deconvolution, obtain:
Wherein, w1、w2And wnThe effective band range of 1,2 and n of focus is respectively indicated, w indicates effective frequency of joint deconvolution processing
Band is the union of all source wavelet effective frequency belt widths;Corresponding to the effective band range of some source wavelet, more focus
Effective band range w corresponding to result after combination is obviously broader;1/S (w) is the expression of deconvolution filter frequency domain
It can be returned time-domain by inverse fourier transform and earthquake record carries out direct convolution and obtains deconvolution result by formula.
2. the joint the Method of Deconvolution as described in claim 1 based on a variety of vibroseis acquisition data, it is characterised in that: it is described
It is excited in a variety of focus that areal carries out data acquisition in identical or approximately uniform position, the signal for recording data connects
Device is received to fix position in different vibroseis acquisitions.
3. the joint the Method of Deconvolution as described in claim 1 based on a variety of vibroseis acquisition data, it is characterised in that: it is described
When can change in a variety of focus signal receiver corresponding with its position that areal carries out data acquisition, but pass through
It moves, make the reflected path of different focus-signal receivers identical after correction or dephasing processing.
4. the joint the Method of Deconvolution as described in claim 1 based on a variety of vibroseis acquisition data, it is characterised in that: focus
Wave si(t) it can use well-log information synthesis or obtained by earthquake record inverting, for air gun and spark source, wavelet
Then it can solve to obtain by simulation or the measured signal based near field.
5. the joint the Method of Deconvolution as described in claim 1 based on a variety of vibroseis acquisition data, it is characterised in that: will own
Data further include the steps that carrying out Noise Elimination or remove noise before carrying out in-phase stacking.
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WO2020078073A1 (en) * | 2018-10-18 | 2020-04-23 | 国家海洋局第二海洋研究所 | Joint deconvolution method employing data acquired from multiple hypocenters |
CN114545500A (en) * | 2022-01-29 | 2022-05-27 | 煤炭科学研究总院有限公司 | Method and device for determining wave velocity distribution information |
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CN114859409B (en) * | 2022-04-11 | 2023-03-31 | 中山大学 | Method and device for acquiring information of rock ring discontinuity of oceanic rock |
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