A deep learning-aided approach for estimating field permeability map by fusing well logs,well tests,and seismic data
Grigoriy Shutov Viktor Duplyakov Shadfar Davoodi Anton Morozov Dmitriy Popkov Kirill Pavlenko Albert Vainshtein Viktor Kotezhekov Sergey Kaygorodov Boris Belozerov Mars M.Khasanov Vladimir Vanovskiy Andrei Osiptsov Evgeny Burnaev
Petroleum2025,Vol.11Issue(6):P.813-824,12.
Petroleum2025,Vol.11Issue(6):P.813-824,12.DOI:10.1016/j.petlm.2025.11.005
A deep learning-aided approach for estimating field permeability map by fusing well logs,well tests,and seismic data
摘要
关键词
Data fusion/Permeability/Convolutional neural network/Seismic/Kernel regression分类
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Grigoriy Shutov,Viktor Duplyakov,Shadfar Davoodi,Anton Morozov,Dmitriy Popkov,Kirill Pavlenko,Albert Vainshtein,Viktor Kotezhekov,Sergey Kaygorodov,Boris Belozerov,Mars M.Khasanov,Vladimir Vanovskiy,Andrei Osiptsov,Evgeny Burnaev..A deep learning-aided approach for estimating field permeability map by fusing well logs,well tests,and seismic data[J].Petroleum,2025,11(6):P.813-824,12.基金项目
supported by the grant for research centers in the field of AI provided by the Ministry of Economic Development of the Russian Federation in accordance with the agreement000000C313925P4F0002 and the agreement with Skoltech N◦139-10-2025-033 ()