This dataset includes additional figures for the study of "Modeling Flow in Naturally Fractured Reservoirs: Effect of Fracture Aperture Distribution on Dominant Sub-Network for Flow".
Fracture network connectivity and aperture (or conductivity) distribution are two crucial features controlling the flow behavior of naturally fractured reservoirs. The effect of connectivity on flow properties is well documented. We focus here on the influence of fracture aperture distribution. We model a two-dimensional fractured reservoir in which the matrix is impermeable and the fractures are well-connected. The fractures obey a power-law length distribution, as observed in natural fracture networks. For the aperture distribution, since the information from subsurface fracture networks is limited, we test a number of cases: log-normal distributions (from narrow to broad), power-law distributions (from narrow to broad), and one case where the aperture is proportional to the fracture length. We find that even a well-connected fracture network can behave like a much sparser network when the aperture distribution is broad enough ( ≤ 2 for power-law aperture distributions and ≥ 0.4 for log-normal aperture distributions). Specifically, most fractures can be eliminated leaving the remaining dominant sub-network with 90% of the permeability of the original fracture network. We determine how broad the aperture distribution must be to approach this behavior and the dependence of the dominant sub-network on the parameters of the aperture distribution. We also explore whether one can identify the dominant sub-network without doing flow calculations