| Statistical discontinuity network characterization methods require assumptions regarding the probability distributions of discontinuity geometry parameters, such as, intensity, lengths, orientations, locations, and interconnectivity. Such assumptions do not always conform to the characteristics of the discontinuity data at any given site. Use of simulation techniques also suffers from the fact that discontinuity length data is often censored, since the discontinuities are often not entirely visible. Also, any bias that may be present in the discontinuity characteristics at any specific field site are difficult to incorporate in existing models.;In this work, the Bookstrap method is proposed. This is a relatively new nonparametric statistical technique, where no a priori assumptions are necessary regarding the probability distributions of discontinuity geometry parameters. It is a general method of estimating parameters of independent and identically distributed random variables, when their probability distribution functions are unknown. The method involves replacing the actual, but unknown, probability distribution of a characteristic with an empirical distribution based on observed data, and subsequently resampling the data with replacement, to obtain a Monte Carlo distribution of the random variable. The applicability of the method lies in the fact that only measurable field data is used to automatically estimate the statistical behavior of the discontinuity network, including bias, thus eliminating the need to find a statistical model that fits the data.;This study shows how the bootstrap method may be used to estimate the characteristics of a discontinuity network, in two dimensions, through comparison with analytical and simulation methods. A data completion mechanism is used to estimate the total lengths of partially measurable discontinuity traces. Bootstrap estimates of the parameters are given as mean values with bias corrected confidence intervals, and cumulative probability distributions. Finally, the method is used to estimate the fluid flow through such a network with bias-corrected confidence intervals.;The bootstrap method is demonstrated to be a robust method for the characterization of discontinuity networks and fluid flow in a rock mass. It is applicable to any field site without modifications , the only requirement for use being the availability of computational capabilities. |
