Improved MMP Correlation for CO2 Floods Using Analytical Theory
- Hua Yuan (PetroTel Inc.) | Russell T. Johns (U. of Texas at Austin) | Azubuike M. Egwuenu (U. of Texas at Austin) | Birol Dindoruk (Shell Intl. E&P Inc.)
- Document ID
- Society of Petroleum Engineers
- SPE Reservoir Evaluation & Engineering
- Publication Date
- October 2005
- Document Type
- Journal Paper
- 418 - 425
- 2005. Society of Petroleum Engineers
- 5.4.2 Gas Injection Methods, 5.6.4 Drillstem/Well Testing, 5.5.1 Simulator Development, 5.3.2 Multiphase Flow, 5.2 Reservoir Fluid Dynamics, 5.2 Fluid Characterization, 4.6 Natural Gas, 4.1.2 Separation and Treating, 4.1.5 Processing Equipment, 5.2.1 Phase Behavior and PVT Measurements, 5.5 Reservoir Simulation, 5.2.2 Fluid Modeling, Equations of State, 5.4 Enhanced Recovery
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Local displacement efficiency from CO2 gas injection is highly dependent onthe minimum miscibility pressure (MMP). Correlations are sometimes used toestimate the MMP where the injected fluid may or may not contain impuritiessuch as methane. These correlations, however, are based on a limited set ofexperimental data and, as such, are not widely applicable. They also do notaccount accurately for the more complex condensing/vaporizing (CV) displacementprocess.
This paper presents new MMP correlations for the displacement ofmulticomponent oil by CO2 and impure CO2. The approach is to use recentlydeveloped analytical theory for MMP calculations from equations of state (EOSs)to generate MMP correlations for displacements by pure and impure CO2. Theadvantage of this approach is that MMPs for a wide range of temperatures andreservoir fluids can be calculated quickly and accurately without introducinguncertainties associated with slimtube MMPs and other numerical methods. Theimproved MMP correlations are based solely on the reservoir temperature, themolecular weight of C7+, and the percentage of intermediates (C2-C6) in theoil. The MMPs from the improved correlations are compared to currently usedcorrelations and 41 experimentally measured MMPs. Correlations are alsodeveloped for impure-CO2 floods, in which the injection stream may contain upto 40% methane. The new correlations are more accurate for a wider range ofconditions than the currently used correlations.
Whorton et al. received a patent in 1952 to improve oil recovery by theinjection of CO2. CO2 injection has been ongoing ever since, primarily becauseCO2 develops multicontact miscibility (MCM) with reservoir fluids at lowpressures. There are also potential environmental benefits of CO2 injection inthat subsurface sequestration of greenhouse gases has become an important U.S.priority.
The MMP is an important optimization parameter in CO2 floods. Recoveriesfrom slimtube experiments often give a slope change at the MMP. Above the MMP,slimtube recoveries (or local displacement efficiencies) typically do notincrease significantly with enrichment. Thus, the accurate determination of MMPis important in gasflood design.
Pseudoternary diagrams traditionally have been used to explain the behaviorof multicontact miscible (MCM) gas-drive processes. Real oil displacements byCO2, however, have recently been shown to have features of both vaporizing andcondensing drives. The 2D nature of pseudoternary diagrams often leads toincorrect interpretations, especially for CV drives. Analytical theory has nosuch restrictions and can be applied for any number of components. The CVprocess greatly complicates the accurate estimation of MMP in that miscibilityis developed not at the leading edge (condensing region) or trailing edge(vaporizing region) of the displacement, but in between the condensing andvaporizing regions.
Four primary methods have been used in recent years to determine MMPs forspecific fluid displacements: slimtube experiments,10 compositionalsimulation,12 mixing-cell models, and analytical methods. Each of these methodshas advantages and disadvantages. Slimtube experiments use real fluids but areexpensive and time consuming to perform and can give misleading resultsdepending on the level of physical dispersion present. Fine-grid compositionalsimulations and mixing-cell models can suffer from numerical-dispersion effectsand are also time consuming to perform. Dispersion-free analytical methods areoften very fast, but like simulation and mixing-cell models, they rely on anaccurate fluid characterization by an EOS.
A variety of correlations for the estimation of the MMP have been developedfrom regressions of slimtube data. Although less accurate, correlations arequick and easy to use and generally require only a few input parameters. Hence,they are very useful for fast screening of reservoirs for potential CO2flooding. They are also useful when detailed fluid characterizations are notavailable. One significant disadvantage of current MMP correlations is that theregressions use MMPs from slimtube data, which are themselves uncertain.
Some MMP correlations require only the input of reservoir temperature andthe API gravity of the reservoir fluid. Other, more-accurate correlationsrequire reservoir temperature and the total C2-C6 content of the reservoirfluid. A few require detailed EOS characterizations. In nearly all of thecorrelations, the methane content of the oil is assumed to not affect the MMPsignificantly. Orr et al. show why this is true using analytical theory.
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