希尔伯特-黄变换地震信号时频分析与属性提取
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摘要
地震信号属于非线性和非平稳信号,传统的分析方法主要包括短时傅立叶变换、小波变换和Cohen类时频分布等等;希尔伯特-黄变换是分析非平稳信号的新方法,该方法的关键部分是信号的经验模态分解,通过经验模态分解,复杂的信号可以分解为有限的数量很少的几个固有模态函数,从而可以得到信号的希尔伯特时频谱;将该方法应用于单个的地震道数据,可以对地震道进行经验模态分解并得到希尔伯特谱,应用于地震剖面,可以得到意义更加明确的瞬时频率和瞬时振幅等地震属性,模型试算和实际应用表明了该方法的有效性.
Seismic data are nonlinear and nonstationary signals,traditional analysis methods include short-time Fourier transform,wavelet analysis,Cohen's class timefrequency analysis and so on;Hilbert-Huang transform is a new kind of method to analyze nonstationary signals,the key part of the method is the empirical mode decomposition(EMD) method with which any complicated data set can be decomposed into a finite and often small number of intrinsic mode functions(IMFs) that admit well-behaved Hilbert transforms.Use it to a seismic trace,the EMD decomposes trace into several IMFs and instantaneous frequency of the trace are required;Use it to a seismic section,it provides instantaneous frequency and instantaneous phase seismic attributes which are more meaningful than before;Model test and actual application have shown the validity of this method.
Seismic data are nonlinear and nonstationary signals,traditional analysis methods include short-time Fourier transform,wavelet analysis,Cohen's class timefrequency analysis and so on;Hilbert-Huang transform is a new kind of method to analyze nonstationary signals,the key part of the method is the empirical mode decomposition(EMD) method with which any complicated data set can be decomposed into a finite and often small number of intrinsic mode functions(IMFs) that admit well-behaved Hilbert transforms.Use it to a seismic trace,the EMD decomposes trace into several IMFs and instantaneous frequency of the trace are required;Use it to a seismic section,it provides instantaneous frequency and instantaneous phase seismic attributes which are more meaningful than before;Model test and actual application have shown the validity of this method.
引文
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[3]金雷,李月,杨宝俊.用时频峰值滤波方法消减地震勘探资料中随机噪声的初步研究[J].地球物理学进展,2005,20(3):724~728.
[4]李春峰,Liner C.基于小波多尺度分析的奇性指数:一种新地震属性[J].地球物理学报,2005,48(4):882~888.
[5]吕公河,于常青,等.叠后地震属性分析在油气田勘探开发中的应用[J].地球物理学进展,2006,21(1):161~166.
[6]印兴耀,张奎,张广智.联合时频分布及其矩属性的应用[J].石油地球物理勘探,2003,38(5):521~526.
[7]殷文,印兴耀.基于MPI的时频分布的改进及应用[J].地球物理学进展,2005,20(1):165~169.
[8]Taner M,et al.Complex seismic trace analysis[J].Geophys-ics,1979,44(6):1041~1063.
[9]Yin X Y,Wu G C.Application of Wavelet Transform in 3DSeismic Sequence Analysis[A].SEG 1998 Annual Meeting.
[10]Hassan H.Empirical Mode Decomposition(EMD)of poten-tial field data:airborne gravity data as an example[A].SEG/Houston 2005 Annual Meeting,704~706.
[11]Ivan Magrin-Chagnolleauet al.Empirical mode decomposi-tion based time-frequency attributes[A].SEG 1999 AnnualMeeting.
[12]张延玲,杨长春,贾曙光.地震属性技术的研究和应用[J].地球物理学进展,2005,20(4):1129~1133.
[13]闫述,陈明生.瞬变电磁场资料的联合时-频分析解释[J].地球物理学报,2005,48(1):203~208.
[14]陈雨红,杨长春,等.几种时频分析方法比较[J].地球物理学进展,2006,21(4):1180~1185.
[2]刘喜武,刘洪,等.局域波分解及其在地震信号时频分析中的应用[J].地球物理学进展,2007,22(2):365~375.
[3]金雷,李月,杨宝俊.用时频峰值滤波方法消减地震勘探资料中随机噪声的初步研究[J].地球物理学进展,2005,20(3):724~728.
[4]李春峰,Liner C.基于小波多尺度分析的奇性指数:一种新地震属性[J].地球物理学报,2005,48(4):882~888.
[5]吕公河,于常青,等.叠后地震属性分析在油气田勘探开发中的应用[J].地球物理学进展,2006,21(1):161~166.
[6]印兴耀,张奎,张广智.联合时频分布及其矩属性的应用[J].石油地球物理勘探,2003,38(5):521~526.
[7]殷文,印兴耀.基于MPI的时频分布的改进及应用[J].地球物理学进展,2005,20(1):165~169.
[8]Taner M,et al.Complex seismic trace analysis[J].Geophys-ics,1979,44(6):1041~1063.
[9]Yin X Y,Wu G C.Application of Wavelet Transform in 3DSeismic Sequence Analysis[A].SEG 1998 Annual Meeting.
[10]Hassan H.Empirical Mode Decomposition(EMD)of poten-tial field data:airborne gravity data as an example[A].SEG/Houston 2005 Annual Meeting,704~706.
[11]Ivan Magrin-Chagnolleauet al.Empirical mode decomposi-tion based time-frequency attributes[A].SEG 1999 AnnualMeeting.
[12]张延玲,杨长春,贾曙光.地震属性技术的研究和应用[J].地球物理学进展,2005,20(4):1129~1133.
[13]闫述,陈明生.瞬变电磁场资料的联合时-频分析解释[J].地球物理学报,2005,48(1):203~208.
[14]陈雨红,杨长春,等.几种时频分析方法比较[J].地球物理学进展,2006,21(4):1180~1185.
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