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You would have heard of governments and businesses setting large targets to reduce carbon emissions, with the UK aiming for net zero by 2050 which includes its offshore oil and gas industry. Recently we’ve heard BP announce its commitment to the same target, a move that will see them focus on initiatives such as tree planting, carbon capture technologies as well as an investment in renewables.
Reducing flaring and complying with flaring guidelines is an essential component for all industrial companies – oil and gas producers, power stations, refineries and manufactures, and one that is 100% necessary as we fight climate change.
We chatted with Trevor Bloch, Group CEO and Founder about the use of AI Predictive Analytics for reducing emissions.
When equipment at industrial manufacturing plants fails or has an unplanned events, the operators have to burn off the excess fuel when shutting down the facility. This directly produces an increase in emissions. Preventing unplanned shutdowns by predicting faults before they occur is just one way that increasing reliability helps to reduce emissions. AI Predictive Analytics can identify issues 5-10 days out from an unplanned event, allowing opperators the time to intervene to prevent the event, or if they do have to shut-down to perform maintenance, do it in a controlled manner that eliminates the need for flaring.
AI is a learning engine, it learns how the facility works under all different types of working conditions. The technology can be used to predict failures and process upsets to improve reliability, and prevent unnecessary emissions into the environment. It can also be used to learn what produces the most amount of emissions during normal operating conditions, to give critical insights into what can be done on the plant to decrease emissions during everyday operations. This can be applied to manufacturing, power stations, oil and gas platforms and refinning facilities to help reduce the base load of emissons while the plants are in steady state operation. By reducing the base-load of emissions and improving the reliability of assets, AI can help reduce the overall environmental impact of these facilities.
One of our oil and gas clients came to us with an aging platform that was unreliable. It was suffering from gas lift injection issues and was constantly tripping. The platform was only meeting 50% of its flaring target. VROC was able to work with this organisation, applying our AI technology to provide critical insights into how the whole platform was working, identifying the root cause of integrity issues and forecasting the health of critical assets. Among other production improvements and benefits, the platform has started to meet 100% of its flaring compliance. View case study
If you would like to know more about how AI can help you with your net zero emissions goals, please contact our team.
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The efficient deployment, continuous retraining of models with live data and monitoring of model accuracy falls under the categorisation called MLOps. As businesses have hundreds and even.
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