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Alireza Fazlali

Alireza Fazlali

Academic rank: Professor
ORCID: https://orcid.org/0000-0001-8970-2479
Education: PhD.
ScopusId: 15723406500
HIndex:
Faculty: Engineering
Address: Arak University
Phone:

Research

Title
Prediction of minimum miscibility pressure in oil reservoirs using a modified SAFT equation of state
Type
JournalPaper
Keywords
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Year
2013
Journal Fuel
DOI
Researchers Alireza Fazlali ، Mohammad Nikoukar ، Alireza Agha Aminiha ، Amir Hosein Mohammadi

Abstract

In a miscible gas flooding to heavy oil reservoirs, multiple-contact miscibility between injected gas and reservoir oil can be achieved at pressure greater than a minimum value that is referred to Minimum Miscibility Pressure (MMP). This research includes two parts: first, modification of simplified SAFT (mSSAFT) equation of state is derived to describe vapor-liquid equilibrium calculations and second, prediction of MMP according to forward multiple contact model is done. With respect to objective function, adjustable parameters of SSAFT and mSSAFT were obtained for 21 pure compounds. Comparison of AAD% of the results of mSSAFT, SSAFT and PR EOSs in predicting vapor pressure, liquid density and enthalpy shows that mSSAFT is the most accurate of all. Also, accuracy of these three EOSs for various mixtures has been verified, and the results confirm the reliability of mSSAFT EOS. At last, AAD% of MMP prediction by mentioned EOSs (mSSAFT is 2.20%, SSAFT is 3.25% and PR is 4.13%) proves that Statistical EOSs are more reliable than cubic EOS in modeling MMP.