Prediction of two-phase compressibility factor in gas condensate reservoirs using genetic algorithm approach Online publication date: Mon, 25-Mar-2019
by Ehsan Kamari; Saber Mohammadi; Mohammad Mahdi Mohammadi; Mohsen Masihi
International Journal of Oil, Gas and Coal Technology (IJOGCT), Vol. 20, No. 3, 2019
Abstract: As experimental determination of two-phase compressibility factor in gas condensate reservoirs is expensive/time-consuming, developing a reliable theoretical-based method is vital for this purpose. Here, based on data of constant-volume-depletion experiments, genetic algorithm method was used to develop a correlation for estimating the two-phase compressibility factor in gas condensate reservoirs. The proposed correlation was validated with experimental data of five gas condensate reservoirs, and also compared with most reliable correlation presented in the literature by Rayes et al. (1992). It was found that the proposed correlation by genetic algorithm predicts the experimental values of two-phase compressibility factor with a good accuracy and better than the Rayes et al.'s (1992) correlation. [Received: July 30, 2016; Accepted: February 9, 2017]
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Oil, Gas and Coal Technology (IJOGCT):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email subs@inderscience.com
Our Blog 
Follow us on Twitter 
Visit us on Facebook