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商品詳細
Machine Learning Applications in Subsurface Energy Resource Management: State of the Art and Future Prognosis.
・ISBN 978-1-032-07452-8 hard GB£ 145.99
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| 著者・編者 | Mishra, Srikanta (ed.), |
|---|---|
| 出版社 | (CRC Press, UK) |
| 出版年月 | 2022 |
| ページ数 | 360 pp. |
| 言語 | ENG |
| ニュース番号 | ＜A01-66240＞ |
解説
The utilization of machine learning (ML) techniques to understand hidden patterns and build data-driven predictive models from complex multivariate datasets is rapidly increasing in many applied science and engineering disciplines, including geo-energy. Motivated by these developments, Machine Learning Applications in Subsurface Energy Resource Management presents a current snapshot of the state of the art and future outlook for ML applications to manage subsurface energy resources (e.g., oil and gas, geologic carbon sequestration, and geothermal energy).
- Covers ML applications across multiple application domains (reservoir characterization, drilling, production, reservoir modeling, and predictive maintenance)
- Offers a variety of perspectives from authors representing operating companies, universities, and research organizations
- Provides an array of case studies illustrating the latest applications of several ML techniques
- Includes a literature review and future outlook for each application domain
This book is targeted at practicing petroleum engineers or geoscientists interested in developing a broad understanding of ML applications across several subsurface domains. It is also aimed as a supplementary reading for graduate-level courses and will also appeal to professionals and researchers working with hydrogeology and nuclear waste disposal.