HighTech and Innovation Journal · 2020 · 79 citations · 46 references
EngineeringEarth SciencesPetroleum EngineeringBayesian Data AnalysisPetrophysicsSubsurface Fluid FlowFluid-flow In Porous MediaNetwork CentralityPermeability AnalysisPermeability CharacterizationPermeability EstimationPorosity AnalysisAbsolute PermeabilityCentralityClusteringK-core DecompositionPore Network AnalysisPore Throat StructurePore-scale PermeabilityPorous Structures
This article develops a Bayesian framework to quantify the absolute permeability of water in a porous structure from the geometry and clustering parameters of its underlying pore-throat network. These parameters include the network's diameter, transivity, degree, centrality, assortativity, edge density, K-core decomposition, Kleinberg's hub centrality scores, Kleinberg's authority centrality scores, length, and porosity. In addition, the incorporated clustering aspects of the networks have been determined with respect to several clustering criteria: edge betweenness, greedy optimization of modularity, multi-level optimization of modularity, and short random walks. As such, the article takes the first steps towards creating a database of micro-networks for micro-scale porous structures, to be used as the main input stream for the proposed Bayesian scheme. Doi: 10.28991/HIJ-2020-01-04-02 Full Text: PDF
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