Influence of heterogeneity on gas transport in natural clays

a stochastic analysis

Journal Article (2026)
Author(s)

Zhaojiang Huang (TU Delft - Civil Engineering & Geosciences)

Rik Hoedemaker (TU Delft - Civil Engineering & Geosciences)

Joaquín Liaudat (Technische Universität Darmstadt, TU Delft - Civil Engineering & Geosciences)

Bram Van Den Eijnden (Deltares, TU Delft - Civil Engineering & Geosciences)

Philip J. Vardon (TU Delft - Civil Engineering & Geosciences)

Michael A. Hicks (TU Delft - Civil Engineering & Geosciences)

Anne Catherine Dieudonné (TU Delft - Civil Engineering & Geosciences)

Research Group
Geo-engineering
DOI related publication
https://doi.org/10.1680/jenge.25.00049 Final published version
More Info
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Publication Year
2026
Language
English
Research Group
Geo-engineering
Journal title
Environmental Geotechnics
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16
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Abstract

Clay-rich geological formations are considered as host rocks for deep geological disposal of radioactive waste. Over the long term, gas will be produced and will migrate through the surrounding geological formation. Gas transport mechanisms have been investigated in laboratory tests. However, the effects of material heterogeneity remain insufficiently explored. This paper presents a stochastic analysis of two-phase flow in clays under gas injection, incorporating spatially correlated porosity. The study evaluates the effects of sample size, gas injection pressure, and the choice between two-dimensional (2D) and two-dimensional (3D) conditions on the statistical outputs, including mean behaviour and variability. The results indicate that larger samples exhibit reduced variability in the degree of saturation and gas permeability due to enhanced averaging effects. Moreover, the variation in results is higher under high gas injection pressure compared to low gas injection pressure. In addition, the variability of results is significantly reduced in 3D simulations compared to 2D, with high-permeability regions more likely to form continuous pathways under 3D conditions, emphasising the necessity of accounting for 3D effects. The findings indicate that sample size is a critical factor in experiments, as it influences the number of tests required to achieve results within a desired level of accuracy.