Driving Down Operational Emissions and Costs
Oil and gas operators are facing a dual challenge - to lower CO₂ emissions whilst also maximising production. Against this backdrop, asset teams are focused on operating cleaner, more reliably and more productively than ever before.
As part of their drive to achieve net zero, a UKCS operator required a solution that helped their asset teams identify the daily operational changes they could make to minimise emissions whilst maximising production.
The operator rolled emissions.AI out to one of their assets to help them translate operational data into meaningful insights.
emissions.AI uses physics-guided machine learning and optimisation technologies to continually calculate the lowest achievable emissions from an asset at any time, based on current plant configuration and production targets.
The user interface highlights in near real time any excess emissions and the exact contributors and causes and pinpoints opportunities for emissions reduction.
The cloud-based platform was fully customised and live on the asset within 8 weeks.
In addition to helping the asset teams make more informed operational decisions, emissions.AI also helped to forecast emissions costs and predict year end figures versus the company’s decarbonisation targets. This visibility helped to drive cultural change and awareness.
The power of data is that you can put the right information into the right people’s hands at the right time so that they can make a difference.
The following cumulative savings opportunities were identified (with no CAPEX requirements):
tonnes of annual excess CO₂ emissions opportunity, representing 10% of total annual emissions volume.
annual cost savings potential through a reduction in EU ETS costs and gas losses.