Reservoir Simulation: Machine Learning and Modeling provides the latest information and popular advances in reservoir simulation. The book explains common terminology, concepts and equations through multiple figures and short instructional videos, better preparing engineers for a modeling project that avoids problems. Well-designed exercises and an interactive website with downloadable algorithms give readers a faster start on advancing their own cases. Both computational methods and engineering cases are explained, thus bridging opportunities between computational science and petroleum engineering. This book delivers a critical reference for today's petroleum and reservoir engineer to optimize more complex developments. Helps readers understand commonly used definitions, equations and the solution methods used in reservoir simulation Uses world-leading technology to enhance oil recovery by CO2 flooding, pore network modeling for unconventional reservoirs, and data analytics using machine learning Presents practical knowledge with problems and solutions on modeling and simulation cases through a hands-on interactive website