Inverse Modeling of Groundwater Flow in a 3D Fractured Media

Abstract

In order to quantify the uncertainty in the prediction of three-dimensional groundwater flow and mass transport in a fractured volcanic tuff, a Monte-Carlo approach is used. An ensemble of equally likely realizations of 3-D spatially variable hydraulic conductivity is generated and used as input to groundwater flow and advective transport model.To reduce the uncertainty in the model predictions, the hydraulic conductivity fields integrate different types of data. On one hand, they are conditioned to hydraulic conductivity measurements and soft information on hydraulic conductivities taken from a structural geology model. On the other hand, they are conditioned to piezometric head measurements. While conditioning to hard and soft hydraulic conductivity data can be achieved by standard geostatis-tical techniques, conditioning to hydraulic head measurements is non trivial because hydraulic conductivity and hydraulic head are non linearly related through the groundwater flow equation. Conditioning to hydraulic head measurements is accomplished by the self-calibrated method, a technique combining geostatistics and non-linear optimization. The methodology is demonstrated in a 3-D fractured site using data on conductivity and on transient heads from a pumping test. Ensembles of hydraulic conductivity realizations conditioned to different types of information are used as input to a groundwater flow and advective transport model; the resulting hydraulic head fields and particle arrival times are compared in terms of their variability to conclude that, for this case study, incorporating hydraulic head data reduces the uncertainty in the conductivity realizations, but it does not in particle arrival times and arrival locations.