The Tuning of the Todd and Longstaff Mixing Parameter in Limited Compositional Simulation to Optimize Recovery from a Gas Condensate Reservoir
Thesis
A gas condensate reservoir is a type of gas reservoir that exists when the reservoir temperature is between the critical temperature and the cricondentherm. Compositional simulators are used to simulate these types of reservoirs but they require a lot of input data and high CPU processing time. Black oil simulators have been employed to simulate these types of reservoirs by introducing a mixing parameter to determine the degree of mixing between the injected fluid and the fluid in place. This research focuses on the tuning of the Todd and Longstaff mixing parameter in limited compositional simulation to optimize recovery from a gas condensate reservoir. This research was achieved by studying the production performance of a condensate reservoir using a limited compositional simulator. Three different production schemes were analyzed in the case study namely, natural depletion, gas injection, and water alternating gas (WAG) injection. Comparative analysis was carried out for all production schemes in the case study to determine similarities and differences between the results from the fully compositional and limited compositional simulation. Both simulators were used to track the saturations and pressures at the layers in the model where the production well was completed. The tracked saturations and pressures were used to determine the impact of condensate banking on reservoir performance. A set of well configurations and injection patterns was used to evaluate the impact of varying the Todd and Longstaff mixing parameter on the gas condensate recovery and also to determine the optimal mixing parameter for gas injection and WAG injection in gas condensate reservoirs. Sensitivity analysis was employed to determine the effect of Todd and Longstaff mixing parameter, initial water saturation, and permeability anisotropy on the cumulative recovery. The results obtained from this study shows that; for a lean gas condensate reservoir, the results from the fully compositional and limited compositional simulation are not similar if the Todd and Longstaff mixing parameter is not optimized, natural depletion of gas condensate reservoirs is not very effective because of the condensate banking and low condensate recovery, gas injection and WAG process are the recommended methods to produce gas condensate reservoirs. It is concluded that for optimal recovery from a lean gas condensate reservoir the mixing parameter should be between 0.990 and 0.996, and permeability anisotropy has a significant effect on condensate recovery.