Machine Learning Applications in Subsurface Energy Resource Management State of the Art and Future Prognosis
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- Hardcover
- Taschenbuch ausgewählt
- eBook
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Sprache:Englisch
Fr. 78.90
inkl. gesetzl. MwSt.,
Beschreibung
Produktdetails
Einband
Taschenbuch
Abbildungen
farbige, schwarzweisse Abbildungen
Herausgeber
Srikanta MishraVerlag
Taylor and FrancisSeitenzahl
384
Maße (L/B)
22.9/15.2 cm
Sprache
Englisch
ISBN
978-1-03-207455-9
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 the practicing petroleum engineer or geoscientist 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.
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