Object This study aims to investigate the influence of process parameters on the performance and energy consumption of the MDEA desulfurization unit in a natural gas purification plant of PetroChina Changqing Oilfield Company, and to clarify the directions and paths for process parameter optimization and technological improvement.

Method The factors influencing the H₂S and CO₂ contents in the product gas and the energy consumption of the MDEA desulfurization unit were studied through on-site tests and numerical simulations. In addition, the amine filtration system was modified to mitigate the negative impacts of solution oxidation and degradation on the process performance.

Result First, the controllable parameters had no significant effect on the product gas flow rate. Within the specified parameter ranges, both the H₂S mass concentration and the CO₂ mole fraction in the product gas met the requirements of Class 1 gas indicators specified in GB 17820—2018 Natural gas; thus, optimization of the product gas flow rate and quality using controllable parameters was unnecessary. Second, the change in the energy consumption of the desulfurization unit was mainly related to the coupling effect of the solution circulation flow rate and the feed gas temperature. In contrast, no interaction effect was observed between the lean solvent inlet temperature and the MDEA mass fraction. It is recommended that the unit operate with the following optimal controllable parameters: solution circulation flow rate of 60-64 m³/h, feed gas temperature of 0-27 ℃, lean solvent inlet temperature of 30-45 ℃, and MDEA mass fraction of 34%-42%. Under this operating mode, the energy consumption of the unit was reduced by 34%-42%. Third, under the influence of the actual ranges of uncontrollable parameters such as the feed gas flow rate and the H₂S and CO₂ contents in the feed gas, the H₂S and CO₂ contents in the product gas and the energy consumption of the unit remained relatively stable. Therefore, optimizing the controllable parameters alone was sufficient to meet the practical application requirements.

Conclusion The research results can provide technical support for the process intelligent optimization of the MDEA desulfurization unit in a natural gas purification plant with a processing capacity of 3.75×10⁶ m³/d.