Journal of Jilin University(Earth Science Edition) ›› 2017, Vol. 47 ›› Issue (1): 224-233.doi: 10.13278/j.cnki.jjuese.201701302

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Reconstruction Method of near Offset Data Using Multiples and 2D Matched Filters

Sun Chengyu1, Xie Junfa1,2, Zhang Li3, Zhang Xiaomei2, Li Shian1   

  1. 1. School of Geosciences, China University of Petroleum, Qingdao 266580, Shandong, China;
    2. Research Institute of Petroleum Exploration & Development-Northwest, PetroChina, Lanzhou 730020;
    3. Geophysical Prospecting Research Institute, JOECO, SINOPEC, Nanjing 210046
  • Received:2016-07-16 Online:2017-01-26 Published:2017-01-26
  • Supported by:
    Supported bythe National Natural Science Foundation of China (41374123) and the National Special Oil and Gas Foundation of China (2016ZX05007-006)

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Abstract: In seismic data acquisition, it is always difficult to collect near offset data due to the influences of surface conditions, source and so on, affecting the follow-up data processing. We proposed a reconstruction method of near offset using multiples and two dimensional matched filters to solve the problem. First, we constructed pseudo primaries from surface-related multiples with cross-correlation method. Then we computed matched filters from the pseudo primaries and reconstruct near offset using the filters in time and space window. Finally, root mean square amplitude correction method was used to correct the amplitude of reconstruction data. The reconstruction process was designed in frequency domain to avoid large amount of calculation based on Wiener filtering method to get the matched filters, the computational efficiency was improved by using fast Fourier transform algorithm. The spatial continuity of the data reconstructed by two dimensional matched filters is better than that of one dimensional matched filters. We proved the correctness and effectiveness of the method by testing on Sigsbee 2B data and real seismic data.

Key words: surface-related multiple reflections, two dimensional matched filters, data reconstruction, near offset, root-mean-square amplitude correction

CLC Number: 

  • P631.4
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