Quantitative Methods in Reservoir Engineering

Quantitative Methods in Reservoir Engineering, Second Edition, brings together the critical aspects of the industry to create more accurate models and better financial forecasts for oil and gas assets. Updated to cover more practical applications related to intelligent infill drilling, optimized well pattern arrangement, water flooding with modern wells, and multiphase flow, this new edition helps reservoir engineers better lay the mathematical foundations for analytical or semi-analytical methods in today's more difficult reservoir engineering applications.

Authored by a worldwide expert on computational flow modeling, this reference integrates current mathematical methods to aid in understanding more complex well systems and ultimately guides the engineer to choose the most profitable well path. The book delivers a valuable tool that will keep reservoir engineers up-to-speed in this fast-paced sector of the oil and gas market.

• Stay competitive with new content on unconventional reservoir simulation
• Get updated with new material on formation testing and flow simulation for complex well systems and paths
• Apply methods derived from real-world case studies and calculation examples

Wilson Chin is currently President and Founder of Stratamagnetic Software, LLC. Started in 1999, his company develops scientific models for oil and gas exploration and production clients such as Baker Hughes, CNPC, Halliburton, Schlumberger, and the US Department of Energy. Previously, he worked for Halliburton, BP, Schlumberger and Boeing. He has published 13 books focused on reservoir engineering, formation evaluation, sensor design, drilling, and computational methods. He was also recently a Consultant for GE Oil and Gas MWD design. Wilson has also taught at the University of Houston as an Adjunct Professor and has earned awards and partnerships through the US Department of Energy as well as over 70 patents. Wilson has authored multiple conference papers and journal articles. He earned a B.Sc. in Aerospace Engineering and Applied Math from New York University, a M.Sc. in Aerospace Engineering from California Institute of Technology, and a Ph.D. in Physics, Math, and Aerospace from the Massachusetts Institute of Technology.