Hybrid modelling for combined design optimization of CO2 removal and compression in raw natural gas treatment complexes

Abstract CO2 removal in raw natural gas is required to meet the sale gas specifications. The chemical solvent absorption method is one of the most commonly used technologies. The absorption-based processes, however, require an enormous amount of energy to regenerate the solvent, and are designed to discharge the captured CO2 into the atmosphere directly. The energy efficiency and greenhouse gas emissions should be considered in the gas treatment process. In this study, a new process, combining CO2 removal and compression, is proposed for raw natural gas treatment complexes. Compared with the conventional absorption-based processes, in the new process CO2 is not stripped from rich solvent in one distillation column but through multi-stage flash separators operating under different pressures and temperatures. The CO2 removed from each stage is then compressed separately to the proper pressure for carbon transportation and storage. A mathematical model is then developed to determine the optimum process configuration and operating conditions. A surrogate-based optimization framework is presented in order to strike a good balance between computational efficiency and model accuracy. The complex units are replaced by Kriging surrogate models. Aspen HYSYS is used to generated sampling points for the construction of surrogates. A method of dimension reduction is introduced to compact the surrogate models by selecting essential variables. Finally, a hybrid optimization model comprising of the surrogate models for “complex” units and explicit models for the rest of the process is formulated. The cases show the total annual cost of the CO2 removal and compression can be reduced by 20.6%–28.8% for different sweet gas purity specifications.