Shale Analytics Data-Driven Analytics in Unconventional Resources /

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 d...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριος συγγραφέας: Mohaghegh, Shahab D. (Συγγραφέας)
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Cham : Springer International Publishing : Imprint: Springer, 2017.
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
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245 1 0 |a Shale Analytics  |h [electronic resource] :  |b Data-Driven Analytics in Unconventional Resources /  |c by Shahab D. Mohaghegh. 
264 1 |a Cham :  |b Springer International Publishing :  |b Imprint: Springer,  |c 2017. 
300 |a XIV, 287 p. 243 illus., 235 illus. in color.  |b online resource. 
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505 0 |a 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. 
520 |a 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. 
650 0 |a Energy. 
650 0 |a Fossil fuels. 
650 0 |a Economic geology. 
650 0 |a Mineral resources. 
650 0 |a Geotechnical engineering. 
650 0 |a Data mining. 
650 1 4 |a Energy. 
650 2 4 |a Fossil Fuels (incl. Carbon Capture). 
650 2 4 |a Data Mining and Knowledge Discovery. 
650 2 4 |a Economic Geology. 
650 2 4 |a Mineral Resources. 
650 2 4 |a Geotechnical Engineering & Applied Earth Sciences. 
710 2 |a SpringerLink (Online service) 
773 0 |t Springer eBooks 
776 0 8 |i Printed edition:  |z 9783319487519 
856 4 0 |u http://dx.doi.org/10.1007/978-3-319-48753-3  |z Full Text via HEAL-Link 
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950 |a Energy (Springer-40367)