Data-driven analytics for the geological storage of CO2
"Data-driven analytics is enjoying unprecedented popularity among oil and gas professionals. A large number of reservoir engineering problems associated with geological storage of CO2 require development of numerical reservoir simulation models. The numerical models are used to understand the i...
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| 1. Verfasser: | |
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| Format: | UnknownFormat |
| Sprache: | eng |
| Veröffentlicht: |
Boca Raton, London, New York
CRC Press
2018
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| Schlagworte: |
Geological carbon sequestration
> Hydrocarbon reservoirs
> Mathematical models
> Quantitative research
> Carbon dioxide capture and storage
> Porengrundwasserleiter
> Speichergestein
> Kohlendioxid
> Sequestrierung
> Datenanalyse
> Poröser Stoff
> Gasspeicherung
> Unterirdische Lagerung
> Big Data
> Explorative Datenanalyse
> Statistische Analyse
> Dichtheit
> Porosität
> Künstliche Intelligenz
> Maschinelles Lernen
> Neuronales Netz
> Datenauswertung
> Erdgasgeologie
> Erdölgeologie
> Geostatistik
> Modellierung
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| Online Zugang: | Inhaltsverzeichnis Leseprobe und Literaturverzeichnis |
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Tag hinzufügen | Zusammenfassung: | "Data-driven analytics is enjoying unprecedented popularity among oil and gas professionals. A large number of reservoir engineering problems associated with geological storage of CO2 require development of numerical reservoir simulation models. The numerical models are used to understand the impact of injection of CO2 in saline aquifers, depleted oil and gas reservoirs, as well as CO2-EOR projects. This book discusses application of data-driven analytics to geological storage of CO2. It explains the technology that allows for uncertainty quantification and optimization of CO2 storage projects. It also deals with actual case studies from Australia and the United States"-- Storage of CO2 in geological formations -- Petroleum data analytics -- Smart proxy modeling -- CO2 storage in depleted gas reservoirs -- CO2 storage in saline aquifers -- CO2 storage in shale using smart proxy -- CO2-EOR as a storage mechanism -- Leak detection in CO2 storage sites |
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| Beschreibung: | Literaturverzeichnis: Seite 255-273 |
| Beschreibung: | xix, 282 Seiten Illustrationen |
| ISBN: | 9781138197145 978-1-138-19714-5 |