A New Oilfield Production Prediction Method Based On GM(1,n)
| Autor: | Huan Liu, X. F. Ding, Zhe-Zhi Liu |
|---|---|
| Rok vydání: | 2013 |
| Předmět: |
Mathematical optimization
Fuel Technology Artificial neural network Rate of convergence Computer science Property (programming) General Chemical Engineering Energy Engineering and Power Technology Production (economics) General Chemistry Variation (game tree) Geotechnical Engineering and Engineering Geology Functional simulation |
| Zdroj: | Petroleum Science and Technology. 32:22-28 |
| ISSN: | 1532-2459 1091-6466 |
| DOI: | 10.1080/10916466.2011.585357 |
| Popis: | Oilfield production prediction is one of the most important contents in dynamic analysis of oilfield development. At first, the authors produce an improved neural network algorithm. It not only keeps the property of high predicting accuracy, but it also greatly improves the convergence rate by choosing a new searching direction. Then, by considering the shortcomings of the variation tendency of prediction indices, they combine it with the GM (1,1) prediction model and get a new functional simulation prediction method. At last, the authors put this new method into actual oilfield production prediction and gain good predicting results. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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