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Three different variations of PSO algorithms, i.e. Canonical, GaussianBare-bone and L\'evy Bare-bone PSO, are tested to optimize the ultimate oilrecovery of a large heavy oil reservoir. The performance of these algorithmswas compared in terms of convergence behaviour and the final optimizationresults. It is found that, in general, all three types of PSO methods are ableto improve the objective function. The best objective function is found byusing the Canonical PSO, while the other two methods give similar results. TheGaussian Bare-bone PSO may picks positions that are far away from the optimalsolution. The L\'evy Bare-bone PSO has similar convergence behaviour as theCanonical PSO. For the specific optimization problem investigated in thisstudy, it is found that the temperature of the injection steam, CO2 compositionin the injection gas, and the gas injection rates have bigger impact on theobjective function, while steam injection rate and the liquid production ratehave less impact on the objective function.

Application of particle swarm optimization for enhanced cyclic steam stimulation in a offshore heavy oil reservoir