Info
- Utilizzare la checkbox di selezione a fianco di ciascun documento per attivare le funzionalità di stampa, invio email, download nei formati disponibili del (i) record.
Artificial intelligence & data mining applications in the E&P industry [[electronic resource] /] / Shahab D. Mohaghegh, Saud M. Al-Fattah, Andrei S. Popa
| Artificial intelligence & data mining applications in the E&P industry [[electronic resource] /] / Shahab D. Mohaghegh, Saud M. Al-Fattah, Andrei S. Popa |
| Autore | Mohaghegh Shahab D |
| Pubbl/distr/stampa | Richardson, TX, : Society of Petroleum Engineers, c2011 |
| Descrizione fisica | 1 online resource (271 p.) |
| Altri autori (Persone) |
Al-FattahSaud M
PopaAndrei S |
| Collana | Getting up to speed |
| Soggetto topico |
Petroleum engineering
Neural networks (Computer science) Data mining |
| Soggetto genere / forma | Electronic books. |
| ISBN | 1-61399-064-2 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| 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"" |
| Record Nr. | UNINA-9910463083303321 |
Mohaghegh Shahab D
|
||
| Richardson, TX, : Society of Petroleum Engineers, c2011 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Shale Analytics [[electronic resource] ] : Data-Driven Analytics in Unconventional Resources / / by Shahab D. Mohaghegh
| Shale Analytics [[electronic resource] ] : Data-Driven Analytics in Unconventional Resources / / by Shahab D. Mohaghegh |
| Autore | Mohaghegh Shahab D |
| Edizione | [1st ed. 2017.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017 |
| Descrizione fisica | 1 online resource (XIV, 287 p. 243 illus., 235 illus. in color.) |
| Disciplina | 662.6 |
| Soggetto topico |
Fossil fuels
Data mining Economic geology Mineral resources Geotechnical engineering Fossil Fuels (incl. Carbon Capture) Data Mining and Knowledge Discovery Economic Geology Mineral Resources Geotechnical Engineering & Applied Earth Sciences |
| ISBN | 9783319487533 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | 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. |
| Record Nr. | UNINA-9910163986903321 |
|
Mohaghegh Shahab D
|
||
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||