基于f-x EMD波场分离的绕射多次波压制方法

doi:10.13278/j.cnki.jjuese.20200111

摘要/Abstract

摘要： 自由表面多次波压制（SRME）方法是海洋地震数据处理中的关键步骤。当存在崎岖海底条件时，绕射波十分发育，常规SRME算法很难将复杂绕射多次波有效消除。对压制效果较差的多次波进行成因分析，首先基于f-x EMD波场分离算法，将全数据分解为反射部分和绕射部分，再对其进行多次波预测，获得绕射预测多次波子集：反射-绕射预测多次波、绕射-反射预测多次波和绕射-绕射预测多次波。然后，改进常规SRME算法的迭代过程，在SRME的迭代过程中使用与原数据中多次波更加匹配的绕射多次波子集进行多次波压制。与常规SRME算法的对比结果表明，改进的SRME算法在理论数据和实际数据处理中对多次波的压制都取得更好的效果。

关键词: 自由表面多次波压制, f-x EMD波场分离, 反射-绕射预测多次波, 绕射-反射预测多次波, 绕射-绕射预测多次波

Abstract: Surface-related multiple elimination (SRME) is a key step in marine seismic data processing. However, under rough seabed conditions, diffractions are well developed,and the conventional SRME can hardly eliminate complex diffracted multiples. To analyze the causes of multiples with poor suppression effect, firstly we proposed wavefield separation based on f-x EMD to separate the whole data into a reflection part and a diffraction part, so that the multiple prediction can be carried out with these different subsets of the input data, and then the new subsets of predicted multiples can be obtained as reflected-diffracted predicted multiples, diffracted-reflected predicted multiples, and diffracted-diffracted predicted multiples. Further, we modified the interactive process of the conventional SRME by using the better matched diffracted multiple subsets to eliminate multiples. Compared with the conventional SRME, our improved SRME achieved better multiple attenuation results in both synthetic data and field data.

Key words: surface-related multiple elimination, f-x EMD wavefield separation, reflected-diffracted predicted multiples, diffracted-reflected predicted multiples, diffracted-diffracted predicted multiples

中图分类号:

P631.4

王睿, 王德利, 胡斌, 王铁兴, 王通, 崔亚龙. 基于f-x EMD波场分离的绕射多次波压制方法[J]. 吉林大学学报(地球科学版), 2021, 51(2): 597-606.

Wang Rui, Wang Deli, Hu Bin, Wang Tiexing, Wang Tong, Cui Yalong. Diffracted Multiple Elimination Based on f-x EMD Wavefield Separation[J]. Journal of Jilin University(Earth Science Edition), 2021, 51(2): 597-606.

参考文献

[1] Verschuur D J. Surface-Related Multiple Elimination:An Inversion Approach[D]. Delft:Delft University of Technology, 1991.
[2] Verschuur D J, Berkhout A J, Wapenaar C P A. Adaptive Surface-Related Multiple Elimination[J]. Geophysics, 1992, 57(9):1166-1177.
[3] Verschuur D J, Kabir M M N. Comparison of Surface-Related Multiple Elimination with Radon Multiple Elimination[J]. Journal of Seismic Exploration, 1992(1):363-377.
[4] Berkhout A J, Verschuur D J. Estimation of Multiple Scattering by Iterative Inversion:Part I:Theoretical Considerations[J]. Geophysics, 1997, 62(5):1586-1595.
[5] Verschuur D J. Estimation of Multiple Scattering by Iterative Inversion, Part Ⅱ:Practical Aspects and Examples[J]. Geophysics, 1997, 62(5):1596-1611.
[6] Herrmann F J. Curvelet-Domain Multiple Elimination with Sparseness Constraints[J]. Annual International Meeting Seg Expanded Abstracts, 2004, 12(1):13-33.
[7] van Groenestijn G J A, Verschuur D J. Estimation of Primaries and Near-Offset Reconstruction by Sparse Inversion:Marine Data Applications[J]. Geophysics, 2009, 74(6):119-128.
[8] Lopez G A,Verschuur D J. Closed-Loop Surface-Related Multiple Elimination and Its Application to Simultaneous Data Reconstruction[J]. Geophysics, 2015, 80(6):189-199.
[9] van Dedem E J. 3D Surface-Related Multiple Prediction[D]. Deltf:Delft University of Technology, 2002.
[10] van Dedem E J, Verschuur D J. Analysis of Surface-Related Multiples in a 3-D Media[C]//Society of Exploration Geophysicists 67th Annual International Meeting.[S.l.]:Society of Exploration Geophysicists, 1997:1180-1183.
[11] van Dedem E J, Verschuur D J. 3D Surface-Related Multiple Prediction:An Inversion Approach[C]//SEG Technical Program Expanded Abstracts 2000.[S. l.]:Society of Exploration Geophysicists, 2000:1965-1968.
[12] van Dedem E J, Verschuur D J. 3D Surface-Related Multiple Prediction:A Sparse Inversion Approach[J]. Geophysics, 2005, 70(3):31-43.
[13] 王通,王德利,冯飞,等.三维稀疏反演多次波预测及曲波域匹配相减技术[J].吉林大学学报(地球科学版),2017,47(6):1865-1874. Wang Tong, Wang Deli, Feng Fei, et al. Multiple Prediction with 3D Sparse Inversion and Curvelet Match[J]. Journal of Jilin University (Earth Science Edition), 2017, 47(6):1865-1874.
[14] 王铁兴,王德利,孙婧,等. 基于三维稀疏反演的混合震源数据分离与一次波估计[J].吉林大学学报(地球科学版),2020,50(3):895-904. Wang Tiexing, Wang Deli, Sun Jing, et al. Separation and Primary Estimation of Blended Data by 3D Sparse Inversion[J]. Journal of Jilin University (Earth Science Edition), 2020,50(3):895-904.
[15] 张莉, 王笑雪, 韦振权,等. 南海北部陆坡区多次波组合压制技术[J]. 物探与化探, 2015(5):985-993. Zhang Li, Wang Xiaoxue, Wei Zhenquan, et al.Combination of Multiple Attenuation Technique on the Northern Slope of the South China Sea[J]. Geophysical and Geochemical Exploration, 2015(5):985-993.
[16] 贾连凯, 吴时国, 赵昌垒. 多次波压制技术在南海北部陆缘深水区的应用[J]. 地球物理学进展, 2014, 29(2):920-930. Jia Liankai, Wu Shiguo, Zhao Changlei. Application of Multiple Elimination Techniques in the Deepwater Continental Margin of Northern South China Sea[J]. Progress in Geophysics, 2014, 29(2):920-930.
[17] Verschuur D J, Wang Deli, Herrmann F J. Multi-Term Multiple Prediction Using Separated Reflections and Diffractions Combined with Curvelet-Based Subtractio[C]//Society of Exploration Geophysicists 77th Annual International Meeting.[S. l.]:Society of Exploration Geophysicists, 2007:2535-2539.
[18] 刘琦. 基于反射、散射波场分离的多次波消除方法研究[D]. 长春:吉林大学, 2009. Liu Qi. Multiple Elimination Study Based on Wavefields Separation Between the Reflecting and Scattering[D]. Changchun:Jilin University, 2009.
[19] Khaidukov V, Landa E, Moser T J. Diffraction Imaging by Focusing-Defocusing:An Outlook on Seismic Superresolution[J]. Geophysics, 2004, 69(6):1478-1490.
[20] Taner M T, Fomel S, Landa E. Separation and Imaging of Seismic Diffractions Using Plane-Wave Decomposition[J]. SEG Technical Program Expanded Abstracts, 2006, 25(1):35-41.
[21] 黎孝璋,邓勇,赫建伟,等.复杂海底自由表面多次波预测方法[J].石油地球物理勘探,2020,55(1):64-70. Li Xiaozhang, Deng Yong, Hao Jianwei,et al. Free-Surface-Related Multiple Prediction for Complex Seafloor[J]. Oil Geophysical Prospecting, 2020, 55(1):64-70.
[22] Yilmaz O,Taner M T. Discrete Plane-Wave Decomposition by Least-Mean-Square-Error Method[J]. Geophysics, 1994, 59(6):973-982.
[23] Maïza Bekara, Baan M V D. Random and Coherent Noise Attenuation by Empirical Mode Decomposition[J]. Geophysics, 2009, 74(5):89-98.
[24] Cai Hanpeng, He Zhenhua, Huang Deji. Seismic Data Denoising Based on Mixed Time-Frequency Methods[J]. Applied Geophysics, 2011, 8(4):319-327.
[25] Huang N E, Shen Z, Long S R, et al. The Empirical Mode Decomposition and the Hilbert Spectrum for Nonlinear and Non-Stationary Time Series Analysis[J]. Proceedings A, 1998, 454:903-995.

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