A Precise Mathematical Correlation to Estimate Product Yield of Delayed Coking Units

Document Type : Research Paper

Authors

1 Faculty of Chemical and Petroleum Engineering, University of Tabriz, Tabriz, Iran

2 Mechanical Engineering Department, King Fahd University of Petroleum and Minerals

Abstract

Typical models are employed to estimate the product yields of delayed coking units using complicated and multistep calculations. In current study, a new first-order mathematical model have been proposed to estimate delayed coking products yield utilizing the Volk’s model as the baseline. The modified coefficients of Volk's model for industrial level are 0.634, 0.589, 1, and 1.116 for gas, gasoline, gasoil, and coke yield prediction, respectively. In Compare to other models, the proposed model showed very close and similar trend with industrial data in yield prediction, and the average error for gas production was 0.25%. For the gasoline, almost all of the other models have overestimated efficiency. However, current model prediction was obtained close to the industrial data with average error of 14 % that is almost three times better than the Volk’s model prediction (which was the most accurate model previously). The industrial data for the gasoil was underestimated by all previous models. However, the average error of proposed model for prediction of gasoil yield was 13% while other models’ estimation error is much higher. For the coke production, this newly developed model is the most accurate one compared to other predictive models.

Keywords

References

  1. Zhao, H., Ierapetritou, M. G., Shah, N. K. and Rong, G. 2017. "Integrated model of refining and petrochemical plant for enterprise-wide optimization", Computers & Chemical Engineering, 97, pp. 194-207. https://doi.org/10.1016/j.compchemeng.2016.11.020
  2. Zhang, W., Huang, D., Wang, Y. and Wang, J. 2008. "Adaptive State Feedback Predictive Control and Expert Control for a Delayed Coking Furnace", Chinese Journal of Chemical Engineering, 16(4), pp. 590-598. https://doi.org/10.1016/S1004-9541(08)60126-3
  3. Stratiev, D., Shishkova, I., Tankov, I. and Pavlova, A. 2019. "Challenges in characterization of residual oils. A review", Journal of Petroleum Since and Engineering, 178, pp. 227-250. https://doi.org/10.1016/j.petrol.2019.03.026
  4. Carrillo, J. A. and Corredor, L. M. 2013. "Upgrading of heavy crude oils: Castilla", Fuel Processing Technology, 109, pp. 156-162. https://doi.org/10.1016/j.fuproc.2012.09.059
  5. Singh, J., Kumar, S. and Garg, M. O. 2012. "Kinetic modelling of thermal cracking of petroleum residues: A critique", Fuel Processing Technology, 94(1), pp. 131-144. https://doi.org/10.1016/j.fuproc.2011.10.023
  6. Volk, M., Wisecarver, K. and Sheppard, C. 2003. "Fundamentals of Delayed Coking Joint Industry Project", Tulsa, Oklahoma.
  7. Sawarkar, A. N., Pandit, A. B. and Joshi, J. B. 2007. "Studies in Coking of Arabian Mix Vacuum Residue", Chemical Engineering Research and Design, 85(4), pp. 481-491. https://doi.org/10.1205/cherd06159
  8. Asgharzadeh-Shishavan, R., Ghashghaee, M. and Karimzadeh, R. 2011. "Investigation of kinetics and cracked oil structural changes in thermal cracking of Iranian vacuum residues", Fuel Processing Technology, 92(12), pp. 2226-2234. https://doi.org/10.1016/j.fuproc.2011.07.008
  9. Sbaaei, E. S. and Ahmed, T. S. 2018. "Predictive modeling and optimization for an industrial Coker Complex Hydrotreating unit – development and a case study", Fuel, 212, pp. 61-76. https://doi.org/10.1016/j.fuel.2017.10.032
  10. Aguilar, R. A., Ancheyta, J. and Trejo, F. 2012. "Simulation and planning of a petroleum refinery based on carbon rejection processes", Fuel, 100, pp. 80-90. https://doi.org/10.1016/j.fuel.2012.01.056
  11. Ghashghaee, M. 2015. "Predictive correlations for thermal upgrading of petroleum residues", Journal of Analytical and Applied Pyrolysis, 115, pp. 326-336. https://doi.org/10.1016/j.jaap.2015.08.013
  12. Gonçalves, M. L. A., Mota, D. A. P., Cerqueira, W. V., André, D., Saraiva, L. M., Coelho, M. I. F., Teixeira, A. M. R. F. and Teixeira, M. A. G. 2010. "Knowledge of petroleum heavy residue potential as feedstock in refining process using thermogravimetry", Fuel Processing Technology, 91(9), pp. 983-987. https://doi.org/10.1016/j.fuproc.2010.02.016
  13. Guo, A., Zhang, X. and Wang, Z. 2008. "Simulated delayed coking characteristics of petroleum residues and fractions by thermogravimetry", Fuel Processing Technology, 89(7), pp. 643-650. https://doi.org/10.1016/j.fuproc.2007.12.006
  14. Tian, L., Shen, B. and Liu, J. 2012. "Building and Application of Delayed Coking Structure-Oriented Lumping Model", Ind. Eng. Chem. Res., 51(10), pp. 3923–3931. https://doi.org/10.1021/ie2025272
  15. Smith, A. F., Quddus, J., Howell, D., Reed, T., Landrum, C. and Clifton, B. 2006. "Refinery Modeling, Advanced Chemical Engineering Design", University of Oklahoma, Norman, OK.
  16. Sawarkar, A. N., Pandit, A. B., Samant, S. D. and Joshi, J. B. 2007. "Petroleum Residue Upgrading Via Delayed Coking: A Review", The Canadian Journal of Chemical Engineering, 85(1), pp. 1–24. https://doi.org/10.1002/cjce.5450850101
  17. Rodríguez-Reinoso, F., Santana, P., Palazon, E. R., Diez, M. A. and Marsh, H. 1998. "Delayed coking: Industrial and laboratory aspects", Carbon, 36(1-2), pp. 105-116. https://doi.org/10.1016/S0008-6223(97)00154-1
  18. Lei, Y., Zhang, B., Hou, X. and Chen, Q. 2013. "A Novel Strategy for Simulating the Main Fractionator of Delayed Cokers by Separating the De-superheating Process", Chinese Journal of Chemical Engineering, 21(3), pp. 285-294. https://doi.org/10.1016/S1004-9541(13)60472-4
  19. Vakilalroayaei, H., Biglari, M., Elkamel, A. and Lohi, A. 2012. "Dynamic behavior of coke drum process safety valves during blocked outlet condition in the refinery delayed coking unit", Journal of Loss Prevention in the Process Industries, 25(2), pp. 336-343. https://doi.org/10.1016/j.jlp.2011.12.002
  20. Zahedi, G., Lohi, A. and Karami, Z. 2009. "A Neural Network Approach for Identification and Modeling of Delayed Coking Plant", International Journal of Chemical Reactor Engineering, 7(1). https://doi.org/10.2202/1542-6580.1832
  21. Zhang, K. and Yu, J. 1999. "Modeling delayed coking plant via RBF neural networks", International Joint Conference on Neural Networks, 3485, pp. 3483-3486. https://doi.org/10.1109/IJCNN.1999.836226
  22. Elliott, J. 2004. "Fine-tune your delayed coker: obstacles and objectives: Refining developments", Hydrocarbon Processing, 83(9), pp. 83-90.
  23. Elliott, J. D. 2003. "Optimize coker operations: Refinning developments", Hydrocarbon Processing, 82(9), pp. 85-90.
  24. Stefani, A. 1996. "Debottleneck delayed cokers for greater profitability", Hydrocarbon Processing, 75(6).
  25. Chang, A. I., Nishioka, K. and Yamakawa, T. 2001. "Advanced control project stabilizes delayed coker, increases throughput", Oil and Gas Journal, 99, pp. 52-56.
  26. Depew, C. A., Hashemi, M. H. and Davis, J. 1988. "Evaluation of Alternative Control Strategies for Delayed Coker by Dynamic Simulation", American Control Conference, pp. 240-246.
  27. Haseloff, V., Friedman, Y. Z. and Goodhart, S. G. 2007. "Implementing coker advanced process control: Process and plant optimization", Hydrocarbon Processing, 86(6), pp. 99-103.
  28. Chen, Q. L., Yin, Q. H., Wang, S. P. and Hua, B. 2004. "Energy-use analysis and improvement for delayed coking units", Energy, 29(12-15), pp. 2225-2237. https://doi.org/10.1016/j.energy.2004.03.021
  29. Wang, C., Chen, Q. and Hua, B. 2006. "Analysis of delayed coking process of different heat exchange and fractionation options", Petroleum Refinery Engineering, 36, pp. 19-22.
  30. Cassata, J., Dasgupta, S. and Gandhi, S. 1993. "Modeling of tower relief dynamics: Part 1", Hydrocarbon Processing, 72.
  31. Goyal, R. K. and Al-Ansari, E. G. 2009. "Impact of emergency shutdown devices on relief system sizing and design", Journal of Loss Prevention in the Process Industries, 22(1), pp. 35-44. https://doi.org/10.1016/j.jlp.2008.07.008
  32. Zhou, X., Chen, S. and Li, C. L. 2007. "A Predictive Kinetic Model for Delayed Coking", Petroleum Science and Technology, 25(12), pp. 1539-1548. https://doi.org/10.1080/10916460500529001
  33. Castiglioni, B. 1983. "How to predict coker yield", Hydrocarbon Process, 62(9).
  34. Ren, J., Meng, X., Xu, C., Song, Z., Jiang, Q. and Liu, Z. 2012. "Analysis and calculation model of energy consumption and product yields of delayed coking units", Petroleum Science, 9, pp. 100-105. https://doi.org/10.1007/s12182-012-0189-6
  35. Gary, J. and Handwerk, G. 2001. "Petroleum Refining: Technology and Economics", 4th Edition Marcel Dekker Inc.
  36. Maples, R. E. 2000. "Petroleum refinery process economics", Pennwell Books.
  37. Muñoz, J. A. D., Aguilar, R., Castañeda, L. C. and Ancheyta, J. 2013. "Comparison of Correlations for Estimating Product Yields from Delayed Coking", Energy Fuels, 27(11), pp. 7179–7190. https://doi.org/10.1021/ef4014423
  38. Almerri, H. A. 2004. "Correlation and modeling of thermal cracking yields in the delayed coking process".
Journal of Chemical and Petroleum Engineering
Volume 57, Issue 1
June 2023
Pages 13-25

Files

History

  • Receive Date: 13 January 2022
  • Revise Date: 18 November 2022
  • Accept Date: 28 November 2022

Share

How to cite

Statistics