A rigorous approach to predict nitrogen-crude oil minimum miscibility pressure of pure and nitrogen mixtures
Created by W.Langdon from
gp-bibliography.bib Revision:1.7975
- @Article{Fathinasab:2015:FPE,
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author = "Mohammad Fathinasab and Shahab Ayatollahi and
Abdolhossein Hemmati-Sarapardeh",
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title = "A rigorous approach to predict nitrogen-crude oil
minimum miscibility pressure of pure and nitrogen
mixtures",
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journal = "Fluid Phase Equilibria",
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volume = "399",
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pages = "30--39",
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year = "2015",
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ISSN = "0378-3812",
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DOI = "doi:10.1016/j.fluid.2015.04.003",
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URL = "http://www.sciencedirect.com/science/article/pii/S0378381215001946",
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abstract = "Nitrogen has been appeared as a competitive gas
injection alternative for gas-based enhanced oil
recovery (EOR) processes. Minimum miscibility pressure
(MMP) is the most important parameter to successfully
design N2 flooding, which is traditionally measured
through time consuming, expensive and cumbersome
experiments. In this communication, genetic programming
(GP) and constrained multivariable search methods have
been combined to create a simple correlation for
accurate determination of the MMP of N2-crude oil,
based on the explicit functionality of reservoir
temperature as well as thermodynamic properties of
crude oil and injection gas. The parameters of the
developed correlation include reservoir temperature,
average critical temperature of injection gas, volatile
and intermediate fractions of reservoir oil and heptane
plus-fraction molecular weight of crude oil. A set of
experimental data pool from the literature was
collected to evaluate and compare the results of the
developed correlation with pre-existing correlations
through statistical and graphical error analyses. The
results of this study illustrate that the proposed
correlation is more reliable and accurate than the
pre-existing models in a wide range of thermodynamic
and process conditions. The proposed correlation
predicts the total data set (93 MMP data of pure and N2
mixture streams as well as lean gases) with an average
absolute relative error of 10.02percent. Finally, by
employing the relevancy factor, it was found that the
intermediate components of crude oil have the most
significant impact on the nitrogen MMP estimation.",
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keywords = "genetic algorithms, genetic programming, Minimum
miscibility pressure, Nitrogen, Lean gas, Constrained
multivariable search methods",
- }
Genetic Programming entries for
Mohammad Fathinasab
Shahab Ayatollahi
Abdolhossein Hemmati-Sarapardeh
Citations