The Z-factor  correlations for fluid mixtures provide fast computational procedures using the fluid mixture properties rather than multi-component procedures of Equation of State. 


These correlations are usually modelled through the pseudo-reduced fluid properties

Pseudo-reduced temperature

Pseudo-critical temperature

Pseudo-reduced pressure

Pseudo-critical pressure


Charts

Standing-Katz Z-factor correlation chart

Implicit Correlations


These correlations are quite accurate and work in a wide range of pressures and temperatures but computationally expensive and may have problems with convergence when approaching the critical temperature.

Dranchuk, Purvis and Robinson (1971)

Hall and Yarborough (1973)

Dranchuk and Abou-Kassem (1975)

Explicit Correlations


The explicit correlations do not have convergence issues, generate smooth derivatives for compressibility calculations and provide fast computing.

Artificial Neural Network correlations
Ahmed (2017)
Kareem (2016)
Brill & Beggs (1973)
Standing-Katz (1942)
Sanjari and Nemati’s Correlation (2012)
Azizi, Behbahani and Isazadeh’s Correlation (2010)
Heidaryan, Moghdasi and Rahimi’s Correlation (2010)


See also


Natural Science / Physics /Thermodynamics / Equation of State / Z-factor

Pseudo-Critical Point Correlations @model ]


Gaganis, An Efficient Method to Predict Compressibility Factor of Natural Gas Streams, energies-12-02577-v2, 2019.pdf

Moiseeva, Malyshev, Compressibility factor of natural gas determination by means of molecular dynamics simulations, AIP Advance, 2019doi.org:10.1063:1.5096618.pdf

Kareem, New explicit correlation for the compressibility factor of natural gas, JPEPT, 2016, doi.10.1007:s13202-015-0209-3.pdf

wareem

Univ Leeds

[pdf] Okoro Emeka Emmanuel ,Measurement of the Best Z-Factor Correlation Using Gas Well Inflow Performance Data in Niger-Delta, International Journal of Applied Engineering Research ISSN 0973-4562 Volume 12, Number 12 (2017)