Hydrocarbon gas often contains some amounts of heavier hydrocarbons and non-hydrocarbon components that contribute to its properties (i.e., viscosity and density). Prediction of the density and viscosity values for hydrocarbon gases is necessary in several hydrocarbon gas engineering calculations such as calculation of gas reserves, gas metering, gas compression, estimating the pressure gradient in gas wells and design of pipeline and surface facilities. Literature correlations for the density and viscosity of pure hydrocarbon gas such as methane, ethane, propane, butane and isobutene are available. However, wide-ranging and accurate correlations for predicting the gas viscosity and density are not available for gas mixtures associated with heavier hydrocarbon components and impurities components such as carbon dioxide and nitrogen, helium, and hydrogen sulphide. This paper presents two new models for estimating the density and viscosity of pure hydrocarbon gases and hydrocarbon gas mixtures containing high amount of pentane plus and small concentration of none-hydrocarbon components (i.e., carbon dioxide, nitrogen, and helium), over a wide range of temperature and pressure, on the basis of fuzzy logic approach. The density model was developed using apparent molecular weight, pseudoreduced temperature, and pseudoreduced pressure. However, the viscosity model was developed using density, apparent molecular weight, and pseudoreduced temperature. The fuzzy models were derived from 5350 measurements of density and viscosity of various pure gases and gas mixtures. The partitioning of the input space into fuzzy regions, represented by the individual rules, was obtained through fuzzy clustering. Accuracy of the new fuzzy models were compared to various literature correlations by blind test using 1460 measurements of density and viscosity. The results show that the new fuzzy models are more accurate than the compared correlations.
Accurate determination of the density, viscosity, and phase behaviour of pure hydrocarbon gases and hydrocarbon gas mixtures is essential for reliable reservoir characterization and simulation and hence for optimum usage and exploitation. The variety of possible natural gas mixtures at different conditions of interest preclude obtaining the relevant data by experimental means alone, thus requiring the development of prediction methods. Natural gas is a mixture of many components. Wide ranging correlations for the viscosity of the lower alkanes, such as methane, ethane, propane, butane and iso-butane have already been developed and are available in the literature [1–3]. However, wide-ranging correlations are often not readily available for many of the higher alkanes and impurities such as carbon monoxide and hydrogen sulfide. These fluids may be present in small quantities in natural gas and are important when modeling the mixture properties [4].
In this paper, the fuzzy logic approach was applied for developing new efficient empirical models to estimate density, and viscosity of pure hydrocarbon gases (from Methane to pentane) and hydrocarbon gas mixtures (different gas mixtures of Methane with Ethane and/or Propane,..., n-Decane) containing small concentration of non-hydrocarbon components (i.e., carbon dioxide, nitrogen, and helium), over a wide range of temperature (0–238 °C) and pressure (1–890 bar). The new models are designed to be simpler and more efficient than the existing equations of state "EOS".
