The Future of Carbon Capture and Storage Technology: Innovative Approach with Digital Twin




CCS, Digital Twin, Process Simulation, CO2 Transport, Risk Analysis


In order to fight climate change, the EU has set a goal of achieving net-zero greenhouse gas emissions by 2050. To achieve carbon neutrality, greenhouse emissions from human activities should be at least 85% lower than in 1990. The remaining 15% can be achieved through additional measures such as increasing carbon capture and storage (CCS) and reducing emissions. CCS will facilitate the decarbonization of heavy industry, contribute to the emergence of a clean hydrogen economy, and aid in achieving net-zero emissions. As an emerging technology in the Industry 4.0, digital twin (DT) is gaining attention due to the possibilities arising from its application, such as precise process optimization in the design phase, quality control, monitoring, decision-making, and through comprehensive modeling of the physical world as a group of connected digital models. The introduction of digital technologies into the CCS sector has the potential to revolutionize the way CO2 capture, transportation, and storage processes are carried out. This article aims to present the fundamental value of different modeling techniques, technologies enabling the creation of DT’s uncertainty quantification methods commonly used in Digital Twins, as well as the application of Digital Twin in CCS technology and the potential benefits it can bring, including increases efficiency and cost minimization. Additionally, the possibilities of using DS’s in improving process monitoring and forecasting were discussed which can contribute to better emission control and increases system effectiveness. Current research and projects utilizing this technology were also presented, including real-time modeling of fluid flow, CO2 transport network optimization and storage process improvement.




How to Cite

Bielka, P. (2023). The Future of Carbon Capture and Storage Technology: Innovative Approach with Digital Twin. Journal of Geotechnology and Energy, 40(2), 5–10.