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Effects of permeability heterogeneity on CO2 injectivity and storage efficiency coefficient
Uppsala University, Disciplinary Domain of Science and Technology, Earth Sciences, Department of Earth Sciences, LUVAL.ORCID iD: 0000-0002-9417-5586
Uppsala University, Disciplinary Domain of Science and Technology, Earth Sciences, Department of Earth Sciences, LUVAL.
Uppsala University, Disciplinary Domain of Science and Technology, Earth Sciences, Department of Earth Sciences, LUVAL.
Uppsala University, Disciplinary Domain of Science and Technology, Earth Sciences, Department of Earth Sciences, LUVAL.
2016 (English)In: Greenhouse Gases: Science and Technology, E-ISSN 2152-3878, Vol. 6, no 1, 112-124 p.Article in journal (Refereed) Published
Abstract [en]

We study the dependency of CO2 storage efficiency coefficient (E) and injectivity index (Iinj) on the geostatistical parameters of the permeability field. CO2 injection simulations are conducted for multiple realizations of log-normally distributed permeability fields parameterized by log permeability standard deviation (𝜎) and dimensionless horizontal correlation length (𝜆). Results show that the injectivity index increases with increasing 𝜆, the magnitude of the effect depending on 𝜎. Increasing 𝜎 leads to poorer injectivity for cases with small 𝜆, but improves injectivity when 𝜆 is large. Further analysis indicates that the enhancing effect of 𝜎 on injectivity can be attributed to cases with channelized flow, while the decrease effect of 𝜎 is seen in more dispersive flow regime. The dependence of injectivity on both 𝜆 and 𝜎 is captured with a linear correlation between Iinj and a parameter group (𝜆/ξ)𝜎, where ξ is a dimensionless scaling parameter. The storage efficiency coefficient, on the other hand, decreases with both increasing 𝜎 and 𝜆, and a simple linear fit is found between E and the parameter group 𝜆𝜎2, a well-established heterogeneity parameter group describing e.g. macro-dispersivity in solute transport studies. The above relationships provide potentially useful tools for preliminary evaluation of a site. Future studies should address the validity of the relationships in alternative injection scenarios and domain geometries.

Place, publisher, year, edition, pages
2016. Vol. 6, no 1, 112-124 p.
Keyword [en]
CO2 sequestration; storage capacity; injectivity; permeability heterogeneity; numerical simulation
National Category
Oceanography, Hydrology, Water Resources Geophysical Engineering
URN: urn:nbn:se:uu:diva-279379DOI: 10.1002/ghg.1540ISI: 000369976400010OAI: oai:DiVA.org:uu-279379DiVA: diva2:908731
EU, FP7, Seventh Framework Programme, MustangEU, FP7, Seventh Framework Programme, PanaceaSwedish National Infrastructure for Computing (SNIC), p2007023
Available from: 2016-03-03 Created: 2016-03-01 Last updated: 2016-08-26Bibliographically approved
In thesis
1. CO2 storage in deep saline aquifers: Models for geological heterogeneity and large domains
Open this publication in new window or tab >>CO2 storage in deep saline aquifers: Models for geological heterogeneity and large domains
2016 (English)Doctoral thesis, comprehensive summary (Other academic)
Alternative title[zh]
二氧化碳的深部盐水层地质封存 : 储层非均质性及大尺度模型的研究
Abstract [en]

This work presents model development and model analyses of CO2 storage in deep saline aquifers. The goal has been two-fold, firstly to develop models and address the system behaviour under geological heterogeneity, second to tackle the issues related to problem scale as modelling of the CO2 storage systems can become prohibitively complex when large systems are considered.

The work starts from a Monte Carlo analysis of heterogeneous 2D domains with a focus on the sensitivity of two CO2  storage performance measurements, namely, the injectivity index (Iinj) and storage efficiency coefficient (E), on parameters characterizing heterogeneity. It is found that E and Iinj are determined by two different parameter groups which both include correlation length (λ) and standard deviation (σ) of the permeability. Next, the issue of upscaling is addressed by modelling a heterogeneous system with multi-modal heterogeneity and an upscaling scheme of the constitutive relationships is proposed to enable the numerical simulation to be done using a coarser geological mesh built for a larger domain. Finally, in order to better address stochastically heterogeneous systems, a new method for model simulations and uncertainty analysis based on a Gaussian processes emulator is introduced. Instead of conventional point estimates this Bayesian approach can efficiently approximate cumulative distribution functions for the selected outputs which are CO2 breakthrough time and its total mass. After focusing on reservoir behaviour in small domains and modelling the heterogeneity effects in them, the work moves to predictive modelling of large scale CO2  storage systems. To maximize the confidence in the model predictions, a set of different modelling approaches of varying complexity is employed, including a semi-analytical model, a sharp-interface vertical equilibrium (VE) model and a TOUGH2MP / ECO2N model. Based on this approach, the CO2 storage potential of two large scale sites is modelled, namely the South Scania site, Sweden and the Dalders Monocline in the Baltic Sea basin.

The methodologies developed and demonstrated in this work enable improved analyses of CO2 geological storage at both small and large scales, including better approaches to address medium heterogeneity. Finally, recommendations for future work are also discussed.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2016. 70 p.
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Science and Technology, ISSN 1651-6214 ; 1390
CO2, Carbon Capture Storage, Storage Capacity, Injectivity, Monte Carlo, Gaussian, Permeability, Upscaling, 二氧化碳, 地質封存, 高斯仿真, 滲透係數, 非均質性, 升尺度, 存儲效能, 場地模擬, 不確定性, 壓力累積
National Category
Geosciences, Multidisciplinary
urn:nbn:se:uu:diva-279382 (URN)978-91-554-9625-8 (ISBN)
Public defence
2016-09-16, Hamberg, Villavägen 16, Uppsala, 13:15 (English)
Available from: 2016-08-24 Created: 2016-03-01 Last updated: 2016-10-12

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