弱反射地震信号特征及识别方法理论研究
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摘要
现代地震勘探中,弱反射地震信号是不可回避的。本文分别从厚层和薄层中弱信号幅值特征的角度,研究了弱信号的频谱特征及噪声对弱信号的影响程度,并运用信号奇异值分解方法(SVD)和曲波变换方法,对弱信号的检测和识别进行了初步探讨。结果表明:①当信噪比为0.5时,用肉眼无法识别出弱信号;②当信噪比为2时,可以识别出对应薄层调谐厚度;③计算包含在相邻强反射信号中弱信号的频谱,无法反映弱信号的特征;④应用SVD可以检测混杂在噪声中的水平层弱信号,应用曲波变换可以从中检测出非水平层弱信号。
Seismic weak signal is a real big challenge for seismic explorations.Based on amplitude characteristics of seismic weak signal in thick and thin layers,this paper analyzes the spectrum characteristics of seismic weak signal as well as the influence of noise on it.In addition,we conduct preliminary discussions about the detection and identification of weak signal using the singular value decomposition(SVD) and curvelet transform.The results indicate that: 1.It is basically impossible to detect weak signal by visual recognition when S/N<0.5;2.For thin reservoirs,the tuning thickness could be identified if the S/N is 2;3.The spectrum of the weak signal involved in the adjacent strong reflection cannot show its characteristic;4.Horizontal weak events mixed with noise can be effectively detected by the SVD method while non-horizontal weak events mixed with noise can be detected by curvelet transform.
Seismic weak signal is a real big challenge for seismic explorations.Based on amplitude characteristics of seismic weak signal in thick and thin layers,this paper analyzes the spectrum characteristics of seismic weak signal as well as the influence of noise on it.In addition,we conduct preliminary discussions about the detection and identification of weak signal using the singular value decomposition(SVD) and curvelet transform.The results indicate that: 1.It is basically impossible to detect weak signal by visual recognition when S/N<0.5;2.For thin reservoirs,the tuning thickness could be identified if the S/N is 2;3.The spectrum of the weak signal involved in the adjacent strong reflection cannot show its characteristic;4.Horizontal weak events mixed with noise can be effectively detected by the SVD method while non-horizontal weak events mixed with noise can be detected by curvelet transform.
引文
[1]马宁,陈莉,王晓军等.小波变换在弱信号检测中的应用.哈尔滨工业大学学报,2009,41(3):257~258Ma Ning,Chen Li,Wang Xiao-jun et a1.Application ofwavelet transformin weak signal monitoring.Journalof Harbin Institute of Technology,2009,41(3):257~258
[2]曾刚,侯祥博.应用小波变换和双谱方法实现弱信号检测.数字信号处理,2009,33(6):60~62
[3]詹毅,周熙襄.小波包分析与奇异值分解(SVD)叠前去噪方法.石油地球物理勘探,2004,39(4):394~397Zhan Yi,Zhou Xi-xiang.Analysis of wavelet packageand prestack noise suppressed methodin singular valuedecomposition(SVD).OGP,2004,39(4):394~397
[4]郭小龙.基于混沌理论的弱信号检测方法研究.江苏:江苏科技大学出版社,2007
[5]徐晓刚,徐冠雷,王孝通等.经验模式分解(EMD)及其应用.电子学报,2009,37(3):581~585Xu Xiao-gang,Xu Guan-lei,Wang Xiao-tong et al.Em-pirical mode decomposition and its application.ActaElectronica Sinica,2009,37(3):581~585
[6]吕文彪,尹成,张白林等.利用独立分量分析法去除地震噪声.石油地球物理勘探,2007,42(2):132~139LWen-biao,Yin Cheng,Zhang Bai-lin et a1.Usingin-dependent component analysis to eli minate seismic noi-ses.OGP,2007,42(2):132~139
[7]陈遵德,段天友,朱广生.SVD滤波方法的改进及应用.石油地球物理勘探,1994,29(6):783~792Chen Zun-de,Duan Tian-you,Zhu Guang-sheng.I m-provement of singular-value decompositionfiltering andthe application.OGP,1994,29(6):783~792
[8]陆文凯,李衍达.SVD分解法提高地震资料的信噪比和分辨率.石油地球物理勘探,1998,33(增刊1):145~149
[2]曾刚,侯祥博.应用小波变换和双谱方法实现弱信号检测.数字信号处理,2009,33(6):60~62
[3]詹毅,周熙襄.小波包分析与奇异值分解(SVD)叠前去噪方法.石油地球物理勘探,2004,39(4):394~397Zhan Yi,Zhou Xi-xiang.Analysis of wavelet packageand prestack noise suppressed methodin singular valuedecomposition(SVD).OGP,2004,39(4):394~397
[4]郭小龙.基于混沌理论的弱信号检测方法研究.江苏:江苏科技大学出版社,2007
[5]徐晓刚,徐冠雷,王孝通等.经验模式分解(EMD)及其应用.电子学报,2009,37(3):581~585Xu Xiao-gang,Xu Guan-lei,Wang Xiao-tong et al.Em-pirical mode decomposition and its application.ActaElectronica Sinica,2009,37(3):581~585
[6]吕文彪,尹成,张白林等.利用独立分量分析法去除地震噪声.石油地球物理勘探,2007,42(2):132~139LWen-biao,Yin Cheng,Zhang Bai-lin et a1.Usingin-dependent component analysis to eli minate seismic noi-ses.OGP,2007,42(2):132~139
[7]陈遵德,段天友,朱广生.SVD滤波方法的改进及应用.石油地球物理勘探,1994,29(6):783~792Chen Zun-de,Duan Tian-you,Zhu Guang-sheng.I m-provement of singular-value decompositionfiltering andthe application.OGP,1994,29(6):783~792
[8]陆文凯,李衍达.SVD分解法提高地震资料的信噪比和分辨率.石油地球物理勘探,1998,33(增刊1):145~149
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