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|Title:||Connectivity field: a measure for characterising fracture networks|
|Citation:||Mathematical Geosciences, 2015; 47(1):63-83|
|Younes Fadakar Alghalandis, Peter A. Dowd, Chaoshui Xu|
|Abstract:||Analysis of the connectivity of a fracture network is an important component of the design, assessment and development of fracture-based reservoirs in geothermal, petroleum and groundwater resource applications. It is a useful means of characterising the flow pathways and the mechanical behaviours of reservoirs. An appropriate practical measure is required for connectivity characterisation because of the extreme complexity of fracture networks. In this paper, we propose the connectivity field (CF), as a useful measure to evaluate the spatial connectivity characteristics of fractures in a fracture network. The CF can be applied on both a particular realisation of a fracture network model (for deterministic evaluation) and on stochastic fracture network models using stochastic modelling and Monte Carlo simulations (for probabilistic evaluation with uncertainties). Two extensions are also proposed: the generalised connectivity field, a measure that is independent of support size, and the probabilistic connectivity field. Potential applications of the CF and its extensions are in determining the optimal location of an injection or production well so as to maximise reservoir performance and in determining potential flow pathways in fracture networks. The average CF map shows strong correlations with the Xf and P21 measures. The relationships between the CF measures, the fracture intersection density and the fracture network connectivity index are also investigated.|
|Keywords:||Connectivity field; Connectivity index; Discrete fracture network; Fractured reservoir; Intersection density|
|Rights:||© International Association for Mathematical Geosciences 2014|
|Appears in Collections:||Aurora harvest 2|
Civil and Environmental Engineering publications
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