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• What process and operational areas have refiners demonstrated a positive ROI in the application of artificial intelligence and machine learning strategies?

  Feb-2025

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Answers

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• Heather Gilligan, Imubit, heather.gilligan@imubit.com

  Artificial intelligence (AI) and machine learning strategies are being applied across all process and operational areas in many different business applications. Some have been in place for many years, such as machine learning to find anomalies in the operation of rotating equipment as part of predictive maintenance. However, it was only recently that AI and machine learning strategies moved from an advisory capacity to closed loop, where an action is automatically executed as a result of the AI model calculation.

  In this newer world of closed-loop AI optimisation, Imubit  is seeing refiners capture the highest value when applying the technology to complex and nonlinear processes. Some notable applications include conversion units, such as FCCs and hydrocrackers, and multi-unit feed and multi-unit product optimisation. One example of the latter involves balancing T90s across multiple units to push the diesel pool to the T90 limit and upgrade molecules from gasoil.

  Some of the quantified benefits that have been reported publicly by customers using closed-loop AI optimisation include:
  • 0.5°F improvement in average ULSD T90 vs baseline (reported by Delek US at 2024 AFPM Summit)
  • 2% FCC debutaniser tower throughput capacity increase, removing bottleneck and allowing them to push FCC conversion (reported by Big West Oil in June 2024 Imubit webinar)
  • FCC liquid volume yield improvement of 0.6% (reported by Big West Oil in June 2024 Imubit webinar).
  • Reduced conservatism in diesel flash target by 2°F, enabling increased, on-spec, diesel throughput (reported by Big West Oil in June 2024 Imubit webinar).
  • 25% reduction in sub-optimal coke drum cycles significantly reducing coker giveaway (reported by Marathon Petroleum Corporation Garyville Refinery at AFPM Summit 2024).

   

  Jan-2025