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.
Bistacchi, A., Mittempergher, S., Martinelli, M., Storti, F. (2020). On a new robust workflow for the statistical and spatial analysis of fracture data collected with scanlines (or the importance of stationarity). SOLID EARTH, 11(6), 2535-2547 [10.5194/se-11-2535-2020].
On a new robust workflow for the statistical and spatial analysis of fracture data collected with scanlines (or the importance of stationarity)
Bistacchi, Andrea
;Mittempergher, Silvia;Martinelli, Mattia;
2020
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, 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.File | Dimensione | Formato | |
---|---|---|---|
10281-297827_VoR.pdf
accesso aperto
Tipologia di allegato:
Publisher’s Version (Version of Record, VoR)
Licenza:
Creative Commons
Dimensione
2.22 MB
Formato
Adobe PDF
|
2.22 MB | Adobe PDF | Visualizza/Apri |
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.