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Buchbeschreibung Zustand: New. Bestandsnummer des Verkäufers ABLIING23Mar3113020206119
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Buchbeschreibung PF. Zustand: New. Bestandsnummer des Verkäufers 6666-IUK-9783639708622
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Buchbeschreibung Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -A major task of every oil company is oil field optimization, i.e. maximizing oil production and reducing operational cost. Knowledge about injector-producer relationships (IPRs) is crucial for optimal operation of oil fields. However, inferring IPRs has been a challenging problem due to the unknown underlying structure of oil fields, continuous change of the underlying structure over time, and the large number of wells, i.e. typically, hundreds of injection wells and hundreds of production wells. This book provides two different approaches which map the IPRs problem to a large-scale parameter estimation problem. One approach is constrained nonlinear optimization and the other is machine learning approach. The two approaches demonstrate that not only prediction accuracy but also computational efficiency can be achieved for large-scale parameter estimation problems. This book should help field engineers optimally operate oil fields and show researchers practical examples about how to apply optimization and machine learning techniques to oil field optimization. 120 pp. Englisch. Bestandsnummer des Verkäufers 9783639708622
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Buchbeschreibung PAP. Zustand: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. Bestandsnummer des Verkäufers L0-9783639708622
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Buchbeschreibung Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - A major task of every oil company is oil field optimization, i.e. maximizing oil production and reducing operational cost. Knowledge about injector-producer relationships (IPRs) is crucial for optimal operation of oil fields. However, inferring IPRs has been a challenging problem due to the unknown underlying structure of oil fields, continuous change of the underlying structure over time, and the large number of wells, i.e. typically, hundreds of injection wells and hundreds of production wells. This book provides two different approaches which map the IPRs problem to a large-scale parameter estimation problem. One approach is constrained nonlinear optimization and the other is machine learning approach. The two approaches demonstrate that not only prediction accuracy but also computational efficiency can be achieved for large-scale parameter estimation problems. This book should help field engineers optimally operate oil fields and show researchers practical examples about how to apply optimization and machine learning techniques to oil field optimization. Bestandsnummer des Verkäufers 9783639708622
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Buchbeschreibung PAP. Zustand: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. Bestandsnummer des Verkäufers L0-9783639708622
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Buchbeschreibung Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Lee HyokyeongHyokyeong Lee received her Ph.D. in computer science from University of Southern California in 2010. Her research interests are machine learning, optimization, and their applications to various fields including petroleum. Bestandsnummer des Verkäufers 4999157
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