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Fast 2D forward modeling of electromagnetic propagation well logs using finite element method and data-driven deep learning

A.M.Petrov A.R.Leonenko K.N.Danilovskiy O.V.Nechaev

Artificial Intelligence in Geosciences2025，Vol.6Issue(1)：P.85-96,12.

Artificial Intelligence in Geosciences2025，Vol.6Issue(1)：P.85-96,12.DOI:10.1016/j.aiig.2025.100112

Fast 2D forward modeling of electromagnetic propagation well logs using finite element method and data-driven deep learning

A.M.Petrov ¹A.R.Leonenko ¹K.N.Danilovskiy ¹O.V.Nechaev¹

作者信息

1. The Trofimuk Institute of Petroleum Geology and Geophysics,Siberian Branch of the Russian Academy of Sciences(IPGG SB RAS),Koptug ave.3,Novosibirsk,630090,Russia
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摘要

关键词

Petrophysics/Electromagnetic propagation logging/Forward modeling/Finite element method/Residual neural networks

分类

天文与地球科学

引用本文复制引用

A.M.Petrov,A.R.Leonenko,K.N.Danilovskiy,O.V.Nechaev..Fast 2D forward modeling of electromagnetic propagation well logs using finite element method and data-driven deep learning[J].Artificial Intelligence in Geosciences,2025,6(1):P.85-96,12.

基金项目

financially supported by the Russian federal research project No.FWZZ-2022-0026“Innovative aspects of electro-dynamics in problems of exploration and oilfield geophysics”. （）

Artificial Intelligence in Geosciences

ISSN：2666-5441

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