Machine Learning Applications in Subsurface Energy Resource Management (eBook, PDF)

State of the Art and Future Prognosis
Redaktion: Mishra, Srikanta

• Format: PDF

Produktbeschreibung

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.

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Produktdetails

• Verlag: Taylor & Francis eBooks
• Seitenzahl: 378
• Erscheinungstermin: 27. Dezember 2022
• Englisch
• ISBN-13: 9781000823875
• Artikelnr.: 66653122