Compressibility factor model of sweet, sour, and condensate gases using genetic programming
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- @Article{Shokir2012785,
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author = "Eissa M. El-M. Shokir and Musaed N. El-Awad and
Adulhrahman A. Al-Quraishi and Osama A. Al-Mahdy",
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title = "Compressibility factor model of sweet, sour, and
condensate gases using genetic programming",
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journal = "Chemical Engineering Research and Design",
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year = "2012",
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volume = "90",
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number = "6",
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month = jun,
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pages = "785--792",
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note = "Special Issue on the 3rd European Process
intensification Conference",
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keywords = "genetic algorithms, genetic programming, Gas
compressibility factor, Sour gas, Condensate gas",
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ISSN = "0263-8762",
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URL = "http://www.sciencedirect.com/science/article/pii/S0263876211003911",
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DOI = "doi:10.1016/j.cherd.2011.10.006",
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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 J AlAwad
Adulhrahman A Al-Quraishi
Osama A Al-Mahdy
Citations