A CLUSTERED FRACTAL DISCRETE FRACTURE NETWORK MODEL FOR FRACTURED COAL

Author:

LIANG XIN12ORCID,HOU PENG3ORCID,LIU GUANNAN4ORCID,XUE YI12ORCID,LIU JIA12ORCID,GAO FENG4ORCID,ZHANG ZHIZHEN4ORCID

Affiliation:

1. State Key Laboratory of Eco-hydraulics in Northwest Arid Region, Xi’an University of Technology, Xi’an 710048, P. R. China

2. School of Civil Engineering and Architecture, Xi’an University of Technology, Xi’an 710048, P. R. China

3. School of Civil Engineering, Wuhan University, Wuhan 430072, P. R. China

4. State Key Laboratory for Geomechanics & Deep Underground Engineering, China University of Mining and Technology, Xuzhou, Jiangsu Province 221116, P. R. China

Abstract

The fracture network in fractured coal is the main channel of coal seam gas flow. Not only the geometric topology properties (such as fractal characteristics) of a single fracture but also the connection topology properties (interconnection characteristics between fractures) of the fracture network have an important impact on the fluid flow in fracture networks. In this study, the connection topology properties of the fracture network in the fractured coal are explored based on the complex network theory for the first time. The property parameters such as the fracture node degree, the clustering coefficient, and the average path length are analyzed. It shows that the average clustering coefficient of the fracture network in fractured coal is larger, and the average path length is smaller. The connection property of the fracture network in the fractured coal presents a typical “small-world” clustering model. Further, by considering the fractal characteristics of the single fracture and the clustering characteristics of the fracture network, an improved clustered fractal discrete fracture network (DFN) model is developed. Then, based on the lattice Boltzmann method, the permeability properties of the generated clustered fractal DFNs are analyzed. The results show that the permeability of DFNs is positively correlated with the average clustering coefficient of fracture network, and negatively correlated with the fractal dimension of fracture. Therefore, the topological clustering characteristics of fracture networks and the fractal characteristics of fractures cannot be ignored in describing the fluid flow in the fracture network, and our clustered fractal DFN model provides a new idea for guiding the optimization design in DFN engineering.

Funder

National Natural Science Foundation of China

Natural Science Foundation of Shaanxi Provincial Department of Education

Key Research and Development Projects of Shaanxi Province

Publisher

World Scientific Pub Co Pte Ltd

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