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.
"Sinopsis" puede pertenecer a otra edición de este libro.
Reza Yousefzadeh is currently a postgraduate researcher in reservoir engineering at Amirkabir University of Technology (Tehran Polytechnic). He got his master's and bachelor's degree from the same university in reservoir engineering and petroleum engineering, respectively. His research fields included well placement optimization, facilitating well placement optimization using fast marching method, uncertainty management in well placement optimization under geological uncertainty, and applying machine learning algorithms to different petroleum-related problems such as field development optimization and history matching.
Reza is currently working on addressing some of the common challenges in uncertainty management in robust field development optimization and has published several technical papers in this regard. He is specially working on reducing the computational cost and improving the parametrization quality of the geological realizations. In this regard, his primary focus is on using deep learning methods capable of handling three-dimensional models with complex and non-Gaussian distributions.
Dr Alireza Kazemi, BSc, MSc, PhD, obtained his PhD from Heriot-Watt University where he conducted his research on time lapse seismic history matching and his MSc studies was on reservoir engineering at IFP School.
He is currently an assistant professor in the department of petroleum and chemical engineering at Sultan Qaboos University in Oman. He teaches subjects including reservoir simulation, enhanced oil recovery, fluid flow in the porous media, carbon capture and storage and advanced reservoir engineering. His current research is focused on the application of machine learning algorithms in scale deposition, reservoir simulation history matching and uncertainty quantification and modelling and simulation of underground CO2 and hydrogen storage. He has published more than 45 technical papers.
Mohammad Ahmadi is currently an Associate Professor of reservoir engineering at Amirkabir University of Technology (Tehran Polytechnic). He has got his MSc and PhD degrees from the French Petroleum Institute (IFP) and Heriot-Watt University in reservoir engineering and petroleum engineering, respectively. His research activities has been focused on Numerical Methods for Flow in Porous Media, inverse modeling in porous media, and Deep Learning and Artificial Intelligence for reservoir geomodeling and uncertainty quantification. Mohammad is currently working on development of closed loop field development and data assimilation techniques for history matching and production optimization. He has published more than 50 technical papers in this area of research. He is specially working on Computational Methods for Modeling of Heterogeneous Reservoirs with uncertain Geometrically Complex Geological Structure."Sobre este título" puede pertenecer a otra edición de este libro.
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Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 148 pp. Englisch. Nº de ref. del artículo: 9783031280788
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Taschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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. Nº de ref. del artículo: 9783031280788
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Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. 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 sourc. Nº de ref. del artículo: 812308039
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Taschenbuch. Condición: Neu. Neuware -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.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 148 pp. Englisch. Nº de ref. del artículo: 9783031280788
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