Summary
Local displacement efficiency from CO2 gas injection is highly dependent on
the minimum miscibility pressure (MMP). Correlations are sometimes used to
estimate the MMP where the injected fluid may or may not contain impurities
such as methane. These correlations, however, are based on a limited set of
experimental data and, as such, are not widely applicable. They also do not
account accurately for the more complex condensing/vaporizing (CV) displacement
process.
This paper presents new MMP correlations for the displacement of
multicomponent oil by CO2 and impure CO2. The approach is to use recently
developed analytical theory for MMP calculations from equations of state (EOSs)
to generate MMP correlations for displacements by pure and impure CO2. The
advantage of this approach is that MMPs for a wide range of temperatures and
reservoir fluids can be calculated quickly and accurately without introducing
uncertainties associated with slimtube MMPs and other numerical methods. The
improved MMP correlations are based solely on the reservoir temperature, the
molecular weight of C7+, and the percentage of intermediates (C2–C6) in the
oil. The MMPs from the improved correlations are compared to currently used
correlations and 41 experimentally measured MMPs. Correlations are also
developed for impure-CO2 floods, in which the injection stream may contain up
to 40% methane. The new correlations are more accurate for a wider range of
conditions than the currently used correlations.
Introduction
Whorton et al. received a patent in 1952 to improve oil recovery by the
injection of CO2. CO2 injection has been ongoing ever since, primarily because
CO2 develops multicontact miscibility (MCM) with reservoir fluids at low
pressures. There are also potential environmental benefits of CO2 injection in
that subsurface sequestration of greenhouse gases has become an important U.S.
priority.
The MMP is an important optimization parameter in CO2 floods. Recoveries
from slimtube experiments often give a slope change at the MMP. Above the MMP,
slimtube recoveries (or local displacement efficiencies) typically do not
increase significantly with enrichment. Thus, the accurate determination of MMP
is important in gasflood design.
Pseudoternary diagrams traditionally have been used to explain the behavior
of multicontact miscible (MCM) gas-drive processes. Real oil displacements by
CO2, however, have recently been shown to have features of both vaporizing and
condensing drives. The 2D nature of pseudoternary diagrams often leads to
incorrect interpretations, especially for CV drives. Analytical theory has no
such restrictions and can be applied for any number of components. The CV
process greatly complicates the accurate estimation of MMP in that miscibility
is developed not at the leading edge (condensing region) or trailing edge
(vaporizing region) of the displacement, but in between the condensing and
vaporizing regions.
Four primary methods have been used in recent years to determine MMPs for
specific fluid displacements: slimtube experiments,10 compositional
simulation,12 mixing-cell models, and analytical methods. Each of these methods
has advantages and disadvantages. Slimtube experiments use real fluids but are
expensive and time consuming to perform and can give misleading results
depending on the level of physical dispersion present. Fine-grid compositional
simulations and mixing-cell models can suffer from numerical-dispersion effects
and are also time consuming to perform. Dispersion-free analytical methods are
often very fast, but like simulation and mixing-cell models, they rely on an
accurate fluid characterization by an EOS.
A variety of correlations for the estimation of the MMP have been developed
from regressions of slimtube data. Although less accurate, correlations are
quick and easy to use and generally require only a few input parameters. Hence,
they are very useful for fast screening of reservoirs for potential CO2
flooding. They are also useful when detailed fluid characterizations are not
available. One significant disadvantage of current MMP correlations is that the
regressions use MMPs from slimtube data, which are themselves uncertain.
Some MMP correlations require only the input of reservoir temperature and
the API gravity of the reservoir fluid. Other, more-accurate correlations
require reservoir temperature and the total C2–C6 content of the reservoir
fluid. A few require detailed EOS characterizations. In nearly all of the
correlations, the methane content of the oil is assumed to not affect the MMP
significantly. Orr et al. show why this is true using analytical theory.
© 2005. Society of Petroleum Engineers
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History
- Original manuscript received:
24 June 2004
- Revised manuscript received:
20 June 2005
- Manuscript approved:
5 August 2005
- Version of record:
15 October 2005
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