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 Online-Ressource
Verfasst von:Yousefzadeh, Reza [VerfasserIn]   i
 Kazemi, Alireza [VerfasserIn]   i
 Ahmadi, Mohammad [VerfasserIn]   i
 Gholinezhad, Jebraeel [VerfasserIn]   i
Titel:Introduction to Geological Uncertainty Management in Reservoir Characterization and Optimization
Titelzusatz:Robust Optimization and History Matching
Verf.angabe:by Reza Yousefzadeh, Alireza Kazemi, Mohammad Ahmadi, Jebraeel Gholinezhad
Ausgabe:1st ed. 2023.
Verlagsort:Cham
 Cham
Verlag:Springer International Publishing
 Imprint: Springer
E-Jahr:2023
Jahr:2023.
 2023.
Umfang:1 Online-Ressource(XIV, 132 p. 27 illus., 23 illus. in color.)
Gesamttitel/Reihe:SpringerBriefs in Petroleum Geoscience & Engineering
ISBN:978-3-031-28079-5
Abstract:Chapter 1. Introduction to Uncertainty in Reservoir Engineering -- Chapter 2. Geological Uncertainty Quantification -- Chapter 3. Reducing the Geological Uncertainty by History Matching -- Chapter 4. Dimensionality Reduction Methods used in History Matching -- Chapter 5. Field Development Optimization under Geological Uncertainty -- Chapter 6. History Matching and Robust Optimization Using Proxies. .
 This book explores methods for managing uncertainty in reservoir characterization and optimization. It covers the fundamentals, challenges, and solutions to tackle the challenges made by geological uncertainty. The first chapter discusses types and sources of uncertainty and the challenges in different phases of reservoir management, along with general methods to manage it. The second chapter focuses on geological uncertainty, explaining its impact on field development and methods to handle it using prior information, seismic and petrophysical data, and geological parametrization. The third chapter deals with reducing geological uncertainty through history matching and the various methods used, including closed-loop management, ensemble assimilation, and stochastic optimization. The fourth chapter presents dimensionality reduction methods to tackle high-dimensional geological realizations. The fifth chapter covers field development optimization using robust optimization, including solutions for its challenges such as high computational cost and risk attitudes. The final chapter introduces different types of proxy models in history matching and robust optimization, discussing their pros and cons, and applications. The book will be of interest to researchers and professors, geologists and professionals in oil and gas production and exploration.
DOI:doi:10.1007/978-3-031-28079-5
URL:Resolving-System: https://doi.org/10.1007/978-3-031-28079-5
 DOI: https://doi.org/10.1007/978-3-031-28079-5
Schlagwörter:(s)Mathematisches Modell   i / (s)Erdölgewinnung   i / (s)Erdgasgewinnung   i / (s)Speichergestein   i / (s)Modellierung   i / (s)Stochastisches Modell   i
 (s)Erdöllagerstätte   i / (s)Erdölgewinnung   i / (s)Lagerstättenkunde   i / (s)Optimierung   i / (s)Geostatistik   i / (s)Bayes-Entscheidungstheorie   i
 (s)Speichergestein   i / (s)Maschinelles Lernen   i / (s)Unvollkommene Information   i / (s)Permeabilität   i / (s)Porosität   i
Datenträger:Online-Ressource
Dokumenttyp:Einführung
 Lehrbuch
Sprache:eng
Bibliogr. Hinweis:Erscheint auch als : Druck-Ausgabe
 Erscheint auch als : Druck-Ausgabe
 Erscheint auch als : Druck-Ausgabe
K10plus-PPN:1841949140
 
 
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