The multiobjective genetic algorithm can be used to optimize two conflicting objectives, oil production and polymer utility factor in polymer flood design. This approach provides a set of optimal solutions which can be considered as trade-off curve (Pareto front) to maximize oil production while preserving polymer performance. Then an optimal polymer flood design can be considered from post-optimization analysis. A 2D synthetic example, and a 3D field-scale application, accounting for geologic uncertainty, showed that beyond the optimal design, a relatively minor increase in oil production requires much more polymer injection and the polymer utility factor increases substantially. iii DEDICATION To my parents for their love, care and support iv ACKNOWLEDGEMENTS I would like to thank my academic advisor, Dr. Akhil Datta-Gupta for his valuable guidance throughout the course of this research. Also I want to thank my committee members, Dr. King and Dr. Mohanty for his valuable feedback and questions that have shaped the work in this research.I would like to thanks Fulbright for financial support and this valuable experience to be part of the family, PTTEP for their support and working experience which is very useful for my study.Special thanks to my colleagues at MCERI group; Satyajit for his inspiring ideas,

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