Using Analytical Solutions in Compositional Streamline Simulation of a Field-Scale CO2-Injection Project in a Condensate Reservoir
- Carolyn Jennifer Seto (Stanford University) | Kristian Jessen (Stanford University) | Franklin M. Orr (Stanford University)
- Document ID
- Society of Petroleum Engineers
- SPE Reservoir Evaluation & Engineering
- Publication Date
- August 2007
- Document Type
- Journal Paper
- 393 - 405
- 2007. Society of Petroleum Engineers
- 5.2.1 Phase Behavior and PVT Measurements, 5.4.3 Gas Cycling, 5.2 Reservoir Fluid Dynamics, 5.1 Reservoir Characterisation, 5.3.2 Multiphase Flow, 5.4.2 Gas Injection Methods, 5.5 Reservoir Simulation, 4.3.4 Scale, 5.1.5 Geologic Modeling, 4.1.5 Processing Equipment, 5.2.2 Fluid Modeling, Equations of State, 5.8.7 Carbonate Reservoir, 4.1.2 Separation and Treating, 5.7.2 Recovery Factors, 5.5.7 Streamline Simulation, 5.8.8 Gas-condensate reservoirs, 5.4 Enhanced Recovery, 5.4.9 Miscible Methods, 5.1.1 Exploration, Development, Structural Geology
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This paper applies compositional streamline simulation to model a real field-scale project that is a combination of enhanced condensate recovery and geologic storage of CO2. These processes are inherently compositional, and detailed compositional fluid descriptions must be used to represent the displacement behavior accurately. We demonstrate that compositional streamline simulation, along with the use of analytical solutions for condensate displacement, is computationally efficient enough to permit high resolution of spatial heterogeneity as well as detailed characterization of the fluid system.
We present a simulation study comparing streamline and finite-difference results for 2D and 3D examples to demonstrate that the compositional streamline method is an efficient computational method for modeling CO2 storage and condensate vaporization in gas reservoirs. Although the streamline method makes many simplifications regarding the effects of gravity and capillary crossflow, in heterogeneity-dominated systems such as the condensate system presented, comparison of finite-difference and streamline results confirms that these simplifications are reasonable.
Concerns about rising concentrations of CO2 in the atmosphere have led to consideration of CO2 injection into depleted gas reservoirs as a way to store CO2 that otherwise would be released into the atmosphere (Oldenburg and Benson 2002). Gas-reservoir settings may be attractive as potential CO2-storage sites because they are known to have a seal that can trap buoyant gas. Moreover, depleted gas reservoirs may contain condensate, a portion of which could be recovered by means of CO2 injection (Jessen and Orr 2004a), offsetting a portion of the costs involved in injection. In this paper, the interplay between CO2 storage and enhanced condensate recovery is examined by use of compositional streamline simulation.
Gas-cycling schemes for enhanced condensate recovery are inherently compositional because condensate is moved primarily by transferring components to the mobile vapor phase. Hence, evaluation of the performance of such processes requires the use of compositional simulation. Recovery efficiency of a gas-injection scheme is determined partly by the local displacement efficiency and partly by fluid flow within the reservoir. Local displacement efficiency is controlled by the phase behavior of mixtures of the injection gas with the fluids present in the reservoir, which is, in turn, strongly influenced by the fluid description used for equation-of-state calculations of phase behavior. Fluid flow is often controlled by reservoir heterogeneities. Breakthrough of injected CO2 at production wells will limit the amount of economically recoverable condensate, influencing the portion of the cost of CO2 storage that can be offset by gas and condensate production. Therefore, accurate evaluation of the performance of a gas-cycling scheme requires both high-resolution representation of heterogeneity in the reservoir and use of an adequate number of components to describe the phase behavior of the fluid.
Finite-difference compositional simulation is the conventional way to solve such problems. This approach involves solving a material balance written for each component, for each reservoir element (gridblock), in each timestep of the simulation, requiring at least one flash calculation per gridblock per timestep. For large models or complex fluid descriptions, this method can be sufficiently expensive computationally that field-scale calculations are impractically slow. To reduce computation time, current industry practice is to simplify the geological model and fluid description. As a result, there is clearly some loss of accuracy resulting from the less-detailed representation of phase behavior and reservoir heterogeneities, as well as from the effects of numerical errors caused by the use of large gridblocks.
An alternative to conventional finite-difference compositional simulation is compositional streamline simulation (Thiele et al. 1997; Crane et al. 2000; Jessen and Orr 2002). In this approach, the flow is represented as a series of 1D displacements along streamlines. For more details on streamline simulation, see the review by King and Datta-Gupta (1998).
In reservoir displacements that are dominated by effects of heterogeneities, streamline locations change slowly; hence, streamlines can be updated infrequently. The resulting simulations run much faster than comparable finite-difference simulations (Thiele et al. 1997; Jessen and Orr 2002)if an efficient method is available for solving the 1D compositional flow problem.
|File Size||3 MB||Number of Pages||13|
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