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Unsupervised deep learning with higher-order total-variation regularization for multidimensional seismic data reconstruction 원문보기

Geophysics, v.87 no.2, 2022년, pp.V59 - V73  

Larsen Greiner, Thomas André (University of Oslo, Department of Geoscience, Sem Sælands vei 1, Oslo NO 0316, Norway and Lundin-Energy Norway AS, Strandveien 4, Lysaker NO 1366, Norway. (corresponding author).) ,  Lie, Jan Erik (Lundin-Energy Norway AS, Strandveien 4, Lysaker NO 1366, Norway.) ,  Kolbjørnsen, Odd (Lundin-Energy Norway AS, Strandveien 4, Lysaker NO 1366, Norway and University of Oslo, Department of Mathematics, Moltke Moes vei 35, Oslo NO 0851, Norway.) ,  Kjelsrud Evensen, Andreas (Lundin-Energy Norway AS, Strandveien 4, Lysaker NO 1366, Norway.) ,  Harris Nilsen, Espen (Lundin-Energy Norway AS, Strandveien 4, Lysaker NO 1366, Norway.) ,  Zhao, Hao (Listen AS, Gaustadallé) ,  Demyanov, Vasily (en 21, Oslo NO 0349, Norway.) ,  Gelius, Leiv-J. (Heriot-Watt University, Institute of Petroleum Engineering, Third Gait, Edinburgh EH14 4AS, UK.)

Abstract AI-Helper 아이콘AI-Helper

In 3D marine seismic acquisition, the seismic wavefield is not sampled uniformly in the spatial directions. This leads to a seismic wavefield consisting of irregularly and sparsely populated traces with large gaps between consecutive sail lines, especially in the near offsets. The problem of reconst...

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