| 書目名稱 | Machine Learning in the Oil and Gas Industry | | 副標題 | Including Geoscience | | 編輯 | Yogendra Narayan Pandey,Ayush Rastogi,Luigi Sapute | | 視頻video | http://file.papertrans.cn/621/620706/620706.mp4 | | 概述 | Contains real-life oil and gas company examples, based on data sets from those industries.Covers supervised and unsupervised learning.Covers diverse industry topics, including geophysics, geological m | | 圖書封面 |  | | 描述 | .Apply machine and deep learning to solve some of the challenges in the oil and gas industry. The book begins with a brief discussion of the oil and gas exploration and production life cycle in the context of data flow through the different stages of industry operations. This leads to a survey of some interesting problems, which are good candidates for applying machine and deep learning approaches. The initial chapters provide a primer on the Python programming language used for implementing the algorithms; this is followed by an overview of supervised and unsupervised machine learning concepts. The authors provide industry examples using open source data sets along with practical explanations of the algorithms, without diving too deep into the theoretical aspects of the algorithms employed. .Machine Learning in the Oil and Gas Industry. covers problems encompassing diverse industry topics, including geophysics (seismic interpretation), geological modeling, reservoir engineering, and production engineering.?..Throughout the book, the emphasis is on providing a practical approach with step-by-step explanations and code examples for implementing machine and deep learning algorithms f | | 出版日期 | Book 2020 | | 關鍵詞 | Python; Machine Learning; Deep Learning; Data Processing; Geological Modeling; Reservoir Modeling; Supervi | | 版次 | 1 | | doi | https://doi.org/10.1007/978-1-4842-6094-4 | | isbn_softcover | 978-1-4842-6093-7 | | isbn_ebook | 978-1-4842-6094-4 | | copyright | Yogendra Narayan Pandey, Ayush Rastogi, Sribharath Kainkaryam, Srimoyee Bhattacharya, and Luigi Sapu |
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