Reservoir Simulation: Machine Learning and Modeling helps the engineer step into the current and most popular advances in
reservoir simulation, learning from current experiments and speeding up potential collaboration opportunities in research
and technology. This reference explains common terminology, concepts, and equations through multiple figures and rigorous
derivations, better preparing the engineer for the next step forward in a modeling project and avoid repeating existing progress.
Well-designed exercises, case studies and numerical examples give the engineer a faster start on advancing their own cases.
Both computational methods and engineering cases are explained, bridging the opportunities between computational science and
petroleum engineering. This book delivers a critical reference for today's petroleum and reservoir engineer to optimize more