CN111427088A - Seismic data low-frequency compensation method for identifying thin mutual reservoir - Google Patents
Seismic data low-frequency compensation method for identifying thin mutual reservoir Download PDFInfo
- Publication number
- CN111427088A CN111427088A CN202010167760.7A CN202010167760A CN111427088A CN 111427088 A CN111427088 A CN 111427088A CN 202010167760 A CN202010167760 A CN 202010167760A CN 111427088 A CN111427088 A CN 111427088A
- Authority
- CN
- China
- Prior art keywords
- seismic
- frequency
- seismic data
- spectrum
- wavelet
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Withdrawn
Links
- 238000000034 method Methods 0.000 title claims abstract description 61
- 238000001228 spectrum Methods 0.000 claims abstract description 97
- 238000012952 Resampling Methods 0.000 claims abstract description 11
- 238000012545 processing Methods 0.000 claims abstract description 10
- 230000005540 biological transmission Effects 0.000 claims abstract description 9
- 230000000694 effects Effects 0.000 claims abstract description 7
- 238000001914 filtration Methods 0.000 claims description 13
- 238000006243 chemical reaction Methods 0.000 claims description 4
- 238000009499 grossing Methods 0.000 claims description 4
- 230000003595 spectral effect Effects 0.000 claims description 4
- 230000006835 compression Effects 0.000 claims description 2
- 238000007906 compression Methods 0.000 claims description 2
- 230000001419 dependent effect Effects 0.000 claims description 2
- 230000010339 dilation Effects 0.000 claims description 2
- 230000001965 increasing effect Effects 0.000 abstract description 8
- 230000002708 enhancing effect Effects 0.000 abstract description 2
- 239000000284 extract Substances 0.000 abstract 1
- 230000002401 inhibitory effect Effects 0.000 abstract 1
- 230000000644 propagated effect Effects 0.000 abstract 1
- 238000005457 optimization Methods 0.000 description 6
- 230000009286 beneficial effect Effects 0.000 description 5
- 238000010586 diagram Methods 0.000 description 4
- 108010003272 Hyaluronate lyase Proteins 0.000 description 2
- 238000012546 transfer Methods 0.000 description 2
- 238000010521 absorption reaction Methods 0.000 description 1
- 238000012937 correction Methods 0.000 description 1
- 238000012217 deletion Methods 0.000 description 1
- 230000037430 deletion Effects 0.000 description 1
- 238000009795 derivation Methods 0.000 description 1
- 238000003384 imaging method Methods 0.000 description 1
- 238000010606 normalization Methods 0.000 description 1
- 238000007781 pre-processing Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
- G01V1/28—Processing seismic data, e.g. for interpretation or for event detection
- G01V1/36—Effecting static or dynamic corrections on records, e.g. correcting spread; Correlating seismic signals; Eliminating effects of unwanted energy
- G01V1/362—Effecting static or dynamic corrections; Stacking
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
- G01V1/28—Processing seismic data, e.g. for interpretation or for event detection
- G01V1/36—Effecting static or dynamic corrections on records, e.g. correcting spread; Correlating seismic signals; Eliminating effects of unwanted energy
- G01V1/364—Seismic filtering
- G01V1/366—Seismic filtering by correlation of seismic signals
Landscapes
- Engineering & Computer Science (AREA)
- Remote Sensing (AREA)
- Physics & Mathematics (AREA)
- Life Sciences & Earth Sciences (AREA)
- Acoustics & Sound (AREA)
- Environmental & Geological Engineering (AREA)
- Geology (AREA)
- General Life Sciences & Earth Sciences (AREA)
- General Physics & Mathematics (AREA)
- Geophysics (AREA)
- Geophysics And Detection Of Objects (AREA)
Abstract
The invention relates to a seismic data low-frequency compensation method for identifying a thin mutual reservoir; in order to solve the difficulty of thin mutual reservoir identification, a method for performing low-frequency compensation on seismic data according to the physical principle of resampling seismic frequency is provided; estimating seismic wavelets from seismic data; (2) setting continuation factors for seismic low-frequency component compensation; (3) expanding the low-frequency component of the seismic wavelet spectrum; (4) constructing a transmission filter according to the wavelet spectrums before and after expansion; (5) applying a conductive filter to perform low-frequency compensation processing on the seismic data; the method extracts accurate seismic wavelets from actual seismic data, wherein the seismic wavelets have the advantage of reflecting the waveform distortion effect of seismic waves when the seismic waves are propagated in a stratum medium; the method has the advantages of enriching low-frequency components of the seismic data and increasing effective bandwidth of the seismic data; the method has the advantages of inhibiting seismic wavelet side lobes and improving the longitudinal resolution of seismic records, thereby enhancing the thin mutual reservoir identification capability.
Description
Technical Field
The invention relates to a seismic exploration data compensation method, in particular to a seismic data low-frequency compensation method for identifying a thin mutual reservoir.
Background
At present, geological targets of oil and gas containing basins in the world are more and more complex, problems of thin reservoirs, small transverse span and the like are faced, and a geophysical method for improving seismic data resolution is urgently needed to be developed, so that thin mutual reservoirs rich in oil and gas are effectively described. The resolution of the seismic data is directly controlled by the length of the seismic wavelet, and the shorter the wavelet length of the time domain is, the higher the resolution of the seismic data is.
However, in practice seismic waves propagate in subsurface formationsWhen the seismic wave is generated, the high-frequency energy of the seismic wave is gradually absorbed by a viscoelastic stratum medium, the seismic wavelet presented on a seismic reflection section is gradually stretched along with the increase of the seismic wave propagation distance, and the wavelet stretching directly causes the gradual reduction of the seismic data resolution. The inventor of the present invention first proposed a stabilized inverse Q filtering method in 2002, so as to improve the resolution of seismic data (a stable and effective application of inverse Q filtering,Geophysics67/2002/inventors; an Inverse Q-filter for differential resolution enhancement,Geophysics71/2006/inventors; seismicinversie Q filtering, Blackwell Publishing, Oxford, UK/2008/inventor). The inverse Q filtering method can only correct the phase of the seismic wave before, and cannot compensate the amplitude of the seismic data. And the Wang's stabilized inverse Q filtering method realizes amplitude compensation and phase correction of seismic data synchronization.
After the amplitude of the seismic data is compensated by the inverse Q filtering method, the main frequency is increased. However, after the amplitude spectrum normalization processing, while the dominant frequency is shifted to the high frequency direction, the amplitude of the low frequency amplitude with respect to the dominant frequency seems to be suppressed, and a phenomenon of "low frequency missing" appears, although the absolute value of the amplitude may not be changed. The phenomenon of low-frequency deletion tends to influence the subsequent imaging processing of seismic data and the effect of reservoir inversion.
Even if the seismic data are not subjected to inverse Q filtering processing, the seismic data have low-frequency missing phenomenon because a low-frequency wave limiting means is required to be adopted for suppressing interference such as surface waves during field data acquisition or data preprocessing. For example, due to the limitation of the geophone equipment, the seismic signals collected in the field lack low-frequency components after being uploaded by the geophone. This low frequency filtering phenomenon can be expressed by the detector transfer function, and if the denominator term of the detector transfer function can be cancelled as much as possible, the low frequency filtering effect of the detector can be compensated (CN 105866838A/2016.08.17). However, the propagation process of seismic waves in the viscoelastic medium of the stratum and the absorption attenuation of the seismic waves during the propagation process are the main factors causing waveform distortion.
Although practitioners have proposed multiplying the low frequency amplitude of seismic data by a frequency independent factor to achieve the purpose of raising the amplitude, this method has no obvious effect in practical applications (CN 105093329A/2015.11.25). More importantly, the method has no clear physical basis as a support for the process technology.
Disclosure of Invention
The present invention aims to overcome the above-mentioned drawbacks of the prior art and to provide a seismic data low frequency compensation method for identifying thin interbed reservoirs, which method is capable of identifying thin layer reflections from seismic sections.
In order to achieve the above object, the present invention provides a seismic data low frequency compensation method for identifying thin mutual reservoirs, which is characterized in that the method for performing low frequency compensation on seismic data is based on the physical principle of resampling seismic frequency. Estimating seismic wavelets from seismic data; (2) setting continuation factors for seismic low-frequency component compensation; (3) expanding the low-frequency component of the seismic wavelet spectrum; (4) constructing a transmission filter according to the wavelet spectrums before and after expansion; (5) and applying a conductive filter to perform low-frequency compensation processing on the seismic data. The step (1) is to extract accurate seismic wavelets from the actual seismic records. The seismic wavelet has the advantage of reflecting the waveform distortion effect of seismic waves when the seismic waves propagate in a stratum medium. Meanwhile, the step (5) has the advantage of being able to identify thin layer reflections from seismic sections.
As optimization, the step (1) estimates the seismic wavelets from the seismic data volume and is realized by three steps: calculating a power spectrum of the seismic data; smoothing and filtering to obtain an amplitude spectrum of the seismic wavelet; and determining the phase of the wavelet and constructing the constant-phase seismic wavelet.
As an optimization, the extension factor for expanding the low-frequency component of the earthquake in the step (2) is a frequency-variable factor and is resampling of different frequencies, and is not a conventional constant factor independent of frequency.
As optimization, the step (2) sets continuation factors of the low-frequency components of the earthquake, and is realized in two steps, firstly, the step ƒ for identifying the thin cross-spectrum and estimating the earthquake main frequency Ƥ Ground, earthThe dominant frequency of vibration is approximately equal to the mean frequency ƒ m (ii) a And selects the reference frequency ƒ for spectrum expansion r Is 0.8 ƒ Ƥ ≤ƒ r <ƒ Ƥ (ii) a Then, setting the frequency spectrum expansion factor of the frequency conversion as follows: when 0 is less than or equal to ƒ<ƒ r When, a (ƒ) = λ + (1- λ) ƒ/ƒ r (ii) a When ƒ is more than or equal to ƒ r Where, a (ƒ) =1, where ƒ is frequency and λ is an adjustable parameter, 0 is taken<Lambda is less than or equal to 0.5. From 0Hz to ƒ for frequency ƒ r The frequency band of (1) has a spectrum spreading factor gradually increased from lambda to 1, and the spectrum extends towards the low frequency direction, and the frequency ƒ is more than or equal to ƒ r The frequency band of (2) has a fixed spectrum expansion factor of 1, i.e. no expansion is made to the spectrum.
As optimization, the method for extending the spectrum of the low-frequency component of the seismic wavelet in the step (3) comprises the following steps: the extension method proposed by modifying the classical Fourier transform extension theory, the frequency dependent compression and stretching factor, and the setting of the equalization operator to keep the total energy of the power spectrum constant.
As an optimization, the physical basis of the low-frequency extension of the seismic wavelet in the step (3) is based on the basic principle of resampling frequency components in the seismic low-frequency band, and each frequency component of the signal comprises both amplitude and corresponding phase.
The expansion mode is optimized as Ŵ (ƒ) =1/ã | W (ƒ/a (ƒ)) | exp (i ø (ƒ/a (ƒ))), wherein | W (ƒ) | is the amplitude spectrum of the wavelet, ø (ƒ) is the phase spectrum, Ŵ (ƒ) is the wavelet spectrum after expansion, when 0<a(ƒ)<1, expanding the frequency spectrum to the low-frequency direction; is not less than 0 and not more than ƒ<ƒ r The extent to which the spectrum extends towards lower frequencies in the frequency range depends on 1/a (ƒ). The spectral broadening factors are integrated over the full frequency range and their mean is taken as the energy balance operator ã.
And (4) constructing a conduction filter, and calculating a complex conduction filter according to the wavelet spectrums before and after the low-frequency expansion. Constructing a transmission filter by adopting an inverse problem solving method; the spectrum of the initial seismic wavelet is W (ƒ), the spectrum of the post-expansion seismic wavelet is Ŵ (ƒ), and the spectrum expansion is expressed as a guided filter H (ƒ)ƒ): w (ƒ) H (ƒ) = Ŵ (ƒ); the conduction filter H (ƒ) is constructed as follows:
here complex conjugate, take a slight positive value to solve the inverse problem.
As an optimization, the step (5) of applying the conductive filter to perform low-frequency expansion processing on the seismic data is to apply a conductive filter H (ƒ) to the frequency domain seismic data to generate new frequency domain seismic data: Ŝ (ƒ) = H (ƒ) S (ƒ), the inverse fourier transform is implemented to output seismic data in the time domain, and the resolution of new data is improved.
After the technical scheme is adopted, the seismic data low-frequency compensation method for identifying the thin mutual reservoir has the beneficial effects that: the low-frequency component of the seismic data is enriched, and the effective frequency bandwidth of the seismic data is increased; the beneficial effects still lie in: the method inhibits the side lobe of the seismic wavelet, and improves the longitudinal resolution of the seismic record, thereby enhancing the capability of identifying the thin layer reflection from the seismic section.
Drawings
FIG. 1 is a block flow diagram of a seismic data low frequency compensation method of the present invention for identifying thin interbed reservoirs; FIG. 2 is a frequency shift diagram of a seismic data low frequency compensation method of the present invention for identifying thin interbed reservoirs; FIG. 3 is a seismic wavelet spectrum expansion diagram of the seismic data low-frequency compensation method for identifying thin interbed reservoirs of the present invention, in which the solid line is the amplitude spectrum of the seismic wavelet and the dotted line is the amplitude spectrum after low-frequency expansion; FIG. 4 is a graph comparing the original seismic spectrum (top) of the seismic data low frequency compensation method of the present invention for identifying thin interbed reservoirs with the seismic spectrum after low frequency compensation (bottom); FIG. 4 is a graph of amplitude spectra corresponding to wavelets before and after low frequency compensation; FIG. 5 is a graph comparing the seismic wavelet spectrum and time domain seismic wavelets (solid line) of the seismic data low frequency compensation method of the present invention for identifying thin interbed reservoirs with the seismic wavelet spectrum and time domain seismic wavelets after low frequency propagation (dashed line). The amplitude is expressed in decibels in fig. 5.
Detailed Description
The invention discloses a seismic data low-frequency compensation method for identifying a thin mutual reservoir, which is a method for performing low-frequency compensation on seismic data according to the physical principle of resampling seismic frequency. The implementation steps comprise: (1) estimating seismic wavelets from the seismic data; (2) setting continuation factors of seismic low-frequency compensation; (3) expanding the low-frequency component of the seismic wavelet spectrum; (4) constructing a transmission filter according to the wavelet spectrums before and after expansion; (5) and applying a conductive filter to perform low-frequency compensation processing on the seismic data.
The step (1) is to extract accurate seismic wavelets from actual seismic data, wherein the wavelets have the advantage of reflecting the waveform distortion effect of seismic waves when the seismic waves propagate in a stratum medium. The step (1) of estimating the seismic wavelet from the seismic data is realized in three steps: calculating a power spectrum of the seismic data; smoothing and filtering to obtain an amplitude spectrum of the seismic wavelet; and determining the phase of the wavelet and constructing the constant-phase seismic wavelet.
The continuation factor for expanding the low-frequency component of the earthquake in the step (2) is a frequency-variable factor and is resampling of different frequencies, and is not a conventional constant factor independent of the frequency.
The step (2) is to set continuation factors of the low-frequency components of the earthquake and is realized by two steps, firstly, the step ƒ is used for identifying the thin cross-spectrum and estimating the earthquake main frequency Ƥ Seismic dominant frequency approximately equal to mean frequency ƒ m (ii) a And selects the reference frequency ƒ for spectrum expansion r Is 0.8 ƒ Ƥ ≤ƒ r <ƒ Ƥ (ii) a Then, setting the frequency spectrum expansion factor of the frequency conversion as follows: when 0 is less than or equal to ƒ<ƒ r When, a (ƒ) = λ + (1- λ) ƒ/ƒ r (ii) a When ƒ is more than or equal to ƒ r Where, a (ƒ) =1, where ƒ is frequency and λ is an adjustable parameter, 0 is taken<Lambda is less than or equal to 0.5. From 0Hz to ƒ for frequency ƒ r The frequency band of (1) has a spectrum spreading factor gradually increased from lambda to 1, and the spectrum extends towards the low frequency direction, and the frequency ƒ is more than or equal to ƒ r The frequency band of (2) has a fixed spectrum expansion factor of 1, i.e. no expansion is made to the spectrum.
Expanding the seism in the step (3)The physical basis of the seismic wavelet low frequency extension in step (3) is based on the basic principle of resampling frequency components in the seismic low frequency band, and each frequency component of the signal includes both amplitude and corresponding phase, Ŵ (ƒ) =1/ã | W (ƒ/a (ƒ)) | exp (i ø (ƒ/a (ƒ))), where | W (ƒ) | is the amplitude spectrum of the wavelet, ø (ƒ) is the phase spectrum, Ŵ (ƒ) is the wavelet spectrum after extension, when 0<a(ƒ)<1, expanding the frequency spectrum to the low-frequency direction; is not less than 0 and not more than ƒ<ƒ r The extent to which the spectrum extends towards lower frequencies in the frequency range depends on 1/a (ƒ). The spectral broadening factor a (ƒ) is integrated over the full frequency range, and the average is taken as the energy balance operator ã.
And (4) the conduction filter is constructed by calculating a complex conduction filter according to the wavelet spectrums before and after low-frequency expansion. Constructing a transmission filter by adopting an inverse problem solving method; the spectrum of the starting seismic wavelet is W (ƒ), the spectrum of the post-dilation seismic wavelet is Ŵ (ƒ), and the spectral dilation is expressed as a guided filter H (ƒ): w (ƒ) H (ƒ) = Ŵ (ƒ); the conduction filter H (ƒ) is constructed as follows:
here complex conjugate, take a slight positive value to solve the inverse problem.
The step (5) of applying the conductive filter to perform low-frequency expansion processing on the seismic data is to apply a conductive filter H (ƒ) to the frequency domain seismic data to generate new frequency domain seismic data: Ŝ (ƒ) = H (ƒ) S (ƒ), the inverse fourier transform is implemented to output seismic data in the time domain, and the resolution of new data is improved. Therefore, the method has the advantage of being able to identify thin layer reflections from seismic sections.
In conclusion, the seismic data low-frequency compensation method for identifying the thin interbed reservoir has the beneficial effects that: the low-frequency component of the seismic data is enriched, and the effective frequency bandwidth of the seismic data is increased; the side lobe of the seismic wavelet is restrained, the longitudinal resolution of the seismic record is improved, and therefore the thin layer reflection can be identified from the seismic section.
In order to make the method and advantages of the invention for low frequency compensation of seismic data for identifying thin interbedded reservoirs more clear, embodiments of the invention are described in more detail below with reference to the accompanying drawings. FIG. 1 is a basic implementation flow of the spectrum expansion method for compensating low-frequency components of seismic data, which is suitable for identifying thin mutual reservoirs.
And S101, estimating seismic wavelets from the seismic data volume, wherein the estimation is realized in three steps. Calculating a power spectrum of the seismic data; smoothing and filtering to obtain an amplitude spectrum of the seismic wavelet; and determining the phase of the wavelet and constructing the constant-phase seismic wavelet.
And S102, setting continuation factors of the low-frequency components of the earthquake, and realizing the continuation factors by two steps. First, mean frequency is estimated from the power spectrum of the seismic data: ƒ m ＝∑ƒƒW2(ƒ)/ ∑ƒW2(ƒ), mean frequency ƒ m May be approximately equal to the seismic dominant frequency ƒ Ƥ . For example, according to the theoretical derivation of the frequency of the Ricker wavelet (Geophysics, vol: 80/2015/inventor), the relationship between the mean frequency and the dominant frequency of the Rake wavelet is ƒ m ≈1.064ƒ Ƥ . The invention selects the reference frequency ƒ during the spectrum expansion r Is 0.8 ƒ Ƥ ≤ƒ r <ƒ Ƥ . Then, setting the frequency spectrum expansion factor of the frequency conversion as follows: when 0 is less than or equal to ƒ<ƒ r When, a (ƒ) = λ + (1- λ) ƒ/ƒ r (ii) a When ƒ is not less than, alpha (ƒ) = 1. Where ƒ is the frequency and λ is an adjustable parameter, 0<Lambda is less than or equal to 0.5. For frequency) ƒ changed from 0 to ƒ r The spectrum expansion factor is gradually increased from lambda to 1, and the spectrum is extended towards the low frequency direction. For frequencies ƒ ≧ ƒ r The frequency band of (2) has a fixed spectrum expansion factor of 1, i.e. no expansion is made to the spectrum.
Step S103, expanding the frequency spectrum of the wavelet by applying the frequency spectrum expansion factor.
The expansion mode is Ŵ (ƒ) =1/ã | W (ƒ/a (ƒ)) | exp (i ø (ƒ/a (ƒ))), wherein | W (ƒ) | is the amplitude spectrum of the wavelet, ø (ƒ) is the phase spectrum, Ŵ (ƒ) is the wavelet spectrum after expansion.
The physical basis on which the spectrum continuation method of the invention is based is the fundamental principle of resampling frequency components in the low frequency band of an earthquake. Fig. 2 is a frequency shift diagram of the seismic low-frequency spectrum expansion process according to the embodiment of the invention, in which the dotted line is the case, the solid line is the case, and the dotted line is the case. For example, the spectrum of frequency 0.3 after expansion is taken from the spectrum of 0.81,0.68,0.59 before stretching. In both cases, the frequency shifts to the lower frequency. Each frequency component of the signal includes both an amplitude and a corresponding phase.
The case of the solid line in fig. 2 is applied to the embodiment of fig. 3. The bandwidth is measured at a position half the main amplitude. The low frequency broadening embodiment of fig. 3 shows that the left boundary position of the band is shifted from 8 Hz to around 2Hz after the low frequency of the sub-wave is broadened. The invention provides a method for integrating the spectrum expansion factors in the full frequency range, and taking the average value of the spectrum expansion factors as an energy balance operator.
And step S104, constructing a transmission filter according to the wavelet spectrums before and after expansion. The spectrum of the original seismic wavelet is that of the expanded seismic wavelet, and the spectrum expansion is expressed as a transmission filter: . Therefore, the transmission filter is constructed as follows by using an inverse problem solving method:
here complex conjugate, take a slight positive value to stabilize the solution to the inverse problem.
And step S105, applying a conductive filter to perform low-frequency expansion processing on the seismic data. Applying a guided filter to the frequency domain seismic data to generate new frequency domain seismic data: Ŝ (ƒ) = H (ƒ) S (ƒ), the inverse fourier transform is implemented to output seismic data in the time domain, and the resolution of new data is improved.
FIG. 4 compares the spectrum of the original seismic data (top plot) with the spectrum of the seismic data after low frequency compensation (bottom plot), and shows the smooth curves of the spectrum of the seismic data before and after low frequency compensation, and the smooth curves in the top plot are used to construct the amplitude spectra of the original wavelet. As shown in the figure, the seismic data low-frequency compensation method for identifying the thin mutual reservoir has the beneficial effects of enriching the low-frequency components of the seismic data and increasing the effective frequency bandwidth of the seismic data.
FIG. 5 compares the spectrum of the seismic wavelet before low frequency compensation (solid line) with the spectrum of the seismic wavelet after low frequency compensation (dashed line), where the amplitude is expressed in decibels; FIG. 5 compares the seismic wavelet before low frequency compensation (solid line) and the seismic wavelet after low frequency compensation (dashed line) simultaneously. As shown in the figure, the seismic data low-frequency compensation method for identifying the thin interbedded reservoir has the beneficial effects that seismic wavelet side lobes are suppressed, so that the longitudinal resolution of seismic data is improved, and the capability of identifying thin layer reflection from a seismic profile is enhanced.
Claims (9)
1. A seismic data low-frequency compensation method for identifying thin interbed reservoirs is characterized in that the method is a method for performing low-frequency compensation on seismic data according to the physical principle of resampling seismic frequency, and comprises the steps of (1) estimating seismic wavelets from the seismic data; (2) setting continuation factors for seismic low-frequency component compensation; (3) expanding the low-frequency component of the seismic wavelet spectrum; (4) constructing a transmission filter according to the wavelet spectrums before and after expansion; (5) applying a conductive filter to perform low-frequency compensation processing on the seismic data; and (1) extracting seismic wavelets which accurately reflect the waveform distortion effect of seismic waves when the seismic waves propagate in a stratum medium from the actual seismic records.
2. The method of seismic data low frequency compensation for identifying thin interbedded reservoirs of claim 1, wherein the seismic wavelets are estimated from a seismic data volume; the method is realized by three steps: calculating a power spectrum of the seismic data; smoothing and filtering to obtain an amplitude spectrum of the seismic wavelet; and determining the phase of the wavelet and constructing the constant-phase seismic wavelet.
3. The seismic data low frequency compensation method for identifying thin interbedded reservoirs of claim 1, wherein the step (2) prolongation factor is a frequency-variant factor, and is a resampling of different frequencies, rather than a conventional constant factor independent of frequency.
4. The seismic data low frequency compensation method for identifying thin interbed reservoir as claimed in claim 1, wherein said step (2) sets continuation factor of seismic low frequency component, and is implemented in two steps, first, said step ƒ for identifying thin interbed spectrum to estimate seismic dominant frequency Ƥ Seismic dominant frequency approximately equal to mean frequency ƒ m (ii) a And selects the reference frequency ƒ for spectrum expansion r Is 0.8 ƒ Ƥ ≤ƒ r <ƒ Ƥ (ii) a Then, setting the frequency spectrum expansion factor of the frequency conversion as follows: when 0 is less than or equal to ƒ<ƒ r When, a (ƒ) = λ + (1- λ) ƒ/ƒ r (ii) a When ƒ is more than or equal to ƒ r Where, a (ƒ) =1, where ƒ is frequency and λ is an adjustable parameter, 0 is taken<λ≤0.5。
5. The seismic data low frequency compensation method for identifying thin interbedded reservoirs of claim 1, wherein the step (3) of expanding the spectrum continuation method of the low frequency component of the seismic wavelet comprises: the extension method proposed by modifying the classical Fourier transform extension theory, the frequency dependent compression and stretching factor, and the setting of the equalization operator to keep the total energy of the power spectrum constant.
6. The seismic data low frequency compensation method for identifying thin interbedded reservoirs of claim 1, wherein the physical basis of the seismic wavelet low frequency propagation in step (3) is based on the fundamental principle of resampling frequency components in the seismic low frequency band, and each frequency component of the signal includes both amplitude and corresponding phase.
7. The seismic data low frequency compensation method for identifying the thin interbed reservoir as claimed in claim 6, wherein the expansion is carried out in a manner of Ŵ (ƒ) =1/ã | W (ƒ/a (ƒ)) | exp (i ø (ƒ/a (ƒ))), where | W (ƒ) | is an amplitude spectrum of a wavelet, ø (ƒ) is a phase spectrum, and Ŵ (ƒ) is a wavelet spectrum after the expansion.
8. The seismic data low frequency compensation method for identifying thin interbedded reservoirs of claim 1, wherein said step (4) of constructing the conductive filter calculates the complex conductive filter based on wavelet spectra before and after the low frequency propagation.
9. The seismic data low frequency compensation method for identifying thin interbedded reservoirs of claim 8, wherein a conductive filter is constructed using an inverse problem solving method; the spectrum of the starting seismic wavelet is W (ƒ), the spectrum of the post-dilation seismic wavelet is Ŵ (ƒ), and the spectral dilation is expressed as a guided filter H (ƒ): w (ƒ) H (ƒ) = Ŵ (ƒ); the conduction filter H (ƒ) is constructed as follows:
here complex conjugate, take a slight positive value to solve the inverse problem.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010167760.7A CN111427088A (en) | 2020-03-11 | 2020-03-11 | Seismic data low-frequency compensation method for identifying thin mutual reservoir |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010167760.7A CN111427088A (en) | 2020-03-11 | 2020-03-11 | Seismic data low-frequency compensation method for identifying thin mutual reservoir |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN111427088A true CN111427088A (en) | 2020-07-17 |
Family
ID=71547566
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010167760.7A Withdrawn CN111427088A (en) | 2020-03-11 | 2020-03-11 | Seismic data low-frequency compensation method for identifying thin mutual reservoir |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111427088A (en) |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112925013A (en) * | 2021-01-28 | 2021-06-08 | 中国石油化工股份有限公司 | Seismic data high-resolution processing method based on full-band continuation fidelity |
| CN113359187A (en) * | 2021-06-16 | 2021-09-07 | 王仰华 | Wavelet sidelobe elimination method for seismic data |
| CN113960671A (en) * | 2020-07-20 | 2022-01-21 | 中国石油化工股份有限公司 | Frequency-dependent wavelet compression processing method, device, computer equipment and storage medium |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105093329A (en) * | 2015-08-25 | 2015-11-25 | 中国石油天然气集团公司 | Automatic compensation method and automatic compensation device for low frequency information of seismic data |
| CN105116443A (en) * | 2015-07-27 | 2015-12-02 | 中国石油天然气集团公司 | Energy compensation method and device for low-frequency signal |
| CN105866838A (en) * | 2016-05-17 | 2016-08-17 | 中国石油天然气股份有限公司 | Seismic data low-frequency information compensation method and device |
| CN106772574A (en) * | 2016-11-28 | 2017-05-31 | 中国石油集团川庆钻探工程有限公司地球物理勘探公司 | A kind of spectrum continuation method of holding low-frequency information |
| CN110596758A (en) * | 2019-10-21 | 2019-12-20 | 中国石油化工股份有限公司 | Seismic signal low-frequency energy compensation method |
-
2020
- 2020-03-11 CN CN202010167760.7A patent/CN111427088A/en not_active Withdrawn
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105116443A (en) * | 2015-07-27 | 2015-12-02 | 中国石油天然气集团公司 | Energy compensation method and device for low-frequency signal |
| CN105093329A (en) * | 2015-08-25 | 2015-11-25 | 中国石油天然气集团公司 | Automatic compensation method and automatic compensation device for low frequency information of seismic data |
| CN105866838A (en) * | 2016-05-17 | 2016-08-17 | 中国石油天然气股份有限公司 | Seismic data low-frequency information compensation method and device |
| CN106772574A (en) * | 2016-11-28 | 2017-05-31 | 中国石油集团川庆钻探工程有限公司地球物理勘探公司 | A kind of spectrum continuation method of holding low-frequency information |
| CN110596758A (en) * | 2019-10-21 | 2019-12-20 | 中国石油化工股份有限公司 | Seismic signal low-frequency energy compensation method |
Non-Patent Citations (2)
| Title |
|---|
| SHUANGQUAN CHEN 等: "Seismic Resolution Enhancement by Frequency-Dependent Wavelet Scaling", 《IEEE GEOSCIENCE AND REMOTE SENSING LETTERS》 * |
| XIWU LIU 等: "Seismic resolution enhancement in shale-oil reservoirs", 《GEOPHYSICS》 * |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113960671A (en) * | 2020-07-20 | 2022-01-21 | 中国石油化工股份有限公司 | Frequency-dependent wavelet compression processing method, device, computer equipment and storage medium |
| CN113960671B (en) * | 2020-07-20 | 2024-04-16 | 中国石油化工股份有限公司 | Method, apparatus, computer device and storage medium for compressing frequency-variable wavelets |
| CN112925013A (en) * | 2021-01-28 | 2021-06-08 | 中国石油化工股份有限公司 | Seismic data high-resolution processing method based on full-band continuation fidelity |
| CN112925013B (en) * | 2021-01-28 | 2022-07-15 | 中国石油化工股份有限公司 | Seismic data high-resolution processing method based on full-band continuation fidelity |
| CN113359187A (en) * | 2021-06-16 | 2021-09-07 | 王仰华 | Wavelet sidelobe elimination method for seismic data |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN106597532B (en) | Pre-stack seismic data frequency band expanding method combining well data and horizon data | |
| CN111427088A (en) | Seismic data low-frequency compensation method for identifying thin mutual reservoir | |
| US20150168573A1 (en) | Geologic quality factor inversion method | |
| CN106405645B (en) | Frequency processing method is opened up in a kind of controllable earthquake of signal-to-noise ratio based on data quality analysis | |
| CN110187388B (en) | Stable seismic quality factor Q estimation method based on variational modal decomposition | |
| CN108614295B (en) | Stratum Q value calculation method based on generalized seismic wavelets | |
| CN108845357B (en) | Method for estimating formation equivalent quality factor based on synchronous extrusion wavelet transform | |
| CN103645507A (en) | A processing method for seismic records | |
| Wang et al. | Improving the resolution of seismic traces based on the secondary time–frequency spectrum | |
| Liu et al. | Seismic quality factor estimation using frequency-dependent linear fitting | |
| CN112099083B (en) | Quality factor estimation method and system based on bispectrum spectrum comparison | |
| CN109975874B (en) | Controllable seismic source scanning signal design method based on damping rake wavelets | |
| CN114428280A (en) | Seismic data low-frequency information compensation method and application thereof | |
| CN113359187B (en) | Wavelet sidelobe elimination method for seismic data | |
| CN114371505A (en) | Multi-wavelet inversion method and system based on seismic frequency division technology | |
| CN105093312A (en) | Seismic relative wave impedance prediction method and device based on frequency domain multi-order differentiation | |
| CN112925013B (en) | Seismic data high-resolution processing method based on full-band continuation fidelity | |
| CN112213775B (en) | Fidelity frequency-boosting method for high-coverage-frequency pre-stack seismic data | |
| CN110749923A (en) | Deconvolution method for improving resolution based on norm equation | |
| CN109884705B (en) | Processing method for improving seismic resolution by double-constraint time-frequency domain sub-spectrum | |
| Ben‐Feng et al. | A stable and efficient attenuation compensation method based on inversion | |
| CN113625341A (en) | Quality factor estimation method, device and system based on cepstrum analysis | |
| CN110794455B (en) | Seismic wave propagation energy attenuation compensation method | |
| CN112526604B (en) | Self-adaptive low-frequency compensation method and system based on target layer spectrum analysis | |
| CN114002736B (en) | Seismic exploration multi-frequency data fusion method based on weight deconvolution |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| WW01 | Invention patent application withdrawn after publication |
Application publication date: 20200717 |
|
| WW01 | Invention patent application withdrawn after publication |