Publication | Open Access
A Multi-Scale Fractal Approach for Coal Permeability Estimation via MIP and NMR Methods
16
Citations
29
References
2022
Year
Rock TestingEnvironmental MonitoringEngineeringHydrogeophysicsPermeability PredictionEarth SciencePorous BodyFluid PropertiesNmr Experimental DataPorous MediaTransport PhenomenaHydraulic PropertyMulti-scale Fractal ApproachHydrogeologyNmr MethodsCoal Permeability EstimationMultiphase FlowFormation DamageHydrologyCoal BasinCoal Bed MethaneRock PropertiesCoal UtilizationPore StructureEnvironmental EngineeringCivil EngineeringGeomechanicsPorosityRock PhysicPetroleum EngineeringMultiscale Modeling
Permeability in porous media has an important role in many engineering applications, which depends mainly on the pore size, distribution, and connectivity of porous media. As the pore structure distribution of coal has a multi-scale fractal dimension characteristic, this study aimed to propose a multi-scale fractal dimension characteristics units model (MFU) to describe the pore structure distribution by analyzing the multi-scale fractal dimension characteristics of coal pore media. Then, a multi-scale fractal permeability model was established based on MFU. The pore structure distribution was obtained by mercury injection porosimetry (MIP) and nuclear magnetic resonance (NMR) experiments. Based on MIP and NMR experimental data, the permeability contribution of different pore diameters were calculated. The results show that the permeability contribution of the micropore was minimal and can be ignored. The permeability contribution of mesopores was about 1–5%, and the permeability contribution of macropores was about 95–99%, which plays a decisive role in the seepage process. The calculated results, based on multi-scale fractal permeability model and the experimental permeability data, are in the same order of magnitude. The permeability prediction based on proposed model is better than classical single fractal permeability model.
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