Oil and gas companies must safely and significantly reduce their CO₂ emissions to assist governments globally in achieving their net-zero targets – this directional change has to be balanced with the desire and requirement to satisfy global energy demands and production safety.
This innovative machine-learning software platform uses operational data, plant configurations, installed capacity, current production performance and operating model data to dynamically present contextualised insights. It aids decision-making and drives daily operational actions to improve energy management and reduce flaring, costs and emissions.
Energy companies have a major role to play in achieving net-zero targets for CO₂. To do this, current ways of operating need to be overhauled in a manner that sustains production rates, protects people and the environment, and supports the net-zero agenda. This is a tall order, and investment in technology and innovation alone will not achieve this, but it will go a long way to support this ambition.
The starting point in reducing the CO₂ footprint of a production asset is to understand how much CO₂ is being produced daily via operational demands.
Without reliable data sets or the resources required to provide analytical insights of ongoing plant configuration changes, start-up optimisation and process optimisation, net-zero operations from production assets and efficient cost saving energy management will be difficult to achieve.
This software platform uncovers valuable information hidden deep within existing equipment and production data. It enables oil and gas companies to access new insights and seek out emissions reduction opportunities through operational changes, without any CAPEX investment.
This platform harnesses the power of physics-guided machine learning and optimisation technologies to continuously calculate the lowest achievable emissions from an oil and gas asset at any time – based on current plant configuration and production targets. Excess emissions problems and their causes are highlighted via the intuitive user interface in near real-time and necessary configuration changes that will resolve them are identified.
Once implemented, customised and fully live – which takes from four to eight weeks – this cloud-based platform is proven to help operators significantly reduce annual CO₂ emissions through proactive daily operational changes. The contextualised insights that dynamically adapt to changes in fluid rates, properties, degradation, mode of operation and emerging constraints, highlight opportunities to remove excess CO₂ emissions and energy leakage, while also optimising the production process.
This also delivers annual financial savings through a reduction in emissions costs and fuel gas losses. It improves asset energy management; reduces flaring and drives cultural change and awareness. These insights help to guide and better inform decisions and day-to-day operational actions that operators can take, as well as highlighting longer term material improvement opportunities.
Reduced CO₂ emissions
Reduced emissions costs
Reduced fuel gas losses
Improved operational stability
Optimised power usage
Reduced operational costs
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