Modeling PVT Properties of Crude Oil Systems Using Type-2 Fuzzy Logic Systems
| Autor: | Ali Selamat, Abdul Azeez Abdul Raheem, Sunday O. Olatunji |
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| Rok vydání: | 2010 |
| Předmět: |
Mathematical optimization
Neuro-fuzzy Computer science business.industry Stability (learning theory) Prediction interval Interval (mathematics) Machine learning computer.software_genre Fuzzy logic Consistency (database systems) Reservoir engineering Feedforward neural network Artificial intelligence business computer |
| Zdroj: | Computational Collective Intelligence. Technologies and Applications ISBN: 9783642166921 ICCCI (1) |
| DOI: | 10.1007/978-3-642-16693-8_51 |
| Popis: | This paper presented a prediction model of Pressure-Volume-Temperature (PVT) properties of crude oil systems based on type-2 fuzzy logic systems. PVT properties are very important in the reservoir engineering computations, and its accurate determination is important in the primary and subsequent development of an oil field. Earlier developed models are confronted with several limitations especially in uncertain situations coupled with their characteristics instability during predictions. In this paper, an interval type-2 fuzzy logic based model is proposed and implemented to improve PVT properties predictions. Comparative studies have been carried out and empirical results show that the newly proposed approach outperforms others in general and particularly in the area of stability, consistency and the ability to adequately handle uncertainties. Another unique advantage of the proposed model is its ability to generate prediction intervals without extra computational cost. |
| Databáze: | OpenAIRE |
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