To use the model for troubleshooting
Modelling, troubleshooting, case studies
Data historian, l ab analysis, c orrosion data
Petro-SIM + OLI engine
KPI (in Petro-SIM)
To identify deviation based on low and high value
pH, Cl conc, solid, generalised corrosion rate*, velocity etc.
Stream properties
Corrosion rate, metallurgy
OLI application
*Only when operating below ionic dew point
Corrosion analysis
Figure 7 Corrosion digital twin
techniques, Journal of Industrial Information Integration , 26, 2022, pp.100,272. https://doi.org/10.1016/j.jii.2021.100272. 2 Yadav V G, Yadav G D, Patankar S C, The production of fuels and chemicals in the new world: critical analysis of the choice between crude oil and biomass vis-à-vis sustainability and the environment, Clean Technologies and Environmental Policy , 22(9), (2020), pp.1757-1774. https://doi.org/10.1007/s10098-020-01945-5. 3 Alsayoof L, Shams M, The role of crude oil selection in enhancing the profitability of a local refinery with lube hydro-processing capacity, Chemical Engineering Research and Design, 185, 2022, pp.146-162. https://doi.org/10.1016/j.cherd.2022.07.002. 4 Wanasinghe T R, Wroblewski L, Petersen B K, Gosine R G, James L A, De Silva O, Mann G K I, Warrian P J, Digital Twin for the Oil and Gas Industry: Overview, Research Trends, Opportunities, and Challenges, IEEE Access , 8, 2020, pp.104,175–104,197. https://doi.org/10.1109/ access.2020.2998723. 5 Min Q, Lu Y, Liu S, Su C, Wang B, Machine learning based digital twin framework for production optimisation in petrochemical Industry, International Journal of Information Management, 49, 2019, 502–519. https://doi.org/10.1016/j.ijinfomgt.2019.05.020. 6 Singh A, Be in Control of Your Operation – Integrating Real-Time Optimisation with Advanced Process Control for Optimum Energy Management and Optimisation. OnePetro, 2022. 7 Sarantinoudis N, Tsinarakis G, Dedousis P, Arampatsis G, Model- Based Simulation Framework for Digital Twins in the Process Industry. IEEE Access, 11, 2023, pp.111,701-111,714. https://doi.org/10.1109/ access.2023.3322926. 8 Schempp P, Kohler S, Mensebach M, Preuss K, Troger M, Proceedings of the European Corrosion Congress, Prague, Czech Republic, Paper No. 88826 (EFC Working Party 15: Corrosion in the Refinery Industry), 2017. Michelle Wicmandy is the Marketing Campaigns Manager at KBC (A Yokogawa Company) in Houston, Texas, with more than 20 years of experience in marketing and communications. She serves on the Forbes Communication Council and has contributed to both academic and trade publications. She holds a DBA in business administration. Jagadesh Donepudi is the Director for Business Development South Asia at KBC (A Yokogawa Company) in India. He has more than 30 years of experience adding value to refineries and upstream oil and gas companies via digitalisation, digital twins, and energy transitions. He holds a PhD in chemical engineering from the University of Mumbai. Rodolfo Tellez-Schmill is the Product Champion for Process Simulation at KBC (A Yokogawa Company) in Canada. He has more than 20 years of experience in chemical engineering, including process engineering, qual - ity control, project management, R&D, technical support, and training He holds a PhD in chemical engineering from the University of Calgary.
Conclusion Standing at the crossroads of innovation and challenge, refiners face the complexities of the refinery and petro - chemical industry. At this moment, KPIs emerge as valuable tools that monitor critical metrics such as temperature, pres - sure, and equipment status. These metrics not only provide insights but also serve as catalysts for innovation, helping refiners navigate the intricacies of yields, energy variances, column performances, and more. Refineries and petrochemical plants are increasingly adopting digital technologies. One such tool, the digital twin, has proven to be a multi-faceted solution for both opera - tional and design stages based on our experience. In this article, we present a case study of a refinery that benefited from digital twin applications, including: • KPI visualisation incorporates intrinsic parameters like flooding and heat exchanger fouling characteristics • Production accounting systems leverage mass balances and elemental balances to identify and address real losses within the production process • Supply chain planning systems update LP vectors to rep - resent non-linear sensitivities for more robust supply chain planning • Production optimisation closes gaps based on bench - marking parameters to improve gross margins • Real-time optimisation continuously calculates gains by optimising set points in real time • Corrosion monitoring minimises corrosion rates and imple - ments corrective actions to prevent pipe corrosion, ensuring the longevity and reliability of the infrastructure. These applications emphasise the wide-ranging ben - efits that a process digital twin simulation software offers refiners, demonstrating its potential to revolutionise various aspects of plant operations and design. This point of convergence should not be seen as a period of uncertainty. Rather, it represents a strategic juncture where the industry holistically assesses its over - all performance and implements strategies for continuous improvement. It serves as a roadmap that motivates the industry to drive toward a sustained state of excellence. References 1 Priyanka E B, Thangavel S, Gao X-S, Sivakumar N S, Digital twin for oil pipeline risk estimation using prognostic and machine learning
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