Most of the world’s oil reserves come from improved exploitation of already known fields using increasingly sophisticated methods. Recoverable reserves are therefore estimated based on the various methods of field exploitation. Given this trend, every oil company must have a detailed understanding of the internal architecture of its underground reservoirs. To this end, identifying a reservoir’s lithofacies allows us to drill in porous areas with lower clay content. Identifying the lithofacies is the first step in reservoir characterization. The lithofacies consists of a description of the various geological formations comprising a well. To solve our most complex problems, we need to go beyond standard mathematical techniques. As an alternative, we need to supplement conventional analysis methods with several emerging methodologies, such as artificial intelligence. This book reports on and contributes to investigating the potential of new connectionist techniques in reservoir characterization.
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Paperback. Etat : new. Paperback. Most of the world's oil reserves come from improved exploitation of already known fields using increasingly sophisticated methods. Recoverable reserves are therefore estimated based on the various methods of field exploitation. Given this trend, every oil company must have a detailed understanding of the internal architecture of its underground reservoirs. To this end, identifying a reservoir's lithofacies allows us to drill in porous areas with lower clay content. Identifying the lithofacies is the first step in reservoir characterization. The lithofacies consists of a description of the various geological formations comprising a well. To solve our most complex problems, we need to go beyond standard mathematical techniques. As an alternative, we need to supplement conventional analysis methods with several emerging methodologies, such as artificial intelligence. This book reports on and contributes to investigating the potential of new connectionist techniques in reservoir characterization. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N° de réf. du vendeur 9786209873997
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Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Most of the world's oil reserves come from improved exploitation of already known fields using increasingly sophisticated methods. Recoverable reserves are therefore estimated based on the various methods of field exploitation. Given this trend, every oil company must have a detailed understanding of the internal architecture of its underground reservoirs. To this end, identifying a reservoir's lithofacies allows us to drill in porous areas with lower clay content. Identifying the lithofacies is the first step in reservoir characterization. The lithofacies consists of a description of the various geological formations comprising a well. To solve our most complex problems, we need to go beyond standard mathematical techniques. As an alternative, we need to supplement conventional analysis methods with several emerging methodologies, such as artificial intelligence. This book reports on and contributes to investigating the potential of new connectionist techniques in reservoir characterization. N° de réf. du vendeur 9786209873997
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Paperback. Etat : new. Paperback. Most of the world's oil reserves come from improved exploitation of already known fields using increasingly sophisticated methods. Recoverable reserves are therefore estimated based on the various methods of field exploitation. Given this trend, every oil company must have a detailed understanding of the internal architecture of its underground reservoirs. To this end, identifying a reservoir's lithofacies allows us to drill in porous areas with lower clay content. Identifying the lithofacies is the first step in reservoir characterization. The lithofacies consists of a description of the various geological formations comprising a well. To solve our most complex problems, we need to go beyond standard mathematical techniques. As an alternative, we need to supplement conventional analysis methods with several emerging methodologies, such as artificial intelligence. This book reports on and contributes to investigating the potential of new connectionist techniques in reservoir characterization. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. N° de réf. du vendeur 9786209873997
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Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -Most of the world's oil reserves come from improved exploitation of already known fields using increasingly sophisticated methods. Recoverable reserves are therefore estimated based on the various methods of field exploitation. Given this trend, every oil company must have a detailed understanding of the internal architecture of its underground reservoirs. To this end, identifying a reservoir's lithofacies allows us to drill in porous areas with lower clay content. Identifying the lithofacies is the first step in reservoir characterization. The lithofacies consists of a description of the various geological formations comprising a well. To solve our most complex problems, we need to go beyond standard mathematical techniques. As an alternative, we need to supplement conventional analysis methods with several emerging methodologies, such as artificial intelligence. This book reports on and contributes to investigating the potential of new connectionist techniques in reservoir characterization.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 64 pp. Englisch. N° de réf. du vendeur 9786209873997
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Taschenbuch. Etat : Neu. Reservoir Characterization Using Neural and Fractal Analysis | Lithofacies Classification Using Artificial Neural Networks Combined with Fractal Analysis. Applications | Leila Aliouane (u. a.) | Taschenbuch | Englisch | 2026 | Our Knowledge Publishing | EAN 9786209873997 | Verantwortliche Person für die EU: SIA OmniScriptum Publishing, Brivibas Gatve 197, 1039 RIGA, LETTLAND, customerservice[at]vdm-vsg[dot]de | Anbieter: preigu. N° de réf. du vendeur 134952535
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