Seismic Data Regularization

Seismic Data Regularization is a computational method in seismic data processing that transforms irregularly sampled seismic traces into a regularly sampled grid by interpolating missing data points while preserving the underlying wavefield characteristics.

127

Publications

7.4K

Citations

303

Authors

130

Institutions

Publications per year

2017–2026

37

Authors

303

  1. SF
    Sergey Fomel

    The University of Texas at Austin, United States

    12 publications · 1.4K citations

    12

    h-index

  2. MD
    Mauricio D. Sacchi

    University of Alberta, Canada

    12 publications · 1.3K citations

    12

    h-index

  3. FJ
    Felix J. Herrmann

    University of British Columbia, Canada

    9 publications · 512 citations

    9

    h-index

  4. YC
    Yangkang Chen

    China University of Petroleum, Beijing, China

    9 publications · 693 citations

    9

    h-index

  5. GL
    Guochang Liu

    China University of Petroleum, Beijing, China

    5 publications · 391 citations

    5

    h-index

1–5 of 303

Venues

  1. Geophysics

    41 publications · 4.3K citations

    30

    h-index

  2. 9

    h-index

  3. Geophysical Journal International

    GJI · 6 publications · 269 citations

    6

    h-index

  4. Journal of Applied Geophysics

    5 publications · 308 citations

    5

    h-index

  5. Geophysical Prospecting

    4 publications · 356 citations

    4

    h-index

1–5