For offshore units the compactness is one of the most important factors to consider due to the limited space. Therefore, it is better to try to reduce the process equipment counts from process synthesis analysis particularly in offshore liquefaction units. This paper introduces a simplified integrated process that reduces equipment and operating cost without considerable loss of liquefaction efficiency. Moreover, the study performs economic analysis for a conventional co-production of liquefied natural gas (LNG) and NGL process compared to the new integrated process under the lean feed condition. The dual mixed refrigerant (DMR) cycle is selected for liquefaction. The genetic algorithm (GA) is chosen as optimization method in this study. The results show that the capital expenditure and operating cost can be reduced remarkably by the simplified integrated scheme with little loss of gross profit compared to the base case.
Natural gas is an international clean energy which increases speedily in East Asia (IGU, 2016). With increasing unconventional shale gas reservoirs in Australia and U.S. the demand of exploitation of lean gas reservoirs will increase in next few years (Gadelle, 2013). Therefore, design and economic evaluation of the integrated liquefaction and natural gas liquids (NGL) recovery process for lean feed is required to meet recent increasing demand for lean gas reservoirs.
When natural gas is liquefied at atmospheric pressure the volume will be significantly reduced about 1/600* volume of gaseous natural gas. Hence, LNG has economic advantages in long distance transportation. Because of the complex and energy intensive characteristics of liquefaction processes, a number of liquefaction technologies have been developed (Austbø et al., 2014). The representative processes are single mixed refrigerant (SMR), propane pre-cooled mixed refrigerant (C3MR), dual mixed refrigerant (DMR) and mixed fluid cascade (MFC) processes. The end flash gas was utilized in order to improve liquefaction energy efficiency for various liquefaction schemes including SMR and C3MR (Lim et al., 2014). The C3MR liquefaction process had been discussed to meet market demands for capacity and specifications (Pillarella et al., 2007). The optimal operating conditions of DMR process was obtained by adopting the combination of genetic algorithm (GA) and sequential quadratic programming (Lee et al., 2011). Economic analysis of SMR and N2 expander cycles were conducted for small scale liquefaction plants (Yin et al., 2008)
