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Evaluation of water permeability of rough fractures based on a self-affine fractal model and optimized segmentation algorithm

•Self-affine rough fractures were used to investigate fluid flow in rock masses.•A local cubic law was developed to evaluate fracture permeability.•The standard deviation and Hurst exponent of fractures were considered.•A Cuckoo optimisation method was used to segment fractures into smaller parts.•T...

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Bibliographic Details
Published in:Advances in water resources 2019-07, Vol.129, p.99-111
Main Authors: Ju, Yang, Dong, Jiabin, Gao, Feng, Wang, Jianguo
Format: Article
Language:English
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Summary:•Self-affine rough fractures were used to investigate fluid flow in rock masses.•A local cubic law was developed to evaluate fracture permeability.•The standard deviation and Hurst exponent of fractures were considered.•A Cuckoo optimisation method was used to segment fractures into smaller parts.•The segment strategies for fractures were optimized and verified by experiments. The water permeability of natural fractures is highly related to their morphological characteristics. For fractures with irregular profiles and variable apertures, it is challenging to define an appropriate aperture to apply the traditional cubic law for evaluating permeability. In this study, we propose a novel approach that integrates the standard deviation and the Hurst exponent of a self-affine fracture profile to characterise the effects of fracture morphology on permeability using Cuckoo search algorithms. A modified local cubic law was derived to evaluate permeability, considering the roughness and Hurst exponent of fractures. The required number of segments for a fracture was obtained by comparing simulation results using Lattice Boltzmann methods. The proposed permeability model and segment strategy were validated by experiments on rough fractures. The results show that the number of segments required for the model can be directly derived from the dimensionless aperture (i.e., mechanical aperture/length of fracture media).
ISSN:0309-1708
1872-9657
DOI:10.1016/j.advwatres.2019.05.007