Parallel Dantzig–Wolfe decomposition of petroleum production allocation problems
| Autor: | Mikael Rönnqvist, Bjarne A. Foss, Eirik Hagem, Vidar Gunnerud, Erlend Torgnes |
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| Rok vydání: | 2012 |
| Předmět: |
Marketing
Mathematical optimization 021103 operations research Optimization problem Operations research Computer science Lift (data mining) business.industry Strategy and Management Reliability (computer networking) 0211 other engineering and technologies Parallel algorithm Scheduling (production processes) 02 engineering and technology Management Science and Operations Research Management Information Systems Scheduling (computing) 0202 electrical engineering electronic engineering information engineering Dantzig–Wolfe decomposition Production (economics) 020201 artificial intelligence & image processing Project management business |
| Zdroj: | Journal of the Operational Research Society. 63:950-968 |
| ISSN: | 1476-9360 0160-5682 |
| DOI: | 10.1057/jors.2011.62 |
| Popis: | This article discusses the optimization of a petroleum production allocation problem through a parallel Dantzig–Wolfe algorithm. Petroleum production allocation problems are problems in which the determination of optimal production rates, lift gas rates and well connections are the central decisions. The motivation for modelling and solving such optimization problems stems from the value that lies in an increased production rate and the current lack of integrated software that considers petroleum production systems as a whole. Through our computational study, which is based on realistic production data from the Troll West field, we show the increase in computational efficiency that a parallel Dantzig–Wolfe algorithm offers. In addition, we show that previously implemented standard parallel algorithms lead to an inefficient use of parallel resources. A more advanced parallel algorithm is therefore developed to improve efficiency, making it possible to scale the algorithm by adding more CPUs and thus approach a reasonable solution time for realistic-sized problems. |
| Databáze: | OpenAIRE |
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