DT4GCS –- Digital Twin for Geological CO2 Storage and Control

TitleDT4GCS –- Digital Twin for Geological CO2 Storage and Control
Publication TypeConference
Year of Publication2024
AuthorsFelix J. Herrmann, Abhinav Prakash Gahlot, Rafael Orozco, Ziyi Yin, Haoyun Li
Conference NameGigatonnes CO2 Storage Workshop
KeywordsBayesian inference, CCS, deep learning, digital twin, Imaging, monitoring, Uncertainty quantification

Our industry is experiencing significant changes due to AI and the challenges of the energy transition. While some view these changes as threats, recent advances in AI offer unique opportunities, especially in the context of Digital Twins for subsurface monitoring and control. IBM defines “A digital twin is a virtual representation of an object or system that spans its lifecycle, is updated from real-time data, and uses simulation, machine learning and reasoning to help decision-making.” During this talk, we will explore these concepts and their significance in addressing the challenges of monitoring and control of geological CO2 storage projects. This talk also aims to illustrate how Digital Twins can serve as a platform to integrate the seemingly disparate and siloed fields of geophysics and reservoir engineering.


(Geophysical Research for Gigatonnes CO2 Storage Workshop, Golden)

Citation Keyherrmann2024CSMdt