Reservoir Simulations

Reservoir and petroleum engineers must stay up to date on the latest technology in reservoir simulation which is a fast-moving area of development. Reservoir Simulation: Machine Learning and Modeling will help 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 short instructional videos, better preparing the engineer for the next step forward in a modeling project and avoid repeating existing progress. Well-designed exercises and an interactive website with downloadable algorithms 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. Reservoir Simulation: Machine Learning and Modeling delivers a critical reference for today's petroleum and reservoir engineer to optimize more complex developments.

• Understand commonly used definitions, equations, and solution methods used in reservoir simulation
• Use world-leading technology to enhance oil recovery by CO2 flooding, pore network modeling for unconventional reservoirs, and data analytics using machine learning
• Gain practical knowledge with problems and solutions on modeling and simulation cases through a hands-on interactive website