Air-injection-based recovery processes are receiving increased interest because of their high recovery potentials and applicability to a wide range of reservoirs. However, most operators require a certain level of confidence in the potential recovery from these (or any) processes before committing resources, which can be achieved with the use of numerical reservoir simulation.

In a previous paper, (Gutiérrez et al. 2009) it was proposed that after successful laboratory testing, analytical calculations and semiquantitative simulation models would be used for pilot design and further optimization of the actual operation. However, the specific steps for building the field-scale-simulation models were not addressed explicitly. This paper discusses a detailed workflow that can be followed to engineer an air-injection project using thermal reservoir simulation.

The first step of the simulation study involves the selection of a kinetic model that either can be developed specifically for the reservoir in question or taken from public literature. Second, the oil would be characterized in terms of the same pseudocomponents employed by the kinetic model, and relevant pressure/volume/temperature (PVT) data would be matched to develop a fluid model for the thermal simulator. This new fluid model is used in the field-scale-simulation model to history match the production history (i.e., before air injection) of the field. Third, relevant combustion-tube tests would be history matched to validate the kinetic model and refine the thermal data that would be entered into the field-scale model. Finally, the results and knowledge gained from the combustion-tube match(es) are applied to the field-scale model with the proper upscaling of some parameters. This simulation model would aid in selecting optimum well locations and operating strategies of the pilot. It would then be refined as the actual operation progresses to enhance its predictability and allow further optimization of the project.

Technical considerations, advantages, and limitations of each step of the workflow are discussed in detail. This paper also presents workflow variations and recommendations applicable to new and already-mature air-injection projects for which simulation models are being developed.

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