LEADER 03804nam  22006255  450 
001 9910163986903321
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010   $a9783319487533
024 7 $a10.1007/978-3-319-48753-3
035   $a(CKB)3710000001053488
035   $a(DE-He213)978-3-319-48753-3
035   $a(MiAaPQ)EBC4803562
035   $a(PPN)198872844
035   $a(EXLCZ)993710000001053488
100   $a20170210d2017      u|         0
101 0 $aeng
135   $aurnn|008mamaa
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 10$aShale Analytics $eData-Driven Analytics in Unconventional Resources /$fby Shahab D. Mohaghegh
205   $a1st ed. 2017.
210  1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2017.
215   $a1 online resource (XIV, 287 p. 243 illus., 235 illus. in color.) 
311   $a3-319-48751-5 
311   $a3-319-48753-1 
320   $aIncludes bibliographical references.
327   $aData-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.
330   $aThis 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.
606   $aFossil fuels
606   $aData mining
606   $aEconomic geology
606   $aMineral resources
606   $aGeotechnical engineering
606   $aFossil Fuels (incl. Carbon Capture)$3https://scigraph.springernature.com/ontologies/product-market-codes/114000
606   $aData Mining and Knowledge Discovery$3https://scigraph.springernature.com/ontologies/product-market-codes/I18030
606   $aEconomic Geology$3https://scigraph.springernature.com/ontologies/product-market-codes/G17010
606   $aMineral Resources$3https://scigraph.springernature.com/ontologies/product-market-codes/G38010
606   $aGeotechnical Engineering & Applied Earth Sciences$3https://scigraph.springernature.com/ontologies/product-market-codes/G37010
615  0$aFossil fuels.
615  0$aData mining.
615  0$aEconomic geology.
615  0$aMineral resources.
615  0$aGeotechnical engineering.
615 14$aFossil Fuels (incl. Carbon Capture).
615 24$aData Mining and Knowledge Discovery.
615 24$aEconomic Geology.
615 24$aMineral Resources.
615 24$aGeotechnical Engineering & Applied Earth Sciences.
676   $a662.6
700   $aMohaghegh$b Shahab D$4aut$4http://id.loc.gov/vocabulary/relators/aut$0887000
906   $aBOOK
912   $a9910163986903321
996   $aShale Analytics$92177661
997   $aUNINA