Radon-domain interferometric interpolation for reconstruction of the near-offset gap in marine seismic data

被引:15
|
作者
Xu, Zhuo [1 ,2 ]
Sopher, Daniel [3 ]
Juhlin, Christopher [3 ]
Han, Liguo [1 ,2 ]
Gong, Xiangbo [1 ,2 ]
机构
[1] Jilin Univ, Coll Geoexplorat Sci & Technol, Changchun 130026, Jilin, Peoples R China
[2] Minist Land & Resources, Key Lab Appl Geophys, Changchun 130026, Jilin, Peoples R China
[3] Uppsala Univ, Dept Earth Sci, Villavagen 16, S-75236 Uppsala, Sweden
基金
中国国家自然科学基金;
关键词
Interferometric interpolation; Cross-correlation; Multiple; Near-offset gap; Radon transform; SPARSE INVERSION; REFLECTIONS; ATTENUATION; PRIMARIES;
D O I
10.1016/j.jappgeo.2018.02.012
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
In towed marine seismic data acquisition, a gap between the source and the nearest recording channel is typical. Therefore, extrapolation of the missing near-offset traces is often required to avoid unwanted effects in subsequent data processing steps. However, most existing interpolation methods perform poorly when extrapolating traces. Interferometric interpolation methods are one particular method that have been developed for filling in trace gaps in shot gathers. Interferometry-type interpolation methods differ from conventional interpolation methods as they utilize information from several adjacent shot records to fill in the missing traces. In this study, we aim to improve upon the results generated by conventional time-space domain interferometric interpolation by performing interferometric interpolation in the Radon domain, in order to overcome the effects of irregular data sampling and limited source-receiver aperture. We apply both time-space and Radon-domain interferometric interpolation methods to the Sigsbee2B synthetic dataset and a real towed marine dataset from the Baltic Sea with the primary aim to improve the image of the seabed through extrapolation into the near-offset gap. Radon-domain interferometric interpolation performs better at interpolating the missing near offset traces than conventional interferometric interpolation when applied to data with irregular geometry and limited source-receiver aperture. We also compare the interferometric interpolated results with those obtained using solely Radon transform (RT) based interpolation and show that interferometry-type interpolation performs better than solely RT-based interpolation when extrapolating the missing near-offset traces. After data processing, we show that the image of the seabed is improved by performing interferometry-type interpolation, especially when Radon-domain interferometric interpolation is applied. (C) 2018 Elsevier B.V. All rights reserved.
引用
收藏
页码:125 / 141
页数:17
相关论文
共 13 条
  • [1] Reconstruction of the near-offset gap in marine seismic data using seismic interferometric interpolation
    Xu, Zhuo
    Sopher, Daniel
    Juhlin, Christopher
    Han, Liguo
    GEOPHYSICAL PROSPECTING, 2018, 66 : 1 - 26
  • [2] Radon domain interferometric interpolation of sparse seismic data
    Shao, Jie
    Wang, Yibo
    Chang, Xu
    GEOPHYSICS, 2021, 86 (05) : WC89 - WC104
  • [3] Estimation of primaries and near-offset reconstruction by sparse inversion: Marine data applications
    van Groenestijn, G. J. A.
    Verschuur, D. J.
    GEOPHYSICS, 2009, 74 (06) : R119 - R128
  • [4] Radon-domain acoustic and elastodynamic interferometric redatuming of VSP data
    Xu, Zhuo
    Gong, Xiangbo
    Juhlin, Christopher
    Zhang, Fengjiao
    Li, Xiaolong
    Han, Liguo
    GEOPHYSICAL JOURNAL INTERNATIONAL, 2024, 240 (01) : 117 - 137
  • [5] Missing Shots and Near-Offset Reconstruction of Marine Seismic Data With Towered Streamers via Self-Supervised Deep Learning
    Wang, Benfeng
    Han, Dong
    Li, Jiakuo
    IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2022, 60
  • [6] Estimating primaries by sparse inversion and application to near-offset data reconstruction
    van Groenestijn, G. J. A.
    Verschuur, D. J.
    GEOPHYSICS, 2009, 74 (03) : A23 - A28
  • [7] Near offset reconstruction for marine seismic data using a convolutional neural network
    Huff, Owen Rohwer
    Thorkildsen, Vemund Stenbekk
    Greiner, Thomas Larsen
    Lie, Jan Erik
    Evensen, Andreas Kjelsrud
    Bugge, Aina Juell
    Faleide, Jan Inge
    GEOPHYSICAL PROSPECTING, 2024, 72 (06) : 2164 - 2185
  • [8] Wavelet-Radon domain dealiasing and interpolation of seismic data
    Yu, Zhou
    Ferguson, John
    McMechan, George
    Anno, Phil
    GEOPHYSICS, 2007, 72 (02) : V41 - V49
  • [9] Regridding and data interpolation of projection domain and Radon domain for super-resolution tomograpic reconstruction
    Yu, Qingkun
    Guan, Xiaoning
    PROCEEDINGS OF 2013 IEEE INTERNATIONAL CONFERENCE ON MEDICAL IMAGING PHYSICS AND ENGINEERING (ICMIPE), 2013, : 83 - 85
  • [10] Seismic Data Reconstruction Using a Phase-Shift-Plus-Interpolation-Based Apex-Shifted Hyperbolic Radon Transform
    Wang, Yue
    Gong, Xiangbo
    Hu, Bin
    REMOTE SENSING, 2024, 16 (07)