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  • Persistent Homology as a Heterogeneity Metric for Predicting Pore Size Change in Dissolving Carbonates Dataset

    work
    Creator:
    Thompson, Ellen P. and Ellis, Brian R.
    Description:
    Accurate prediction of physical alterations in carbonate reservoirs under dissolution is critical for development of subsurface energy technologies. The impact of mineral dissolution on flow characteristics depends on the connectivity and tortuosity of the pore network. Persistent homology is a tool from algebraic topology that describes the size and connectivity of topological features. When applied to 3D X-ray computed tomography (XCT) imagery of rock cores, it provides a novel metric of pore network heterogeneity. Prior works have demonstrated the efficacy of persistent homology in predicting flow properties in numerical simulations of flow through porous media. Its ability to combine size, spatial distribution, and connectivity information make it a promising tool for understanding reactive transport in complex pore networks, yet limited work has been done to apply persistence analysis to experimental studies on natural rocks. In this study, three limestone cores were imaged by XCT before and after acid-driven dissolution flow through experiments. Each XCT scan was analyzed using persistent homology. In all three rocks, permeability increase was driven by the growth of large, connected pore bodies. The two most homogenous samples saw an increased effect nearer to the flow inlet, suggesting emerging preferential flow paths as the reaction front progresses. The most heterogeneous sample showed an increase in along-core homogeneity during reaction. Variability of persistence showed moderate positive correlation with pore body size increase. Persistence heterogeneity analysis could be used to anticipate where greatest pore size evolution may occur in a reservoir targeted for subsurface development, improving confidence in project viability.
    Keyword:
    Carbonate dissolution, X-ray computed tomography, Porous media, Topology, and Persistent homology
    Citation to related publication:
    Thompson, E.P.; Ellis, B.R. (2023) Persistent Homology as a Heterogeneity Metric for Predicting Pore Size Change in Dissolving Carbonates. In Review.
    Discipline:
    Science and Engineering