Introduction to Geological Uncertainty Management in Reservoir Characterization and Optimization: Robust Optimization and History Matching (SpringerBriefs in Petroleum Geoscience & Engineering)

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.

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.

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.