%0 Journal Article
%T Modeling of Two-Phase Gas Deviation Factor for Gas-Condensate Reservoir using Artificial 
Neural Network
%A Adedapo A. Omotosho
%A Oluwatoyin O. Akinsete
%J Journal Information: ISSN: Frequency: Journal DOI: Peer-review model: NAAS Score (2017): Digital Archiving: Advances in Research
%D 2018
%R 10.9734/AIR/2018/39401
%X In petroleum engineering, reservoir fluid characterization is of great importance. Accurate determination of the two-phase gas deviation factor is essential in modeling gas-condensate and gas reservoirs, pipeline flow and reserve estimation, this is because the reservoir fluid is in a two-phase state at pressures below the dew-point pressure. Correlations are replete for predicting single-phase gas deviation factor using different Equation of State (EOS), but no correlation have been found to accurately predict the two-phase gas deviation factor.
%U http://www.sciencedomain.org/abstract/23572