CN111487675B - Method for generating seismic data high signal-to-noise ratio and high resolution time frequency spectrum - Google Patents
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Abstract
The invention relates to a method for generating a high-signal-to-noise-ratio high-resolution time frequency spectrum of seismic data, which is realized by multi-channel weighted synthesis along a formation dip angle and a mode of constructing an adaptive mask filter; the method comprises the following steps: estimating dip angles of each time-space position on the seismic section; constructing a plurality of weighted synthesis channels aiming at each time position, and calculating an instantaneous autocorrelation function of an analytic signal of the synthesis channels; calculating standard Weiwei time-frequency distribution and corresponding flat-virtual Weiwei distribution; constructing a time-frequency spectrum self-adaptive mask filter; and realizing mask filtering of standard Weiwei time-frequency distribution to obtain an optimized seismic channel time-frequency spectrum. The method has the characteristics of high signal-to-noise ratio and high resolution, simultaneously has the capability of eliminating cross interference, and has the advantage of clearly separating the spatial distribution of the sandstone reservoir and the spatial distribution of the system containing the coal bed when the actual three-dimensional seismic data is used for reservoir prediction.
Description
Technical Field
The invention relates to the field of geophysical signal analysis, in particular to a method for generating a seismic data time frequency spectrum with high signal-to-noise ratio and high resolution.
Background
Time-frequency spectrum analysis of seismic data is a key means for reservoir geophysical research. Intuitively, the time-frequency spectrum analysis is to generate corresponding frequency spectrum point by point according to the time sampling sequence of any seismic single channel, and is to convert a one-dimensional seismic channel changing along with time into a two-dimensional spectrum changing along with time and frequency. This two-dimensional spectrum is called the time spectrum.
The Wigner-Ville time frequency distribution method is one of effective methods for calculating the time frequency spectrum of the seismic trace. The implementation process can be divided into three basic steps: calculating analytic signals of the seismic traces, calculating an instantaneous autocorrelation function of the analytic signals, and calculating Fourier transform of the autocorrelation function. Because the analytical signal and the instantaneous autocorrelation function are adopted in the calculation method of the Weiwei time-frequency distribution, the Weiwei time-frequency distribution has the characteristic of high resolution. However, it is because the computation of the instantaneous autocorrelation function leads to severe cross-interference between the components contained in the signal.
In order to suppress the cross-interference between the above-mentioned signal components, researchers have proposed a calculation method called the flat-imaginary wiry distribution. It contains two layers of meaning, one "smooth" refers to the suppression of interference in the time direction, and one "virtual" actually refers to the suppression of interference in the frequency direction. However, the suppression processing in both the time direction and the frequency direction is essentially low-pass filtering, and this has the effect of losing high-frequency components and reducing the resolution of the time spectrum.
Because the time frequency spectrum calculation method is a single-channel analysis method, the generated time frequency spectrum is influenced by the signal-to-noise ratio of seismic data, the signal-to-noise ratio of the time frequency spectrum is low, and the time frequency spectrum between channels lacks space consistency, thereby causing difficulty in the interpretation and application of the seismic time frequency spectrum.
By combining the analysis, the spectrum resolution is high but the cross interference is serious in the standard Weiwei time spectrum, the cross interference is inhibited but the resolution is reduced in the flat-virtual Weiwei time spectrum, and the calculation of the time spectrum is single-channel operation, so that the generated earthquake time spectrum has poor signal-to-noise ratio and is seriously influenced by earthquake data noise, and the application of the time spectrum and the geophysical explanation are difficult.
Disclosure of Invention
The invention aims to overcome the defects of the existing method and provides a method for generating a high-signal-to-noise-ratio high-resolution time spectrum of seismic data. The method for generating the earthquake time frequency spectrum has the advantages of high signal-to-noise ratio and high resolution.
In order to achieve the purpose, the seismic data high signal-to-noise ratio high resolution time frequency spectrum generation method provided by the invention improves the signal-to-noise ratio of the seismic time frequency spectrum by multi-channel weighted synthesis along the formation dip angle and utilizing the spatial continuity of seismic reflection homophase axes; the resolution of the frequency spectrum during earthquake is enhanced by a method of constructing an adaptive mask filter. The method has the advantages of high resolution and high signal-to-noise ratio.
As optimization, the seismic data high signal-to-noise ratio high resolution time frequency spectrum generation method specifically comprises the following steps: (1) estimating dip angles of each time-space position on the seismic section; (2) constructing a plurality of weighted synthesis channels aiming at each time position, and calculating an instantaneous autocorrelation function of an analytic signal of the synthesis channels; (3) calculating standard Weiwei (Wigner-Ville) time-frequency distribution and corresponding flat-virtual Weiwei distribution; (4) constructing a time-frequency spectrum self-adaptive mask filter; (5) and realizing mask filtering of standard Weiwei time-frequency distribution to obtain an optimized seismic channel time-frequency spectrum.
As optimization, the step (1) of estimating the dip angle of each time-space position from the actual seismic section is to construct a nonlinear equation set by adopting a discrete plane wave analytic equation mode, and estimate the time-varying and space-varying stratigraphic dip angles by a calculation method for solving a nonlinear problem.
Estimating the dip angle of each time-space position on the seismic section by adopting a plane wave analytic equation:
in the formulatIs a time sample of the seismic trace,xis the spatial location of the seismic traces,u(t,x) Is the seismic wavefield and σ is the dip of the linear event. Discretizing the plane wave analytic equation and expressing the plane wave analytic equation in a vector matrix form
f(σ) = e T [C(σ)○U]e = 0,
Where U is the data matrix, C (σ) is the matrix composed of the coefficients of the two-dimensional filter in the reverse order, [ C (σ) ] U]Is a multiplication by elements or a Hadamard product of two matrices, e is a full 1 vector. The introduction of the all-1-vector e in the above formula realizes the pair matrix [ C (sigma) ] U]The sum of all elements in. By solving a system of non-linear equationsf(σ) ≈ 0 estimates time-varying and space-varying formation dip angles.
As an optimization, step (2) implements the following three steps at each time position: constructing a composite track by performing multi-channel weighting according to local dip anglesx(t) (ii) a Calculating an analytic signal of the composite tracez(t) (ii) a Calculating the instantaneous autocorrelation function of the analytic signal:k(t,τ) = z(t+τ/2) z*(t-τ/2) in the formulaτIs the lag time of the instantaneous auto-correlation,z*(t) Is analyzing the signalz(t) The complex number of (c) is conjugated.
As optimization, step (3) uses the instantaneous autocorrelation function obtained in step (2) to calculate the standard wiry time-frequency distribution as follows:
and the corresponding Ping-Xunwei distribution was calculated as follows:
in the formulah(τ) Is a symmetric function with time as a variable, which functions as a low-pass filter along the frequency axis,g(t) Is another function of time as a variable, which functions as a low-pass filter along the time axis, andg(0) = h(0)。
as optimization, the mask filter in step (4) is constructed as follows:
the middle ratio ofW SP (t,f)|2 / |W(t,f)|2Is the similarity of the two power spectra,εis an adjustment parameter that controls the position of the mask filter boundary,ηthen it is the parameter that controls the smoothness of the mask filter boundary, settingηNot less than 2. For the sake of stability of the estimation, int,f) The power spectrum estimate at a point is the sum of the power spectra within a small two-dimensional window centered at that point.
As optimization, the constructed mask filter has the characteristics of the flattest passband and the adjusting parameters thereofεEffectively controlling the boundary position of the filter; setting a boundary smoothness parameterη= 4 regulating parameterεWhen = 0.05, any imaging spectral point with a power spectrum ratio value less than 20% can be filtered out from the time-frequency spectrum.
As optimization, the implementation process of the step (5) is divided into two steps: distribution of amplitude spectrum of Weiwei time-frequency distributionW(t,f) The l is filtered out and the filter is implemented,
(ii) a The wiry time frequency spectrum is reconstructed,
in the formulaƟ(t,f) The method is an original phase spectrum of Weiwei time-frequency distribution, and finally obtains a seismic channel optimized time-frequency spectrum with high signal-to-noise ratio and high resolution.
After the embodiment is adopted, the invention has the following beneficial effects: (1) the method has the advantages that the method has high resolution, the generated time frequency spectrum has the same high resolution as that of standard Weiwei distribution, and the method has the same capability of eliminating cross interference as that of flat-virtual Weiwei distribution. (2) The method has the advantage of high signal-to-noise ratio, and can clearly separate the spatial distribution of the sandstone reservoir and the spatial distribution of the coal-containing bed when the actual three-dimensional seismic data is used for reservoir prediction.
Drawings
FIG. 1 is a flow chart of a basic implementation of the seismic data high signal-to-noise ratio and high resolution time-frequency spectrum generation method of the present invention; FIG. 2 is a diagram of an actual seismic section (top) and its estimated dip (bottom) according to an embodiment of the present invention.
Fig. 3 is a mask filter proposed by the present invention, having the flattest passband characteristic. The horizontal axis in the diagram is the ratio of two power spectra +W SP (t,f)|2/|W(t,f)|2Calculating the boundary smoothness parameterηThe value is 4, and the adjusting parameters corresponding to the coefficient curves of the three mask filtersεThe values are 0.1,0.05,0.01, respectively.
FIG. 4 is a diagram of an embodiment of the present invention applied to a composite trace containing 4 wavelets comparing the standard Weir distribution of the composite trace, the Ping-Vwei distribution of the composite trace, and the time-frequency spectrum generated by the method of the present invention. Fig. 4 shows that the optimized temporal spectrum generated by the method of the present invention has the same high resolution as the standard wiry distribution, while the method has the same cross-interference rejection capability as the flat-imaginary wiry distribution.
FIG. 5 is an embodiment of the present invention applied to actual three-dimensional seismic recordings for reservoir prediction. The top plot is a time slice of a three-dimensional seismic data volume. The spectrum slice of the middle graph reflects the spatial distribution of the coal measure strata of the region, and the primary frequency of the reflection earthquake of the coal measure strata of the region is 15 Hz. The spectral slice of the lower graph is the spatial distribution of the sandstone reservoir in the region, which reflects seismic dominant frequencies of 20 hertz. The figure shows the high signal-to-noise ratio characteristic of the method of the invention, enabling a clear separation of the spatial distribution of the sandstone reservoir and the coal-derived formation.
Detailed Description
The method for generating the seismic data high signal-to-noise ratio and high resolution time frequency spectrum comprises the steps of improving the signal-to-noise ratio of the seismic time frequency spectrum by means of multi-channel weighted synthesis along the dip angle of the stratum and utilizing the spatial continuity of seismic reflection in-phase axes; the resolution of the frequency spectrum during earthquake is enhanced by a method of constructing an adaptive mask filter. The method comprises the following specific steps: (1) estimating dip angles of each time-space position on the seismic section; (2) constructing a plurality of weighted synthesis channels aiming at each time position, and calculating an instantaneous autocorrelation function of an analytic signal of the synthesis channels; (3) calculating standard Weiwei (Wigner-Ville) time-frequency distribution and corresponding flat-virtual Weiwei distribution; (4) constructing a time-frequency spectrum self-adaptive mask filter; (5) and realizing mask filtering of standard Weiwei time-frequency distribution to obtain an optimized seismic channel time-frequency spectrum.
In the step (1), the estimation of the dip angle of each time-space position from the actual seismic section is to construct a nonlinear equation set by discretizing a plane wave analytic equation, and estimate the dip angles of the time-varying and space-varying stratums by a calculation method for solving a nonlinear problem. Estimating the dip angle of each time-space position on the seismic section by adopting a plane wave analytic equation:
in the formulatIs the point in time of the seismic trace,xis the spatial location of the seismic traces,u(t,x) Is seismic waveThe field, σ, is the inclination of the linear in-phase axis. Discretizing the plane wave analytic equation and expressing the plane wave analytic equation in a vector matrix formf(σ)=e T [C(σ)○U]e =0, where U is the data matrix and C (σ) is the matrix composed of the coefficients of the two-dimensional filter in the reverse order, with dimensions identical to the data matrix U, [ C (σ) > U]Is a multiplication by elements or Hadamard product of two matrices, e being a full "1" vector. The introduction of the all-1 vector e in the above formula realizes the pair matrix [ C (sigma) ] U]The sum of all elements in. By solving a system of non-linear equationsf(σ) ≈ 0 estimates time-varying and space-varying formation dip angles.
The step (2) realizes the following three steps at each time position: constructing a composite track by performing multi-channel weighting according to local dip anglesx(t) (ii) a Calculating an analytic signal of the composite tracez(t) (ii) a Calculating the instantaneous autocorrelation function of the analytic signal:k(t,τ)= z(t+τ/2) z*(t-τ/2) In the formulaτIs the lag time of the autocorrelation function,z*(t) Is analyzing the signalz(t) The complex number of (c) is conjugated.
And (3) calculating the standard Weiwei time-frequency distribution by using the autocorrelation function in the step (2) as follows:
and the corresponding Ping-Xunwei distribution was calculated as follows:
in the formulah(τ) Is a symmetric function with time as a variable, which functions as a low-pass filter along the frequency axis,g(t) Is another function of time as a variable, which functions as a low-pass filter along the time axis, andg(0) = h(0)。
the mask filter in the step (4) is constructed as follows:
the middle ratio ofW SP (t,f)|2/|W(t,f)|2Is the similarity of the two power spectra,εis an adjustment parameter that controls the position of the mask filter boundary,ηthen it is the parameter that controls the smoothness of the mask filter boundary, settingηNot less than 2. For the sake of stability, int,f) The amplitude estimate at a point is the sum of the amplitudes within a small two-dimensional window centered at that point. The constructed mask filter has the characteristics of the flattest passband and the adjusting parameterεEffectively controlling the boundary position of the filter; setting a boundary smoothness parameterηAdjustment parameter with value 4εWhen the value is 0.05, any imaging spectrum point with the power spectrum ratio of less than 20 percent can be filtered from the time-frequency spectrum.
The implementation process of the step (5) is divided into two steps: distribution of amplitude spectrum of Weiwei time-frequency distributionW(t,f) The l is filtered out and the filter is implemented,
(ii) a The wiry time frequency spectrum is reconstructed,
in the formulaƟ(t,f) The method is an original phase spectrum of Weiwei time-frequency distribution, and finally obtains a seismic channel optimized time-frequency spectrum with high signal-to-noise ratio and high resolution.
In order to make the technical scheme and advantages of the invention more apparent, the following detailed description of the embodiments of the invention is provided in conjunction with the accompanying drawings. The invention provides a method for generating a high-signal-to-noise-ratio high-resolution time spectrum of seismic data. FIG. 1 is a flow chart of a basic implementation of the method of the present invention.
Step S101, estimating the dip angle of each time-space position on the seismic section. Using a plane wave analytic equation:
in the formulatIs the point in time of the seismic trace,xis the spatial location of the seismic traces,u(t,x) Is the seismic wavefield and σ is the dip of the linear event. Discretizing the plane wave analytic equation and expressing the plane wave analytic equation in a vector matrix form
f(σ) = e T [C(σ)○U]e = 0
Where U is the data matrix, C (σ) is the matrix composed of the coefficients of the two-dimensional filter in the reverse order, [ C (σ) ] U]Is element-wise multiplication or Hadamard multiplication of two matrices, e is a full 1 vector, and the introduction of the full 1 vector e in the above formula realizes the pair of matrices [ C (sigma) ] U]The sum of all elements in. By solving a system of non-linear equationsf(σ) ≈ 0 estimates time-varying and space-varying formation dip angles.
FIG. 2 is an actual seismic section (top) and its estimated dip (bottom) of an embodiment of the invention. The arrows in the figure are the estimated local dip directions, coinciding with the true in-phase axes of the actual seismic event of the background.
Step S102, the following three steps are realized at each time position: constructing a composite track by performing multi-channel weighting according to local dip anglesx(t) (ii) a Calculating an analytic signal of the composite tracez(t) (ii) a Calculating the instantaneous autocorrelation function of the analytic signal:k(t,τ)= z (t+τ/2) z*(t-τ/2) In the formulaτIs the lag time of the autocorrelation function,z*(t) Is analyzing the signalz(t) The complex number of (c) is conjugated.
Step S103, calculating the standard Weiwei time-frequency distribution by using the instantaneous autocorrelation function obtained in the step S102 as follows:
and the corresponding Ping-Xunwei distribution was calculated as follows:
in the formulah(τ) Is a symmetric function with time as a variable, which functions as a low-pass filter along the frequency axis,g(t) Is another function of time as a variable, which functions as a low-pass filter along the time axis, andg(0) = h(0)。
step S104, the mask filter is constructed as follows:
the middle ratio ofW SP (t,f)|2/|W(t,f)|2Is the similarity of the two power spectra,εis an adjustment parameter that controls the position of the mask filter boundary,ηthen it is the parameter that controls the smoothness of the mask filter boundary, settingηNot less than 2. For the sake of stability, int,f) The amplitude estimate at a point is the sum of the amplitudes within a small two-dimensional window centered at that point. As shown in FIG. 3, the constructed mask filter has the flattest passband characteristic, which adjusts the parametersεEffectively controlling the boundaries of the filter; setting a boundary smoothness parameterηAdjustment parameter with value 4εWhen the value is 0.05, any imaging spectrum point with the power spectrum ratio of less than 20 percent can be filtered from the time-frequency spectrum.
And step S105, realizing mask filtering of the standard Weiwei time-frequency distribution. The implementation process comprises two steps: distribution of amplitude spectrum of Weiwei time-frequency distributionW(t,f) The l is filtered out and the filter is implemented,
(ii) a The wiry time frequency spectrum is reconstructed,
in the formulaƟ(t,f) The method is an original phase spectrum of Weiwei time-frequency distribution, and finally obtains a seismic channel optimized time-frequency spectrum with high signal-to-noise ratio and high resolution.
The invention also provides two embodiments [ fig. 4, fig. 5], which illustrate that the invention has the following beneficial effects:
(1) as shown in FIG. 4, a composite trace contains 4 wavelets, and in its standard Weir distribution, the cross-interference between wavelets is very significant except for the energy blob corresponding to 4 wavelets; on the flat-virtual weiwei distribution of the composite trace, although the cross interference is completely eliminated, 4 effective energy blobs are obviously spread, so that the resolution of the time spectrum is lowered; finally, the time frequency spectrum generated by the method has the high resolution as that of the standard Weiwei distribution, and meanwhile, the method has the capability of eliminating cross interference as that of the flat-virtual Weiwei distribution.
(2) FIG. 5 is an embodiment of the present invention applied to actual three-dimensional seismic recordings for reservoir prediction. The top plot is a time slice of a three-dimensional seismic data volume. The spectral slice of the middle graph reflects the spatial distribution of the coal measure strata of the region, and the primary frequency of the reflection earthquake of the coal measure strata of the region is 15 Hz. Note that the coal measure stratigraphic space variation of the middle graph has similarities with some parts of the upper graph. The spectral slice of the lower graph is the spatial distribution of the sandstone reservoir in the region, and the reflection seismic main frequency of the sandstone reservoir in the region is 20 Hz. As shown in fig. 5, the method has the advantage of high signal-to-noise ratio, and can clearly separate the spatial distribution of the sandstone reservoir and the spatial distribution of the coal-series stratum when the actual three-dimensional seismic data is used for reservoir prediction.
Claims (3)
1. A method for generating a high-signal-to-noise-ratio high-resolution time spectrum of seismic data is characterized in that the signal-to-noise ratio of the seismic time spectrum is improved by multi-channel weighted synthesis along the dip angle of a stratum by utilizing the spatial continuity of seismic reflection event axes; enhancing the resolution of the frequency spectrum during earthquake by a method of constructing an adaptive mask filter;
the method comprises the following specific steps: (1) estimating dip angles of each time-space position on the seismic section; (2) constructing a plurality of weighted synthesis channels aiming at each time position, and calculating an instantaneous autocorrelation function of an analytic signal of the synthesis channels; (3) calculating standard Wigner-Ville time frequency distributionW(t, f) And its corresponding Ping-Weiwei distributionW SP (t, f) (ii) a (4) Constructing a time-frequency spectrum self-adaptive mask filter; (5) realizing mask filtering of standard Weiwei time-frequency distribution to obtain an optimized seismic channel time-frequency spectrum;
the mask filter in the step (4) is constructed as follows:
the middle ratio ofW SP (t, f)|2 / |W(t, f)|2Is the similarity of the two power spectra,εis an adjustment parameter that controls the position of the mask filter boundary,ηthen it is the parameter that controls the smoothness of the mask filter boundary, settingη≥ 2。
2. The method of claim 1, wherein the mask filter is constructed to have the flattest passband characteristics and the tuning parameters thereofεEffectively controlling the boundary position of the mask filter; setting a boundary smoothness parameterη= 4 regulating parameterεWhen = 0.05, any imaging spectral point with a power spectrum ratio value less than 20% can be filtered out from the time-frequency spectrum.
3. The method for generating the seismic data time spectrum with high signal-to-noise ratio and high resolution according to claim 1, wherein the step (5) is implemented by two steps: distribution of amplitude spectrum of Weiwei time-frequency distributionW(t,f) The l is filtered out and the filter is implemented,
(ii) a The wiry time frequency spectrum is reconstructed,
in the formulaƟ(t, f) The method is an original phase spectrum of Weiwei time-frequency distribution, and finally obtains a seismic channel optimized time-frequency spectrum with high signal-to-noise ratio and high resolution.
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