地震信号的时频分析及其在苏里格气田薄储层识别中的应用
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摘要
本文介绍地震信号的时频分析方法及其在苏里格气田薄储层识别中的应用。论文的主要内容包括有:
(1)介绍了短时傅立叶变换、小波变换、Wigner-Ville变换等几种常用的时频分析方法,讨论了Wigner-Ville变换中交叉项的干扰问题及其抑制方法。
(2)通过模型仿真、实际信号分析应用等对上述几种时频分析方法的分辨率及应用条件进行了对比研究工作,认为平滑伪Wigner-Ville变换拥有最好的时频分辨率,同时实现了对交叉项干扰的压制。
(3)介绍了Hilbert变换和Hilbert-Huang变换的基本原理,并通过实验分析对比了两种方法在提取瞬时频率时的效果,认为Hilbert变换所要求的信号必须是窄带的或者是平稳的。对于非平稳的或是含有噪声的信号,Hilbert变换求取的瞬时频率就有可能出现负值,因此用Hilbert变换对非平稳的地震信号求取的瞬时频率无实际意义;而Hilbert-Huang变换先通过经验模态分解将信号分解成若干个基本模式分量,再进行Hilbert变换,从而赋予了瞬时频率实际的意义。
(4)苏里格气田是我国发现的储量最大的天然气田,构造相对简单但河道砂岩储层薄且横向变化快,在地震记录上识别困难。对苏里格气田某区块的二维地震数据进行平滑伪Wigner-Ville分布、Hilbert-Huang变换时频分析,以井资料为标定,分析研究了地震时频分析方法识别该气田薄储层的能力。实验结果表明平滑伪Wigner-Ville分布能识别厚约10m的砂岩储层,Hilbert-Huang变换能识别10~20m的砂岩储层。
This thesis introduces time-frequency analysis of seismic signal and its application to thin reservoir identification in the Su Lige Gas Field. The main content of the thesis are as follow:
1. General time-frequency analysis methods are introduced, including short-time Fourier transformation, wavelet transformation, Wigner-Ville distribution; and the disturb terms and suppression methods in Wigner-Ville distribution are discussed.
2. It gets the result that the smooth pseudo Wigner-Ville distribution has the best time-frequency resolution and eliminate the disturb terms by comparing these methods.
3.The basic theory of Hilbert transformation and Hilbert-Huang transformation are introduced; and comparing two methods in extracting instantaneous frequency gets the result that if signal is non-stationary or contains noise, instantaneous frequency may be negative and lose the practical significance in Hilbert transformation; but instantaneous frequency has the practical significance in Hilbert-Huang transformation, as signal is decomposed several Intrinsic Mode Function by empirical mode decomposition firstly, then in Hilbert transformation.
4. Su Lige Gas Field is the largest reserves of natural gas fields in china. The characteristic is relatively simple structure but thin sandstone reservoirs and fast variation in horizontal so that it is difficult to be identified in seismic records. The Use of smooth pseudo Wigner-Ville distribution and Hilbert-Huang transformation analyzed 2-D seismic data of one block in Su Lige Gas Field. According as well data, the study on th??solution of seismic time-frequency analysis identify thin reservoir. The result shows that smooth pseudo Wigner-Ville distribution can identify about 10m sandstone reservoir; Hilbert-Huang transformation can identify 10~20m sand bodies.
(1)介绍了短时傅立叶变换、小波变换、Wigner-Ville变换等几种常用的时频分析方法,讨论了Wigner-Ville变换中交叉项的干扰问题及其抑制方法。
(2)通过模型仿真、实际信号分析应用等对上述几种时频分析方法的分辨率及应用条件进行了对比研究工作,认为平滑伪Wigner-Ville变换拥有最好的时频分辨率,同时实现了对交叉项干扰的压制。
(3)介绍了Hilbert变换和Hilbert-Huang变换的基本原理,并通过实验分析对比了两种方法在提取瞬时频率时的效果,认为Hilbert变换所要求的信号必须是窄带的或者是平稳的。对于非平稳的或是含有噪声的信号,Hilbert变换求取的瞬时频率就有可能出现负值,因此用Hilbert变换对非平稳的地震信号求取的瞬时频率无实际意义;而Hilbert-Huang变换先通过经验模态分解将信号分解成若干个基本模式分量,再进行Hilbert变换,从而赋予了瞬时频率实际的意义。
(4)苏里格气田是我国发现的储量最大的天然气田,构造相对简单但河道砂岩储层薄且横向变化快,在地震记录上识别困难。对苏里格气田某区块的二维地震数据进行平滑伪Wigner-Ville分布、Hilbert-Huang变换时频分析,以井资料为标定,分析研究了地震时频分析方法识别该气田薄储层的能力。实验结果表明平滑伪Wigner-Ville分布能识别厚约10m的砂岩储层,Hilbert-Huang变换能识别10~20m的砂岩储层。
This thesis introduces time-frequency analysis of seismic signal and its application to thin reservoir identification in the Su Lige Gas Field. The main content of the thesis are as follow:
1. General time-frequency analysis methods are introduced, including short-time Fourier transformation, wavelet transformation, Wigner-Ville distribution; and the disturb terms and suppression methods in Wigner-Ville distribution are discussed.
2. It gets the result that the smooth pseudo Wigner-Ville distribution has the best time-frequency resolution and eliminate the disturb terms by comparing these methods.
3.The basic theory of Hilbert transformation and Hilbert-Huang transformation are introduced; and comparing two methods in extracting instantaneous frequency gets the result that if signal is non-stationary or contains noise, instantaneous frequency may be negative and lose the practical significance in Hilbert transformation; but instantaneous frequency has the practical significance in Hilbert-Huang transformation, as signal is decomposed several Intrinsic Mode Function by empirical mode decomposition firstly, then in Hilbert transformation.
4. Su Lige Gas Field is the largest reserves of natural gas fields in china. The characteristic is relatively simple structure but thin sandstone reservoirs and fast variation in horizontal so that it is difficult to be identified in seismic records. The Use of smooth pseudo Wigner-Ville distribution and Hilbert-Huang transformation analyzed 2-D seismic data of one block in Su Lige Gas Field. According as well data, the study on th??solution of seismic time-frequency analysis identify thin reservoir. The result shows that smooth pseudo Wigner-Ville distribution can identify about 10m sandstone reservoir; Hilbert-Huang transformation can identify 10~20m sand bodies.
引文
[1]陆基孟.地震勘探原理(第二版)[M].东营:石油大学出版社,1993.
[2]刘震.储层地震地层学[M].北京:地质出版社,1997:182~186
[3]张贤达,保铮.非平稳信号分析与处理[M].北京:国防工业出版社,1998
[4]薛大力,徐明杰,龚姚进,白明轩.地震分频解释技术在沈143井区储层预测中的应用[J].大庆石油地质与开发,2007,26(3):128~131
[5]刘喜武,刘洪,李幼铭,年静波.基于广义S变换研究地震地层特征[J].地球物理学进展,2006,21(2):440~451
[6]刘喜武,年静波,刘洪.基于广义S变换的地震波能量衰减分析[J].勘探地球物理进展,2006,29(1):20~24.
[7]刘葵,刘招军,朱建伟等.时频分析在石油地球物理勘探中的应用[J].世界地质,2000,19(3):282~284.
[8] GREG PARTYKA.谱分解在储层表征中的应用[J].石油物探译丛.2000(6):66-73.
[9]周开明,刘贤红,查树贵,陈德刚,刘其军.几种时频分析技术的性能研究j及在河道砂体预测中的应用[J].天然气工业(增刊A, 2007(27)):453~451
[10] Gabor D. Theory of communication[J].Journal of IEEE,1946,93:488-497
[11] Ville J.Theorie et Transmissions,1948,2A:61-74
[12] Cohen L. Generalized phase-space distribution functions [J]. Jour Math phys, 1966, 7:781-786.
[13] Morlet J, Arens G, Fourgeau E, Giard D. Wave propagation and sampling theory-Part I: complex signal and scattering in multilayered media[J].Geophysics,1982,47:203-221
[14] Morlet J, Arens G, Fourgeau E, Giard D. Wave propagation and sampling theory-Part II: complex signal and scattering in multilayered media[J].Geophysics,1982,47:222-236
[15]刘企英.利用地震信息进行油气预测[M].北京:石油工业出版社,1994.
[16]高静怀.小波变换与信号瞬时特征分析[J].地球物理学报.1997,40(6):821-832
[17]王彦春.神经网络及其在石油物探中的应用[D].??垦宦畚腯.成都:成都理工学院,1994.
[18] Huang N E, Zheng Shen, Long S R, et al. The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analyze [J]. Proc R Soc Lond, 1998, 454: 903-995.
[19] Hlawatsch F, G F Boudreaux - Bartels. Linear and quadratic time-frequency signal representations[J ] .IEEE Signal Processing , 1992 ,9 (2) : 21～67.
[20]胡广书.现代信号处理教程[M].北京:清华大学出版社.2004
[21]葛哲学,陈仲生.Matlab时频分析技术及其应用[M].北京:人民邮电出版社.2006
[22]飞思科技产品研发中心.小波分析理论与Matlab7实现[M].北京:电子工业出版社.2006
[23]陈斌.时频分析及在地震分析中的应用研究[学位论文][D].四川成都,成都理工大学硕士论文.2006
[24] Gabor, D. Theory of communication [J].Journal of the Institute of Electrical Engineers, 1946(93):429~457
[25] Tanner M T, Koehler F, Sheriff R E .Complex trace analysis [J]. Geophysics, 1979, 44:1041~1063
[26] Robertson J D et al. Complex seismic trace analysis of thin beds [J]. Geophysics, 1984(49):344~352
[27] Barnes A E. Theory of 2-D complex seismic trace analysis beds [J]. Geophysics, 1984(49):264~272
[28]徐伯勋,白旭滨,于常青.地震勘探信息技术提取、分析和预测[A],地质出版社2001.
[29]何正嘉,訾艳阳,张西宁.现代信号处理及工程应用[M].西安交通大学出版社.2007
[30]张贤达,保铮.非平稳信号分析与处理[M].国防工业出版社.2001
[31] Barnes, A. E. When the concepts of spectral frequency and instantaneous frequency converge, The leading Edge, 1993a,12,1020-1023
[32] Huang N E, Wu M C, Long S R, et al. A confidence limit for the empirical mode decomposition and Hilbert spectral analysis [J]. Proceedings of the Royal Society of London, 2003(459): 2317-2345.
[33]田建章,吴耀辉.廊固凹陷万庄构造薄砂层储层预测[J].石油地球物理勘探.2006,41(2):177~182
[34]叶泰然,苏锦义,刘兴艳.分频解释技术在川西砂岩储层预测中的应用[j].石油物探.2008,47(1):73~76
[35] Brown, A.R, Interpretation of three-dimensional seismic data[J],Fourth Edition, AAPG Memoir 42
[36]刘书强,蒋志兵,肖高杰.频谱成像技术的开发和应用[J].吐哈油气.2006,11(3):278~281
[37]牛聪,张益明.频谱成像技术在储层厚度预测中的应用[J].石油物探.2008,47(5):494~497
[38]崔凤林,管叶君.时频分析——薄互层结构研究的新途径[J].石油物探.1992,31(2):1~15
[39]石颖,刘洪.地震信号的复地震道分析及应用[J].地球物理学进展.2008,23(5):1538~1543
[40]钟佑明,秦树人,汤宝平.Hilbert-Huang变换中的理论研究.震动与冲击[J],2002,21(4):13~17
[41] Norden E. Huang, Shen Z, Long S R, et al. The empirical mode decomposition. Proc.R.Sco.??,1998,454:903~995
[42]杨培杰,印兴耀,张广智.希尔伯特-黄变换地震信号时频分析与属性提取.地球物理学进展[J].2007,22(5):1585~1590
[43]皮红梅,刘财,王典.利用Hilbert-Huang变换提取地震信号瞬时参数[J].石油地球物理勘探[J].2007,42(4):418~424.
[44]高静怀,陈凤,陈树民.利用地震瞬时谱属性进行薄互层分析[J].煤田地质与勘探.2005,33(3):67~70
[2]刘震.储层地震地层学[M].北京:地质出版社,1997:182~186
[3]张贤达,保铮.非平稳信号分析与处理[M].北京:国防工业出版社,1998
[4]薛大力,徐明杰,龚姚进,白明轩.地震分频解释技术在沈143井区储层预测中的应用[J].大庆石油地质与开发,2007,26(3):128~131
[5]刘喜武,刘洪,李幼铭,年静波.基于广义S变换研究地震地层特征[J].地球物理学进展,2006,21(2):440~451
[6]刘喜武,年静波,刘洪.基于广义S变换的地震波能量衰减分析[J].勘探地球物理进展,2006,29(1):20~24.
[7]刘葵,刘招军,朱建伟等.时频分析在石油地球物理勘探中的应用[J].世界地质,2000,19(3):282~284.
[8] GREG PARTYKA.谱分解在储层表征中的应用[J].石油物探译丛.2000(6):66-73.
[9]周开明,刘贤红,查树贵,陈德刚,刘其军.几种时频分析技术的性能研究j及在河道砂体预测中的应用[J].天然气工业(增刊A, 2007(27)):453~451
[10] Gabor D. Theory of communication[J].Journal of IEEE,1946,93:488-497
[11] Ville J.Theorie et Transmissions,1948,2A:61-74
[12] Cohen L. Generalized phase-space distribution functions [J]. Jour Math phys, 1966, 7:781-786.
[13] Morlet J, Arens G, Fourgeau E, Giard D. Wave propagation and sampling theory-Part I: complex signal and scattering in multilayered media[J].Geophysics,1982,47:203-221
[14] Morlet J, Arens G, Fourgeau E, Giard D. Wave propagation and sampling theory-Part II: complex signal and scattering in multilayered media[J].Geophysics,1982,47:222-236
[15]刘企英.利用地震信息进行油气预测[M].北京:石油工业出版社,1994.
[16]高静怀.小波变换与信号瞬时特征分析[J].地球物理学报.1997,40(6):821-832
[17]王彦春.神经网络及其在石油物探中的应用[D].??垦宦畚腯.成都:成都理工学院,1994.
[18] Huang N E, Zheng Shen, Long S R, et al. The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analyze [J]. Proc R Soc Lond, 1998, 454: 903-995.
[19] Hlawatsch F, G F Boudreaux - Bartels. Linear and quadratic time-frequency signal representations[J ] .IEEE Signal Processing , 1992 ,9 (2) : 21～67.
[20]胡广书.现代信号处理教程[M].北京:清华大学出版社.2004
[21]葛哲学,陈仲生.Matlab时频分析技术及其应用[M].北京:人民邮电出版社.2006
[22]飞思科技产品研发中心.小波分析理论与Matlab7实现[M].北京:电子工业出版社.2006
[23]陈斌.时频分析及在地震分析中的应用研究[学位论文][D].四川成都,成都理工大学硕士论文.2006
[24] Gabor, D. Theory of communication [J].Journal of the Institute of Electrical Engineers, 1946(93):429~457
[25] Tanner M T, Koehler F, Sheriff R E .Complex trace analysis [J]. Geophysics, 1979, 44:1041~1063
[26] Robertson J D et al. Complex seismic trace analysis of thin beds [J]. Geophysics, 1984(49):344~352
[27] Barnes A E. Theory of 2-D complex seismic trace analysis beds [J]. Geophysics, 1984(49):264~272
[28]徐伯勋,白旭滨,于常青.地震勘探信息技术提取、分析和预测[A],地质出版社2001.
[29]何正嘉,訾艳阳,张西宁.现代信号处理及工程应用[M].西安交通大学出版社.2007
[30]张贤达,保铮.非平稳信号分析与处理[M].国防工业出版社.2001
[31] Barnes, A. E. When the concepts of spectral frequency and instantaneous frequency converge, The leading Edge, 1993a,12,1020-1023
[32] Huang N E, Wu M C, Long S R, et al. A confidence limit for the empirical mode decomposition and Hilbert spectral analysis [J]. Proceedings of the Royal Society of London, 2003(459): 2317-2345.
[33]田建章,吴耀辉.廊固凹陷万庄构造薄砂层储层预测[J].石油地球物理勘探.2006,41(2):177~182
[34]叶泰然,苏锦义,刘兴艳.分频解释技术在川西砂岩储层预测中的应用[j].石油物探.2008,47(1):73~76
[35] Brown, A.R, Interpretation of three-dimensional seismic data[J],Fourth Edition, AAPG Memoir 42
[36]刘书强,蒋志兵,肖高杰.频谱成像技术的开发和应用[J].吐哈油气.2006,11(3):278~281
[37]牛聪,张益明.频谱成像技术在储层厚度预测中的应用[J].石油物探.2008,47(5):494~497
[38]崔凤林,管叶君.时频分析——薄互层结构研究的新途径[J].石油物探.1992,31(2):1~15
[39]石颖,刘洪.地震信号的复地震道分析及应用[J].地球物理学进展.2008,23(5):1538~1543
[40]钟佑明,秦树人,汤宝平.Hilbert-Huang变换中的理论研究.震动与冲击[J],2002,21(4):13~17
[41] Norden E. Huang, Shen Z, Long S R, et al. The empirical mode decomposition. Proc.R.Sco.??,1998,454:903~995
[42]杨培杰,印兴耀,张广智.希尔伯特-黄变换地震信号时频分析与属性提取.地球物理学进展[J].2007,22(5):1585~1590
[43]皮红梅,刘财,王典.利用Hilbert-Huang变换提取地震信号瞬时参数[J].石油地球物理勘探[J].2007,42(4):418~424.
[44]高静怀,陈凤,陈树民.利用地震瞬时谱属性进行薄互层分析[J].煤田地质与勘探.2005,33(3):67~70