The Application Of Big Data Technology In Improving The Yield Of Reforming Gasoline

Maoming Petrochemical Company’s 1 million tons/year continuous reforming unit has been under high-load operating conditions for a long time.By adopting measures such as optimizing the raw materials and operating conditions,the production of gasoline has been improved to a certain extent,but there is still a gap from the expected value.In connection with the industrial big data analysis project carried out by Sinopec Corp.,this paper carries out related research and production practices for improving the yield of catalytic reformed gasoline based on big data technology.The paper relies on industrial analysis(big data)technology platform to carry out relevant research work.Based on nine real-time databases of reformer,LIMS,MES,HSE,and other systems,the correlation algorithm in big data analysis technology is used to perform data mining on these massive data,examining correlations and ignoring causality,simply through data-based,trying to find potential factors to improve the yield of gasoline.Through the excavation of the operation data of the device,it is found that the operational variables such as the F602 branch flow rate of the pre-hydro stripping column reboiler has a strong positive correlation with the gasoline yield.Based on industrial verification,industrial optimization is implemented.Achieved good results: After increasing the flow rate of the F602 branch of the stripping tower reboiler 6t/h,the gasoline yield increased by 0.14% to 0.42%.This measure improves the fractionation effect and reduces the following C5 components that do not undergo a reforming reaction into the reactor,thereby increasing the actual reforming feed,increasing the production capacity and achieving the purpose of increasing the output of gasoline.Achieved potential and efficiency enhancement,increased annual benefits by more than RMB 6,984,300,and achieved good economic and social benefits.