Application of the discrete fracture network concept with field data: Possibilities of model calibration and validation

Abstract

The uneven flow distribution observed in a migration experiment in the Stripa research mine is analyzed with a discrete fracture network model. Data on the measured inflow distribution and trace geometry in the experimental drift are the basic sources for estimation of the model parameters. Direct estimates cannot provide a unique definition of input data to the model; thus different combinations of input data need to be analyzed in the network model. Detailed measurements of the inflow distribution in the experimental drift provided an opportunity to determine the model parameters through calibration in the network model. Calibration was performed on the mean inflow, distribution of flow, and trace geometry observed in the roof of the experimental drift. The simulation results show that the model can be calibrated to produce an areal flow distribution that is consistent with the measured one. The uncertainties in the input parameters are thus reduced, but different combinations of input data are still possible. The calibration simulations show that the length of conductive fractures per area might be used as a calibration parameter. Simulations based on different combinations of fracture size and density but with the same length of conductive fracture traces produced similar flow distributions. The validity of the calibrated model is explored by predicting the flow into the boreholes at the experimental site. The resulting inflow distributions accord well with those measured in two of the three boreholes. The properties of the third borehole, which differ substantially from the other two, could not be explained by the simulation results.