Simplified 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 the behavior of gas viscosity and gas density for hydrocarbon gas mixtures. 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 an extensive database of measured gas viscosity and gas density (>5000 points for gas viscosity and >8000 points for gas density). This database was used to evaluate existing models for gas viscosity and gas density. In this work we provide new models for gas density and gas viscosity, as well as optimization of existing models using this database. The objectives of this research are: To create a large-scale database of measured gas viscosity and gas density data which contains all of the information required 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, validated, and presented graphically. For this study, we created a large-scale database of gas properties using existing sources available in the literature. Our database includes: composition, viscosity, density, temperature, pressure, pseudoreduced properties and the gas compressibility factor. We use this database to evaluate the applicability of the existing models used to estimate hydrocarbon gas viscosity and gas density (or more specifically, the zfactor). Finally, we provide new models and calculation procedures for estimating hydrocarbon gas viscosity and we also provide new optimizations of the existing equations-of-state (EOS) typically used for the calculation of the gas z-factor.

Imbibition of hydraulic fracturing fluids into partially saturated shale

“…Two bounding values were considered for the viscosity of the fracturing fluid (wetting phase) ‐ slick water with a viscosity of 4 cP [ Kostenuk and Browne , ] and fresh water with a viscosity of 0.5 cP [ U.S. National Institute of Standards and Technology , ]. The bounding values for the nonwetting phase viscosity represent methane and medium crude oil, with viscosities of 0.02 cP and 15 cP respectively [ Londono et al ., ]. We include different viscosities in the nonwetting phase because the crude oil to natural gas ratio is high in the Bakken and low in the Marcellus [ U.S. Energy Information Administration , ], which could lead to significantly different imbibed volumes.…”

A Dynamic Reserve Evaluation Method for an Ultra-Deep Fractured Tight Sandstone Gas Reservoir

“…Other reservoir parameters were set as shown in Table 1. The viscosity of natural gas was calculated using the viscosity correlation proposed by Londono et al [37,38], and the gas compressibility factor was determined [39]. The relationships between the gas viscosity µ g , compressibility factor C g , formation volume factor B g , and pressure are shown in Figure 5.…”

Prediction of Natural Gas Z-Factor by Using ANN Method

“…Among the several EOSs for natural gas, AGA8 [6] equation is the well-known equation. Londono et al [7] proposed simple correlation to calculate hydrocarbon gases density. Gysling [8] reported an aeroelastic model of Coriolis mass and density meter.…”