Summary
Accurate performance prediction of miscible enhanced-oil-recovery (EOR)
projects or CO2 sequestration in depleted oil and gas reservoirs relies in part
on the ability of an equation-of-state (EOS) model to adequately represent the
properties of a wide range of mixtures of the resident fluid and the injected
fluid(s). The mixtures that form when gas displaces oil in a porous medium
will, in many cases, differ significantly from compositions created in swelling
tests and other standard pressure/volume/temperature (PVT) experiments.
Multicontact experiments (e.g., slimtube displacements) are often used to
condition an EOS model before application in performance evaluation of miscible
displacements. However, no clear understanding exists of the impact on the
resultant accuracy of the selected characterization procedure when the fluid
description is subsequently included in reservoir simulation.
In this paper, we present a detailed analysis of the quality of two
different characterization procedures over a broad range of reservoir fluids
(13 samples) for which experimental swelling-test and slimtube-displacement
data are available. We explore the impact of including swelling-test and
slimtube experiments in the data reduction and demonstrate that for some
gas/oil systems, swelling tests do not contribute to a more accurate prediction
of multicontact miscibility. Finally, we report on the impact that use of EOS
models based on different characterization procedures can have on recovery
predictions from dynamic 1D displacement calculations.
Introduction
During the past few decades, a significant effort has been invested in the
studies and development of improved-oil-recovery processes. From a technical
point of view, gas injection can be a very efficient method for improving the
oil production, particularly in the case when miscibility develops during the
displacement process. The lowest pressure at which a gas should be injected
into the reservoir to obtain the multicontact miscible displacement—the minimum
miscibility pressure (MMP)—has consequently attained a very important status in
EOR studies.
Various methods for measuring and calculating the MMP have been proposed in
the literature. Many of these are based on simplifications such as the ternary
representation of the compositional space. This method fails to honor the
existence of a combined mechanism controlling the development of miscibility in
real reservoir fluids. Zick (1986) and Stalkup (1987) described the existence
of the condensing/vaporizing mechanism. They showed that the development of
miscibility (MMP) in multicomponent gas-displacement processes could,
independent of the mechanism controlling the development of miscibility, be
predicted accurately by 1D compositional simulations. A semianalytical method
for predicting the MMP was later presented by Wang and Orr (1997), who played
an important role in the development and application of the analytical theory
of gas-injection processes. Jessen et al. (1998) subsequently developed an
efficient algorithm for performing these calculations, reducing the MMP
calculation time to a few seconds even for fluid descriptions of 10 components
or more. Later, Jessen et al. (2001) used this approach to generate approximate
solutions to the dispersion-free, 1D-displacement problem for multicomponent
gas-injection processes.
Analytical and numerical methods for predicting the performance of a
gas-injection process depend on an EOS to predict the phase behavior of the
mixtures that form in the course of a displacement process. The role of the
phase behavior in relation to numerical diffusion in compositional reservoir
simulation has been pointed out previously by Stalkup (1990) and by Stalkup et
al. (1990). Recently, Jessen et al. (2004) proposed a method to quantify the
interplay of the phase behavior and numerical diffusion in a finite-difference
simulation of a gas-injection process. By analyzing the phase behavior of the
injection-gas/reservoir-fluid system, a measure of the impact, referred to as
the dispersive distance, can be calculated. The dispersive distance is useful
when designing and interpreting large-scale compositional reservoir
simulations.
© 2007. Society of Petroleum Engineers
View full textPDF
(
1,341 KB
)
History
- Original manuscript received:
27 July 2005
- Meeting paper published:
9 October 2005
- Revised manuscript received:
11 February 2007
- Manuscript approved:
17 February 2007
- Version of record:
20 October 2007
View Cart
