Invasion percolation Markov Chains – A probabilistic framework for assessing vertical CO2 migration

• An Invasion Percolation Markov Chain approach is developed to model CO 2 vertical migration • Key geological controls are threshold pressures, layer topography and vertical pathways • A good match to Sleipner was obtained but results were very sensitive to model assumptions • The study demonstrates the value of a multiple seal system for geological storage of CO 2 Potential CO 2 storage sites need to perform risk assessments on the likelihood of anomalous events such as leakage. The intrinsic heterogeneity of the rock system with uncertain values for the capillary threshold pressures of the various rock elements is the most likely reason for unexpected vertical migration of CO 2 within a storage complex. This study shows how the Invasion Percolation Markov Chain approach can be used to address this concern. We tested the approach using detailed 3D models of the multi-layer plume at Sleipner showing that even small variations in the threshold pressures of the shales can impact the flow of CO 2 into multiple accumulations. Models with and without shale breaks reveal the importance of vertical feeders and/or faults, and the geometry of the shale layers is also crucial as the CO 2 strongly conforms to topography. We demonstrate that the vertical migration of CO 2 at Sleipner follows a Markovian model in which the probability of later migration events is highly dependent of the probability of preceding events. This case study illustrates how the initial migration events, which have the highest probability of occurring, should be the focus of CO 2 storage risk assessments.

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Institutions

Publication Details

Journal
International journal of greenhouse gas control
Published
2025-03-01
DOI
https://doi.org/10.1016/j.ijggc.2025.104338
Citations
2
Primary Topic
Atmospheric and Environmental Gas Dynamics
Type
article
Field-Weighted Citation Impact
2.21

Funders

Controls
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article

Invasion percolation Markov Chains – A probabilistic framework for assessing vertical CO2 migration

Philip Ringrose, Jo Eidsvik, Tor Andre Haugdahl, Andrea Callioli Santi
2 citations
International journal of greenhouse gas control
Atmospheric and Environmental Gas Dynamics
2.21
article

Invasion percolation Markov Chains – A probabilistic framework for assessing vertical CO2 migration

Philip Ringrose, Jo Eidsvik, Tor Andre Haugdahl, Andrea Callioli Santi
article en
2 citations

Abstract

• An Invasion Percolation Markov Chain approach is developed to model CO 2 vertical migration • Key geological controls are threshold pressures, layer topography and vertical pathways • A good match to Sleipner was obtained but results were very sensitive to model assumptions • The study demonstrates the value of a multiple seal system for geological storage of CO 2 Potential CO 2 storage sites need to perform risk assessments on the likelihood of anomalous events such as leakage. The intrinsic heterogeneity of the rock system with uncertain values for the capillary threshold pressures of the various rock elements is the most likely reason for unexpected vertical migration of CO 2 within a storage complex. This study shows how the Invasion Percolation Markov Chain approach can be used to address this concern. We tested the approach using detailed 3D models of the multi-layer plume at Sleipner showing that even small variations in the threshold pressures of the shales can impact the flow of CO 2 into multiple accumulations. Models with and without shale breaks reveal the importance of vertical feeders and/or faults, and the geometry of the shale layers is also crucial as the CO 2 strongly conforms to topography. We demonstrate that the vertical migration of CO 2 at Sleipner follows a Markovian model in which the probability of later migration events is highly dependent of the probability of preceding events. This case study illustrates how the initial migration events, which have the highest probability of occurring, should be the focus of CO 2 storage risk assessments.

International journal of greenhouse gas controlVol. 142
Norwegian University of Science and Technology (NO), Institute for Forecasting of the Slovak Academy of Sciences (SK)
Norges Teknisk-Naturvitenskapelige Universitet, Science Foundation Ireland, Norges Forskningsråd
Reduced inequalities
Openalex Percentile: Top 15%
Atmospheric and Environmental Gas Dynamics
2.21
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