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The channelisation of flows through fractured geological systems can critically impact processes like groundwater contamination, geothermal energy extraction, hydrogen storage, and carbon sequestration. Despite its importance, characterising flow channelisation and development of predictive models remains challenging due to complex interactions across multiple scales. This paper discusses new opportunities to characterise flow channelisation in fractured media across scales. Flow channelisation primarily occurs at two scales, within a single fracture, and across an interconnected network. At the single fracture scale, the detailed control and reproducibility of additive manufacturing (three-dimensional printing) provides a breakthrough opportunity to validate direct numerical simulations of flow and reactive transport. At the network scale, graph-based machine learning algorithms designed to naturally account for the complex connectivity that occurs in fractured media may provide a revolutionary advancement in computational science.

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