Created by W.Langdon from gp-bibliography.bib Revision:1.4420

@Article{Shokir2012785, author = "Eissa M. El-M. Shokir and Musaed N. El-Awad and Adulhrahman A. Al-Quraishi and Osama A. Al-Mahdy", title = "Compressibility factor model of sweet, sour, and condensate gases using genetic programming", journal = "Chemical Engineering Research and Design", volume = "90", number = "6", pages = "785--792", year = "2012", note = "Special Issue on the 3rd European Process intensification Conference", ISSN = "0263-8762", DOI = "doi:10.1016/j.cherd.2011.10.006", URL = "http://www.sciencedirect.com/science/article/pii/S0263876211003911", keywords = "genetic algorithms, genetic programming, Gas compressibility factor, Sour gas, Condensate gas", abstract = "Gas compressibility factor (z-factor) is necessary in most petroleum engineering calculations. The most common sources of z-factor values are experimental measurements, equations of state (EOS) and empirical correlations. There are more than twenty correlations available with two variables for calculating the z-factor from fitting Standing-Katz chart values in an EOS or just through fitting techniques. However, these correlations are too complex, which require initial value and longer computations, and have significant error. This work presents a new model for estimating z-factors of sweet gases, sour gases and gas condensates using genetic programming (GP). The z-factor model was developed using pseudo-reduced pressure, and pseudo-reduced temperature. Moreover, two new models of pseudo-critical pressure and temperature were built as a function of the gas composition (mol percent of C1-C7+, H2S, CO2, and N2) and the specific gravity of the C7+. The developed new GP-based model yields a more accurate prediction of gas z-factor compared to the commonly used correlations and EOS's.", }

Genetic Programming entries for Eissa M El-M Shokir Musaed N El-Awad Adulhrahman A Al-Quraishi Osama A Al-Mahdy