摘要
小波变换作为一种具有多分辨率特征的时频分析方法得到了广泛应用,但受不确定性原理影响,其时频分辨率有限。压缩小波变换(synchrosqueezing wavelet transform,SWT)通过对小波变换的复系数谱在尺度方向进行压缩重排,提高了小波变换的分辨率,同时保持了其完整的数学可逆性。合成信号和实际单道记录测试结果表明,压缩小波变换能够更准确地刻画信号的时频特征;实际地震资料时频分析应用试验中,基于压缩小波变换谱分解方法的目标储层油气检测结果与钻井结果吻合,对储层位置的刻画更加准确,低频异常的现象更加明显,能显著降低储层流体检测的多解性。
Although continuous wavelet transform is widely used as a time/frequency analysis method in the field of geophysics because of its multiresolution,the resolution of time/frequency is negatively affected by the Heisenberg uncertainty principle.The synchrosqueezing wavelet transform(SWT)is to squeeze and reconstruct complex coefficient spectra in scale orientation.It enhances the resolution of wavelet transform and preserve its mathematic reversibility.Test results of synthetic signal and the actual single trace record show this method can characterize signal time/frequency with higher accuracy.The application of field seismic data shows that hydrocarbon detection results for target reservoir with synchrosqueezing wavelet transform is consistent with drilling results.It has a more accurate characterization of reservoir location and a more obvious low-frequency anomaly,and even greatly reduces the multisolution of reservoir fluid detection.
引文
[1]Partyka G,Gridley J,Lopez J.Interpretational applications of spectral decomposition in reservoir characterization[J].The Leading Edge,1999,18(3):353-360
[2]Sinha S,Routh P S,Anno P D,et al.Spectral decomposition of seismic data with continuous-wavelet transforms[J].Geophysics,2005,70(6):19-25
[3]Sattar F,Salomonsson G.The use of a filter bank and the Wigner-Ville distribution for time-frequency representation[J].IEEE Transactions on Signal Processing,1999,47(6):1776-1783
[4]Battista B M,Knapp C,McGee T,et al.Application of the empirical mode decomposition and HilbertHuang transform to seismic reflection data[J].Geophysics,2007,72(2):H29-H37
[5]Daubechies I,Lu J,Wu H T.Synchrosqueezed wavelet transforms:an empirical mode decomposition-like tool[J].Applied and Computational Harmonic Analysis,2011,30(2):243-261
[6]Shang S,Han L G,Hu W.Seismic data analysis using synchrosqueezing wavelet transform[J].Expanded Abstracts of 83rd Annual Internat SEG Mtg,2013,4330-4334
[7]Herrera R H,Han J J,van der Baan M.Application of the synchrosqueezing transform in seismic timefrequency analysis[J].Geophysics,2014,79(3):V55-V64
[8]Daubechies I,Maes S.A nonlinear squeezing of the continuous wavelet transform based on auditory nerve models[C]∥Aldroubi A,Unser M.Wavelets in Medicine and Biology.Boca Raton:CRC Press,1996:527-546
[9]Sinha S,Routh P S,Anno P D,et al.Spectral decomposition of seismic data with continuous-wavelet transform[J].Geophysics,2005,70(6):P19-P25