Reservoir Simulations: Machine Learning and Modeling

Shuyu Sun, Tao Zhang

Research output: Book/ReportBookpeer-review

22 Scopus citations

Abstract

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 complex developments.

Original languageEnglish (US)
PublisherElsevier
Number of pages332
ISBN (Electronic)9780128209578
DOIs
StatePublished - Jan 1 2020

Bibliographical note

Publisher Copyright:
© 2020 Elsevier Inc.

ASJC Scopus subject areas

  • General Energy

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