Viscosity and Density Correlations for Hydrocarbon Gases and Pure and Impure Gas Mixtures

Abstract

In this work, newly developed correlations for hydrocarbon gas viscosity and density are presented. The models were built and tested using a large database of experimental measurements collected through extensive literature search. The database covers gas composition, viscosity, density, temperature, pressure, pseudoreduced pressure and temperature and compressibility factor for different gases, and pure and impure gas mixtures containing high amount of pentane plus and small concentration of nonhydrocarbon components. Gas viscosity and gas density models were built with 800 randomly selected data points extracted from the large database. The models were developed using the Alternating Conditional Expectations (ACE) algorithm. The models' accuracy was validated using the rest of the database, and their efficiency was tested against some commonly used correlations. The developed models seemed very efficient and they accurately predicted the experimental viscosity and density measurements, overcoming several constraints limiting the other correlations' accuracy with average absolute errors of 3.95% and 4.93% for the gas viscosity and gas density models, respectively. Sensitivity analysis of the proposed gas viscosity model indicated the positive impact of density and pseudoreduced temperature and the trivial impact of pseudoreduced pressure. The gas density model was found to be sensitive to all input parameters of pseudoreduced temperature, apparent molecular weight, and pseudoreduced pressure listed on the order of their impact. Negative impact was predicted for reduced temperature, whereas positive ones werenoticed for the pseudoreduced pressure and gas apparent molecular weight.

Keywords:

• alternating conditional expectations algorithms
• density
• natural gas
• viscosity