CN107132577B - A kind of seismic attenuation method of estimation based on area under spectrum variation - Google Patents
A kind of seismic attenuation method of estimation based on area under spectrum variation Download PDFInfo
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Abstract
The invention discloses a kind of seismic attenuation methods of estimation based on area under spectrum variation, including step 1：Practical source wavelet and its parameter are estimated using Chang Xiangwei wavelets；Step 2：Calculate the Fourier spectrum area of source wavelet；Step 3：Calculate the Fourier spectrum area of decaying wavelet；Step 4：Calculate the Fourier spectrum area change amount of source wavelet and the wavelet that decays；Step 5：Versus Q value is calculated, seismic data decay behavior is carried out.The present invention is using Chang Xiangwei higher-order spectras source wavelet and obtains estimation parameter, and the variable quantity of Fourier spectrum area, is calculated versus Q value between the source wavelet obtained using estimation and decaying wavelet, carries out seismic attenuation estimation and decaying reservoir is portrayed.By to carrying out decay behavior without synthetic seismogram make an uproar and noisy, demonstrating the Stability and veracity of this method.This method is applied to real data, decay behavior result can portray gas-bearing reservoir well.
Description
Technical field
The invention belongs to the signal processing in geophysical exploration, data process and interpretation fields, are related to a kind of based on spectrum
The seismic attenuation method of estimation of area change.
Background technology
Underground medium is the viscoelastic medium, and the viscoelasticity of medium makes the waveform for the seismic wavelet propagated in underground medium
Broadening, dominant frequency reduce, and frequency band narrows, and energy gradually weakens and is eventually converted into thermal energy.The loss of seismic wave energy by it is a variety of because
Element causes, and the medium with different saturation, permeability, porosity is different to the extent of deterioration of seismic wave energy.Quality factor q
Value is to measure the important parameter of diectric attenuation characteristic, may be used to indicate stratum oil-gas possibility.It declines on the stratum estimated by seismic data
Subtract, can be used for lithology and containing fluid analysis, RESERVOIR RECOGNITION and hydrocarbon indication etc..
Tonn (1991) compares a variety of Q values methods of estimation in its survey article, including when the wavelet of time-domain rises
Between the matching method of method, pulse amplitude damped method, analytic signal method, wavelet/phase simulation etc. and frequency domain, frequency spectrum simulation
Method, spectrum are than method etc..Tonn points out that none of these methods can be suitably used for all situations, according to noise level and receives record
Type, different methods are suitable for different situations, such as when the focus of VSP data is controllable and data protects width, analytic signal
The result of method estimation is better than the estimated result of other methods, and when data does not protect width, spectrum analog method is more applicable；Not noisy
In the case of, spectrum can obtain believable as a result, but being no longer applicable in noisy this method than method.Spectrum is to propose earliest than method
One of method, this method principle is simple, easy to operate, can obtain in good signal to noise situations it is preferable as a result,
To being widely applied.Singleton etc. (2006) is composed using Gabor-Morlet to be estimated Q values than method and carries out Q compensation.
Parra etc. (2006) is based on spectrum and has estimated natural attenuation from component direct P wave than method, and the Q curves of estimation combine other logs,
It is related or related with hydrocarbon saturation with lithology that can distinguish abnormal.Rise time and pulse amplitude damped method are to adopting
Sample rate and signal-to-noise ratio dependence are larger, and the usual error of estimated result is larger, and matching technique method and logarithmic spectrum than method as, be applicable in
In the higher data of signal-to-noise ratio.
Other than the method that Tonn is listed, time-domain method also has pulse width broadening method etc., and frequency domain has centroid frequency
Deflection method (CFS), crest frequency Mobile Method (PFS), wavelet envelope peak instantaneous frequency method (WEPIF) etc. and time-frequency domain side
Method, such as wavelet field peak value method of scales, wavelet field energy attenuation method, Lipschitz index methods, time-frequency spectrum spectrum are than method.Pulse is wide
Spend broadening method by Kjartansson (1979) propose, this method using pulse width, Q values, walk when between empirical equation estimate
Q values, reduce noise jamming to a certain extent；Centroid frequency deflection method uses centroid frequency and peak respectively with crest frequency Mobile Method
Value frequency and when walking between parsing relationship estimation Q values.The definition of centroid frequency is the average frequency weighted with amplitude spectrum, barycenter
Frequency deviation method is suitable for the wider earthquake record of frequency band, and crest frequency is defined as the maximum value of frequency spectrum.Wavelet envelope peak
Instantaneous frequency method estimates Q values, the party using the relationship of corresponding instantaneous frequency and Q values at the peak value of the instantaneous amplitude envelope of wavelet
Method is suitable for poststack ground return data and zero bias VSP data, and easy to operate, noise immunity is strong, and longitudinal resolution is high.In addition, Zhu
Fixed to wait (2006) using the proportionate relationship estimation decaying between the dominant frequency offset moved to low frequency and Q values, this method is suitable for
VSP data, calculating speed are fast.Estimate in frequency domain Q values be by extract different frequency information for example dominant frequency, crest frequency,
Centre frequency, instantaneous frequency, the instantaneous frequency etc. at envelope peak, and find these specific component frequency information and Q values it
Between relationship seek Q values, different frequency informations has different stability, noise immunity and extraction convenience.Time-frequency domain
In method, the scale factor (i.e. energy decay factor) of the wavelet transformed domain such as Li Hongbing decays to portray, from peak value scale
Direct estimation decays in variable quantity, and Innanen (2003) is decayed using local signal regularization and the estimation of Lipschitz indexes,
Give the empirical equation of Q values estimation.
Preceding common Q values extracting method is all base such as centroid frequency deflection method (CFS) and crest frequency Mobile Method (PFS)
In single, specific frequency variation, to carry out Q value estimations.It is muting ideally, can obtain accurate, steady
Fixed decay behavior result；But actual seismic data inevitably contain noise, these conventional methods hardly result in one
Stable Q value estimated results.
Invention content
It is an object of the invention to overcome the above-mentioned prior art, a kind of earthquake changed based on area under spectrum is provided and is declined
Subtract method of estimation
In order to achieve the above objectives, the present invention is achieved by the following scheme：
A kind of seismic attenuation method of estimation based on area under spectrum variation, includes the following steps：
Step 1：Practical source wavelet and its parameter are estimated using Chang Xiangwei wavelets；
Step 2：Calculate the Fourier spectrum area of source wavelet；
Step 3：Calculate the Fourier spectrum area of decaying wavelet；
Step 4：Calculate the Fourier spectrum area change amount of source wavelet and the wavelet that decays；
Step 5：Versus Q value is calculated, seismic data decay behavior is carried out.
The present invention, which further improves, to be：
Estimate that the specific method is as follows for source wavelet in step 1：
The definition of Chang Xiangwei wavelets is：
In formula, σ0And δ0Indicate the dominant frequency and standard deviation of Chang Xiangwei wavelets；Phase0For constant, according to different earthquake numbers
According to the different value of selection；I is imaginary unit；Assuming that the amplitude spectrum of practical source wavelet isIt is obtained according to formula (2) estimation
The source wavelet of estimation：
In formula,For the source wavelet of estimation.
The specific method is as follows for the Fourier spectrum area of calculating source wavelet in step 2：
To formula (1) both sides about frequency integrator, the Fourier spectrum area for obtaining the source wavelet of estimation is as follows
Wherein, f is frequency, and e is exponential function.
The specific method is as follows for the area under spectrum of calculating attenuator wave in step 3：
If wavelet propagation time t second in the attenuation medium of quality factor q, the amplitude spectrum for receiving wavelet are
Wherein, t is the TWT that wavelet is propagated in attenuation medium；
Equally to frequency integrator, the area under spectrum for the wavelet that must decay is on formula (4) both sides
The specific method is as follows for the area under spectrum difference of calculating source wavelet and the wavelet that decays in step 4：
The Fourier spectrum area of the middle decaying wavelet of the source wavelet Fourier spectrum face permanent (5) estimated in formula (3) is made
Difference, obtaining area under spectrum variable quantity is
Versus Q value is calculated in step 5, and the specific method is as follows：
Changed using the area under spectrum for the source wavelet estimated in formula (6) and the area under spectrum of decaying wavelet, solution obtains opposite Q
Value, expression formula are as follows：
S-transformation is chosen to calculate the Fourier spectrum of time-varying seismic data；The definition of the S-transformation of real seismic signal s (t) is
In formula, t and f are the TWT and Fourier frequency that wavelet is propagated in attenuation medium；τ joins for time-shifting
Number, i.e., the center of Gaussian window in S-transformation；According to Paasche Wa Er theorems, in formula (8) definition of S-transformation be rewritten as：
In formula, S (α) is the Fourier transformation of seismic signal s (t)；According to formula (9), using Fast Fourier Transform (FFT), quickly
Ground calculates S-transformation；Using the S-transformation in formula (9), the Fourier spectrum area of seismic data is calculated, seismic data decaying is carried out and estimates
Meter.
Compared with prior art, the invention has the advantages that：
The present invention proposes a kind of seismic attenuation method of estimation based on Fourier spectrum area change.This method utilizes first
Chang Xiangwei higher-order spectras source wavelet simultaneously obtains estimation parameter, between the source wavelet obtained using estimation and decaying wavelet in Fu
Versus Q value is calculated in the variable quantity of leaf area under spectrum, carries out seismic attenuation estimation and decaying reservoir is portrayed.The invention is applied
In synthetic seismic data and actual seismic data, it was demonstrated that this method can accurately portray seismic data decaying, and to containing
Data of making an uproar can obtain a stable, accurate decay behavior result.The present invention fully considers the Fourier spectrum of seismic data
The variation of area can obtain a more stable estimated result to carry out the decay behavior of seismic data.The present invention passes through
To carrying out decay behavior without synthetic seismogram make an uproar and noisy, the Stability and veracity of this method is demonstrated.By the party
Method is applied to real data, and decay behavior result can portray gas-bearing reservoir well.
Description of the drawings
Fig. 1 is without synthetic seismic data of making an uproar；Totally 100 track data, time sampling interval are 1 millisecond, which contains
There are two level courses；Source wavelet is the zero phase Ricker wavelets that dominant frequency is 40Hz；Wherein, first layer Q values are 200, second layer Q
Value is respectively 100 (first to the 40th), 30 (41 to the 60th), 60 (61 to the 100th)；
Focus that the practical source wavelets of Fig. 2 (dominant frequency is the Ricker wavelets of 40Hz) and zero-phase wavelet are estimated
Wave；Wherein, the time domain waveform of (a) practical source wavelet and the source wavelet of estimation, (b) practical source wavelet and estimation focus
The Fourier spectrum of wave；
The versus Q value that the variation of seismic data amplitude spectrum and the present invention estimate in Fig. 3 Fig. 2；Wherein, (a) different layers, difference
The Fourier spectrum of the seismic data in road, dark solid line indicate the Fourier spectrum of the 20th track data of first layer, deep solid line, dotted line, short stroke
Line indicates the Fourier spectrum of the second layer the 20th, the 50th and the 80th track data respectively；(b) the opposite Q that present invention estimation obtains
Value；
The noisy synthetic seismic datas of Fig. 4；Synthetic seismic data in Fig. 1, after the white Gaussian noise that signal-to-noise ratio is 5dB is added
Obtain the noisy synthetic seismic data；Other parameters are identical with Fig. 1；
The versus Q value that the variation of noisy seismic data amplitude spectrum and the present invention estimate in Fig. 5 Fig. 4；Wherein, (a) different layers,
The Fourier spectrum of different road seismic datas, concealed wire indicate the 20th track data of first layer Fourier spectrum, deep solid line, dotted line, short stroke
Line indicates the Fourier spectrum of the second layer the 20th, the 50th and the 80th seismic data respectively；(b) phase that present invention estimation obtains
To Q values；
Fig. 6 actual seismic data sections；No. CMP of well 1 and well 2 is 290 and 700；Well 1 is high-yield well, and well 2 is dry-well；
The versus Q value that the source wavelet of Fig. 7 time-domains and frequency domain and the present invention estimate；Wherein, (a) practical source wavelet
The time domain waveform of the source wavelet of (extracting to obtain by shallow-layer data) and estimation, (b) practical source wavelet and estimation source wavelet
Fourier spectrum, (c) centroid frequency deflection method (solid line) and spectrum estimate obtained Q value, (d) this hair than method (dotted line)
The bright versus Q value for estimating to obtain.
Specific implementation mode
The present invention is described in further detail below in conjunction with the accompanying drawings：
Referring to figure, a kind of seismic attenuation method of estimation based on area under spectrum variation
(1) source wavelet is estimated
In actual seismic data processing and decay behavior, often source wavelet is unknown, therefore in the present invention, we
The parameter for the source wavelet estimated practical source wavelet first with Chang Xiangwei wavelets, and estimated, and then carry out earthquake
Data decay behavior.The definition of Chang Xiangwei wavelets is
In formula, σ0And δ0Indicate the dominant frequency and standard deviation of Chang Xiangwei wavelets.Phase0It, can be according to different ground for constant
Shake the different value of data decimation.Assuming that the amplitude spectrum of practical source wavelet isWe can estimate according to formula (2)
The source wavelet of meter
In formula,The source wavelet estimated for the present invention.
(2) area under spectrum for the source wavelet that estimation obtains calculates
To formula (1) both sides about frequency integrator, the Fourier spectrum area for the source wavelet that can must be estimated is as follows
(3) area under spectrum of decaying wavelet calculates
If wavelet propagation time t second in the attenuation medium of quality factor q, the amplitude spectrum for receiving wavelet are
Equally to frequency integrator, the area under spectrum for the wavelet that can must decay is on formula (4) both sides
(4) the area under spectrum difference of source wavelet and decaying wavelet calculates
The Fourier spectrum area of the middle decaying wavelet of the source wavelet Fourier spectrum face permanent (5) estimated in formula (3) is made
Difference, can obtain area under spectrum variable quantity is
In formula, t is the TWT that wavelet is propagated in attenuation medium.
(5) versus Q value calculates
Changed using the area under spectrum for the source wavelet estimated in formula (6) and the area under spectrum of decaying wavelet, can solve to obtain
Versus Q value, expression formula are as follows
Due to the error of estimation source wavelet and estimation parameter, which is a versus Q value, is not real product
Prime factor, but it is presently believed that the versus Q value still can preferably portray the attenuation characteristic of seismic data.In the present invention
Synthetic seismic data experiment and provable conclusion of actual seismic data experiment.
In addition, we choose S-transformation to calculate the Fourier spectrum of time-varying seismic data in the present invention.Real seismic signal s (t)
The definition of S-transformation be
In formula, t and f are time and Fourier frequency.τ is time-shifting parameter, i.e., the center of Gaussian window in S-transformation.Root
According to Paasche Wa Er theorems, in formula (8) definition of S-transformation can be rewritten as
In formula, S (α) is the Fourier transformation of seismic signal s (t).According to formula (9), Fast Fourier Transform (FFT) is utilized
(FFT), S-transformation can rapidly be calculated.Using the S-transformation in formula (9), we can calculate the Fourier spectrum face of seismic data
Product carries out seismic data decay behavior.
Embodiment：
(1) synthetic seismic data example
First, we verify effectiveness of the invention with without making an uproar with noisy synthetic seismic data.Fig. 1 is without the synthesis made an uproar
Seismic data shares 100 seismic datas, wherein containing there are two level courses.Source wavelet is the zero phase that dominant frequency is 40Hz
Ricker wavelets.Time sampling interval is 1 millisecond.The Q values of first layer are 200, and the Q values of the second layer are respectively that 100 (the 1st arrives
40), 30 (41 to the 60th), 60 (61 to the 100th).We use the Chang Xiangwei wavelets in formula (1) first
According to formula (2) estimate source wavelet, result such as Fig. 2 so.Fig. 2 (a) gives practical source wavelet and estimates to obtain normal
The time domain waveform of phase wavelet (source wavelet estimated), Fig. 2 (b) give what practical source wavelet was obtained with estimation
The Fourier spectrum of Chang Xiangwei wavelets (source wavelet estimated), difference between the two are negligible, it is seen that when focus
When wave is unknown, we can obtain source wavelet with Chang Xiangwei higher-order spectras, and obtain estimation parameter.Fig. 3 (a) gives difference
The Fourier spectrum of layer, the not seismic data of people having a common goal, it is seen that Q value differences cause the Fourier spectrum of decaying wavelet to be also to be not quite similar
, therefore the present invention is supported with proofs using the Fourier spectrum area change of differential declines wavelet to carry out the estimation of Q values.Figure
3 (b) gives the present invention versus Q value estimated, although the Q values are not theoretical, true quality factors, this is with respect to Q
Value still can accurately portray the relativeness of seismic data decaying, can portray the decaying of Different Strata well.
Because seismic data inevitably contains noise in actual treatment, therefore we attempt to apply the present invention to contain
The synthetic seismic data made an uproar carries out decay behavior, to prove the validity and stability of this method.Fig. 4 is the synthesis in Fig. 1
The noisy synthetic seismic data that the white Gaussian noise that signal-to-noise ratio is 5dB obtains is added in seismic data, it is seen that under influence of noise, ground
The poor quality of data is shaken, this necessarily brings prodigious influence to seismic attenuation estimation.Fig. 5 (a) gives different layers, not people having a common goal
Noisy seismic data Fourier spectrum, it is seen that noise such as uses centroid frequency deflection method to the severe jamming of Fourier spectrum
(CFS) etc. decay behavior is carried out using single, specific frequency variation, necessarily brings prodigious evaluated error, it is difficult to
To an accurate estimated result.Shown in the versus Q value that the method for the present invention is estimated such as Fig. 5 (b), result can be well
Disclose the relativeness of different layers and differential declines, it is seen that the present invention remains to access one and stable estimates in the case that noisy
Meter is as a result, the estimated result of the versus Q value still can accurately reflect the difference in attenuation of noisy synthetic seismic data.
(2) actual seismic data example
The method of estimation of the present invention is used for actual seismic data by us, attempts to carry out decay behavior.The 2D actual seismics
Data as shown in fig. 6, its time sampling interval be 1 millisecond, share 600 track datas.No. CDP of two mouthfuls of wells is respectively 290 and 700
(in Fig. 6 at vertical line mark), wherein well 1 are high-yield well, contain 9.2 meters of thick gas sands, and well 2 is stripper well, contains 8 meters thick
Sandstone, but log well and show result not gassiness.It is obtained shown in source wavelet such as Fig. 7 (a) and (b), according to reality according to formula (2) estimation
Negligible difference between border source wavelet and the source wavelet of estimation, it is seen that estimation source wavelet is correct in the present invention
Property.Note that since true source wavelet is unknown, which is to be extracted to obtain by shallow earthquake data.We use
Common centroid frequency deflection method (CFS) and spectrum method as a comparison than method (LRS), result such as Fig. 7 (c) is shown, attached in well 1
Closely there is not low reactance-resistance ratio, i.e., strong the phenomenon that decaying, Q values are declined near well 2, that is, are decayed still relatively strong, this is with result of logging well
And it misfits.Shown in versus Q value result such as Fig. 7 (c) that the present invention estimates, pays attention to the low reactance-resistance ratio near 290, i.e., decline by force
Subtract, the high q-factor near 700, i.e. underdamp.Versus Q value that the present invention estimates coincide with well logging result, it was demonstrated that the party
The correctness and validity of method, this method can be used for portraying and predicting for decaying reservoir.
The above content is merely illustrative of the invention's technical idea, and protection scope of the present invention cannot be limited with this, every to press
According to technological thought proposed by the present invention, any change done on the basis of technical solution each falls within claims of the present invention
Protection domain within.
Claims (3)
1. a kind of seismic attenuation method of estimation based on area under spectrum variation, which is characterized in that include the following steps：
Step 1：Practical source wavelet and its parameter are estimated using Chang Xiangwei wavelets；
Estimate that the specific method is as follows for source wavelet：
The definition of Chang Xiangwei wavelets is：
In formula, σ0And δ0Indicate the dominant frequency and standard deviation of Chang Xiangwei wavelets；Phase0For constant, selected according to different seismic datas
Take different values；I is imaginary unit；Assuming that the amplitude spectrum of practical source wavelet isEstimated according to formula (2)
Source wavelet：
In formula,For the source wavelet of estimation；
Step 2：The Fourier spectrum area of source wavelet is calculated, the specific method is as follows：
To formula (1) both sides about frequency integrator, the Fourier spectrum area for obtaining the source wavelet of estimation is as follows
Wherein, f is frequency, and e is exponential function；
Step 3：The Fourier spectrum area of decaying wavelet is calculated, the specific method is as follows：
If wavelet propagation time t second in the attenuation medium of quality factor q, the amplitude spectrum for receiving wavelet are
Wherein, t is the TWT that wavelet is propagated in attenuation medium；
Equally to frequency integrator, the area under spectrum for the wavelet that must decay is on formula (4) both sides
Step 4：Calculate the Fourier spectrum area change amount of source wavelet and the wavelet that decays；
Step 5：Versus Q value is calculated, seismic data decay behavior is carried out.
2. the seismic attenuation method of estimation according to claim 1 based on area under spectrum variation, which is characterized in that in step 4
The specific method is as follows for the area under spectrum difference of calculating source wavelet and the wavelet that decays：
It is poor to make to the Fourier spectrum area of the middle decaying wavelet of the source wavelet Fourier spectrum face permanent (5) estimated in formula (3), obtains
Area under spectrum variable quantity is
3. the seismic attenuation method of estimation according to claim 2 based on area under spectrum variation, which is characterized in that in step 5
Calculating versus Q value, the specific method is as follows：
Being changed using the area under spectrum for the source wavelet estimated in formula (6) and the area under spectrum of decaying wavelet, solution obtains versus Q value,
Expression formula is as follows：
In formula, M0It is defined respectively by formula (3) and formula (5) with M；
S-transformation is chosen to calculate the Fourier spectrum of time-varying seismic data；The definition of the S-transformation of real seismic signal s (t) is
In formula, t and f are the TWT and Fourier frequency that wavelet is propagated in attenuation medium；τ is time-shifting parameter,
The center of Gaussian window i.e. in S-transformation；According to Paasche Wa Er theorems, in formula (8) definition of S-transformation be rewritten as：
In formula, S (α) is the Fourier transformation of seismic signal s (t)；It is rapidly counted using Fast Fourier Transform (FFT) according to formula (9)
Calculate S-transformation；Using the S-transformation in formula (9), the Fourier spectrum area of seismic data is calculated, carries out seismic data decay behavior.
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