Correlations for Hydrocarbon-Gas Viscosity and Gas Density—Validation and Correlation of Behavior Using a Large-Scale Database

Abstract

The focus of this work is on the behavior of hydrocarbon-gas viscosity and gas density. The viscosity of hydrocarbon gases is a function of pressure, temperature, density, and molecular weight, while the gas density is a function of pressure, temperature, and molecular weight. This work presents new approaches for the prediction of gas viscosity and gas density for hydrocarbon gases over practical ranges of pressure, temperature, and composition. These correlations can be used for any hydrocarbon-gas production or transportation operations.In this work, we created a large database of measured gas viscosity and gas density. This database was used to evaluate existing models for gas viscosity and gas density. We also provide new models for gas density and gas viscosity, as well as optimization of existing models, using our new database.The objectives of this research are as follows:• To create a large-scale database of measured gas-viscosity and gas-density data. This database will contain all the information necessary to establish the applicability of various models for gas density and gas viscosity over a wide range of pressures and temperatures.• To evaluate a number of existing models for gas viscosity and gas density.• To develop new models for gas viscosity and gas density using our research database; these models are proposed and validated.For this study, we created a large database from existing sources available in the literature. The properties in our database include composition, viscosity, density, temperature, pressure, pseudoreduced properties, and the gas compressibility factor. We use this database to evaluate the applicability of existing models used to determine hydrocarbon-gas viscosity and hydrocarbon-gas density (or, more specifically, the gas z-factor). Finally, we developed new models and calculation approaches to estimate the hydrocarbon-gas viscosity, and we also provide an optimization of the existing equations of state (EOS) typically used for for the calculation of the gas z-factor. Introduction Hydrocarbon-Gas Viscosity. NIST-SUPERTRAP Algorithm.The state-of-the-art mechanism for the estimation of gas viscosity is most likely the computer program SUPERTRAP, developed at the U.S. Natl. Inst. of Standards and Technology (NIST). 1 SU-PERTRAP was developed from pure-component and mixture data and is stated to provide estimates within engineering accuracy from the triple point of a given substance to temperatures of 1,340.33°F and pressures of 44,100 psia. Because the SUPER-TRAP algorithm requires the composition for a particular sample, it generally would not be suitable for applications in which only the mixture gas gravity and compositions of any contaminants are known. Carr et al. Correlation.Carr et al. 2 developed a two-step procedure to estimate hydrocarbon-gas viscosity. The first step is to determine the gas viscosity at atmospheric conditions (i.e., a reference condition). Once estimated, the viscosity at atmospheric pressure is then adjusted to conditions at temperature and pressu...

Novel Density and Viscosity Correlations for Gases and Gas Mixtures Containing Hydrocarbon and Non-Hydrocarbon Components

“…The same procedures mentioned above for building the new gas density model by fuzzy logic approach were applied. (20) The resulting gas viscosity model is: This study 2.37 ---DAK-EOS (6) 2.77 4.23' Londono et al (19) Optimized DAK-EOS 2.81 3.1" Londono et al (19) Optimized NS-EOS 21.8 24.2" Beggs and Brill (11) 4.58 6. at atmosphere pressure was calculated by the Londono et al (19) correlation at 1 atmosphere. The training data points (ρ g , T Pr , M w , GV), k = 1,2,..., 5,350, are organized in a 5,350 × 4 matrix, as shown in Equation (20), and clustered using the FCM algorithm, as mentioned before, and the number of fuzzy rules are determined by the same fuzzy validity measurement in Equation (18).…”

“…Recently, Londono et al (19) modified the DAK-and NS-EOS by using optimized quadratic relations for the pseudo-critical pressure and temperature as functions of gas specific gravity. The fuzzy-set theory is an efficient tool for modelling the kind of uncertainty associated with vagueness, imprecision and/or a lack of information regarding a particular element of the problem at hand.…”

“…Recently, Londono et al (19) , developed a new correlation for hydrocarbon gas viscosity as a function of the gas viscosity at 1 atmosphere, gas density and temperature. He reported a 4.91% average absolute error for natural gas mixtures.…”

Initiation of a secondary hydraulic fracture and its interaction with the primary fracture

“…Gas properties including hydrocarbon gas density (or, more specifically, the gas z-factor), hydrocarbon gas viscosity and hydrocarbon gas compressibility are updated at each time step based on correlations presented in Ref. [11].…”

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

“…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.…”