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| A new method for network connectivity determination based on fracture network connected clusters |
| 侯孟冬1，2，张 辽1，2，程建超1，2，刘殷彤1，2，毛婷婷1，2，周生昊1，2，王路军3，刘升贵1，薛东杰1，2，3，4* |
(1. State Key Laboratory for Tunnel Engineering, China University of Mining and Technology (Beijing), Beijing 100083, China;
2. School of Mechanics and Civil Engineering, China University of Mining and Technology (Beijing), Beijing 100083, China;
3. State Key Laboratory of Water Resource Protection and Utilization in Coal Mining, National Institute of Clean and Low
Carbon Energy, Beijing 102211, China; 4. State Key Laboratory for Fine Exploration and Intelligent Development of
Coal Resources, China University of Mining and Technology (Beijing), Beijing 100083, China) |
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Abstract The scientific quantification of fracture network topology connectivity is essential for advancing fundamental theories such as rock mechanics. Essentially, it involves establishing a mapping relationship between the geometric topology of fracture networks and rock mechanics variables. To develop a universal evaluation system for fracture connectivity and to quantitatively characterize the topological geometric properties of multi-fracture connectivity, we focus on two key variables: connectivity strength and spatial connectivity effect, approached from both narrow and broad perspectives. Firstly, by considering the differences in coordination numbers between X-type and Y-type topological nodes, we define a new connectivity strength index that incorporates topological parameters of the fracture network. This index serves as a universal measurement tool for comparing the connectivity strength of multi-scale fracture networks. Secondly, using the method for assessing the intersection triangles of fracture geometries, we establish a general geometric criterion for both central and non-central connectivity. We identify three core elements for evaluating planar fracture connectivity: trace length, center position, and direction. We construct a maximum fracture cluster identification method utilizing an intersection node heat map and derive the theoretical expression for the critical trace length. Finally, we establish a percolation model to quantitatively describe the spatial distribution characteristics of fracture-connected clusters.
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2026, Vol. 45 
