CN102998706B - Method and system for attenuating seismic data random noise - Google Patents
Method and system for attenuating seismic data random noise Download PDFInfo
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Abstract
The invention discloses a method and system for attenuating seismic data random noise. The method includes: seismic data are obtained; Fourier transform is performed on the seismic data to generate frequency-space domain seismic data; plural empirical mode decomposition is performed on the frequency-space domain seismic data in the space direction to generate a plurality of modal components; an optimization method is used for generating self-adaptive signal reconstruction operators according to the frequency-space domain seismic data and the plurality of modal components; frequency domain seismic signals are reconstructed and generated according to the self-adaptive signal reconstruction operators and the plurality of modal components; Fourier transform is performed on the frequency domain seismic signals to generate time domain seismic signals after the random noise is attenuated; and a seismic section image after the noise is attenuated is drawn according to the time domain seismic signals after the random noise is attenuated. The method and system for attenuating the seismic data random noise can effectively suppress influence of the random noise on the seismic signals and improve signal to noise ratio of the seismic data.
Description
Technical field
The present invention relates to field of seismic exploration, particularly relate to the seism processing field in oil gas geophysical survey, is a kind of in seismic prospecting, to the method and system that earthquake data random noise decays concretely.
Background technology
Seismic prospecting is a kind of method of exploration utilizing artificial earthquake technology Underground structure.It is according to certain mode artificial excitation seismic event, utilizes the device being referred to as wave detector to receive from the reflected signal of underground, by the process of reflected signal with analyze Underground structure.
But, wave detector is while reception seismic signal, also the random noise in a large number from underground and earth's surface is received, reduce S/N ratio of seismic records, the ability of severe jamming seismic signal reflection underground structure, the decay of random noise and weak signal are recovered to be the important research content in seism processing field.
1, f-x domain space predictive filtering is the random noise attenuation method that current industry member is most widely used, effect is the most stable.The method carries out Signal analysis and noise compacting based on signal in the predictability of Frequency-Space Domain and the unpredictability of random noise.Asking for of its filter operator develops into non-causal operator (Gulunay, 2000) by autoregressive model (AR) cause and effect operator, and denoise algorithm also develops into the even four-dimensional denoising of three-dimensional by two dimension.But the method requires that seismic signal has steady state characteristic in the horizontal, and signal is in the horizontal in local linear trend.For the stratal configuration comparatively strong for Lateral heterogeneity, structure is comparatively complicated, its reflectance signature is difficult to the above-mentioned requirements meeting f-x domain space predictive filtering, can not obtain desirable denoising effect.
2, time frequency analysis class methods can process for unstable state and nonlinear properties, and these class methods grow up along with the rise of the time frequency analyzing tool such as wavelet transformation in recent years.According to useful signal and the random noise distributional difference at time-frequency domain, first by time frequency analyzing tool such as wavelet transformations, geological data is transformed to time-frequency domain, select suitable Time-Frequency Domain Filtering means by useful signal and noise separation again, then inverse transformation obtains the result after denoising to time domain.But, the mathematic(al) manipulation of these class methods lacks clear and definite physical significance in seismic data processing practically, do not consider the inherent characteristics of seismic signal itself, and implementation procedure is complicated, operability is poor, constrains the conversion that the method is applied to industry member by laboratory.
3, Hilbert-Huang transform (HHT) is a kind of Time-Frequency Analysis Method based on the build-in attribute of signal own, non-stationary signal is decomposed into the steady narrow band signal of different scale by the method by empirical mode decomposition (EMD) mode, be called intrinsic mode function (IMF), then the time-frequency spectrum that Hilbert transform just obtains signal carried out to these intrinsic mode functions.The method overcome the weakness that wavelet transformation needs to choose fixing wavelet basis, the intrinsic mode function decomposed reflects the build-in attribute of signal itself, has clear and definite physical significance, more effectively reflects the Analysis On Multi-scale Features of seismic signal.Ivan(1999) empirical mode decomposition method is incorporated into seism processing field by first time, is mainly used in seismic attributes analysis and improves resolution processes.Bekara(2008) empirical mode decomposition is combined with f-x filtering, propose a kind of new f-x territory random noise attenuation method, first Empirical mode decomposition is incorporated into the research of geological data random noise attenuation method.The method utilizes empirical mode decomposition to replace the linear autoregression wave filter of conventional f-x territory predictive filtering, by carrying out empirical mode decomposition to frequency slice and removing first intrinsic mode function, reaches the object of noise compacting.Although random noise is after empirical mode decomposition, major part concentration of energy is in first modal components, but other modal components still there is stronger remaining energy, and the useful signal of complex reflex also can be revealed on first mode component, therefore, in noise removal capability and guarantor's width performance, there is larger defect only by the filtering method of rejecting a certain component or some component.
Summary of the invention
The object of the invention is, in order to overcome the dissatisfactory deficiency of random noise attenuation signal existed in prior art, to provide a kind of method and system of the earthquake data random noise that decays, to solve the problem.
In order to achieve the above object, the embodiment of the invention discloses a kind of method of the earthquake data random noise that decays, comprising: obtain geological data; Described geological data is carried out Fourier transform, the geological data of generated frequency-spatial domain; Direction in space carries out complex empirical mode decomposition to the geological data of described Frequency-Space Domain, generates multiple modal components; According to geological data and described multiple modal components of described Frequency-Space Domain, optimization method is utilized to generate self-adapting signal reconstruct operator; According to described self-adapting signal reconstruct operator and described multiple modal components, reconstruct generated frequency territory seismic signal; Described frequency field seismic signal is carried out inverse fourier transform, generates the time domain seismic signal after random noise attenuation; The seismic section image after noise attentuation is drawn according to the time domain seismic signal after described random noise attenuation.
In order to achieve the above object, the embodiment of the invention also discloses a kind of system of the earthquake data random noise that decays, comprising: seismic data acquisition cell, for obtaining geological data; The geological data generation unit of Frequency-Space Domain, for described geological data is carried out Fourier transform, the geological data of generated frequency-spatial domain; Modal components generation unit, for carrying out complex empirical mode decomposition to the geological data of described Frequency-Space Domain on direction in space, generates multiple modal components; Reconstruct operator generation unit, for according to the geological data of described Frequency-Space Domain and described multiple modal components, utilizes optimization method to generate self-adapting signal and reconstructs operator; Frequency field seismic signal generation unit, for according to described self-adapting signal reconstruct operator and described multiple modal components, reconstructs generated frequency territory seismic signal; Time domain seismic signal generation unit, for described frequency field seismic signal is carried out inverse fourier transform, generates the time domain seismic signal after random noise attenuation; Seismic section image drawing unit, for drawing the seismic section image after noise attentuation according to the time domain seismic signal after described random noise attenuation.
The method and system of the decay earthquake data random noise of the embodiment of the present invention, automatically can identify and reconstruct by the seismic signal of random noise severe contamination, effective Attenuating Random Noise is on the impact of seismic signal, improve seismic data signal to noise ratio (S/N ratio), enhance the accuracy of detection of seismic signal to underground labyrinth and oil and gas reservoir, for Structure interpretation with seismic data and reservoir prediction provide high-quality basic data.
Accompanying drawing explanation
In order to be illustrated more clearly in the embodiment of the present invention or technical scheme of the prior art, be briefly described to the accompanying drawing used required in embodiment or description of the prior art below, apparently, accompanying drawing in the following describes is only some embodiments of the present invention, for those skilled in the art, under the prerequisite not paying creative work, other accompanying drawing can also be obtained according to these accompanying drawings.
Fig. 1 is each IMF spectrum diagram after the white Gaussian noise EMD during the complex empirical mode decomposition in the embodiment of the present invention is introduced decomposes;
Fig. 2 is the schematic diagram utilizing sciagraphy to carry out complex empirical mode decomposition;
Fig. 3 is the process flow diagram of the method for the decay earthquake data random noise of the embodiment of the present invention;
Fig. 4 is the structural representation of the system of the decay earthquake data random noise of the embodiment of the present invention;
Fig. 5 is the carbonatite seismologic record of certain oil field A block gathered in the embodiment of the present invention 1;
Fig. 6 is certain oil field A block carbonatite seismologic record after f-x domain space predictive filtering in the embodiment of the present invention 1;
Fig. 7 is certain oil field A block carbonatite seismologic record after damped system process of the present invention in the embodiment of the present invention 1;
Fig. 8 is the seismologic record of certain oil field B block gathered in the embodiment of the present invention 2;
Fig. 9 is the seismologic record of certain oil field B block after damped system process of the present invention in the embodiment of the present invention 2.
Embodiment
Below in conjunction with the accompanying drawing in the embodiment of the present invention, be clearly and completely described the technical scheme in the embodiment of the present invention, obviously, described embodiment is only the present invention's part embodiment, instead of whole embodiments.Based on the embodiment in the present invention, those of ordinary skill in the art, not making the every other embodiment obtained under creative work prerequisite, belong to the scope of protection of the invention.
Before introducing the specific embodiment of the present invention, in order to understand implementation process of the present invention better, first complex empirical mode decomposition involved in the present invention is simply introduced.
The people such as N E.Huang think, stationary signal should meet two conditions: (1) extreme point number or maximum difference 1 equal with zero crossing number; (2) in arbitrfary point, two the envelope mean values be made up of Local modulus maxima and local minizing point are 0.The signal meeting this condition is called intrinsic mode signal, and corresponding function is called intrinsic mode function (Intrinsic Mode Function, brief note IMF).For complicated non-stationary signal, do not meet IMF condition, therefore the people such as N E.Huang proposes following hypothesis: any signal is all made up of some different natural mode of vibration; Each mode can be linear, also can be nonlinear, and its limit number is identical with number at zero point, and upper and lower envelope is about time shaft Local Symmetric; Whenever, a signal can comprise many intrinsic mode signals; If overlapped between mode, just form composite signal.Process composite signal being decomposed into steady arrowband intrinsic mode signal is called empirical mode decomposition (Empirical Mode Decomposition, EMD), its objective is and complicated non-stationary signal is converted into stationary signal, for subsequent treatment brings convenience.Its core is carried out constantly " screening " to signal exactly, first local maximum and the minimal value of original data series is found out, cubic spline interpolation is utilized to connect local maximum and minimal value, obtain maximum value envelope and minimal value envelope respectively, then the local maximum in each moment and minimal value are averaged, obtain temporal average m (t):
Consider that original data series deducts the new ordered series of numbers that temporal average obtains and whether meets intrinsic mode function two conditions, if meet, then it can be used as an intrinsic mode function, if do not meet, then repeat said process, until satisfy condition as original data series.Like this, first intrinsic mode function c is obtained
1t (), separates it from original data series, then by remainder r
1t () carries out above decomposable process as new sequence, until residual term r
nt () becomes monotonic quantity or constant, now decompose out without IMF, thus terminates to decompose, and obtains isolated n intrinsic mode function component and a trend term r from original data series
n(t), after decomposing, signal can be expressed as:
Due to the decomposition that EMD is based on signal local feature, its characteristic dimension parameter is the data obtained based on actual measurement, therefore decomposes by it the intrinsic mode function that obtains and characterizes the vibration mode of signal on a certain characteristic dimension and frequency variation scope.Carry out EMD to equally distributed white noise signal to decompose and show, it is the half that previous IMF component extreme value is counted that any one IMF component extreme value is counted approximate, and its average period is the twice of previous IMF component, and this feature does not change with the change of data length.As shown in Figure 1, as can be seen from the IMF spectrogram of white Gaussian noise, each IMF dominant frequency is the half of previous IMF dominant frequency, and that is, EMD is equivalent to one two and enters bank of filters.This also illustrates simultaneously, the intrinsic mode function that EMD obtains and frequency-division filter to obtain result be different, the fast vibration component that intrinsic mode function characterizes signal and oscillating component at a slow speed, and containing frequency overlap between different modalities, if weighting scheme can be adopted to be combined by IMF, in fact the process of certain frequency band range data being carried out to " superposition " should be similar to, effectively signal to noise ratio (S/N ratio) can be improved.
Conventional EMD method is at the decomposition method for time-domain signal, and the EMD that conventional method cannot realize complex field signal decomposes.Bekara (2008) proposes and carries out EMD decomposition respectively to the real part of frequency field complex signal and imaginary part, then by the result correspondence combination after decomposing, thus forms the plural IMF after EMD.Although the method solves plural resolution problem, but it remains the algorithm of time domain, essence complex signal is mapped to two independently real-valued single argument spaces, and the mutual relationship existed between the two has been twisted, and the complex number components obtained lacks physical significance.Sciagraphy EMD isolation can realize the empirical mode decomposition of complex signal, first complex signal projects on assigned direction by the method, find projection vector maximum value and ask for maximum value envelope, repeat this process in different directions, form the three-dimensional tube bank that is surrounded signal, tube bank center is defined as oscillator signal at a slow speed, divides the quick concussion after original signal being deducted concussion at a slow speed, be called plural IMF, repeat this process successively and obtain a series of plural IMF.The intrinsic mode function that the method obtains reflects the Vibration Condition of complex signal on different scale, has clear and definite physical significance.As Fig. 2 carries out complex empirical mode decomposition for utilizing sciagraphy, Fig. 2 (a) is complex signal, the tube bank envelope that Fig. 2 (b) is formed in different directions projection for complex signal, Fig. 2 (c) is the oscillating component at a slow speed of tube bank center definition, Fig. 2 (d) is quick oscillator signal, i.e. intrinsic mode function.
Be described above the ultimate principle of complex empirical mode decomposition and the concept of mode function thereof, the present invention is based on said method and complex empirical mode decomposition is carried out to geological data, then adopt optimization method to ask for self-adapting signal by geological data and modal components thereof and reconstruct operator, recycling self-adapting signal reconstruct operator, reconstructs the seismic signal after noise attentuation by the different modalities component of geological data.
Fig. 3 is the process flow diagram of the method for the decay earthquake data random noise of the embodiment of the present invention, and as shown in the figure, the method for the present embodiment comprises:
Step S101, obtains geological data; Step S102, carries out Fourier transform by described geological data, the geological data of generated frequency-spatial domain; Step S103, direction in space carries out complex empirical mode decomposition to the geological data of described Frequency-Space Domain, generates multiple modal components; Step S104, according to geological data and described multiple modal components of described Frequency-Space Domain, utilizes optimization method to generate self-adapting signal reconstruct operator; Step S105, according to described self-adapting signal reconstruct operator and described multiple modal components, reconstruct generated frequency territory seismic signal; Step S106, carries out inverse fourier transform by described frequency field seismic signal, generates the time domain seismic signal after random noise attenuation; Step S107, draws the seismic section image after noise attentuation according to the time domain seismic signal after described random noise attenuation.
In the present embodiment, step S101 obtains geological data x (i, t), i=1,2 ... n, wherein n is record number of channels, in the present embodiment, the record number of channels n of the geological data obtained is 70, certainly the present invention is not limited thereto, can select other numerical value according to actual conditions.
In the present embodiment, described geological data is carried out Fourier transform by step S102, and the geological data of generated frequency-spatial domain, comprising:
To geological data x (i, t), i=1,2 ... n carries out Fourier transform, the geological data X (i, f) of generated frequency-spatial domain, i=1, and 2 ... n; Wherein,
X(i,f)=∫x(i,t)e
-j2πftdt。
In the present embodiment, step S 103 carries out complex empirical mode decomposition to the geological data of described Frequency-Space Domain on direction in space, generates multiple modal components, comprising:
To the geological data X (i, f) of described Frequency-Space Domain, i=1,2 ... n carries out complex empirical mode decomposition, generates multiple modal components C
j(i, f), j=1,2 ..., m, wherein, m is through the number of the modal components of empirical mode decomposition, in the present embodiment, is 9 through the number m of the modal components of empirical mode decomposition.
In the present embodiment, step S104, according to the geological data of described Frequency-Space Domain and described multiple modal components, utilizes optimization method to generate self-adapting signal reconstruct operator, comprising:
Step 1, according to the geological data X (i, f) of described Frequency-Space Domain, i=1,2 ... n builds vectorial X, according to described multiple modal components C
j(i, f), j=1,2 ..., m builds Matrix C, according to described self-adapting signal reconstruct operator A
j(f), j=1,2 ..., m builds vectorial A;
Step 2, sets up objective function E=X-C × A
t;
Step 3, utilizes optimization method to calculate the minimum value of described objective function, generates the self-adapting signal reconstruct operator A under described objective function minimum value
j(f), j=1,2 ..., m;
Now, A=(CC
t+ β I)
-1c
tx, wherein, I is unit matrix, and β is stability ratio of damping, and β=0.01.
In the present embodiment, step S105 is according to described self-adapting signal reconstruct operator and described multiple modal components, and reconstruct generated frequency territory seismic signal, comprising:
Described self-adapting signal is utilized to reconstruct operator A
j(f), j=1,2 ..., m, by described multiple modal components C
j(i, f), j=1,2 ..., m reconstructs described frequency field seismic signal S (i, f), i=1, and 2 ... n:
In the present embodiment, described frequency field seismic signal is carried out inverse fourier transform by step S106, generates the time domain seismic signal after random noise attenuation, comprising:
To the described frequency field seismic signal obtained after reconstruct
carry out inverse fourier transform, generate time domain seismic signal s (i, t) after random noise attenuation, i=1,2 ... n:
s(i,t)=∫S(i,f)e
j2πftdf。
In the present embodiment, step S107 just can draw the seismic section image after noise attentuation according to conventional geological data software for drawing.
Fig. 4 is the structural representation of the system of the decay earthquake data random noise of the embodiment of the present invention, and as shown in the figure, the system of the present embodiment comprises:
Seismic data acquisition cell 101, for obtaining geological data; The geological data generation unit 102 of Frequency-Space Domain, for described geological data is carried out Fourier transform, the geological data of generated frequency-spatial domain; Modal components generation unit 103, for carrying out complex empirical mode decomposition to the geological data of described Frequency-Space Domain on direction in space, generates multiple modal components; Reconstruct operator generation unit 104, for according to the geological data of described Frequency-Space Domain and described multiple modal components, utilizes optimization method to generate self-adapting signal and reconstructs operator; Frequency field seismic signal generation unit 105, for according to described self-adapting signal reconstruct operator and described multiple modal components, reconstructs generated frequency territory seismic signal; Time domain seismic signal generation unit 106, for described frequency field seismic signal is carried out inverse fourier transform, generates the time domain seismic signal after random noise attenuation; Seismic section image drawing unit 107, for drawing the seismic section image after noise attentuation according to the time domain seismic signal after described random noise attenuation.
In the present embodiment, seismic data acquisition cell 101 obtains geological data x (i, t), i=1,2 ... n, wherein n is record number of channels, in the present embodiment, the record number of channels n of the geological data obtained is 70, certainly the present invention is not limited thereto, can select other numerical value according to actual conditions.
In the present embodiment, described geological data is carried out Fourier transform by the geological data generation unit 102 of Frequency-Space Domain, and the geological data of generated frequency-spatial domain, comprising:
To geological data x (i, t), i=1,2 ... n carries out Fourier transform, the geological data X (i, f) of generated frequency-spatial domain, i=1, and 2 ... n; Wherein,
X(i,f)=∫x(i,t)e
-j2πftdt。
In the present embodiment, modal components generation unit 103 carries out complex empirical mode decomposition to the geological data of described Frequency-Space Domain on direction in space, generates multiple modal components, comprising:
To the geological data X (i, f) of described Frequency-Space Domain, i=1,2 ... n carries out complex empirical mode decomposition, generates multiple modal components C
j(i, f), j=1,2 ..., m, wherein, m is through the number of the modal components of empirical mode decomposition, in the present embodiment, is 9 through the number m of the modal components of empirical mode decomposition.
In the present embodiment, reconstruct operator generation unit 104, according to the geological data of described Frequency-Space Domain and described multiple modal components, utilizes optimization method to generate self-adapting signal reconstruct operator, comprising:
Step 1, according to the geological data X (i, f) of described Frequency-Space Domain, i=1,2 ... n builds vectorial X, according to described multiple modal components C
j(i, f), j=1,2 ..., m builds Matrix C, according to described self-adapting signal reconstruct operator A
j(f), j=1,2 ..., m builds vectorial A;
Step 2, sets up objective function E=X-C × A
t;
Step 3, utilizes optimization method to calculate the minimum value of described objective function, generates the self-adapting signal reconstruct operator A under described objective function minimum value
j(f), j=1,2 ..., m;
Now, A=(CC
t+ β I)
-1c
tx, wherein, I is unit matrix, and β is stability ratio of damping, and β=0.01.
In the present embodiment, frequency field seismic signal generation unit 105 is according to described self-adapting signal reconstruct operator and described multiple modal components, and reconstruct generated frequency territory seismic signal, comprising:
Described self-adapting signal is utilized to reconstruct operator A
j(f), j=1,2 ..., m, by described multiple modal components C
j(i, f), j=1,2 ..., m reconstructs described frequency field seismic signal S (i, f), i=1, and 2 ... n:
In the present embodiment, described frequency field seismic signal is carried out inverse fourier transform by time domain seismic signal generation unit 106, generates the time domain seismic signal after random noise attenuation, comprising:
To the described frequency field seismic signal obtained after reconstruct
carry out inverse fourier transform, generate time domain seismic signal s (i, t) after random noise attenuation, i=1,2 ... n:
s(i,t)=∫S(i,f)e
j2πftdf。
In the present embodiment, seismic section image drawing unit 107 just can draw the seismic section image after noise attentuation according to conventional geological data software for drawing.
Embodiment 1:
The present embodiment is the application example of certain oil field A block, this exploration acreage is positioned at innerland, desert, and sand dune is scattered on geological data and creates strong random disturbance, and exploration zone of interest is the carbonate reservoir of about 7000 meters, underground, carbonate inner structure wave impedance difference is less, and reflected signal is more weak.Carbonate inner structure reflection is submerged among scattered noise completely.Fig. 5 is the seismologic record of this exploration acreage field acquisition, and this seismologic record almost be can not see the shadow of usable reflection, is difficult to analyze the architectural feature of carbonate inner structure and describe.Fig. 6 is the result utilizing industry member f-x domain space predictive filtering method to carry out after random noise attenuation, and random noise obtains compacting to a certain extent, the seismic section after denoising can be seen useful signal off and on.Fig. 7 is the result utilizing damped system of the present invention to carry out after random noise attenuation, random noise obtains and decays more thoroughly, recover the reflectance signature of carbonate inner structure structure preferably, for carbonatite structure elucidation and reservoir prediction provide high-quality basic data.
Embodiment 2:
The present embodiment is the application example of certain oil field B block, and this block is adjacent with A block, but signal to noise ratio (S/N ratio) is a little more than the geological data of A block.The geological data that Tu8Shi Gai district gathers soon, it is sandstone formation on 3100ms, it is carbonate formation under 3100ms, due to the pollution of random noise, seismic section shown in Fig. 8 can only track the lineups that several strong reflection interface produces, and weak reflected signal is submerged among noise completely.Fig. 9 is the result utilizing damped system of the present invention to carry out after random noise attenuation, random disturbance obtains effective compacting, recover the weak reflected signal flooded by random noise well, clearly show that stratal configuration and contact relation thereof, increase substantially the precision utilizing seismic signal Underground structure.
The method and system of the decay earthquake data random noise of the embodiment of the present invention, automatically can identify and reconstruct by the seismic signal of random noise severe contamination, effective Attenuating Random Noise is on the impact of seismic signal, improve seismic data signal to noise ratio (S/N ratio), enhance the accuracy of detection of seismic signal to underground labyrinth and oil and gas reservoir, for Structure interpretation with seismic data and reservoir prediction provide high-quality basic data.
Above-described specific embodiment; object of the present invention, technical scheme and beneficial effect are further described; be understood that; the foregoing is only specific embodiments of the invention; the protection domain be not intended to limit the present invention; within the spirit and principles in the present invention all, any amendment made, equivalent replacement, improvement etc., all should be included within protection scope of the present invention.
Claims (7)
1. a method for the earthquake data random noise that decays, is characterized in that, described method comprises:
Step 101, obtains geological data;
Step 102, carries out Fourier transform by described geological data, the geological data of generated frequency-spatial domain;
Step 103, direction in space carries out complex empirical mode decomposition to the geological data of described Frequency-Space Domain, generates multiple modal components;
Step 104, according to geological data and described multiple modal components of described Frequency-Space Domain, utilizes optimization method to generate self-adapting signal reconstruct operator, wherein also comprises:
Step 1, builds vectorial X according to the geological data of described Frequency-Space Domain, builds Matrix C according to described multiple modal components, builds vectorial A according to described self-adapting signal reconstruct operator;
Step 2, sets up objective function E=X-C × A
t;
Step 3, utilizes optimization method to calculate the minimum value of described objective function, generates the self-adapting signal reconstruct operator under described objective function minimum value;
Now, A=(CC
t+ β I)
-1c
tx, wherein, I is unit matrix, and β is stability ratio of damping, and β=0.01;
Step 105, according to described self-adapting signal reconstruct operator and described multiple modal components, reconstruct generated frequency territory seismic signal;
Step 106, carries out inverse fourier transform by described frequency field seismic signal, generates the time domain seismic signal after random noise attenuation;
Step 107, draws the seismic section image after noise attentuation according to the time domain seismic signal after described random noise attenuation.
2. the method for decay earthquake data random noise according to claim 1, is characterized in that, the geological data of described acquisition is x (i, t), i=1,2 ... n, wherein n is record number of channels.
3. the method for decay earthquake data random noise according to claim 2, is characterized in that, described described geological data is carried out Fourier transform, and the geological data of generated frequency-spatial domain, comprising:
To geological data x (i, t), i=1,2 ... n carries out Fourier transform, the geological data X (i, f) of generated frequency-spatial domain, i=1, and 2 ... n; Wherein,
X(i,f)＝∫x(i,t)e
-j2πftdt。
4. the method for decay earthquake data random noise according to claim 3, is characterized in that, describedly on direction in space, carries out complex empirical mode decomposition to the geological data of described Frequency-Space Domain, generates multiple modal components, comprising:
To the geological data X (i, f) of described Frequency-Space Domain, i=1,2 ... n carries out complex empirical mode decomposition, generates multiple modal components C
j(i, f), j=1,2 ..., m, wherein, m is through the number of the modal components of empirical mode decomposition.
5. the method for decay earthquake data random noise according to claim 4, is characterized in that, described according to described self-adapting signal reconstruct operator and described multiple modal components, and reconstruct generated frequency territory seismic signal, comprising:
Described self-adapting signal is utilized to reconstruct operator A
j(f), j=1,2 ..., m, by described multiple modal components C
j(i, f), j=1,2 ..., m reconstructs described frequency field seismic signal S (i, f), i=1, and 2 ... n:
6. the method for decay earthquake data random noise according to claim 5, is characterized in that, described described frequency field seismic signal is carried out inverse fourier transform, generates the time domain seismic signal after random noise attenuation, comprising:
To the described frequency field seismic signal obtained after reconstruct
carry out inverse fourier transform, generate time domain seismic signal s (i, t) after random noise attenuation, i=1,2 ... n
:
s(i,t)＝∫S(i,f)e
j2πftdf。
7. the method for the decay earthquake data random noise according to any one of claim 1-6, is characterized in that, the number m=9 of the described modal components through empirical mode decomposition.
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| CN104375184B (en) * | 2013-08-15 | 2017-04-05 | 中国石油天然气集团公司 | A kind of efficient geological data random noise attenuation method |
| CN105372707A (en) * | 2014-08-27 | 2016-03-02 | 中国石油化工股份有限公司 | Method for attenuating multi-scale seismic data random noise |
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| CN105116442B (en) * | 2015-07-24 | 2019-01-01 | 长江大学 | The reconstructing method of the weak seismic reflection signals of lithologic deposit |
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