Hybrid machine learning algorithms to predict condensate viscosity in the near wellbore regions of gas condensate reservoirs

Gas condensate reservoirs display unique phase behavior and are highly sensitive to reservoir pressure changes. This makes it difficult to determine their PVT characteristics, including their condensate viscosity, which is a key variable in determining their flow behavior. In this study, a novel mac...

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Vydané v:	Journal of natural gas science and engineering Ročník 95; s. 104210
Hlavní autori:	Behesht Abad, Abouzar Rajabi, Mousavi, Seyedmohammadvahid, Mohamadian, Nima, Wood, David A., Ghorbani, Hamzeh, Davoodi, Shadfar, Alvar, Mehdi Ahmadi, Shahbazi, Khalil
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Elsevier B.V 01.11.2021
Predmet:	Gas condensate viscosity Hybrid machine learning algorithms Least squares support vector machine Multi-layer extreme learning machine Multilayer perceptron Multilayer perceptron Hybrid machine learning algorithms Gas condensate viscosity Multi-layer extreme learning machine Least squares support vector machine
ISSN:	1875-5100
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