An equation of state compositional model capable of simulating water vaporization is presented. This approach treats water as a component among other species in the hydrocarbon phases and allows for mass transfer between the aqueous phase and the hydrocarbon phases. The model is validated against single cell PVT experiments. The impact of this formulation on the basic compositional model equations and the solution of the nonlinear and linear system of equations will be discussed. The simulator incorporates a sophisticated well management scheme with a model of a gas plant to evaluate performance under various facility constraints.
The application of this simulator in the management of the Arun gas-condensate reservoir in Indonesia is presented. The first phase of this 5000 cell, 8 component, 50 well study involves establishing reservoir parameters by matching historical pressure performance of individual wells. Predicted total field wellstream composition and cluster condensate gas ratios match historical data very well. The accuracy with which this formulation simulates water vaporization is demonstrated by comparing predicted and measured water vapor production. In the second phase, the reservoir model is used to predict future performance. This simulator has the unique capability of simulating gas processing plant operation to calculate and predict product streams such as LNG, LPG and stabilized condensate. This feature allows one to specify future demand for a product such as LNG. The specification is translated into exact individual well production rates based on their produced well stream composition. Water evaporation has a significant effect on reservoir performance and an even greater effect on tubing flow performance. The model predicts injection gas profiles, extent of retrograde condensation, subsequent revaporization by injection gas, and composition and saturation distributions across the reservoir. The utility of the model predictions in the design of surface facilities, in the determination of well requirements, and in developing strategies to improve product recoveries will be discussed.