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Abstract
Due to simplicity, consistency and flexibility, the Lohrenz-Bray-Clark (LBC)
correlation is the most widely used viscosity model in reservoir engineering.
Unfortunately the LBC viscosity model does not accurately predict liquid
viscosity. Consequently it is necessary to tune the calculated viscosities.
Tuning of the LBC viscosity model is normally performed by modifying the
critical volumes of the C7+
components and/or the LBC coefficients. The tuning procedure is not straight
forward. Special attention is required for three challenging fluid systems:
viscosity of the condensed oil from gas condensates, viscosity changes in
connection with gas injection and viscosity of heavy oils.
This paper describes guidelines for proper tuning and consistency checking
of the LBC viscosity model. Instead of using various correlation-estimated
critical volumes for the C7+ components as in most PVT software, the
initial critical volumes of the C7+ components are calculated based
on component viscosities estimated from a dead-oil empirical correlation.
Global regression to the measured viscosity data is then made with modifiers to
the initial critical volumes. This procedure guarantees monotonically
increasing component viscosities for the C7+ components. In the case
of any regression on LBC coefficients, it is very important to maintain a
monotonic relation of viscosity vs. reduced density.
Viscosity data from three Norwegian offshore reservoirs, from gas condensate
to heavy oil, are used as examples. The guidelines for tuning the LBC viscosity
model presented in this paper provide practical insight and understanding of
how to apply the LBC viscosity model to various fluid systems.
Introduction
Viscosity is an important physical property for fluid flow calculations in
reservoirs, tubing and pipelines. Empirical correlations and
corresponding-states models have been developed for modeling viscosity under
various pressure and temperature conditions.
The Lohrenz-Bray-Clark (LBC) correlation for dense gas mixtures was
published in 1964 by Lohrenz et al.1 based on the original work by
Jossi et al.2 for pure substances. The detailed formula is given in
the next section.
The prediction capability of gas viscosity with the LBC correlation is
reasonable, while the prediction of oil viscosity is usually poor. Other more
recent corresponding-states viscosity models show better prediction capability
for oil viscosity, for example, the Corresponding States Principle (CSP) method
proposed by Pederson et al.3 Due to the simplicity and flexibility,
the LBC correlation is the most widely used viscosity model, especially in most
commercial compositional simulators.
The LBC correlation is very sensitive to mixture density and to the critical
volumes of the heavy components. Adjustment of critical volumes of the heavy
components and/or the LBC coefficients to match the experimental oil viscosity
is usually necessary. However, the tuning procedure is not straight forward,
especially for three challenging fluid systems: viscosity of the condensed oil
from gas condensates, viscosity changes in connection with gas injection and
viscosity for heavy oils.
Conventional tuning methods usually start with the initial critical volumes
which are estimated based on various empirical correlations. The resulting
component viscosity of the C7+ components is often non-monotonically
increasing with molecular weight. This can potentially cause problems in
compositionally sensitive processes, for example, viscosity of the condensed
oil from gas condensates, and viscosity changes during gas injection.
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