Robust Optimization of Cyclic CO2 flooding through the Gas-Assisted Gravity Drainage process under geological uncertainties

The purpose of this research is to determine an estimate for actual optimal oil recovery through cyclic Gas-Assisted Gravity Drainage (GAGD) process in a heterogeneous sandstone reservoir under geological uncertainties. A robust optimization approach was adopted to determine the optimal durations of gas injection, soaking, and oil production under geological uncertainties. 100 stochastic reservoir realizations of the 3D permeability and porosity distributions were created to honor geological constraints. Ranking was applied through quantifying of reservoir oil response to select P10, P50, and, P90 that represent the overall reservoir uncertainty. A compositional reservoir flow simulation was used for the GAGD process performance evaluation. Approximately 200 simulation jobs were created, including the aforementioned durations and geological uncertainty parameters, through Design of Experiments (DoE). The Latin Hypercube Sampling was adopted to create these 200 simulation jobs that then evaluated by the compositional reservoir simulation to calculate the cumulative oil production by the end of 10 prediction years. The robust optimization approach was then applied to select the true optimal solution of the highest oil recovery by taking into account the geological uncertainties in permeability, porosity, and anisotropy models. The nominal optimization of one single realization was also adopted for the comparison. The robust optimization has shown its feasibility to increase oil production through the cyclic GAGD process from 4.535 to 4.62547 billion barrels. However, the nominal optimization case increased oil production to 5.9726 billion barrels. The presented robust optimization workflow under geological uncertainties resulted in higher oil recovery and net present value than nominal realization optimization, with providing degrees of freedom for the decision-maker to significantly reduce the project risk. It was specifically concluded that the robust optimal solution represents the most economically feasible solution to obtain the highest NPV through the GAGD process for a range $(30–80) per barrel oil prices. However, the base case and nominal solution (no geological uncertainties) were not economical when the oil price declines to be less than 36 and 32, respectively.