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:1.3973

@Article{Fathinasab:2015:FPE,
  author =       "Mohammad Fathinasab and Shahab Ayatollahi and 
                 Abdolhossein Hemmati-Sarapardeh",
  title =        "A rigorous approach to predict nitrogen-crude oil
                 minimum miscibility pressure of pure and nitrogen
                 mixtures",
  journal =      "Fluid Phase Equilibria",
  volume =       "399",
  pages =        "30--39",
  year =         "2015",
  ISSN =         "0378-3812",
  DOI =          "doi:10.1016/j.fluid.2015.04.003",
  URL =          "http://www.sciencedirect.com/science/article/pii/S0378381215001946",
  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.",
  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