In this work, the oil treatment plant of Rumaila oil field in Iraq was simulated using Aspen HYSYS. Industrial data from the plant was applied for validating the simulation results. Optimizing the process was performed in both single-objective and multi-objective modes using a genetic algorithm. The process was optimized for reducing CO2, H2S, and CH4 in the outlet oil flow and the energy of the heater simultaneously by changing the molar flow and temperature of dry crude oil and water. The result shows that by decreasing the temperature of the dry crude oil and water, the amount of the consumed energy will decrease to a large extent, but the amount of CO2, H2S, and CH4 in the outlet oil will decrease. Also, it can be concluded that by separating more CO2, H2S, and CH4 in the outlet oil, the temperature should be increased, and as a result, the consumption of energy will be increased. The single-objective optimization results showed that the amount of CO2, H2S, and CH4 decreased by 46.52%, 43.94%, and 27.8%, respectively. On the other hand, the results from multi-objective optimizations illustrated a lower reduction n the amounts of CO2, H2S, and CH4. Consequently, it was concluded that single-objective optimization results were better than multiobjective optimizations.
