Analysis and forecasting of the coking process of oil residues of the Atyrau oil refinery

Background: The deep processing of hydrocarbon raw materials represents the most significant challenge in the oil refining. Nowadays, there are various technologies available worldwide to process heavy oil residues, which enhance the yield of light petroleum products. Among these, delayed coking is regarded as one of the most promising approaches.

Aim: To investigate how the properties of processed raw materials affect the quantitative and qualitative indicators of coking products, we conducted tests using fuel oil samples from the Atyrau Oil Refinery, as well as flux and tar obtained through vacuum distillation followed by subsequent coking at the pilot unit.

Materials and methods: A pilot delayed coking unit was employed for the systematic processing of heavy oil residues. Additionally, mathematical modelling and analysis of the experimental results have been performed to predict the behaviour and outcomes of the coking process under investigation.

Results: The article presents the findings from studies conducted on the coking processes of fuel oil, flux and tar sourced from the Atyrau Oil Refinery. The volatile matter yield index for “crude” coke derived from tar decreases is observed to decrease to 7.1%, while for “crude” coke from fuel oil and flux are 7.8% and 7.4%, respectively. The ash content of coke obtained from tar is measured at 0.29%, whereas samples from fuel oil and flux yield ash contents of 0.23% and 0.26%. These measured values of ash content, volatile matter yield, and the mass fraction of silicon, iron, and vanadium for coke obtained from tar, meet the technical requirements for coke. Additionally, a mathematical prediction of the process was conducted, employing express determination to assess both qualitative and quantitative indicators of the resulting products.

Conclusion: Based on experimental data of the delayed coking unit of Atyrau oil refinery, better quality coke was obtained at the processing of tar compared to the processing of fuel oil and flux. The proposed model can be used to predict the coking process by express-determination of qualitative and quantitative indicators of the obtained products. The developed model can be used for personnel training in the field of modelling technological processes, since it does not require in-depth knowledge of programming, which makes it suitable for the initial training of specialists.