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Title

Prediction of Bubble Point Pressure Using Artificial Neural Network

Year: 1388
COI: ICHEC06_537
Language: EnglishView: 1,167
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Authors

Kiumars kamalyar - Petroleum University of Technology, Ahvaz, Iran
Morteza Yeganeh - Petroleum University of Technology, Ahvaz, Iran

Abstract:

Knowledge of reservoir fluid properties is very important in various reservoir engineering computations such as material balance calculations, well testing, reserve estimating, and numerical reservoir simulations. Ideally, those data should be obtained experimentally. On some occasions, these data are not either available or reliable; then, empirically derived correlations are used to predict PVT properties. An enormous amount of PVT data has been collected and correlated over many years for different types of hydrocarbon systems. Almost all of these correlations were developed by linear or nonlinear multiple regression or graphical techniques. Artificial neural networks (ANN), once successfully trained, offer an alternative way to obtain reliable results for the determination of crude oil PVT properties.

Keywords:

Paper COI Code

This Paper COI Code is ICHEC06_537. Also You can use the following address to link to this article. This link is permanent and is used as an article registration confirmation in the Civilica reference:

https://civilica.com/doc/77809/

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kamalyar, Kiumars and Yeganeh, Morteza,1388,Prediction of Bubble Point Pressure Using Artificial Neural Network,06th International Congress on Chemical Engineering,Hajjiabad,https://civilica.com/doc/77809

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  • The 6th lhterhatiohal Chehical Eigiheering Congress _ Exhibition (ICHEE 2009) ...
  • The 6th lhterhatiohal Chehical Eigiheering Congress _ Exhibition (ICHEE 2009) ...

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Type of center: دانشگاه دولتی
Paper count: 2,136
In the scientometrics section of CIVILICA, you can see the scientific ranking of the Iranian academic and research centers based on the statistics of indexed articles.

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