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Autore: | Mohaghegh Shahab D |
Titolo: | Artificial intelligence & data mining applications in the E&P industry [[electronic resource] /] / Shahab D. Mohaghegh, Saud M. Al-Fattah, Andrei S. Popa |
Pubblicazione: | Richardson, TX, : Society of Petroleum Engineers, c2011 |
Descrizione fisica: | 1 online resource (271 p.) |
Soggetto topico: | Petroleum engineering |
Neural networks (Computer science) | |
Data mining | |
Soggetto genere / forma: | Electronic books. |
Altri autori: | Al-FattahSaud M PopaAndrei S |
Note generali: | Description based upon print version of record. |
Nota di bibliografia: | Includes bibliographical references. |
Nota di contenuto: | ""Foreword""; ""Contents""; ""Virtual-Intelligence Applications in Petroleum Engineering: Part 1�Artificial Neural Networks""; ""Virtual-Intelligence Applications in Petroleum Engineering: Part 2�Evolutionary Computing""; ""Virtual-Intelligence Applications in Petroleum Engineering: Part 3�Fuzzy Logic""; ""Using Artificial Neural Nets To Identify the Well-Test Interpretation Model""; ""Discriminant Analysis and Neural Nets: Valuable Tools To Optimize Completion Practices""; ""An Investigation Into the Application of Fuzzy Logic to Well Stimulation Treatment Design"" |
""Predicting Production Using a Neural Network (Artificial Intelligence Beats Human Intelligence)""""Application of Neural Networks to Modeling Fluid Contacts in Prudhoe Bay""; ""Predicting Well-Stimulation Results in a Gas-Storage Field in the Absence of Reservoir Data With Neural Networks""; ""Candidate Selection for Stimulation of Gas Storage Wells Using Available Data With Neural Networks and Genetic Algorithms""; ""Neural Network Model for Estimating the PVT Properties of Middle East Crude Oils""; ""Intelligent Systems Can Design Optimum Fracturing Jobs"" | |
""Neural-Network Approach To Predict Well Performance Using Available Field Data""""Neural Network Approach Predicts U.S. Natural Gas Production""; ""Integration of Multiphase Flowmetering, Neural Networks, and Fuzzy Logic in Field Performance Monitoring""; ""Recent Developments in Application of Artificial Intelligence in Petroleum Engineering""; ""Zonal Allocation and Increased Production Opportunities Using Data Mining in Kern River""; ""Self-Organizing Maps for Lithofacies Identification and Permeability Prediction""; ""Optimizing Cyclic Steam Oil Production with Genetic Algorithms"" | |
""Analysis of Best Hydraulic Fracturing Practices in the Golden Trend Fields of Oklahoma""""Application of Artificial Intelligence in Gas Storage Management""; ""Using Neural Networks for Candidate Selection and Well Performance Prediction in Water-Shutoff Treatments Using Polymer Gels�A Field-Case Study""; ""The Development of an Artificial Neural Network as a Pressure Transient Analysis Tool for Applications in Double-Porosity Reservoirs""; ""Flow Pattern and Frictional-Pressure-Loss Estimation Using Neural Networks for UBD Operations"" | |
""Uncertainty Analysis of a Giant Oil Field in the Middle East Using Surrogate Reservoir Model""""Artificial-Intelligence Technology Predicts Relative Permeability of Giant Carbonate Reservoirs""; ""Case-Based Reasoning Approach for Well Failure Diagnostics and Planning""; ""Top-Down Intelligent Reservoir Modeling (TDIRM)""; ""New Insight into Integrated Reservoir Management using Top-Down, Intelligent Reservoir Modeling Technique; Application to a Giant and Complex Oil Field in the Middle East"" | |
Titolo autorizzato: | Artificial intelligence & data mining applications in the E&P industry |
ISBN: | 1-61399-064-2 |
Formato: | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione: | Inglese |
Record Nr.: | 9910463083303321 |
Lo trovi qui: | Univ. Federico II |
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