Anisotropy may be observed in rock masses that contain fractures and affects several properties including flow behavior which is controlled by how fractures are clustered in space. While Rose diagrams are often used for delineating "fracture sets" in different directions, it is a challenge to quantify anisotropy in terms of fracture clustering that controls fluid flow. This research attempts to answer the question by capturing the anisotropy in fluid production rates of fracture networks and implements a modified inverted five-spot water flooding pattern. Flow simulation is done by considering the fracture continuum (FC) model and using a Darcy based streamline simulator. The results from this “dynamic modeling” approach is compared with the anisotropy in fracture clustering for a set of natural maps. Coefficient of variation that can differentiate between clustered, random, and anticlustered fractures in 1-dimensional fracture data is used for quantifying the “clustering” anisotropy in 2-dimensional fracture networks. We employ this parameter for evaluating directional clustering in such networks by moving a set of scanlines in two mutually perpendicular directions and finding the respective arithmetic averages. The results show that overall fluid production values tend to be higher in the direction of highly clustered fractures. It implies that a “dynamic” approach can be successfully used for evaluating the anisotropy of a reservoir and larger ratio in production values in two mutually perpendicular directions suggests the presence of fracture clusters. If such anisotropy is taken into account, it can help in building more realistic DFN models.
Analyzing Anisotropy in Fracture Networks: A Flow Simulation Approach
Sahu, Ajay K., and Ankur Roy. "Analyzing Anisotropy in Fracture Networks: A Flow Simulation Approach." Paper presented at the 3rd International Discrete Fracture Network Engineering Conference, Santa Fe, New Mexico, USA, June 2022. doi: https://doi.org/10.56952/ARMA-DFNE-22-2358
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