PREDICTING ANOMALOUS TRANSPORT IN THREE-DIMENSIONAL DISCRETE FRACTURE NETWORKS

Predictive capability of flow and transport in fractured media is critical for informed decision of many civil and geological engineering applications such as geological carbon sequestration, managed aquifer recharge, assessment and remediation of contaminated fractured media, and deep geological nuclear waste repository. While it is well known that tracer transport through fractured media can be often anomalous (non-Fickian), the predictive modeling of transport in fractured media has mostly been limited to 2D discrete fracture networks (DFN). We investigate the effects of aperture heterogeneity and particle initial conditions on anomalous transport in 3D DFNs and propose a parsimonious upscaled transport model that can capture the observed anomalous transport in 3D DFNs.