AI used to cut time and cost of carbon capture and storage design

Heriot-Watt University’s global research institute for net zero is leading a multi-million-pound project to develop the use of AI in carbon capture and storage (CCS).

iNetZ+ geological research
iNetZ+ geological research - Heriot-Watt University

Dubbed ECO-AI, the research team has begun the development of specialist AI techniques for scientific computing, material discovery and financial forecasting, to enable efficient CO2 capture and storage in deep geological formations and to reduce the cost of deploying these techniques.

The Heriot-Watt team, with colleagues from Imperial College London, aims to show how bespoke technologies can enable CCS to be a viable economic option for traditional industries wanting to decarbonise. Targets include hard to decarbonise industries such as steel, cement and chemicals.

Funded by £2.5m from UK Research and Innovation, the ECO-AI project will specifically develop energy-efficient solvents for CO2 capture followed by permanent storage of captured CO2 into geological storage sites, through various AI techniques.

The research is one of the projects being delivered by Heriot-Watt University’s global research institute which is focused on achieving net zero and beyond. Called iNetZ+, the team brings together a range of scientific expertise including chemical engineering, physics, geology, mathematics, computer science and economics.

According to the researchers, by using specialist AI simulators, standard techniques can be replaced for modelling flow migrations, and simulations on a supercomputer that may have previously taken up to 100 days can now be achieved in just 24 hours.

To strengthen its research, the university hosted a two-day workshop and three-day hackathon event, bringing together leading experts in AI, computational science, and CCS.

The workshop event highlighted the role of interdisciplinary collaboration and discussed using digital twins for decision-making around reaching net-zero emissions under uncertainty, as well as incorporating simplified models into large-scale optimisation replicas for complex systems.

In a statement, Professor Ahmed H. Elsheikh, leader of the data and artificial intelligence research theme at iNetZ+, said: “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.

“Based on the great engagement and interactions evidenced in our workshop and hackathon events, we’re confident that through our applied research and with more collaboration with business and industry, we can collectively make a profound impact on the global shift towards a carbon-neutral future.”

More information on the ECO-AI project can be accessed here.