A POMDP Model for Safe Geological Carbon Sequestration
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Abstract (arXiv)
Geological carbon capture and sequestration (CCS), where CO2 is stored in subsurface formations, is a promising and scalable approach for reducing global emissions. However, if done incorrectly, it may lead to earthquakes and leakage of CO2 back to the surface, harming both humans and the environment. These risks are exacerbated by the large amount of uncertainty in the structure of the storage formation. For these reasons, we propose that CCS operations be modeled as a partially observable Markov decision process (POMDP) and decisions be informed using automated planning algorithms. To this end, we develop a simplified model of CCS operations based on a 2D spillpoint analysis that retains many of the challenges and safety considerations of the real-world problem. We show how off-the-shelf POMDP solvers outperform expert baselines for safe CCS planning. This POMDP model can be used as a test bed to drive the development of novel decision-making algorithms for CCS operations.
Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). Builds on 1 of its 13 references that are in the map. First posted on arXiv 25 Oct 2022.
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1 of 13 references.
References · 1
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Citing papers per year: 2022: 1; 2023: 2; 2024: 2; 2025: 1.
6 papers.
- 2023BetaZero: Belief-State Planning for Long-Horizon POMDPs using Learned Approximationscited by 13
- 2024ConstrainedZero: Chance-Constrained POMDP Planning using Learned Probabilistic Failure Surrogates and Adaptive Safety Constraintscited by 7
- 2022Online Planning for Constrained POMDPs with Continuous Spaces through Dual Ascentcited by 5
- 2023Constrained Hierarchical Monte Carlo Belief-State Planningcited by 1
- 2024Addressing Myopic Constrained POMDP Planning with Recursive Dual Ascentcited by 1
- 2025Conditional Deep Generative Models for Belief State Planningcited by 0
- 2025Conditional Deep Generative Models for Belief State Planning16 May 2025
- 2024ConstrainedZero: Chance-Constrained POMDP Planning using Learned Probabilistic Failure Surrogates and Adaptive Safety Constraints1 May 2024
- 2024Addressing Myopic Constrained POMDP Planning with Recursive Dual Ascent26 Mar 2024
- 2023Constrained Hierarchical Monte Carlo Belief-State Planning30 Oct 2023
- 2023BetaZero: Belief-State Planning for Long-Horizon POMDPs using Learned Approximations31 May 2023
- 2022Online Planning for Constrained POMDPs with Continuous Spaces through Dual Ascent23 Dec 2022