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Phan, S. and Sen, M.K. (2019) Deep Learning with Cross-Shape Deep Boltzmann Machine for Pre-Stack Inversion Problem. In: SEG Technical Program Expanded Abstracts 2019, Society of Exploration Geophysicists, 2293-2297. https://doi.org/10.1190/segam2019-3215696.1

has been cited by the following article:

• TITLE: Research on Convolutional Neural Network in the Field of Oil and Gas Exploration

  AUTHORS: Ting Li

  KEYWORDS: CNN, Artificial Intelligence, Deep Learning, Logging Interpretation

  JOURNAL NAME: Open Access Library Journal, Vol.10 No.3, March 14, 2023

  ABSTRACT: In recent years, Convolutional Neural Network (CNN), as a deep learning algorithm, has been widely used in many fields such as computer vision and speech recognition. In the field of geological exploration, CNN has also made great progress. This paper reviews the latest research progress of CNN in the field of geological exploration, and focuses on the application of CNN in logging and seismic exploration. We first introduce the basic principles of CNN, then introduce the specific applications of CNN in logging and seismic exploration, and analyze the advantages and limitations of CNN with specific examples.