时空域同步挤压小波变换联合面波压制方法

林浩然, 邢磊, 刘怀山, 李倩倩, 张洪茂. 2022. 时空域同步挤压小波变换联合面波压制方法. 地球物理学报, 65(9): 3569-3583, doi: 10.6038/cjg2022P0724
引用本文: 林浩然, 邢磊, 刘怀山, 李倩倩, 张洪茂. 2022. 时空域同步挤压小波变换联合面波压制方法. 地球物理学报, 65(9): 3569-3583, doi: 10.6038/cjg2022P0724
LIN HaoRan, XING Lei, LIU HuaiShan, LI QianQian, ZHANG HongMao. 2022. Ground roll suppression with synchrosqueezing wavelet transform in time-spatial domain. Chinese Journal of Geophysics (in Chinese), 65(9): 3569-3583, doi: 10.6038/cjg2022P0724
Citation: LIN HaoRan, XING Lei, LIU HuaiShan, LI QianQian, ZHANG HongMao. 2022. Ground roll suppression with synchrosqueezing wavelet transform in time-spatial domain. Chinese Journal of Geophysics (in Chinese), 65(9): 3569-3583, doi: 10.6038/cjg2022P0724

时空域同步挤压小波变换联合面波压制方法

  • 基金项目:

    国家自然科学基金(91958206,91858215),山东省重点研发计划项目(2019GHY112019),海底科学与探测技术教育部重点实验室开放课题基金(SGPT-20210F-06)和中央高校基本科研业务费专项(202161013)联合资助

详细信息
    作者简介:

    林浩然, 男, 1998年生, 硕士在读, 主要从事地震资料处理方法研究.E-mail: lincc@stu.ouc.edu.cn

    通讯作者: 邢磊, 男, 1984年生, 副教授, 主要从事海洋地球物理勘探研究.E-mail: xingleiouc@ouc.edu.cn
  • 中图分类号: P631

Ground roll suppression with synchrosqueezing wavelet transform in time-spatial domain

More Information
  • 面波是影响地震资料品质的主要因素之一,压制面波干扰是地震资料处理的重要步骤之一.传统的面波压制方法在时频分辨率以及处理结果的信噪比方面存在固有缺陷,不利于面波能量的压制.本文将同步挤压小波变换推广至一维空间域,并提出了一种使用时域和空域同步挤压小波变换联合压制面波干扰的新方法.该方法首先利用时域同步挤压小波变换分离原始地震记录中的面波,为减少分离过程可能对低频有效信号造成的损伤,将初次分离出的低频数据体进行空域同步挤压小波变换,得到空间波数谱,确定面波区域并对该区域同步挤压小波系数充零,压制面波干扰,提取有效信号,将提取出的有效信号重构结果叠加到已分离面波的地震记录中,实现对面波干扰的联合压制.理论和实际资料处理表明,时域同步挤压小波变换和空域同步挤压小波变换联合方法能在有效压制面波干扰的同时,极大程度减少了对有效信号的损害,提高了地震资料的信噪比.

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  • 图 1 

    四种母小波函数重构误差比较

    Figure 1. 

    Comparison of reconstruction errors of four mother wavelet functions

    图 2 

    四种母小波函数的TSWT时频谱

    Figure 2. 

    The time frequency spectrum of TSWT of four mother wavelet functions

    图 3 

    理论模型合成记录

    Figure 3. 

    Theoretical model synthesis record

    图 4 

    理论模型合成记录第35道的时频谱

    Figure 4. 

    The time frequency spectrum of channel 35 of theoretical model synthesis record

    图 5 

    (a) 经TSWT压制面波后的理论模型记录; (b) TSWT分离出的面波记录; (c) 经SSWT重构出的有效信号; (d) 经联合方法处理所得到的最终记录

    Figure 5. 

    (a) Record of theoretical model after suppressing ground roll by TSWT; (b) Ground roll separated by TSWT; (c) Valid signal reconstructed by SSWT; (d) Final record of theoretical model after suppressing ground roll by combination method

    图 6 

    0.32 s时刻信号空间波数谱对比

    Figure 6. 

    Comparison of spatial wavenumber spectrum of signal at 0.32 s

    图 7 

    理论模型记录各有效频段信噪比对比

    Figure 7. 

    Comparison of signal-to-noise ratio of each valid frequency band recorded by theoretical model

    图 8 

    联合方法面波压制效果对比图

    Figure 8. 

    Comparison of ground roll suppression effects of combined method

    图 9 

    SSWT的输入与输出

    Figure 9. 

    Input and output of SSWT

    图 10 

    时空域同步挤压小波变换切片

    Figure 10. 

    Slices of SSWT and TSWT

    图 11 

    原始单炮记录第30道TSWT时频谱和分离出的低频数据体第320 ms SSWT空间波数谱

    Figure 11. 

    The time frequency spectrum of channel 30 of TSWT and spatial wavenumber spectrum at 320 ms of SSWT of the separated low-frequency data

    图 12 

    3组数据的频谱对比

    Figure 12. 

    Spectrum comparison of three datasets

    图 13 

    野外单炮记录各有效频段信噪比对比

    Figure 13. 

    Comparison of signal-to-noise ratio of each valid frequency band recorded by actualdata

    图 14 

    四种面波压制方法实际资料处理结果对比

    Figure 14. 

    Comparison of actual data processing results of four ground roll suppression methods

    图 15 

    实际记录45 Hz切片

    Figure 15. 

    45 Hz slices of actual record

    表 1 

    地层模型参数

    Table 1. 

    Formation model parameters

    层序 纵波速度/(m·s-1) 横波速度/(m·s-1) 密度/(g·cm-3) 深度/m
    1 1000 600 2 150
    2 1850 800 2 500
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  •  

    Auger F, Flandrin P. 1995. Improving the readability of time-frequency and time-scale representations by the reassignment method. IEEE Transactions on Signal Processing, 43(5): 1068-1089, doi: 10.1109/78.382394.

     

    Bao Q Z, Gao J H, Chen W C. 2007. Ridgelet domain method of ground-roll suppression. Chinese Journal of Geophysics (in Chinese), 50(4): 1210-1215.

     

    Bao Q Z, Li QC, Chen W C, et al. 2010. Continuous wavelet transform and ridgelet transform joint ground-roll attenuation method and its application. Geophysical Prospecting for Petroleum (in Chinese), 50 (4): 367-372, 397.

     

    Bi Y Y, Wang J J, Xu X H, et al. 2017. Ground roll attenuation based on the combination of discrete curvelet transform dictionary and two-dimensional local discrete cosine transform dictionary. Geophysical Prospecting for Petroleum (in Chinese), 56(2): 222-231.

     

    Boashash B. 2003. Time Frequency Analysis: A Comprehensive Reference. Oxford: Elsevier Science, 770.

     

    Candès E J, Donoho D L. 1999. Ridgelets: a key to higher-dimensional intermittency. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 357(1760): 2495-2509, doi: 10.1098/rsta.1999.0444.

     

    Candès E J, Donoho D L. 2004. New tight frames of curvelets and optimal representations of objects with piecewise C2 singularities. Communications on Pure and Applied Mathematics, 57(2): 219-266, doi: 10.1002/cpa.10116.

     

    Chen W C, Gao J H, Bao Z Q. 2009. Adaptive attenuation of ground roll via continuous wavelet transform. Chinese Journal of Geophysics (in Chinese), 52(11): 2854-2861, doi: 10.3969/j.issn.0001-5733.2009.11.020.

     

    Chen Y Y, Zhang J H, Lin C Y, et al. 2021. The method and application of minor strike-slip faults identification about deep and ultra-deep carbonate reservoir based on wavelet transform sensitive frequency. Progress in Geophysics (in Chinese), 36(5): 1941-1947, doi: 10.6038/pg2021EE0393.

     

    Clausel M, Oberlin T, Perrier V. 2015. The monogenic synchrosqueezed wavelet transform: a tool for the decomposition/demodulation of AM-FM images. Applied and Computational Harmonic Analysis, 39(3): 450-486, doi: 10.1016/j.acha.2014.10.003.

     

    Dang J W, Huang J G. 2003. Study on the application of fractal theory to the analysis of the space-series of seismic prospecting signal. Journal of Xi′an Shiyou University(Natural Science Edition) (in Chinese), 18(4): 11-14.

     

    Daubechies I, Maes S. 1996. A nonlinear squeezing of the continuous wavelet transform based on auditory nerve models. //Aldroubi A, Unser M eds. Wavelets in Medicine and Biology. New York: CRC Press, 527-544.

     

    Daubechies I, Lu J F, Wu H T. 2011. Synchrosqueezed wavelet transforms: An empirical mode decomposition-like tool. Applied and Computational Harmonic Analysis, 30(2): 243-261, doi: 10.1016/j.acha.2010.08.002.

     

    Daubechies I, Wang Y, Wu H T. 2016. ConceFT: concentration of frequency and time via a multitapered synchrosqueezed transform. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 374(2065): 20150193, doi: 10.1098/rsta.2015.0193.

     

    Deighan A J, Watts D R. 1997. Ground-roll suppression using the wavelet transform. Geophysics, 62(6): 1896-1903, doi: 10.1190/1.1444290.

     

    Kodera K, DeVilledary C, Gendrin R. 1976. A new method for the numerical analysis of non-stationary signals. Physics of the Earth and Planetary Interiors, 12(2-3): 142-150, doi: 10.1016/0031-9201(76)90044-3.

     

    Li C, Liang M. 2012. A generalized synchrosqueezing transform for enhancing signal time-frequency representation. Signal Processing, 92(9): 2264-2274, doi: 10.1016/j.sigpro.2012.02.019.

     

    Liu H, Zhang J Z, Huang Z L. 2016. Surface wave removal with synchrosqueezing wavelet transform. Oil Geophysical Prospecting (in Chinese), 51(1): 71-79.

     

    Liu W, Cao S Y, Liu Y, et al. 2016. Synchrosqueezing transform and its applications in seismic data analysis. Journal of Seismic Exploration, 25(3): 27-44.

     

    Lu J F, Wirth B, Yang H Z. 2016. Combining 2D synchrosqueezed wave packet transform with optimization for crystal image analysis. Journal of the Mechanics and Physics of Solids, 89: 194-210, doi: 10.1016/j.jmps.2016.01.002.

     

    Lu J F, Yang H Z. 2018. Phase-space sketching for crystal image analysis based on synchrosqueezed transforms. SIAM Journal on Imaging Sciences, 11(3): 1954-1978, doi: 10.1137/17M1129441.

     

    Lu P F, Guo A H, He Y S, et al. 2020. Research on surface wave suppression combined with Curvelet transform and Fourier transform. Progress in Geophysics (in Chinese), 35(6): 2181-2187, doi: 10.6038/pg2020DD046.

     

    Ma J Q, Li Q C. 2011. Joint S transformation and TT transformation method of surface wave suppression. Computing Techniques for Geophysical and Geochemical Exploration (in Chinese), 33(3): 252-257.

     

    Niu C, Zhan Y, Li H F. 2006. The contrast of several methods for the signal/noise ratio estimation of seismic records. Computing Techniques for Geophysical and Geochemical Exploration (in Chinese), 28(1): 5-9.

     

    Oberlin T, Meignen S. 2017. The second-order wavelet synchrosqueezing transform. //2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). New Orleans, LA, USA: IEEE, 3994-3998, doi: 10.1109/ICASSP.2017.7952906.

     

    Stéphane M. 2009. Wavelet Tour of Signal Processing: The Sparse Way. 3rd ed. Amsterdam: Academic Press, 805.

     

    Thakur G, Brevdo E, Fu kar N S, et al. 2013. The Synchrosqueezing algorithm for time-varying spectral analysis: Robustness properties and new paleoclimate applications. Signal Processing, 93(5): 1079-1094, doi: 10.1016/j.sigpro.2012.11.029.

     

    Wang H L. 2007. The research of methods to estimate signal-to-noise ratio of seismic record. [Master′s thesis](in Chinese). Chengdu: Chengdu University of Technology.

     

    Wang W Q, Li Z C, Sun X D, et al. 2022. Current situation and development trend of surface wave suppression technology in seismic processing. Progress in Geophysics (in Chinese), 37(3): 1178-1188, doi: 10.6038/pg2022FF0276.

     

    Xu Y, Luo M Z, Wang Z, et al. 2018. Surface wave suppression using generalized S-transform and 2D discrete wavelet transform. Geophysical Prospecting for Petroleum (in Chinese), 57(3): 395-403.

     

    Yang H Z, Lu J F, Brown W P, et al. 2015. Quantitative canvas weave analysis using 2-D synchrosqueezed transforms: application of time-frequency analysis to art investigation. IEEE Signal Processing Magazine, 32(4): 55-63, doi: 10.1109/MSP.2015.2406882.

     

    Zeng X H, Qiao B P, Liu Y M, et al. 2015. Adaptive Groundroll Attenuation Based on the Wavelet Transform. Acta Scientiarum Naturalium Universitatis Pekinensis (in Chinese), 51(5): 837-842.

     

    Zhu X X, Zhang Z S, Gao J H. 2021. Three-dimension extracting transform. Signal Processing, 179: 107830, doi: 10.1016/j.sigpro.2020.107830.

     

    包乾宗, 高静怀, 陈文超. 2007. 面波压制的Ridgelet域方法. 地球物理学报, 50(4): 1210-1215. doi: 10.3321/j.issn:0001-5733.2007.04.030 http://www.geophy.cn/article/id/cjg_1374

     

    包乾宗, 李庆春, 陈文超等. 2011. 联合连续小波变换和脊波变换的面波衰减方法及应用. 石油物探, 50(4): 367-372, 397. doi: 10.3969/j.issn.1000-1441.2011.04.009

     

    毕云云, 汪金菊, 徐小红等. 2017. 基于离散曲波变换字典和二维局部离散余弦变换字典组合的面波压制. 石油物探, 56(2): 222-231. doi: 10.3969/j.issn.1000-1441.2017.02.009

     

    陈文超, 高静怀, 包乾宗. 2009. 基于连续小波变换的自适应面波压制方法. 地球物理学报, 52(11): 2854-2861, doi: 10.3969/j.issn.0001-5733.2009.11.020. http://www.geophy.cn/article/doi/10.3969/j.issn.0001-5733.2009.11.020

     

    陈永芮, 张军华, 林承焰等. 2021. 一种基于小波优势频带的深层-超深层碳酸盐岩走滑断裂识别方法及应用. 地球物理学进展, 36(5): 1941-1947, doi: 10.6038/pg2021EE0393.

     

    党建武, 黄建国. 2003. 基于分形理论的地震信号空间序列分析. 西安石油学院学报(自然科学版), 18(4): 11-14. doi: 10.3969/j.issn.1673-064X.2003.04.003

     

    刘晗, 张建中, 黄忠来. 2016. 应用同步挤压小波变换去除面波. 石油地球物理勘探, 51(1): 71-79. https://www.cnki.com.cn/Article/CJFDTOTAL-SYDQ201601014.htm

     

    路鹏飞, 郭爱华, 何月顺等. 2020. 曲波变换与傅里叶变换联合压制面波方法研究. 地球物理学进展, 35(6): 2181-2187, doi: 10.6038/pg2020DD0464.

     

    马见青, 李庆春. 2011. S变换和TT变换联合压制地震面波. 物探化探计算技术, 33(3): 252-257. https://www.cnki.com.cn/Article/CJFDTOTAL-WTHT201103006.htm

     

    牛聪, 詹毅, 李辉峰. 2006. 对比地震记录信噪比的几种估算方法. 物探化探计算技术, 28(1): 5-9. doi: 10.3969/j.issn.1001-1749.2006.01.003

     

    王红玲. 2007. 地震记录信噪比估算方法研究[硕士论文]. 成都: 成都理工大学.

     

    王伟奇, 李振春, 孙小东等. 2022. 地震处理领域面波压制技术现状及发展趋势. 地球物理学进展, 37(3): 1178-1188, doi: 10.6038/pg2022FF0276.

     

    徐阳, 罗明璋, 王智等. 2018. 广义S变换与二维离散小波变换联合压制面波. 石油物探, 57(3): 395-403. doi: 10.3969/j.issn.1000-1441.2018.03.009

     

    曾祥堃, 乔宝平, 刘依谋等. 2015. 基于小波变换的自适应面波压制方法. 北京大学学报(自然科学版), 51(5): 837-842. https://www.cnki.com.cn/Article/CJFDTOTAL-BJDZ201505008.htm

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出版历程
收稿日期:  2021-09-28
修回日期:  2022-07-12
上线日期:  2022-09-10

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