Reservoir Simulations

Machine Learning and Modeling

; Tao Zhang

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. Les mer
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1941,-

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Vår pris: 1941,-

(Paperback) Fri frakt!
Leveringstid: Sendes innen 21 dager
På grunn av Brexit-tilpasninger og tiltak for å begrense covid-19 kan det dessverre oppstå forsinket levering.

Om boka

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.

Fakta

Innholdsfortegnelse

Preface 1. Introduction 2. Review of classical reservoir simulation 3. Recent progress in pore scale reservoir simulation 4. Recent progress in Darcy's scale reservoir simulation 5. Recent progress in multiscale and mesoscopic reservoir simulation 6. Recent progress in machine learning applications in reservoir simulation 7. Recent progress in accelerating flash cal culation using deep learning algorithms