A new simulation platform for the upstream and downstream oil and gas sectors has been engineered by digital energy management developer KBC. The digital twin process simulation system is designed to deliver advanced optimization with the integration of artificial intelligence and machine learning for the refining, petrochemical, polymer and sustainable aviation fuel (SAF) industries.

Petro-SIM v7.6 combines high-fidelity modeling with improved workflows that allow operators to explore new, low-carbon pathways. Optimized planning and operations help reduce energy waste and production losses. By simulating and optimizing performance across traditional and emerging processes, the software supports more efficient and lower-emission operations in crude refining, renewable fuel production and plastic waste-to-polymer circular processes.

The platform includes a kinetic-based reactor model that simulates Fischer-Tropsch synthesis for SAF production. Users can optimize operations and model the integration with downstream hydro-processing for a complete digital twin of sustainable fuel production. An additional benefit is offered by the ability to resolve difficult blackbox optimization problems to optimize energy efficiency while streamlining production planning and reducing emissions.

Advanced polymer modeling predicts polymer properties, optimizes grade transitions and monitors catalyst impacts to support dynamic production digital twins that minimize downtime and off-spec material.