Abstract. We present an innovative workflow for the statistical analysis of fracture data collected along scanlines, composed of two major stages, each one with alternative options. A prerequisite in our analysis is the assessment of stationarity of the dataset, that is motivated by statistical and geological motivations. Calculating statistics on non-stationary data can be statistically meaningless, and moreover the normalization and/or sub-setting approach that we discuss here can greatly improve our understanding of geological deformation processes. Our methodology is based on the analysis of the cumulative spacing function (CSF) and cumulative spacing derivative (CSD), that allows defining the boundaries of stationary domains in an objective way. Once stationarity has been analysed, other statistical methods already known in literature can be applied. Here we discuss in details methods aimed at understanding the degree of saturation of fracture systems based on the type of spacing distribution, and we evidence their limits in cases where they are not supported by a proper spatial statistics analysis.
On a new robust workflow for the statistical and spatial analysis of fracture data collected with scanlines (or the importance of stationarity) / se-2020-83
