Multilevel Monte Carlo Predictions of First Passage Times in Three‐Dimensional Discrete Fracture Networks: A Graph‐Based Approach

We present a method combining multilevel Monte Carlo (MLMC) and a graph‐based primary subnetwork identification algorithm to provide estimates of the mean and variance of the distribution of first passage times in fracture media at significantly lower computational cost than standard Monte Carlo (MC) methods. Simulations of solute transport are performed using a discrete fracture network (DFN), and instead of using various grid resolutions for levels in the MLMC, which is standard practice in MLMC, we identify a hierarchy of subnetworks in the DFN based on the shortest topological paths through the network using a graph‐based method. While the mean of these ensembles is of critical importance, the variance is also essential in fractured media where uncertainty is an overarching theme, and understanding variability across an ensemble is a requirement for safety assessments. The method provides good estimates of the mean and variance at two orders of magnitude lower computational cost than MC. Key Points Multilevel Monte Carlo is used to predict first passage times in flows through discrete fracture networks The method provides estimates of the mean and variance at several orders of magnitude lower computational cost than standard Monte Carlo We identify a hierarchy of subnetworks based on the shortest topological paths through the network using a graph‐based method