基于S变换的地震信号相干噪声压制研究
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摘要
地震勘探采集到的地震信号中往往包含大量的相干噪声,这些相干噪声严重的妨碍了科研工作者进行正确的地震解释,对这些噪声进行压制已经十分必要。面波和线性干扰这两种主要相干噪声已经引起了人们的高度关注,本文将这两种噪声作为主要的研究对象,相应的研究了不同的压制算法。
本文开篇对地震信号中的噪声和常用的噪声压制方法进行了简单介绍。第二章对经典时频分析方法和S变换时频分析方法进行了介绍。首先介绍时频分析的研究现状;然后通过理论分析和实验仿真完成了经典时频分析的介绍；最后仍然是从理论和实验的角度对S变换进行了详细的介绍,并且通过与经典时频分析对比说明了S变换时频分析的优越之处。
第三章进行S变换在一维地震信号面波压制中的研究。介绍了基于S变换的一维地震信号面波压制算法,该算法通过设计时频滤波器来完成面波压制。在理论模型和实际地震信号上,通过对比傅里叶变换和一维小波变换,证明该算法面波压制的更干净,有效信号保留的更好。
第四章进行S变换在地震记录面波压制中的研究。首先,在研究面波的频率特性和时空分布特征基础上,介绍了基于S变换的地震记录面波压制算法,该算法通过对每道地震信号自动进行S域时频滤波完成面波压制。然后,在理论模型上,对比F-K滤波、小波变换,验证了该算法面波压制更加干净,有效信号保留更好,另外,通过改变面波能量强度并使用信噪比作为评价标准,验证了该算法有广泛的适用性。最后,在实际地震记录上进行对比,并且经过处理效果的频谱分析和频率-波数谱分析,证明该算法面波压制的更加彻底,有效信号连续性保持的更好,有效信号也得到增强。
第五章进行S变换在地震记录线性干扰压制中的研究。介绍了结合自动追踪的S变换算法,该算法通过自动追踪,小窗口区域划定和相关性判断,找到线性干扰存在区域,然后,对该区域使用S变换完成线性干扰压制。在实际地震记录上,通过与MP方法、F-K滤波对比,验证了该算法线性干扰压制更加彻底,不会产生波形畸变的好处。最后,针对线性干扰中存在微弱线性干扰的情况,引入了结合自动追踪的S变换改进算法,该算法通过s域内滤波处理来完成线性干扰压制。在实际地震记录上,通过对比仿真,验证了该算法对于强、弱线性干扰均有较好的压制效果。
The seismic signal of seismic exploration acquisition always contains a lot of coherent noise, which seriously hampers the researchers'work for correct seismic interpretation. Thus it's necessary to suppress these noises. The two primary coherent noise, Surface wave and linear interference, have aroused people's concern. The paper takes these two noises as main research object, and researching on corresponding different algorithms for these noises'suppression.
The paper begins with the introduction of the noises in seismic signals and commonly used methods for noise suppression. In chapter two, classical time-frequency analysis and S transform time-frequency analysis are introduced. This chapter first introduces the research status of time-frequency analysis; then completes classical time-frequency analysis introduced by theoretical analysis and experimental simulation; finally introduces S transform through theoretical analysis and experimental simulation. In this chapter, we explain the advantages of S transform by contrasting with classical time-frequency analysis. It offers support for suppression of surface wave and linear interference.
The third chapter mainly researches on suppression of surface wave in one-dimensional seismic signal. This chapter proposes an algorithm based on S transform to suppress surface wave in one-dimensional seismic signal, by designing time-frequency filter. In the end, comparing with Fourier transform and wavelet transform for surface wave suppression in the theoretical model and real seismic signal, this chapter proves that this algorithm can suppress surface wave cleaner and reserve more effective signal.
The fourth chapter researches on suppression of surface wave in seismic records. This chapter proposes an algorithm based on S transform to suppress surface wave in seismic records, considering the low frequency characteristic and space-time distribution features of surface wave. Comparing with F-K method and wavelet transform of surface wave suppression in theoretical model, this chapter proves that this algorithm can suppress surface wave cleaner and reserve more effective signal. In addition, we show its wide applicability with signal-to-noise ratio as evaluation in theoretical model which has different surface wave energy intensity. In the end, Comparing with F-K method and wavelet transform of surface wave suppression in real seismic records, this chapter proves that this algorithm can suppress surface wave cleaner and reserve more effective signal, and through the analysis of spectrum and frequency-wave number diagram, we obtain a same conclusion.
The fifth chapter mainly researches on suppression of linear interference in seismic records. This chapter proposes an algorithm, which combines automatic tracking and S transform. Combined with automatic tracking, a small window, correlation and S transform, this algorithm can complete linear interference suppression. Comparing with MP (matching pursuit algorithm) method and FK filtering method, it verifies that this algorithm can suppress linear interference more thoroughly without waveform distortion phenomenon. The last section proposes an improved algorithm in order to remove the weak linear interference. This algorithm completes suppression of linear interference through filtering in S domain. It is based on the first algorithm. Comparing with MP method and F-K filtering method, it verifies that this algorithm can suppress strong and weak linear interference.
本文开篇对地震信号中的噪声和常用的噪声压制方法进行了简单介绍。第二章对经典时频分析方法和S变换时频分析方法进行了介绍。首先介绍时频分析的研究现状;然后通过理论分析和实验仿真完成了经典时频分析的介绍；最后仍然是从理论和实验的角度对S变换进行了详细的介绍,并且通过与经典时频分析对比说明了S变换时频分析的优越之处。
第三章进行S变换在一维地震信号面波压制中的研究。介绍了基于S变换的一维地震信号面波压制算法,该算法通过设计时频滤波器来完成面波压制。在理论模型和实际地震信号上,通过对比傅里叶变换和一维小波变换,证明该算法面波压制的更干净,有效信号保留的更好。
第四章进行S变换在地震记录面波压制中的研究。首先,在研究面波的频率特性和时空分布特征基础上,介绍了基于S变换的地震记录面波压制算法,该算法通过对每道地震信号自动进行S域时频滤波完成面波压制。然后,在理论模型上,对比F-K滤波、小波变换,验证了该算法面波压制更加干净,有效信号保留更好,另外,通过改变面波能量强度并使用信噪比作为评价标准,验证了该算法有广泛的适用性。最后,在实际地震记录上进行对比,并且经过处理效果的频谱分析和频率-波数谱分析,证明该算法面波压制的更加彻底,有效信号连续性保持的更好,有效信号也得到增强。
第五章进行S变换在地震记录线性干扰压制中的研究。介绍了结合自动追踪的S变换算法,该算法通过自动追踪,小窗口区域划定和相关性判断,找到线性干扰存在区域,然后,对该区域使用S变换完成线性干扰压制。在实际地震记录上,通过与MP方法、F-K滤波对比,验证了该算法线性干扰压制更加彻底,不会产生波形畸变的好处。最后,针对线性干扰中存在微弱线性干扰的情况,引入了结合自动追踪的S变换改进算法,该算法通过s域内滤波处理来完成线性干扰压制。在实际地震记录上,通过对比仿真,验证了该算法对于强、弱线性干扰均有较好的压制效果。
The seismic signal of seismic exploration acquisition always contains a lot of coherent noise, which seriously hampers the researchers'work for correct seismic interpretation. Thus it's necessary to suppress these noises. The two primary coherent noise, Surface wave and linear interference, have aroused people's concern. The paper takes these two noises as main research object, and researching on corresponding different algorithms for these noises'suppression.
The paper begins with the introduction of the noises in seismic signals and commonly used methods for noise suppression. In chapter two, classical time-frequency analysis and S transform time-frequency analysis are introduced. This chapter first introduces the research status of time-frequency analysis; then completes classical time-frequency analysis introduced by theoretical analysis and experimental simulation; finally introduces S transform through theoretical analysis and experimental simulation. In this chapter, we explain the advantages of S transform by contrasting with classical time-frequency analysis. It offers support for suppression of surface wave and linear interference.
The third chapter mainly researches on suppression of surface wave in one-dimensional seismic signal. This chapter proposes an algorithm based on S transform to suppress surface wave in one-dimensional seismic signal, by designing time-frequency filter. In the end, comparing with Fourier transform and wavelet transform for surface wave suppression in the theoretical model and real seismic signal, this chapter proves that this algorithm can suppress surface wave cleaner and reserve more effective signal.
The fourth chapter researches on suppression of surface wave in seismic records. This chapter proposes an algorithm based on S transform to suppress surface wave in seismic records, considering the low frequency characteristic and space-time distribution features of surface wave. Comparing with F-K method and wavelet transform of surface wave suppression in theoretical model, this chapter proves that this algorithm can suppress surface wave cleaner and reserve more effective signal. In addition, we show its wide applicability with signal-to-noise ratio as evaluation in theoretical model which has different surface wave energy intensity. In the end, Comparing with F-K method and wavelet transform of surface wave suppression in real seismic records, this chapter proves that this algorithm can suppress surface wave cleaner and reserve more effective signal, and through the analysis of spectrum and frequency-wave number diagram, we obtain a same conclusion.
The fifth chapter mainly researches on suppression of linear interference in seismic records. This chapter proposes an algorithm, which combines automatic tracking and S transform. Combined with automatic tracking, a small window, correlation and S transform, this algorithm can complete linear interference suppression. Comparing with MP (matching pursuit algorithm) method and FK filtering method, it verifies that this algorithm can suppress linear interference more thoroughly without waveform distortion phenomenon. The last section proposes an improved algorithm in order to remove the weak linear interference. This algorithm completes suppression of linear interference through filtering in S domain. It is based on the first algorithm. Comparing with MP method and F-K filtering method, it verifies that this algorithm can suppress strong and weak linear interference.
引文
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[10]刘丽娟.时频分析技术及应用[D].成都理工大学硕士学位论文,2008.
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[2]姚姚.地震波场与地震勘探[M].北京：地质出版社,2006.
[3]Stockwell R G. A basis for efficient representation of the S-transform[J]. Digital Signal Processing,2007,17(1):371-393.
[4]何樵登.地震波理论[M].吉林大学出版社,2005.
[5]牟永光.地震数据处理方法[M].北京：石油工业出版社,2007.
[6]詹毅.地震资料叠前去噪方法研究[D].成都理工大学学位论文,2005.
[7]王纯伟.MP算法在地震信号去噪中的应用研究[D].西南交通大学硕士学位论文,2010.
[8]黄立军.浅谈地震信号中的噪声及去除方法[J].内蒙古石油化工,2008,4：31-33.
[9]付燕.人工地震信号去噪方法研究[D].西北工业大学博士学位论文,2002.
[10]刘丽娟.时频分析技术及应用[D].成都理工大学硕士学位论文,2008.
[11]Gabor D. Theory of communication[J]. Journal of the IEEE.1946,93: 429-497.
[12]Cohen L. Generalized Phase-Space Distribution Functions[J]. Journal Of Mathematical Physics,1966,7:781-786.
[13]秦前清,杨宗凯.实用小波分析[M].西安：西安电子科技大学出版社,1998.
[14]Morlet J, Arens G, Fourgeau E, Giard D. Wave progagation and sampling theory-Part Ⅰ:Complex signal and scattering in multilayered media[J]. Geophysics,1982,47:203-221.
[15]Morlet J, Arens G, Fourgeau E, Giard D. Wave progagation and sampling theory-Part Ⅱ:Sampling theory and complex waves[J]. Geophysics,1982, 47(2):222-236.
[16]Stockwell R G, Mansinha L, Lowe R P. Localization of the complex spectrum: the S-transform[J]. IEEE Transactions on Signal Processing,1996,44(4): 998-1001.
[17]Portnoff MR. Time-Frequency Representation of Digital Signals and Systems Based on Short-Time Fourier Analysis[J]. IEEE Transactions on Acoustics, Speech, and Signal Processing,1980, ASSP-28(1).
[18]陈学华.时频分布与地震信号谱分析研究[D].成都理工大学学位论文,2006.
[19]Wigner E. On the quantum correction for thermodynamic equilibrium[J]. Physical Review,1932,40:749-759.
[20]Ville. Theorie et applications de la notion de signal analytique[J].Cables et Transmission,2,1948.
[21]Wilson R, Calway A D, Pearson E R S. A Generalized Wavelet Transform for Fourier analysis:the multiresolution fourier transform and its application to image and audio signal analysis[J]. IEEE Trans. Info. Theory,1992,38: 674-690.
[22]Janssen A. Optimality Property of the Gaussian Window. IEEE Transactions on Acoustics[J]. Speech and Signal Processing,1991, ASSP-39(1).
[23]Brigham E O. The fast fourier transform[J]. Prentics-Hall Inc,1974.
[24]Stockwell R G. S-Transform Analysis of Gravity Wave Activity from a Small Scale Network of Airglow Imagers[D]. The University of Western Ontario, 1999.
[25]Farge M. Wavelet transforms and their application to turbulence[J]. Annual Review of Fluid Mechanics,1992,24:395-457.
[26]尹陈.地震波衰减与流体预测研究[D].成都理工大学硕士学位论文,2008.
[27]马见青,李庆春,樊金生,王美丁.基于S变换的瑞雷面波频散分析[J].地球科学与环境学报,2010,32(3)：320-323.
[28]张玉亮.地震波频率衰减特性及能量增强方法研究[D].中国石油大学(华东),2009.
[29]李媛媛.小波变换去除面波的方法研究[D].长安大学硕士学位论文,2004.
[30]赵馨.地震数据处理中叠前去噪应用研究[D].中国地质大学(北京)硕士学位论文,2008.
[31]李卫忠,张明震,王成礼,马在田,王华忠.压制面波的波场分离方法[J].石油地球物理勘探,1998,33(5)：680-690.
[32]万雪娟.非理想条件下地震面波的性质及压制方法研究[D].中国石油大学硕士学位论文,2009.
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