Copula Modeling and Uncertainty Propagation in Field‐Scale Simulation of CO2 Fault Leakage

Abstract Subsurface storage of CO2 is an important means to mitigate climate change, and the North Sea hosts considerable potential storage resources. To investigate the fate of CO2 over decades in vast reservoirs, numerical simulation based on realistic models is essential. Faults and other complex...

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Main Authors: Per Pettersson, Eirik Keilegavlen, Tor Harald Sandve, Sarah E. Gasda, Sebastian Krumscheid
Format: Article
Language:English
Published: Wiley 2025-01-01
Series:Water Resources Research
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Online Access:https://doi.org/10.1029/2024WR038073
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author Per Pettersson
Eirik Keilegavlen
Tor Harald Sandve
Sarah E. Gasda
Sebastian Krumscheid
author_facet Per Pettersson
Eirik Keilegavlen
Tor Harald Sandve
Sarah E. Gasda
Sebastian Krumscheid
author_sort Per Pettersson
collection DOAJ
description Abstract Subsurface storage of CO2 is an important means to mitigate climate change, and the North Sea hosts considerable potential storage resources. To investigate the fate of CO2 over decades in vast reservoirs, numerical simulation based on realistic models is essential. Faults and other complex geological structures introduce modeling challenges as their effects on storage operations are subject to high uncertainty. We present a computational framework for forward propagation of uncertainty, including stochastic upscaling and copula representation of multivariate distributions for a CO2 storage site model with faults. The Vette fault zone in the Smeaheia formation in the North Sea is used as a test case. The stochastic upscaling method reduces the number of stochastic dimensions and the cost of evaluating the reservoir model. Copulas provide representation of dependent multidimensional random variables and a good fit to data, allow fast sampling and coupling to the forward propagation method via independent uniform random variables. The non‐stationary correlation within the upscaled flow functions are accurately captured by a data‐driven transformation model. The uncertainty in upscaled flow functions and other uncertain parameters are efficiently propagated to leakage estimates using numerical reservoir simulation of a two‐phase system of CO2 and brine. The expectations of leakage are estimated by an adaptive stratified sampling technique which effectively allocates samples in stochastic space. We demonstrate cost reduction compared to standard Monte Carlo of one or two orders of magnitude for simpler test cases, and factors 2–8 cost reduction for stochastic multi‐phase flow properties and more complex stochastic models.
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spelling doaj-art-3b9a91cabf604164ac39103e3db897612025-08-20T02:36:42ZengWileyWater Resources Research0043-13971944-79732025-01-01611n/an/a10.1029/2024WR038073Copula Modeling and Uncertainty Propagation in Field‐Scale Simulation of CO2 Fault LeakagePer Pettersson0Eirik Keilegavlen1Tor Harald Sandve2Sarah E. Gasda3Sebastian Krumscheid4NORCE Norwegian Research Centre Bergen NorwayUniversity of Bergen Bergen NorwayNORCE Norwegian Research Centre Bergen NorwayNORCE Norwegian Research Centre Bergen NorwayKarlsruhe Institute of Technology (KIT) Karlsruhe GermanyAbstract Subsurface storage of CO2 is an important means to mitigate climate change, and the North Sea hosts considerable potential storage resources. To investigate the fate of CO2 over decades in vast reservoirs, numerical simulation based on realistic models is essential. Faults and other complex geological structures introduce modeling challenges as their effects on storage operations are subject to high uncertainty. We present a computational framework for forward propagation of uncertainty, including stochastic upscaling and copula representation of multivariate distributions for a CO2 storage site model with faults. The Vette fault zone in the Smeaheia formation in the North Sea is used as a test case. The stochastic upscaling method reduces the number of stochastic dimensions and the cost of evaluating the reservoir model. Copulas provide representation of dependent multidimensional random variables and a good fit to data, allow fast sampling and coupling to the forward propagation method via independent uniform random variables. The non‐stationary correlation within the upscaled flow functions are accurately captured by a data‐driven transformation model. The uncertainty in upscaled flow functions and other uncertain parameters are efficiently propagated to leakage estimates using numerical reservoir simulation of a two‐phase system of CO2 and brine. The expectations of leakage are estimated by an adaptive stratified sampling technique which effectively allocates samples in stochastic space. We demonstrate cost reduction compared to standard Monte Carlo of one or two orders of magnitude for simpler test cases, and factors 2–8 cost reduction for stochastic multi‐phase flow properties and more complex stochastic models.https://doi.org/10.1029/2024WR038073CO2 storagefault leakage assessmentadaptive sampling methodscopulasstochastic upscaling
spellingShingle Per Pettersson
Eirik Keilegavlen
Tor Harald Sandve
Sarah E. Gasda
Sebastian Krumscheid
Copula Modeling and Uncertainty Propagation in Field‐Scale Simulation of CO2 Fault Leakage
Water Resources Research
CO2 storage
fault leakage assessment
adaptive sampling methods
copulas
stochastic upscaling
title Copula Modeling and Uncertainty Propagation in Field‐Scale Simulation of CO2 Fault Leakage
title_full Copula Modeling and Uncertainty Propagation in Field‐Scale Simulation of CO2 Fault Leakage
title_fullStr Copula Modeling and Uncertainty Propagation in Field‐Scale Simulation of CO2 Fault Leakage
title_full_unstemmed Copula Modeling and Uncertainty Propagation in Field‐Scale Simulation of CO2 Fault Leakage
title_short Copula Modeling and Uncertainty Propagation in Field‐Scale Simulation of CO2 Fault Leakage
title_sort copula modeling and uncertainty propagation in field scale simulation of co2 fault leakage
topic CO2 storage
fault leakage assessment
adaptive sampling methods
copulas
stochastic upscaling
url https://doi.org/10.1029/2024WR038073
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AT eirikkeilegavlen copulamodelinganduncertaintypropagationinfieldscalesimulationofco2faultleakage
AT torharaldsandve copulamodelinganduncertaintypropagationinfieldscalesimulationofco2faultleakage
AT sarahegasda copulamodelinganduncertaintypropagationinfieldscalesimulationofco2faultleakage
AT sebastiankrumscheid copulamodelinganduncertaintypropagationinfieldscalesimulationofco2faultleakage