基于时频滤波的吸收衰减参数估算
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摘要
对地层的吸收衰减估计所面临的一个重要问题是估计的分辨率较低。利用叠后地震反射资料,在尽可能短的时窗内有效地估计衰减是一个具有挑战性的课题。基于Margrave提出的地震记录的非平稳褶积模型,本文提出将时频滤波算子作用于反褶积后的地震记录,得到衰减作用后的反射系数,再行估计吸收衰减,可有效地提高衰减估计的分辨率。该方法不同于目前已知的估计方法,理论上能在小于子波波长的时窗内进行吸收衰减估计。
For seismic attenuation estimation,a key point is to improve the estimation resolution.It is a challenge to estimate attenuation as accurately as possible within a time-window as short as possible.Margrave(1998) proposed a nonstationary-convolution model for a time varying seismic record,which might be an effective way for attenuation estimation.In this paper,a method for seismic attenuation estimation is proposed.First operators of time frequency filtering are applied to a deconvolved seismic trace to obtain a reflectivity after attenuation.Then the attenuation estimation based on the reflectivity is performed.Completely different from the other methods,this method can obtain an attenuation estimation within a short time-window.This window can be shorter than the length of the time-window than the wavelength of the wavelet.
For seismic attenuation estimation,a key point is to improve the estimation resolution.It is a challenge to estimate attenuation as accurately as possible within a time-window as short as possible.Margrave(1998) proposed a nonstationary-convolution model for a time varying seismic record,which might be an effective way for attenuation estimation.In this paper,a method for seismic attenuation estimation is proposed.First operators of time frequency filtering are applied to a deconvolved seismic trace to obtain a reflectivity after attenuation.Then the attenuation estimation based on the reflectivity is performed.Completely different from the other methods,this method can obtain an attenuation estimation within a short time-window.This window can be shorter than the length of the time-window than the wavelength of the wavelet.
引文
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[2]Reine C,Baan M V,Clark R.The robustness of seis-mic attenuation measurements using fixed and varia-ble-window time-frequency transforms.Geophysics,2009,74(2):WA123～WA135
[3]Hale D.Q and adaptive prediction error filters.Stanford Exploration Project Report,1981,28:209～231
[4]Hale D.Q-adaptive deconvolution.Stanford Explo-ration Project Report,1982,30:133～158
[5]Margrave G F.Theory of nonstationary linear filte-ring in the Fourier domain with application to time-variant filtering.Geophysics,1998,63(1):244～259
[6]Margravea G F,Gibsonc P C,Grossmana J et al.TheGabor transform,pseudo differential operators,andseismic deconvolution.Integrated Computer-AidedEngineering,2005,12:43～55
[7]Kjartansson E.Constant Q wave propagation and at-tenuation.Journal of Geophysical Research,1979,84(9):4737～4748
[8]Kolsky H.The propagation of stress pulses in viscoe-lastic solids.Philosophical Magazine,1956,1:693～710
[9]Futterman W I.Dispersive body waves.Journal ofGeophysical Research,1962,67:5279～5291
[10]Robinson J C.A technique for continuous representa-tion of dispersion on seismic data.Geophysics,1979,44(8):1245～1351
[11]Grossman J P,Margrave G F,Lamoureux M P et al.Constant-Q wavelet estimation via a nonstationaryGabor spectral model.CREWES Research Report,2001,13:223～240
[12]Varela C L,Rosa A L R,Ulrych T J.Modeling of at-tenuation and dispersion.Geophysics,1993,58(8):1167～1173
[13]Margrave G F,Lamoureux M P.Gabor deconvolu-tion.CREWES Research Report,2001,13:242～276
[14]Nadarajaha S,Kotz S.Skewed distributions generatedby the normal kernel.Statistics&Probability Let-ters,2003,65:268～277
[15]Umbach D.Some moment relationships for skew-symmetric distributions.Statistics&ProbabilityLetters,2006,76:507～512
[16]Nadarajah S,Kotz S.Skew ModelsⅠ.Acta ApplMath,2007,98:1～28
[17]Nadarajah S,Kotz S.Skew ModelsⅡ.Acta ApplMath,2007,98:29～46
[18]Ramsay J O,Silverman B W.Functional Data Anal-ysis.Springer Science+Business Media Inc,2005
[2]Reine C,Baan M V,Clark R.The robustness of seis-mic attenuation measurements using fixed and varia-ble-window time-frequency transforms.Geophysics,2009,74(2):WA123～WA135
[3]Hale D.Q and adaptive prediction error filters.Stanford Exploration Project Report,1981,28:209～231
[4]Hale D.Q-adaptive deconvolution.Stanford Explo-ration Project Report,1982,30:133～158
[5]Margrave G F.Theory of nonstationary linear filte-ring in the Fourier domain with application to time-variant filtering.Geophysics,1998,63(1):244～259
[6]Margravea G F,Gibsonc P C,Grossmana J et al.TheGabor transform,pseudo differential operators,andseismic deconvolution.Integrated Computer-AidedEngineering,2005,12:43～55
[7]Kjartansson E.Constant Q wave propagation and at-tenuation.Journal of Geophysical Research,1979,84(9):4737～4748
[8]Kolsky H.The propagation of stress pulses in viscoe-lastic solids.Philosophical Magazine,1956,1:693～710
[9]Futterman W I.Dispersive body waves.Journal ofGeophysical Research,1962,67:5279～5291
[10]Robinson J C.A technique for continuous representa-tion of dispersion on seismic data.Geophysics,1979,44(8):1245～1351
[11]Grossman J P,Margrave G F,Lamoureux M P et al.Constant-Q wavelet estimation via a nonstationaryGabor spectral model.CREWES Research Report,2001,13:223～240
[12]Varela C L,Rosa A L R,Ulrych T J.Modeling of at-tenuation and dispersion.Geophysics,1993,58(8):1167～1173
[13]Margrave G F,Lamoureux M P.Gabor deconvolu-tion.CREWES Research Report,2001,13:242～276
[14]Nadarajaha S,Kotz S.Skewed distributions generatedby the normal kernel.Statistics&Probability Let-ters,2003,65:268～277
[15]Umbach D.Some moment relationships for skew-symmetric distributions.Statistics&ProbabilityLetters,2006,76:507～512
[16]Nadarajah S,Kotz S.Skew ModelsⅠ.Acta ApplMath,2007,98:1～28
[17]Nadarajah S,Kotz S.Skew ModelsⅡ.Acta ApplMath,2007,98:29～46
[18]Ramsay J O,Silverman B W.Functional Data Anal-ysis.Springer Science+Business Media Inc,2005
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