Introduction to Geological Uncertainty Management in Reservoir Characterization and Optimization: Robust Optimization and History Matching
Reza Yousefzadeh, Alireza Kazemi, Mohammad Ahmadi, Jebraeel Gholinezhad
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.
年:
2023
出版社:
Springer Nature
语言:
english
页:
142
ISBN 10:
3031280784
ISBN 13:
9783031280788
文件:
EPUB, 12.66 MB
IPFS:
,
english, 2023
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