Comprehensive identification of statistical homogeneity of fractured rock masses for a candidate HLW repository site, China

Determining the statistically homogeneous regions is important for engineering geological modeling and promoting systematic research on regional rock mass characteristics and rock engineering designs. This study proposes a comprehensive framework considering multiple discontinuity geometry parameters (e.g., orientation, trace length, density, and cluster characteristics.) to distinguish statistical homogeneity of fractured rock masses. First, based on the equal-area plot method (Schmidt net), the quantitative judgment ability of the Miller method for determining the similarity between two discontinuity orientation populations was improved by optimizing block network division scheme and blank area merging principle. Then, considering the distribution characteristics of discontinuity in rock mass space and the variation features of discontinuity at different geographical locations, a three-dimensional fracture network model, established using the discontinuity geometry parameters obtained from field investigation, was combined with the fractal dimension method (called the network fractal dimension method; NFD) to further evaluate the statistical homogeneity of fractured rock mass. The proposed approaches were subsequently applied to the identification of the statistical homogeneity of several typical granite fracture outcrops in the Beishan area, which is a candidate site for high-level radioactive waste (HLW) repository of China. The case study reveals that the optimized Miller method is more flexible and applicable than the conventional orientation-based methods, especially in dealing with the complex situation of the coexistence of gentle dip angle and steep dip angle as well as clustering characteristics of discontinuity. The NFD method was used to unify the influence of the main discontinuity characteristic parameters for a logical and unbiased evaluation of the statistical homogeneity. The comprehensive framework developed herein integrates the advantages of the two methods and reduces the interference of subjective evaluation. Therefore, it can be employed to efficiently determine the statistical homogeneity of rock masses at different locations at a large scale without concern over the deviation caused by different directions and size of the compared areas. •A comprehensive framework for distinguishing rock mass statistical homogeneity is presented.•Optimized Miller method and network fractal dimension method are included in this framework.•The flexi