ABOUT SIG MACHINE LEARNING

Our story began in the energy sector, when a leading oil and gas operator set out to optimize its integrated network of wellsites, gathering lines, and compression facilities. The field operates under constantly changing flow and pressure conditions, with multiple artificial lift systems in use – making it time-consuming and difficult for engineers to coordinate production efficiently.

 

To address this, we developed an intelligent wellsite control system that helps production engineers move from optimising single-variable, single-well controllers to managing multi-variable, multi-well control strategies across the entire field. The system replicates the diagnostic and optimization workflow of an engineer; analysing pressures, rates, and lift performance across hundreds of wellsites simultaneously to detect key petrotechnical events, prioritise opportunities, and recommend targeted adjustments - whilst maintaining stable, efficient, and scalable operations.

 

This first of kind project enabled teams to reimagine how their assets are monitored, optimised, and controlled at a system-level, establishing a new foundation for scalable field optimization practices. The solution has delivered up to a 70% reduction in engineering time and, across multiple projects, an average 2% uplift in field production.

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