Journal of Jilin University(Earth Science Edition) ›› 2021, Vol. 51 ›› Issue (2): 597-606.doi: 10.13278/j.cnki.jjuese.20200111

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Diffracted Multiple Elimination Based on f-x EMD Wavefield Separation

Wang Rui1, Wang Deli1, Hu Bin1, Wang Tiexing1, Wang Tong2, Cui Yalong3   

  1. 1. College of GeoExploration Science and Technology, Jilin University, Changchun 130026, China;
    2. Institute of Geophysical and Geochemical Exploration, Chinese Academy of Geological Sciences, Langfang 065000, Hebei, China;
    3. Jilin Zhongdi Geotechnical Engineering Co. LTD, Changchun 130000, China
  • Received:2020-05-04 Published:2021-04-06
  • Supported by:
    Supported by the National Nature Science Foundation of China(2016ZX05026-002-003) and the National Natural Science Foundation of China(41374108)

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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

CLC Number: 

  • P631.4
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[1] Wang Tong, Wang Deli, Feng Fei, Cheng Hao, Wei Jingxuan, Tian Mi. Multiple Prediction with 3D Sparse Inversion and Curvelet Match [J]. Journal of Jilin University(Earth Science Edition), 2017, 47(6): 1865-1874.
[2] SHI Ying, LIU Hong, LI Yu-ying. Surface-Related Multiple Attenuation Method Investigation in Inverse Data Domain [J]. J4, 2011, 41(1): 271-276.
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