Natural gas is one of the main sources of energy. Due to the abrupt change of oil and gas price in the global market, it is important to improve the production process and make it profitable in a sustainable manner. The purpose of the current study was to further enhance the performance of the methyl diethanolamine (MDEA) process plant by retrofitting the NG sweetening plant and subsequent multi-criteria optimization studies. Most of the literature studies focused on modeling and sensitivity analysis with little attention to the retrofitting aspects of the gas sweetening unit. Therefore, process retrofitting and simultaneous multi-objective optimization of the natural gas cleaning process using an elitist nondominated sorting genetic algorithm was carried out for the methyl diethanolamine solvent to improve the performance of the absorption well as regeneration column. Seven operating parameters and four conflicting objective functions were considered to formulate two-objective, three-objective, and four-objective optimization problems. Two separate models, i.e., (1) base case and (2) improved retrofitting case, were developed in ProMax process simulator software, and these were validated with actual plant data. All the optimization problems were solved with the base model and improved retrofitting model, and the Pareto optimal fronts were obtained. Up to 17.5% reduction on process safety indicator damage index (DI) was obtained for the lean-vapor compression (LVC) plant configuration considering the same actual plant return on investment (ROI) of 97.44% without affecting H2S removal efficiency. The retrofitted process with LVC can achieve a 42% reduction of acidification potential (AP) and 29% reduction of global warming potential (GWP) compare to the normal process. Therefore, the LVC process can give enhanced plant performance with H2S removal of 99.38%, which leads to the improved cleaner production of natural gas. However, the retrofitted process provides a comparative economic benefit than the existing process.
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