CN107024718A - Poststack earthquake fluid Forecasting Methodology based on CEEMD SPWVD Time-frequency Spectrum Analysis - Google Patents
Poststack earthquake fluid Forecasting Methodology based on CEEMD SPWVD Time-frequency Spectrum Analysis Download PDFInfo
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Abstract
The invention discloses a kind of poststack earthquake fluid Forecasting Methodology based on CEEMD SPWVD Time-frequency Spectrum Analysis, the present invention solves the wavelet transformation of prior art presence because wavelet basis reason make it that the frequency domain data focusing extracted is not enough, and the defect of accurate frequency component data can not be correctly extracted caused by.The present invention is decomposed using CEEMD empirical mode decomposition methods to seismic channel set data, obtain multiple IMF frequency components, cross-correlation calculation is carried out to seismic traces collection signal and IMF components, reject the low IMF redundant components of cross-correlation coefficient, again SPWVD distributions are carried out to effective IMF components to calculate and be overlapped, obtain CEEMD SPWVD time-frequency spectrums, frequency attenuation gradient calculating finally is carried out to obtained CEEMD SPWVD time-frequency spectrums, it is ensured that most can accurately extract the effective frequency of post-stack seismic data.
Description
Technical field
The invention belongs to STUDIES ON SEISMIC WAVES technical field, especially with a kind of folding based on CEEMD-SPWVD Time-frequency Spectrum Analysis
Earthquake fluid Forecasting Methodology is relevant afterwards.
Background technology
Communication process of the seismic wave in underground medium always produces the attenuation by absorption in terms of amplitude and frequency.Cause ground
The factor of seismic wave decay can be divided into two kinds of internal cause and external cause：Internal cause includes solid and solid in medium, fluid and fluid, solid and
Between fluid caused by friction energy loss, external cause mainly as caused by the inhomogeneities of medium scatter.Actual money
Material shows, when such as oil, the gas and water of when containing fluid in geologic body, and the reflectance factor of seismic wave can increase, and high-frequency absorption is decayed especially
Substantially, in the attenuation trend of e index, therefore how to find suitable physical quantity to characterize such high frequency attenuation, and make good use of
This attenuation by absorption attribute, is applied to fluid detection with regard to important in inhibiting.Seismic wave attenuation by absorption theory comes from sound
Ripple is theoretical.Many oil companies regard the decay of seismic wave as a kind of seismic properties for being used directly to detect oil gas.Therefore, over the ground
The mechanism of production of seismic wave attenuation by absorption, which is studied, to be just particularly important.
Because underground medium complex shape is changeable, seismic wave is received from by epicenter excitation to device is detected, and seismic wave exists
Dielectric surface is by effects such as reflection, transmissions, and the seismic wave that wave detector is received all never is received with path, therefore it
Amplitude, frequency, waveform etc. all changed.Contain various noises in the ripple received simultaneously, due to underground medium shape
State is complicated, and medium is also not quite similar to the different frequency assimilation effect in seismic signal, therefore the frequency of the seismic signal received
Rate is not fixed, is to change with time and change, that is to say, that seismic signal is a kind of non-stationary signal.Practical application
In, research is for the Time-Frequency Analysis Method of seismic wave attenuation by absorption and the physics of acquisition energy accurate Characterization frequency decay attribute
Amount, has great importance to carrying out the fluid identification of reservoir method based on frequency decay.With the development of Time-Frequency Analysis Method,
Conventional Time-Frequency Analysis Method has：Short time discrete Fourier transform, Wigner-Ville distribution (WVD), wavelet transformation, S-transformation, broad sense
S changes, Hilbert-Huang transform (HHT) etc..Time frequency analysis be by data signal use a variety of mathematic(al) manipulations, realize from
Time-frequency domain angle is decomposed and described to the local feature of signal, to reach dissection to Signal fine-feature and more fully
Understanding.
Nowadays Time-Frequency Technology has evolved into a hot spot technology, wherein it is time frequency analysis skill to calculate seismic wave attenuation by absorption
One of most important application in art.
HHT conversion is time-frequency analysis technology developed in recent years, with higher temporal resolution and frequency discrimination
Rate, is widely used in seismic prospecting, therefore have with fluid identification of the HHT transform methods development based on frequency decay in recent years
Certain technology is perspective.HHT conversion is broadly divided into two steps, and the first step is that empirical mode decomposition obtains IMF components, and second step is
Hilbert transform is made to IMF components.Wherein first step empirical mode decomposition method is EMD decomposition methods.
In EMD algorithms, due to being fitted using cubic spline functions to data extreme value, and produced at end points
Swing has been given birth to, also, with the continuous progress of decomposable process, these, which swing, gradually inwardly to be propagated by end points and " pollution " is whole
Data and acquired results distortion is occurred, for low frequency IMF components, the error caused by this boundary effect is more
Seriously.Huang is directed to this problem, the method for proposing to carry out legacy data sequence according to characteristic wave continuation, but does not disclose
Specific processing method, and the patent by this method application.In addition, Huang was also once pointed out, EMD algorithms are faced
Boundary extension problem is not well solved yet.Therefore, exactly because the boundary extension that EMD algorithm self reasons are caused is asked
Topic, i.e., can cause error to time frequency analysis, influence time frequency analysis precision, and the method is directly used in earthquake fluid prediction,
It equally can also influence the precision of fluid prediction.
Fluid prediction method is being carried out using geological data, it is contemplated that the seismic wave attenuation by absorption mechanism of fluid, utilize frequency
Rate attenuation gradient method carries out fluid prediction.The frequency attenuation gradient of seismic wave refers to carrying out seismic wave in the base of time frequency analysis
On plinth, obtained slope value is fitted to the amplitude envelope of seismic wave time-frequency result medium-high frequency part.When being carried out to seismic wave
Frequency analysis can obtain a variety of attributes relevant with frequency of seismic wave, such as the gross energy of seismic wave, seismic wave energy maximum
Corresponding frequency values (i.e. the dominant frequency of seismic wave), instantaneous frequency, Instantaneous dominant frequency, frequency attenuation gradient etc..
2013, Yang Lu is proposed carried out frequency attenuation gradient calculating with generalized S-transform, and pre- for earthquake fluid
Survey.Generalized S-transform is on the basis of S-transformation, two parameters to be introduced to window function to control window function width and decay
Speed, the two parameters determine the trend that Gaussian window changes with frequency, because non-stationary signal has its unique time-frequency difference
Feature, therefore regulation parameter makes it change with the trend that frequency changes.This method weak point, frequency domain signal still takes
Certainly change in Gaussian window, obtained frequency domain signal is limited to window function, contains the signal of other frequency domains.
2014, Xue Yajuan proposed HHT Time-Frequency Analysis Methods, for earthquake fluid prediction.This method is mainly used
EMD empirical mode decompositions, fluid prediction is carried out using earthquake low-frequency information, and this method becomes relative to Fourier in short-term and small echo
Change, time frequency resolution has some improvement.This method is disadvantageous in that, and for be mutated larger nonlinear properties can not gram
Take modal overlap to imitate with end points, so will result in progress earthquake low-frequency information analytical error on this basis, influence fluid is pre-
Survey effect and precision.
The content of the invention
The wavelet transformation existed for above-mentioned background technology is because wavelet basis reason causes the frequency domain data extracted to focus on
Property it is not enough, the defect of accurate frequency component data can not be correctly extracted caused by, the present invention is intended to provide one kind is based on
The poststack earthquake fluid Forecasting Methodology of CEEMD-SPWVD Time-frequency Spectrum Analysis.
Therefore, the present invention uses following technical scheme：One kind is calculated based on CEEMD-SPWVD time-frequency spectrums frequency attenuation gradient
Poststack earthquake fluid Forecasting Methodology, comprise the following steps,
Step one：Operator E is defined firstj(), when a given signal, j-th of mode is tried to achieve by EMD；wi(n) table
Show the zero mean Gaussian white noise N (0,1) of unit variance；I=1 ..., I；εkCoefficient allows to select signal to noise ratio in each stage.
If echo signal x (t) of the earthquake poststack trace gather data for input, realized using different noises and pass through EMD repetitive assignments I times,
Population mean is calculated, and is defined as echo signal x (t) IMF1(t), formula is
Step 2：To k=1, single order residual error r is calculated1(t), formula is
r1(t)=x (t)-IMF1(t)；
Step 3：EMD realizes r1(t)+ε1E1(wi(t)), until meeting first IMF (t) condition, and define overall flat
Average is IMF2(t), formula is
Step 4：To k=2 ..., K, k rank residual errors r is calculatedk(t), formula is
rk(t)=rk-1(t)-IMFk(t)；
Step 5：Extract rk(t)+εkEk(wi(t) IMF)1(t) component, the population mean for calculating them is worth to target
The IMF of signal(k+1)(t), formula is
Step 6：Repeat step (four) (five), untill residual error can not be decomposed again, then obtaining final residual error R (t) is
Step 7：To original object signal x (t), after being decomposed by CEEMD, m effectively IMF components and n are obtained individual invalid
Redundancy IMF components, wherein invalid redundancy IMF components can the completeness extracted of interference signal, it is all must will be invalid superfluous
Remaining IMF components are rejected, and its method is mainly the obtained IMF components to all decomposition, asks remaining echo signal x's (t)
Cross-correlation degree, is invalid redundancy IMF components by the low judgement of cross-correlation degree, and is rejected, and echo signal x (t) is with dividing
The cross-correlation coefficient that solution is obtained between IMF components asks the method to be
Step 8：M obtained after being rejected to step 7 effectively IMF components, each component carries out Hilbert conversion, makes each
Individual basic friction angle component is changed into analytic signal；
Step 9：SPWVD calculating is carried out respectively to m effectively IMF components, and result is superimposed, as signal x (t)
CEEMD-SPWVD distribution, obtain the time-frequency spectrum of single-channel seismic signal：
Step 10：The CEEMD-SPWVD of the single-channel seismic signal obtained to step 9 time-frequency spectrum carries out frequency decay ladder
Degree is calculated, and circular assign the frequency of the energy maximum detected as initial decay frequency in time-frequency spectrum；Calculate
Frequency corresponding to 65% and 85% seismic wave energy, according to the corresponding energy value of frequency, fits declining for frequency and energy
Subtract gradient, obtain the attenuation gradient factor；
Step 11：Earthquake single track data are carried out to above-mentioned steps and carry out loop computation successively according to drawing lines number, you can with
Obtain the CEEMD-SPWVD frequency attenuation gradients of whole geological data.
Following beneficial effect can be reached using the present invention：The present invention is using CEEMD empirical mode decomposition methods to earthquake
Trace gather data are decomposed, and obtain multiple IMF frequency components, and cross-correlation meter is carried out to seismic traces collection signal and IMF components
Calculate, reject the low IMF redundant components of cross-correlation coefficient, then SPWVD distributions are carried out to effective IMF components and calculate and be overlapped,
CEEMD-SPWVD time-frequency spectrums are obtained, frequency attenuation gradient calculating finally is carried out to obtained CEEMD-SPWVD time-frequency spectrums, it is ensured that
It most can accurately extract the effective frequency of post-stack seismic data.The present invention takes into full account the non-stationary of geological data, utilizes
CEEMD-SPWVD time-frequency spectrum algorithm advantages, had both effectively overcome CEEMD to decompose the modal overlap and end effect that may be brought, again
Higher time frequency resolution is ensure that, calculates, can obtain obtaining the enterprising line frequency attenuation gradient of CEEMD-SPWVD time-frequency spectrums
To more accurate result, be conducive to improving earthquake fluid precision of prediction.
Embodiment
Step one of the present invention：Operator E is defined firstj(), when a given signal, j-th of mode is tried to achieve by EMD；wi
(n) the zero mean Gaussian white noise N (0,1) of unit variance is represented；I=1 ..., I；εkCoefficient allows to select to believe in each stage
Make an uproar ratio.If earthquake poststack trace gather data are the echo signal x (t) of input, are realized using different noises and pass through EMD repetitive assignments
I times, population mean is calculated, and be defined as echo signal x (t) IMF1(t), formula is
Step 2：To k=1, single order residual error r is calculated1(t), formula is
r1(t)=x (t)-IMF1(t)；
Step 3：EMD realizes r1(t)+ε1E1(wi(t)), until meeting first IMF (t) condition, and define overall flat
Average is IMF2(t), formula is
Step 4：To k=2 ..., K, k rank residual errors r is calculatedk(t), formula is
rk(t)=rk-1(t)-IMFk(t)；
Step 5：Extract rk(t)+εkEk(wi(t) IMF)1(t) component, the population mean for calculating them is worth to target
The IMF of signal(k+1)(t), formula is
Step 6：Repeat step (four) (five), untill residual error can not be decomposed again, then obtaining final residual error R (t) is
Step 7：To original object signal x (t), after being decomposed by CEEMD, m effectively IMF components and n are obtained individual invalid
Redundancy IMF components, wherein invalid redundancy IMF components can the completeness extracted of interference signal, it is all must will be invalid superfluous
Remaining IMF components are rejected, and its method is mainly the obtained IMF components to all decomposition, asks remaining echo signal x's (t)
Cross-correlation degree, is invalid redundancy IMF components by the low judgement of cross-correlation degree, and is rejected, and echo signal x (t) is with dividing
The cross-correlation coefficient that solution is obtained between IMF components asks the method to be
Step 8：M obtained after being rejected to step 7 effectively IMF components, each component carries out Hilbert conversion, makes each
Individual basic friction angle component is changed into analytic signal；
Step 9：SPWVD calculating is carried out respectively to m effectively IMF components, and result is superimposed, as signal x (t)
CEEMD-SPWVD distribution, obtain the time-frequency spectrum of single-channel seismic signal：
Step 10：The CEEMD-SPWVD of the single-channel seismic signal obtained to step 9 time-frequency spectrum carries out frequency decay ladder
Degree is calculated, and circular assign the frequency of the energy maximum detected as initial decay frequency in time-frequency spectrum；Calculate
Frequency corresponding to 65% and 85% seismic wave energy, according to the corresponding energy value of frequency, fits declining for frequency and energy
Subtract gradient, obtain the attenuation gradient factor；
Step 11：Earthquake single track data are carried out to above-mentioned steps and carry out loop computation successively according to drawing lines number, you can with
Obtain the CEEMD-SPWVD frequency attenuation gradients of whole geological data.
The present invention is mainly by adding two opposite white noise signals into signal to be analyzed, and carry out EMD respectively
Decompose.It is that a specific white noise is added in each stage of decomposition, and calculates a unique residual error to obtain each IMF,
This method can ensure discomposing effect it is suitable with EEMD in the case of, reduce the reconstructed error as caused by white noise there is provided
The Accurate Reconstruction of primary signal, while preferably realizing mode spectral decomposition and with lower calculating cost.
The general principle and principal character and advantages of the present invention of the present invention has been shown and described above.The technology of the industry
Personnel are it should be appreciated that the present invention is not limited to the above embodiments, and the simply explanation described in above-described embodiment and specification is originally
The principle of invention, without departing from the spirit and scope of the present invention, various changes and modifications of the present invention are possible, these changes
Change and improvement all fall within the protetion scope of the claimed invention.The claimed scope of the invention by appended claims and its
Equivalent thereof.
Claims (1)
1. the poststack earthquake fluid Forecasting Methodology based on CEEMD-SPWVD Time-frequency Spectrum Analysis, it is characterised in that comprise the following steps,
Step one：Operator E is defined firstj(), when a given signal, j-th of mode is tried to achieve by EMD；wi(n) represent single
The zero mean Gaussian white noise N (0,1) of position variance；I=1 ..., I；εkCoefficient allows to select signal to noise ratio in each stage, if ground
Echo signal x (t) of the poststack trace gather data for input is shaken, is realized using different noises and passes through EMD repetitive assignments I times, is calculated
Population mean, and it is defined as echo signal x (t) IMF1(t), formula is
Step 2：To k=1, single order residual error r is calculated1(t), formula is
r1(t)=x (t)-IMF1(t)；
Step 3：EMD realizes r1(t)+ε1E1(wi(t)), it is until meeting first IMF (t) condition, and defining population mean
IMF2(t), formula is
Step 4：To k=2 ..., K, k rank residual errors r is calculatedk(t), formula is
rk(t)=rk-1(t)-IMFk(t)；
Step 5：Extract rk(t)+εkEk(wi(t) IMF)1(t) component, the population mean for calculating them is worth to echo signal
IMF(k+1)(t), formula is
Step 6：Repeat step (four) (five), untill residual error can not be decomposed again, then obtaining final residual error R (t) is
Step 7：To original object signal x (t), all IMF components obtained after being decomposed by CEEMD seek remaining echo signal
X (t) cross-correlation degree, is invalid redundancy IMF components by the low judgement of cross-correlation degree, and is rejected, and obtains m and have
Imitate IMF components, echo signal x (t) asks the method to be with decomposing the cross-correlation coefficient that obtains between IMF components
Step 8：M obtained after being rejected to step 7 effectively IMF components, each component carries out Hilbert conversion, makes each base
This modal components is changed into analytic signal；
Step 9：SPWVD calculating is carried out respectively to m effectively IMF components, and result is superimposed, as signal x's (t)
CEEMD-SPWVD is distributed, and obtains the time-frequency spectrum of single-channel seismic signal：
Step 10：The CEEMD-SPWVD of the single-channel seismic signal obtained to step 9 time-frequency spectrum carries out frequency attenuation gradient meter
Calculate, the frequency of the energy maximum detected is assign as initial decay frequency in time-frequency spectrum；The earthquake of calculating 65% and 85%
Frequency corresponding to wave energy, according to the corresponding energy value of frequency, fits the attenuation gradient of frequency and energy, obtains decay ladder
Spend the factor；
Step 11：Earthquake single track data are carried out to above-mentioned steps and carry out loop computation successively according to drawing lines number, you can to obtain
The CEEMD-SPWVD frequency attenuation gradients of whole geological data.
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| CN107422381A (en) * | 2017-09-18 | 2017-12-01 | 西南石油大学 | A kind of earthquake low-frequency information fluid prediction method based on EEMD ICA |
| CN107422381B (en) * | 2017-09-18 | 2019-07-02 | 西南石油大学 | A kind of earthquake low-frequency information fluid prediction method based on EEMD-ICA |
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