Development of ε-insensitive smooth support vector regression for predicting minimum miscibility pressure in CO2 flooding

Development of ε-insensitive smooth support vector regression for predicting minimum miscibility pressure in CO2 flooding

Successful design of a carbon dioxide (CO2) flooding in enhanced oil recovery projects mostly depends on accurate determination of CO2-crude oil minimum miscibility pressure (MMP). Due to the high expensive and time-consuming of experimental determination of MMP, developing a fast and robust metho...

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Bibliographic Details
Main Authors: Shahram Mollaiy-Berneti, Mehdi Abedi-Varaki
Format: Article
Language:English
Published: Prince of Songkla University 2018-02-01
Series:Songklanakarin Journal of Science and Technology (SJST)
Subjects:
CO2 flooding
minimum miscibility pressure
ε-insensitive smooth support vector regression
feed-forward neural network
radial basis function network
Online Access:http://rdo.psu.ac.th/sjstweb/journal/40-1/40-1-6.pdf

Internet

http://rdo.psu.ac.th/sjstweb/journal/40-1/40-1-6.pdf

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