Shale Analytics: Data-Driven Analytics in Unconventional Resources
Autor Shahab D. Mohagheghen Limba Engleză Hardback – 17 feb 2017
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Specificații
ISBN-13: 9783319487519
ISBN-10: 3319487515
Pagini: 295
Ilustrații: XIV, 287 p. 243 illus., 235 illus. in color.
Dimensiuni: 155 x 235 x 24 mm
Greutate: 0.6 kg
Ediția:1st ed. 2017
Editura: Springer International Publishing
Colecția Springer
Locul publicării:Cham, Switzerland
ISBN-10: 3319487515
Pagini: 295
Ilustrații: XIV, 287 p. 243 illus., 235 illus. in color.
Dimensiuni: 155 x 235 x 24 mm
Greutate: 0.6 kg
Ediția:1st ed. 2017
Editura: Springer International Publishing
Colecția Springer
Locul publicării:Cham, Switzerland
Cuprins
Data-Driven Formation Evaluation – Generation of Synthetic Geo-mechanical Well Logs in Shale.- Data-Driven Reservoir Characteristics – Impact of rock and completion parameters in.- Data-Driven Completion Analysis – Analysis, Design and Optimization of Hydraulic Fracturing in Shale.- Data-Driven Reservoir Modeling – Full Field Reservoir Modeling of Marcellus Shale.- Data-Driven Reservoir Modeling – Full Field Reservoir Modeling of Niobrara Formation, DJ Basin.- Data-Driven Reservoir Modeling – AI-Based Proxy of Numerical Reservoir Simulation of Shale.
Notă biografică
Shahab D. Mohaghegh is the president and CEO of Intelligent Solutions, Inc. (ISI) and Professor of Petroleum and Natural Gas Engineering at West Virginia University. A pioneer in the application of Artificial Intelligence and Data Mining in the Exploration and Production industry, he holds B.S., MS, and PhD degrees in petroleum and natural gas engineering. He has authored more than 180 technical papers and carried out more than 50 projects with major international companies. He is a SPE Distinguished Lecturer and has been featured in the Distinguished Author Series of SPE’s Journal of Petroleum Technology (JPT) four times. He has been honored by the U.S. Secretary of Energy for his technical contribution in the aftermath of the Deepwater Horizon (Macondo) incident in the Gulf of Mexico and has served as a member of U.S. Secretary of Energy’s Technical Advisory Committee on Unconventional Resources.
Textul de pe ultima copertă
This book describes the application of modern information technology to reservoir modeling and well management. Data Driven Analytics in Unconventional Resources looks specifically at reservoir modeling and production management of shale reservoirs, since conventional reservoir modeling techniques do not perform well in this environment. Topics covered include tools for analysis, predictive modeling and optimization of production from shale in the absence of well-understood and well-defined physics of fluid flow in shale. Also discussed are important insights into completion practices of production from shale Abundant examples and computer code are given that illustrate the operation of Data-Driven Analytics. The flexibility and power of the technique is demonstrated in numerous real-world situations.
Caracteristici
Describes the use of artificial neural networks and fuzzy sets in petroleum engineering Explains data mining in petroleum engineering Demonstrates the only data driven reservoir modeling and production engineering technique for unconventional resources – especially shale Examines tools for analysis, predictive modeling, and optimization of production from shale in the absence of well-understood and well-defined physics of fluid flow in shale Includes supplementary material: sn.pub/extras