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Data Driven Analytics Geological Storage by Mohaghegh Shahab (24 results)
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Condition: As New. Unread book in perfect condition.
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US$ 94.32
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Condition: New. 1st edition NO-PA16APR2015-KAP.
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Data-driven Analytics for the Geological Storage of Co2
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Add to basketPaperback. Condition: Brand New. 302 pages. 9.21x6.14x9.21 inches. In Stock.
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Data-Driven Analytics for the Geological Storage of CO2
Published by Taylor & Francis Ltd, 2020
ISBN 10: 0367734389 ISBN 13: 9780367734381
Language: English
Seller: THE SAINT BOOKSTORE, Southport, United Kingdom
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Add to basketPaperback / softback. Condition: New. New copy - Usually dispatched within 4 working days. 185.
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Data-driven Analytics for the Geological Storage of Co2
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
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Data-Driven Analytics for the Geological Storage of CO2
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Data-Driven Analytics for the Geological Storage of CO2
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
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Add to basketHardcover. Condition: Brand New. 282 pages. 9.50x6.25x1.00 inches. In Stock.
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Add to basketCondition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Shahab D. Mohaghegh, a pioneer in the application of Artificial Intelligence and Data Mining in the Exploration and Production industry, is the president and CEO of Intelligent Solutions, Inc. (ISI) and Professor of Petroleum and Natural Gas Engineering .
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HRD. Condition: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
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Data-Driven Analytics for the Geological Storage of CO2
Seller: PBShop.store UK, Fairford, GLOS, United Kingdom
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Add to basketHRD. Condition: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
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Add to basketHardcover. Condition: Brand New. 282 pages. 9.50x6.25x1.00 inches. In Stock. This item is printed on demand.
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Add to basketBuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Data-driven analytics is enjoying unprecedented popularity among oil and gas professionals. A large number of reservoir engineering problems associated with geological storage of CO2 require development of numerical reservoir simulation models. The numerical models are used to understand the impact of injection of CO2 in saline aquifers, depleted oil and gas reservoirs, as well as CO2-EOR projects. This book discusses application of data-driven analytics to geological storage of CO2. It explains the technology that allows for uncertainty quantification and optimization of CO2 storage projects. It also deals with actual case studies from Australia and the United States.
