Probabilistic Joint Recovery Method for CO$_2$ Plume Monitoring
Journal:
arXiv
Published Date:
Jan 30, 2025
Abstract
Reducing CO$_2$ emissions is crucial to mitigating climate change. Carbon
Capture and Storage (CCS) is one of the few technologies capable of achieving
net-negative CO$_2$ emissions. However, predicting fluid flow patterns in CCS
remains challenging due to uncertainties in CO$_2$ plume dynamics and reservoir
properties. Building on existing seismic imaging methods like the Joint
Recovery Method (JRM), which lacks uncertainty quantification, we propose the
Probabilistic Joint Recovery Method (pJRM). By estimating posterior
distributions across surveys using a shared generative model, pJRM provides
uncertainty information to improve risk assessment in CCS projects.
