Investigating spatial heterogeneity within fracture networks using hierarchical clustering and graph distance metrics
نویسندگان
چکیده
Abstract. Rock fractures organize as networks, exhibiting natural variation in their spatial arrangements. Therefore, identifying, quantifying, and comparing variations arrangements within network geometries are of interest when explicit fracture representations or discrete models chosen to capture the influence on bulk rock behaviour. Treating networks graphs, we introduce a novel approach quantify variation. The method combines graph similarity measures with hierarchical clustering is applied investigate large-scale 2-D digitized from well-known Lilstock limestone pavements, Bristol Channel, UK. We consider three large, fractured regions, comprising nearly 300 000 spread over 14 200 m2 pavements. Using moving-window sampling approach, first subsample large into subgraphs. Four – fingerprint distance, D-measure, Network Laplacian spectral descriptor (NetLSD), portrait divergence that encapsulate topological relationships geometry then used compute pair-wise subgraph distances serving input for statistical technique. In form dendrograms derived maps, results indicate autocorrelation localized clusters gradually vary tens metres visually discernable quantifiable boundaries. Fractures identified exhibit differences orientations topology. comparison similarity-derived persistence indicates an intra-network not immediately obvious ubiquitous intensity density maps. proposed provides quantitative way identify guiding stochastic geostatistical approaches modelling.
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ژورنال
عنوان ژورنال: Solid Earth
سال: 2021
ISSN: ['1869-9529', '1869-9510']
DOI: https://doi.org/10.5194/se-12-2159-2021