An accurate empirical correlation for predicting natural gas viscosity

A smooth model for the estimation of gas/vapor viscosity of hydrocarbon fluids

“…Heidryan et al [19] also developed a correlation for gas viscosity prediction based on molecular weight, temperature and gas density. Sanjari et al [6] proposed a model based on reduced pressure and temperature. The last model for gas viscosity prediction is AlQuraishi and Shokir [20] which utilizes generalized regression neural networks.…”

“…As mentioned above, experimental measurements of gas viscosity have some problems and because of that, prediction of gas viscosity becomes essential in a lot of hydrocarbon gas engineering calculations including gas compression, gas metering, optimal exploitation, estimating the pressure gradient in gas wells, design of pipeline and surface facilities and phase behavior [2][3][4][5][6]. In what follows, the most commonly used correlations for gas viscosity in oil industry are presented.…”

“…However, this model can be used in a much wider range of reservoir and gas conditions.2: The proposed GEP model follows the actual physical trends perfectly and fits the experimental data points very well. Thus, it can be effectively employed in prediction of the viscosity of pure hydrocarbons and natural gas and it can be employed in any reservoir simulator.3: Lucas[15] correlation overestimates the gas viscosity value, while Carr et al[8], Sutton[17], Jossi et al[10], Dean and Stiel[11], Sanjari et al[6] and Heidarian B[19] correlations underestimate this value.4:The results of sensitivity analysis show that gas molecular weight has the biggest impact on gas viscosity, while pressure has the smallest impact on this value.…”

Review on Natural Gas Thermopysical Property Measurement Techniques

“…Sanjari et al [28] reported in recent study that common prediction methods for natural gas viscosity lead to large deviations when applied for high pressure -high temperature ranges, and thus, these methods should be applied with caution for reservoir estimations. This lack of accuracy for current predictive viscosity models, and the large economical impact of viscosity uncertainties, show the need of experimental accurate natural gas viscosity to analyze i) the effect of natural gas composition on viscosity for wide pressure -temperature ranges, and ii) the predictive performance of current viscosity analyze the predictive performance of current viscosity predictive models and developing more accurate predictive approaches.…”

“…Likewise, conditions of interest, especially the high pressure -high temperature conditions found in many new reservoirs that can be explored with current technologies [30], has a remarkable effect on natural gas viscosity, and discard the use of traditional measurement techniques. The analysis of published viscosity data in the open literature shows its scarcity both in the number of studied systems and the experimental conditions (high pressure data are almost absent) [28,31]. Therefore, systematic studies on natural gas viscosity has to be carried out in wide pressuretemperature ranges and as a function of mixture compositions, for selected mixtures representative of key reservoirs.…”