AI cuts carbon capture design time from 100 days to 24 hours

Staff
By Staff
3 Min Read

A new multimillion-pound project led by Heriot-Watt University’s global research institute for net zero is utilising artificial intelligence (AI) to significantly reduce the time and cost of modelling carbon capture and storage (CCS) methods.

The project, named ECO-AI, aims to develop specialised AI techniques for scientific computing, material discovery and financial forecasting to enable efficient carbon capture and storage in deep geological formations while outlining the financial implications for businesses and policymakers.

The research is expected to demonstrate how bespoke technologies can make CCS an economically viable option for traditional industries, particularly those that are hard to decarbonise, such as steel, cement and chemicals.

The project, in collaboration with Imperial College London, is anticipated to provide a substantial framework for future researchers and aid the UK Government in reaching its net zero target by 2050.

Funded by £2.5 million from UK Research and Innovation, ECO-AI aims to develop energy-efficient solvents for CO2 capture followed by permanent storage of captured CO2 in geological sites through various AI techniques.

By employing specialised AI simulators, standard techniques for modelling flow migrations can be replaced, reducing simulation times on supercomputers from up to 100 days to just 24 hours.

Professor Ahmed H. Elsheikh, leader of the data and artificial intelligence research theme at iNetZ+ said: “Our efforts for the ECO-AI research are primarily focused on refining algorithms that can potentially be applied to CCS in the future in typically hard to decarbonise industries.

“Our research has the ability to really advance existing scientific research streams to source suitable options for safe storage of CO2 without consuming too much energy and without the need to deploy expensive and often time-consuming exploratory investigations.”

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