Probabilistic Joint Recovery Method for CO$_2$ Plume Monitoring

• URL: http://arxiv.org/abs/2501.18761v1
• Date: Thu, 30 Jan 2025 21:32:01 GMT
• Title: Probabilistic Joint Recovery Method for CO$_2$ Plume Monitoring
• Authors: Zijun Deng, Rafael Orozco, Abhinav Prakash Gahlot, Felix J. Herrmann,
• Abstract summary: Carbon Capture and Storage is one of the few technologies capable of achieving net-negative CO$$ emissions. We propose Probabilistic Joint Recovery Method (pJRM) to predict fluid flow patterns in CCS.
• Score: 1.1544215353883025
• License:
• 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.

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