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, which is motivated by statistical and geological considerations. 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 performing non-parametric statistical tests, which allow detecting important features of the spatial distribution of fractures, and on the analysis of the cumulative spacing function (CSF) and cumulative spacing derivative (CSD), which allows defining the boundaries of stationary domains in an objective way. Once stationarity has been analysed, other statistical methods already known in the literature can be applied. Here we discuss in detail 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 in which they are not supported by a proper spatial statistical analysis.

中文翻译：

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在新的强大工作流程上，对通过扫描线收集的裂缝数据进行统计和空间分析（或平稳性的重要性）

我们提出了一种创新的工作流程，用于对沿扫描线收集的裂缝数据进行统计分析，包括两个主要阶段，每个阶段都有其他选择。我们分析的先决条件是评估数据集的平稳性，这是出于统计和地质方面的考虑。计算非平稳数据的统计信息在统计上可能毫无意义，此外，我们在此处讨论的归一化和/或子设置方法可以极大地增进我们对地质变形过程的理解。我们的方法基于执行非参数统计测试（可以检测裂缝的空间分布的重要特征）以及对累积间隔函数（CSF）和累积间隔导数（CSD）进行分析，这可以客观地定义固定域的边界。一旦对平稳性进行了分析，就可以使用文献中已知的其他统计方法。在这里，我们详细讨论了旨在基于间距分布类型来理解裂缝系统饱和度的方法，并且在没有适当的空间统计分析支持的情况下，我们证明了它们的局限性。