Building on its digital twin foundation, Petro-SIM v7.6 delivers enhancements across both first-principles and hybrid modelling, delivering advanced optimisation with the integration of artificial intelligence and machine learning (AI/ML). It allows engineers, operators, and business leaders to accelerate digitalisation, energy transition, and decarbonisation.
Rodolfo Tellez-Schmill, Product Champion for the Petro-SIM process twin, commented: “Any miscalculation in product quality or properties directly impacts production planning, energy use, and profitability. In a volatile market, process optimisation is no longer optional.”
Petro-SIM v7.6 addresses this challenge by combining high-fidelity modelling with improved workflows that allow operators to explore new, low-carbon pathways. These improvements help operators reduce energy waste and production losses, which are key contributors to approximately 5000 million t of carbon dioxide equivalent emissions generated by oil and gas operations each year, as reported in the 2023 IEA World Energy Outlook Report. By simulating and optimising performance across traditional and emerging processes, Petro-SIM supports efficient and lower-emission operations in crude refining, renewable fuel production, and plastic waste-to-polymer circular processes.
Key features and benefits include:
- FTR-SIM (Fischer-Tropsch reactor model) is a robust kinetic-based reactor model that simulates Fischer-Tropsch synthesis for SAF production. It enables users to optimise operations and model the integration with downstream hydroprocessing for a complete digital twin of sustainable fuel production.
- New NOMAD solver for optimisation solves difficult blackbox optimisation problems to optimise energy efficiency while streamlining production planning and reducing emissions.
- AI/ML integration and digitalisation combines AI/ML models with first-principals physics-based models to deliver smarter predictions, improved optimisations, and enhanced decision-making within scheduling and planning.
- Advanced polymer modelling powered by Predici predicts polymer properties, optimises grade transitions, and monitors catalyst impacts to support dynamic production digital twins that minimise downtime and off-specification material.
- Renewables and hydroprocessing enhancements improve kinetic modelling for renewable feedstocks. Enhancements in hydrotreating, isomerization, and hydrocracking simulations include upgrades to liquid recycling and external gas quenching processes that optimize reactor performance while reducing solving times by up to 30%.
- FCC-SIM improvements for bio-oil co-processing enhance oxygen balance modelling and improve assessment of inert loads in FCC overheads during co-processing of bio-oils to help control emissions and optimise product quality.