地震信号匹配处理方法研究
|
摘要
地震信号的匹配技术越来越受到人们的广泛重视,不管是地震数据的拼接成像还是时移地震数据处理,不同时间的地震数据匹配已成波形一致性处理的为核心技术。本文从信号的匹配滤波原理出发,从时间域和频率域分析了地震子波和地震数据的主要特征,研究了最小平方、相关等匹配准则,推导地震信号的匹配算法。以楔形模型和模拟数据为例,对频率域匹配滤波和小波域匹配滤波进行了对比。以单道记录和楔形模型为例,进行频谱分析,分析了在不同震源情况下产生不同子波对匹配滤波的效果,得出小波域的匹配滤波有很好的效果。利用小波分频特性,可以在匹配滤波的同时去除随机噪声,这是其他匹配滤波很难达到的效果。
With the advances in seismic exploration, use different sources to match the filter so that the amplitude and phase of the data line, or in different times and comparative analysis of seismic data. Paper to simulate different focal positions generated in the same seismic data filtering, it can be seismic data analysis and processing, can be a very good analysis of seismic attributes, such as the relationship between geological structure, a series of hydrocarbon key issues. In order to achieve the effectiveness of how the removal of different sources of this type, different surface conditions, different construction age of various objective factors such as construction parameters caused by differences in seismic data, has become the key to solve this problem.
This article will develop a mature combination of wavelet transform and matched filtering, focus on the matched filter based on wavelet transform in seismic data in different data source and application of different times. Especially for the matching portion of the seismic data are discussed in detail and compared with the Wiener filtering, highlighting the wavelet domain filtering, greatly improved signal to noise ratio. Matched filtering in wavelet domain has been largely improved, not only to improve the utilization of the data, but also improves the removal of random noise in the data. Not only matched filtering to achieve the best results in the match, but also to the original data signal to noise ratio has improved a lot. With random noise on seismic convolution model for the effective simulation experiments show that the method is effective.
Fourier transform is an important basis for seismic exploration, this wavelet-based maturity based on the theory of wavelet sub-band features. Matched filtering technology, the prospects are very broad. This according to the advantages of both the two together effectively, using their properties to solve some practical problems.
In this paper, based on previous years through the effectiveness of the method on the matched filter method for effective comparison and interpretation, use LS algorithm to solve the wavelet matched filtering problem, this paper, seismic modeling data to verify the advantages of wavelet transform matched filtering to the Fourier transform matched filtering, so that theoretically shows the matched filter based on wavelet transform has better precision. In addition, this paper, the seismic data as a research point of random noise, some features of wavelet Fourier change is unattainable, especially in wavelet decomposition and reconstruction, that is, frequency characteristics. This characteristic of wavelet matched filtering of wavelet domain stochastic noise in the process of removing the same time reaching the matched filtering can also be a large degree of increased noise ratio. This is the time domain and frequency domain matched filter matched filtering are unable to effect. Finally, the use of wavelet matched filter with a random noise signal and noise to match the reference Road, obtained wavelet matched filter can effectively remove the random noise. And other fx deconvolution, denoising compared to the removal of noise is greatly improved.
With the advances in seismic exploration, use different sources to match the filter so that the amplitude and phase of the data line, or in different times and comparative analysis of seismic data. Paper to simulate different focal positions generated in the same seismic data filtering, it can be seismic data analysis and processing, can be a very good analysis of seismic attributes, such as the relationship between geological structure, a series of hydrocarbon key issues. In order to achieve the effectiveness of how the removal of different sources of this type, different surface conditions, different construction age of various objective factors such as construction parameters caused by differences in seismic data, has become the key to solve this problem.
This article will develop a mature combination of wavelet transform and matched filtering, focus on the matched filter based on wavelet transform in seismic data in different data source and application of different times. Especially for the matching portion of the seismic data are discussed in detail and compared with the Wiener filtering, highlighting the wavelet domain filtering, greatly improved signal to noise ratio. Matched filtering in wavelet domain has been largely improved, not only to improve the utilization of the data, but also improves the removal of random noise in the data. Not only matched filtering to achieve the best results in the match, but also to the original data signal to noise ratio has improved a lot. With random noise on seismic convolution model for the effective simulation experiments show that the method is effective.
Fourier transform is an important basis for seismic exploration, this wavelet-based maturity based on the theory of wavelet sub-band features. Matched filtering technology, the prospects are very broad. This according to the advantages of both the two together effectively, using their properties to solve some practical problems.
In this paper, based on previous years through the effectiveness of the method on the matched filter method for effective comparison and interpretation, use LS algorithm to solve the wavelet matched filtering problem, this paper, seismic modeling data to verify the advantages of wavelet transform matched filtering to the Fourier transform matched filtering, so that theoretically shows the matched filter based on wavelet transform has better precision. In addition, this paper, the seismic data as a research point of random noise, some features of wavelet Fourier change is unattainable, especially in wavelet decomposition and reconstruction, that is, frequency characteristics. This characteristic of wavelet matched filtering of wavelet domain stochastic noise in the process of removing the same time reaching the matched filtering can also be a large degree of increased noise ratio. This is the time domain and frequency domain matched filter matched filtering are unable to effect. Finally, the use of wavelet matched filter with a random noise signal and noise to match the reference Road, obtained wavelet matched filter can effectively remove the random noise. And other fx deconvolution, denoising compared to the removal of noise is greatly improved.
引文
[1]韩国庆,穆龙新,姜建平.委内瑞拉奥里诺科重油带J区块新老二维地震资料精细匹配处理及构造特征分析[J],地球物理学进展2009, 24(1): 238-245.
[2]葛瑞麟.印尼BINJAI地区资料处理中的一致性问题[J].勘探地球物理进展, 2006,29(3): 206-210.
[3]何玉梅,杨玉江,葛勇,等.精细匹配处理技术及其在惠州凹陷二维地震老资料处理中的应用[J].中国海上油气, 2006,18(4): 247-250.
[4]云美厚,丁伟,王开燕,等.地震资料一致性处理方法研究与初步应用[J].石油物探, 2006,45(1): 65-69.
[5]赵建章,张进铎,赖江德,等.海南特殊地理环境下的地震资料处理技术研究[J].勘探地球物理进展, 2008,31(6): 201-205.
[6]宋玉龙.滩浅海地区地震勘探存在问题及其解决方法[J].石油物探, 2005,44(4): 343-347.
[7]林必荣,李培基,陈繁勤.三维地震资料的区块拼接方法及效果[J].石油地球物理勘探, 1995,30(S1): 156-159.
[8]刘成斋.胜利油田三维地震数据连片处理[J].石油地球物理勘探, 2004,39(5): 579-585.
[9]段云卿.匹配滤波与子波整形[J].石油地球物理勘探, 2006,41(2): 156-159.
[10]高少武,赵波,贺振华.可控震源与炸药震源地震数据匹配.中国地球物理年会,2008.中国北京.
[11]赵明秋,牛建国.连接不同震源数据的匹配滤波技术[J].石油地球物理勘探, 2007,42(S1): 136-140.
[12]王西文,周立宏.三维地震资料拼接中的地震子波处理[J].石油物探, 2002,41(4): 448-451.
[13]娄兵,郑鸿明,蒋立.地震测线的拼接技术[J].新疆石油地质, 2001,22(3): 208-210.
[14]邬达理,郑伟建,金晓雷,等.复杂三维地震联片处理技术及其应用实例分析[J].石油物探, 2001,41(1): 9-19.
[15]程金星,朱立华,杨长春,等.基于小波变换的三维地震资料拼接方法[J].石油地球物理勘探, 2004,39(4): 406-408.
[16]王西文,周立宏.三维地震资料拼接中的地震子波处理[J].石油物探, 2002,41 (4): 448- 451.
[17]王元波.三维地震处理连片拼接技术[J].大庆石油地质与开发, 2001,20(3): 67-68.
[18] Weiner N., et al. Extrapolation,Interpolation and Smoothing of Stationany Time Series[M]. Technology Press of The Massachusetts Institute of Technology. 1947: Cambridge.
[19] Gray R.M. On the asymptotic eigenvalue distribution of Toeplitz matrices[J]. IEEE Transactions on Information Theory, 1972, 18: 725-730.
[20] Y.W.Lee. Statistical Theory of Communication,John Wiley and Sons[M]. New York: 1960.
[21]黄绪德.反褶积与地震道反演[M].北京:石油工业出版社, 1992年11月: 313.
[22] Levison N. A huristic exposition of Wiener's mathematical theory of prediction and filtering.[J]. Math.Phys, 1947, 25: 110—119.
[23] Robinson E.A. Predictive decomposition of seismic traces[J]. Geophysics, 1957, 22(4): 767-778.
[24] Schneider W.A., K.L. Larner, J.P. Burg, et al. A new data-processing technique for elimination of ghost arrivals on reflection seismograms[J]. Geophysics, 1964, 29(5): 783-805.
[25] Schneider W.A., E.R. Prince, et al. A new data-processing technique for multiple attenuations exploiting differential normal moveout[J]. Geophysics, 1965, 30: 348-362.
[26] D'Hoeraene J. Foltrage spatio temporel descourbures [J]. Geophys.Prosp., 1966, 14: 27-44.
[27] Wiggins R.A.,E.A. Robinson. Recursive solution of the multichannel filtering problem[J]. Geophysics 1965, 70(8): 1885-1891.
[28] Laster S.J.,A.F. Linville. Application of multichannel filtering to the separation of dispersive modes of progation[J]. Geoph . Res, 1966, 71: 1669-1701.
[29] Treitel S. Principles of Digital Multichannel Filtering [J]. Geophysics, 1970,35(5): 785-811.
[30] Berhout A.J. Least-squares inverse filtering and wavelet deconvolution[J]. Geophysics, 1977, 42(7): 1369-1383.
[31] Maeschall R. Derivation of two-sided recursive filters with seismic application [C]. 48th SEG meeting,San Francisco, 1978(USA, Preprint, Prakla- Seismos, Hannover).
[32] Brotzr R. Maschall,M. Knecht. Signal adjustment of vibroseis and impulsive source data[J]. Geophsical Prospecting, 1987, 35(7): 739-766.
[33] Wallace R.,F.D. Gray. Network Match Filters:A Least-squares Technique for Minmizing[J]. Geophysics, 1992: 1112-1115.
[34]唐恩德,宋锡熊,陈志刚.多种震源联合激发地震数据的处理方法[J].石油地球物理勘探, 1997,32(S1): 148-156.
[35]庄东海,肖春燕,许云,等.四维地震资料处理及其关键[J].地球物理学进展, 1999,14(2): 33-43.
[36]邓怀群,刘雯林,杨春梅,等.时间推移地震勘探中的互均化技术[J].天然气工业, 2000,20(1): 20-23.
[37]陈志卿.匹配滤波技术在临邑三维成果资料处理中的应用[J].油气地质与采收率, 2002,9(6): 10-12.
[38]陈茂根,龚定康,徐新南.东海多块三维地震数据体拼接技术综述[J].海洋石油, 2003,23(3): 36-43.
[39]张仲祜,蒋琳,张林红.地震资料三维联片拼接处理技术[J].新疆石油天然气, 2005,1(3): 38-43.
[40]邬达理,姜游,陈竹梅.串联匹配滤波法在混合震源资料处理中的应用[J].石油物探, 2006,45(6): 611-614.
[41]徐翠娥,龚定康,杨新菊.匹配滤波法在涠西井场调查资料处理中的应用[J].海洋石油, 2006,26(4): 7-12.
[42]陈志卿,张兰.子波一致性校正方法在地震资料处理中的应用——以伊朗Kashan区块为例[J].石油物探, 2006,45(2): 169-172.
[43]李景叶,陈小宏,芮振华.基于匹配滤波的多次波压制方法研究[J].地球物理学进展, 2007,22(1): 200-206.
[44]李鹏,刘伊克,常旭,等.均衡拟多道匹配滤波法在波动方程法压制多次波中的应用[J].地球物理学报, 2007,50(6): 1844-1853.
[45]郭树祥.埕岛桩海地区连片地震资料的数据规则化处理[J].石油物探, 2008,47(4): 387-392.
[46]陈斌,王晓红,张晶.连片波形一致性处理技术研究[J].复杂油气藏, 2009,2(3): 29-32.
[47]张永刚等.两步法统计子波反褶积[J],物探科技通报.1988, (6).
[48]苏贵士,周兴元.改进的子波统计反褶积[J].石油地球物理勘探. 1997, 32(3) :399- 403.
[49]凌云,周熙襄.可控震源自适应地表一致性反褶积[J].石油地球物理勘探, 1994,29(3): 306-315.
[50]周兴元.常相位校正[J].石油地球物理勘探, 1989,24(2): 119-129.
[51]程乾生.信号数字处理的数学原理[M].北京:石油工业出版社, 1993.
[52]牟永光.地震勘探资料数字处理方法[M].北京:石油工业出版社, 1981年11月.
[53] Makhoul J. On the eigenvector of symmetric Toeplitz atrices[J]. IEEE Trans.on Acoustics, Speech and Signal Proc. 1981, 28:868-872.
[54] Danielsen V.,T.V. Karlsson. Extraction of signatures from seismic and well data[J]. First Break, 1984, 2(4): 15-21.
[55]巴特M.地球物理学中的谱分析[M].地震出版社, 1978.
[56] M N.H. Developments in the use of wavelet in communications. In: Proc Milcom'98[C]. 1998: 343-349.
[57] Kelly K.R., W.R. W.,S. Treitel. Synthetic seismograms:A finite-difference approach[J]. Geophysics, 1976, 41(1): 2-27.
[58] Zu-bin C.,L. Jun. Design for vibrator field experiment based on vibrator-earth system[J]. Journal of Geoscientific Research in Northest Asia, 2000, 3(1): 107-113.
[2]葛瑞麟.印尼BINJAI地区资料处理中的一致性问题[J].勘探地球物理进展, 2006,29(3): 206-210.
[3]何玉梅,杨玉江,葛勇,等.精细匹配处理技术及其在惠州凹陷二维地震老资料处理中的应用[J].中国海上油气, 2006,18(4): 247-250.
[4]云美厚,丁伟,王开燕,等.地震资料一致性处理方法研究与初步应用[J].石油物探, 2006,45(1): 65-69.
[5]赵建章,张进铎,赖江德,等.海南特殊地理环境下的地震资料处理技术研究[J].勘探地球物理进展, 2008,31(6): 201-205.
[6]宋玉龙.滩浅海地区地震勘探存在问题及其解决方法[J].石油物探, 2005,44(4): 343-347.
[7]林必荣,李培基,陈繁勤.三维地震资料的区块拼接方法及效果[J].石油地球物理勘探, 1995,30(S1): 156-159.
[8]刘成斋.胜利油田三维地震数据连片处理[J].石油地球物理勘探, 2004,39(5): 579-585.
[9]段云卿.匹配滤波与子波整形[J].石油地球物理勘探, 2006,41(2): 156-159.
[10]高少武,赵波,贺振华.可控震源与炸药震源地震数据匹配.中国地球物理年会,2008.中国北京.
[11]赵明秋,牛建国.连接不同震源数据的匹配滤波技术[J].石油地球物理勘探, 2007,42(S1): 136-140.
[12]王西文,周立宏.三维地震资料拼接中的地震子波处理[J].石油物探, 2002,41(4): 448-451.
[13]娄兵,郑鸿明,蒋立.地震测线的拼接技术[J].新疆石油地质, 2001,22(3): 208-210.
[14]邬达理,郑伟建,金晓雷,等.复杂三维地震联片处理技术及其应用实例分析[J].石油物探, 2001,41(1): 9-19.
[15]程金星,朱立华,杨长春,等.基于小波变换的三维地震资料拼接方法[J].石油地球物理勘探, 2004,39(4): 406-408.
[16]王西文,周立宏.三维地震资料拼接中的地震子波处理[J].石油物探, 2002,41 (4): 448- 451.
[17]王元波.三维地震处理连片拼接技术[J].大庆石油地质与开发, 2001,20(3): 67-68.
[18] Weiner N., et al. Extrapolation,Interpolation and Smoothing of Stationany Time Series[M]. Technology Press of The Massachusetts Institute of Technology. 1947: Cambridge.
[19] Gray R.M. On the asymptotic eigenvalue distribution of Toeplitz matrices[J]. IEEE Transactions on Information Theory, 1972, 18: 725-730.
[20] Y.W.Lee. Statistical Theory of Communication,John Wiley and Sons[M]. New York: 1960.
[21]黄绪德.反褶积与地震道反演[M].北京:石油工业出版社, 1992年11月: 313.
[22] Levison N. A huristic exposition of Wiener's mathematical theory of prediction and filtering.[J]. Math.Phys, 1947, 25: 110—119.
[23] Robinson E.A. Predictive decomposition of seismic traces[J]. Geophysics, 1957, 22(4): 767-778.
[24] Schneider W.A., K.L. Larner, J.P. Burg, et al. A new data-processing technique for elimination of ghost arrivals on reflection seismograms[J]. Geophysics, 1964, 29(5): 783-805.
[25] Schneider W.A., E.R. Prince, et al. A new data-processing technique for multiple attenuations exploiting differential normal moveout[J]. Geophysics, 1965, 30: 348-362.
[26] D'Hoeraene J. Foltrage spatio temporel descourbures [J]. Geophys.Prosp., 1966, 14: 27-44.
[27] Wiggins R.A.,E.A. Robinson. Recursive solution of the multichannel filtering problem[J]. Geophysics 1965, 70(8): 1885-1891.
[28] Laster S.J.,A.F. Linville. Application of multichannel filtering to the separation of dispersive modes of progation[J]. Geoph . Res, 1966, 71: 1669-1701.
[29] Treitel S. Principles of Digital Multichannel Filtering [J]. Geophysics, 1970,35(5): 785-811.
[30] Berhout A.J. Least-squares inverse filtering and wavelet deconvolution[J]. Geophysics, 1977, 42(7): 1369-1383.
[31] Maeschall R. Derivation of two-sided recursive filters with seismic application [C]. 48th SEG meeting,San Francisco, 1978(USA, Preprint, Prakla- Seismos, Hannover).
[32] Brotzr R. Maschall,M. Knecht. Signal adjustment of vibroseis and impulsive source data[J]. Geophsical Prospecting, 1987, 35(7): 739-766.
[33] Wallace R.,F.D. Gray. Network Match Filters:A Least-squares Technique for Minmizing[J]. Geophysics, 1992: 1112-1115.
[34]唐恩德,宋锡熊,陈志刚.多种震源联合激发地震数据的处理方法[J].石油地球物理勘探, 1997,32(S1): 148-156.
[35]庄东海,肖春燕,许云,等.四维地震资料处理及其关键[J].地球物理学进展, 1999,14(2): 33-43.
[36]邓怀群,刘雯林,杨春梅,等.时间推移地震勘探中的互均化技术[J].天然气工业, 2000,20(1): 20-23.
[37]陈志卿.匹配滤波技术在临邑三维成果资料处理中的应用[J].油气地质与采收率, 2002,9(6): 10-12.
[38]陈茂根,龚定康,徐新南.东海多块三维地震数据体拼接技术综述[J].海洋石油, 2003,23(3): 36-43.
[39]张仲祜,蒋琳,张林红.地震资料三维联片拼接处理技术[J].新疆石油天然气, 2005,1(3): 38-43.
[40]邬达理,姜游,陈竹梅.串联匹配滤波法在混合震源资料处理中的应用[J].石油物探, 2006,45(6): 611-614.
[41]徐翠娥,龚定康,杨新菊.匹配滤波法在涠西井场调查资料处理中的应用[J].海洋石油, 2006,26(4): 7-12.
[42]陈志卿,张兰.子波一致性校正方法在地震资料处理中的应用——以伊朗Kashan区块为例[J].石油物探, 2006,45(2): 169-172.
[43]李景叶,陈小宏,芮振华.基于匹配滤波的多次波压制方法研究[J].地球物理学进展, 2007,22(1): 200-206.
[44]李鹏,刘伊克,常旭,等.均衡拟多道匹配滤波法在波动方程法压制多次波中的应用[J].地球物理学报, 2007,50(6): 1844-1853.
[45]郭树祥.埕岛桩海地区连片地震资料的数据规则化处理[J].石油物探, 2008,47(4): 387-392.
[46]陈斌,王晓红,张晶.连片波形一致性处理技术研究[J].复杂油气藏, 2009,2(3): 29-32.
[47]张永刚等.两步法统计子波反褶积[J],物探科技通报.1988, (6).
[48]苏贵士,周兴元.改进的子波统计反褶积[J].石油地球物理勘探. 1997, 32(3) :399- 403.
[49]凌云,周熙襄.可控震源自适应地表一致性反褶积[J].石油地球物理勘探, 1994,29(3): 306-315.
[50]周兴元.常相位校正[J].石油地球物理勘探, 1989,24(2): 119-129.
[51]程乾生.信号数字处理的数学原理[M].北京:石油工业出版社, 1993.
[52]牟永光.地震勘探资料数字处理方法[M].北京:石油工业出版社, 1981年11月.
[53] Makhoul J. On the eigenvector of symmetric Toeplitz atrices[J]. IEEE Trans.on Acoustics, Speech and Signal Proc. 1981, 28:868-872.
[54] Danielsen V.,T.V. Karlsson. Extraction of signatures from seismic and well data[J]. First Break, 1984, 2(4): 15-21.
[55]巴特M.地球物理学中的谱分析[M].地震出版社, 1978.
[56] M N.H. Developments in the use of wavelet in communications. In: Proc Milcom'98[C]. 1998: 343-349.
[57] Kelly K.R., W.R. W.,S. Treitel. Synthetic seismograms:A finite-difference approach[J]. Geophysics, 1976, 41(1): 2-27.
[58] Zu-bin C.,L. Jun. Design for vibrator field experiment based on vibrator-earth system[J]. Journal of Geoscientific Research in Northest Asia, 2000, 3(1): 107-113.