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An optimization study was conducted to determine the optimal operating pressure for the oil and gas separation vessels in the West Qurna 1 oil field. The ASPEN HYSYS software was employed as an effective tool to analyze the optimal pressure for the second and third-stage separators while maintaining a constant operating pressure for the first stage. The analysis involved 10 cases for each separation stage, revealing that the operating pressure of 3.0 Kg/cm2 and 0.7 Kg/cm2 for the second and third stages, respectively, yielded the optimum oil recovery to the flow tank. These pressure set points were selected based on serval factors including API gravity, oil formation volume factor, and gas-oil ratio from the flow tank. To improve the optimization process for separator sizes, a Python code was developed, combining the Newton Raphson Method (NRM), and Lang Cost Method (LCM), with Retention time calculations. In this process, total purchase cost was the objective function. Two design scenarios were examined, corresponding to throughput of 105,000 KBPD and 52,500 KBPD respectively. In the first scenario, the NRM, LCM, and Retention time methods within the Python code were employed, resulting in a three-stage separation train with costs of $1,534,630 for the first stage, $1,438,239 for the second stage and $1,025,978 for the third stage. The Total purchase cost for the separation train was $3,988,847. In the second scenario, utilizing two separators for each stage to process the same throughput resulted in lower costs, totaling $823,851.5 per stage and a total purchase cost of $2,471,553. These costs were calculated using the Lang Cost method, which included the material cost and utilized a Lang factor of 3.1 to determine the total purchase cost after adding shipping, installation, commissioning, and start-up expenses. The first scenario resulted in larger separators and higher costs, while the second scenario showed lower costs, although it required two vessels per stage to process the same throughput. It was observed that the separator efficiencies were influenced by retention time, with increased retention time leading to improved separator efficiency.