Reservoir Simulations
Machine Learning and Modeling
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…
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Produktdetails
Weitere Autoren: Zhang, Tao
- ISBN: 978-0-12-820962-2
- EAN: 9780128209622
- Produktnummer: 35966087
- Verlag: Elsevier Science & Techn.
- Sprache: Englisch
- Erscheinungsjahr: 2020
- Seitenangabe: 340 S.
- Plattform: EPUB
- Masse: 14'952 KB
- Abbildungen: Approx. 200 illustrations
Über den Autor
Shuyu Sun is currently the Director of the Computational Transport Phenomena Laboratory (CTPL) at King Abdullah University of Science and Technology (KAUST) and a Co-Director of the Center for Subsurface Imaging and Fluid Modeling consortium (CSIM) at KAUST. He obtained his Ph.D. degree in computational and applied mathematics from The University of Texas at Austin. His research includes the modelling and simulation of porous media flow at Darcy scales, pore scales and molecular scales. Professor Sun has published about 400 articles, including 220+ refereed journal papers
1 weiteres Werk von Shuyu Sun:
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