Semivariogram is applied to fracture data obtained from detailed scanlinesurveys of nine field sites in western New York, USA in order to investigate the spatial patterns ofnatural fractures. The length of the scanlin...Semivariogram is applied to fracture data obtained from detailed scanlinesurveys of nine field sites in western New York, USA in order to investigate the spatial patterns ofnatural fractures. The length of the scanline is up to 36 m. How both fracture spacing and fracturelength vary with distance is determined through semivariogram calculations. In this study, theauthors developed a FORTRAN program to resample the fracture data from the scanline survey. Bycalculating experimental semivariogram, the authors found five different types of spatial patternsthat can be described by linear, spherical, reversed spherical, polynomial I (for aO) models, of which the last three arc newly proposed in this study. Thewell-structured semivariograms of fracture spacing and length indicate that both the location of thefractures and the length distribution within their structure domains are not random. The results ofthis study also suggest that semivariograms can provide useful information in terms of spatialcorrelation distance for fracture location and fracture length. These semivariograms can also beutilized to design more efficient sampling schemes for further surveys. as well as to define thelimits of highly probable extrapolation of a structure domain.展开更多
文摘Semivariogram is applied to fracture data obtained from detailed scanlinesurveys of nine field sites in western New York, USA in order to investigate the spatial patterns ofnatural fractures. The length of the scanline is up to 36 m. How both fracture spacing and fracturelength vary with distance is determined through semivariogram calculations. In this study, theauthors developed a FORTRAN program to resample the fracture data from the scanline survey. Bycalculating experimental semivariogram, the authors found five different types of spatial patternsthat can be described by linear, spherical, reversed spherical, polynomial I (for aO) models, of which the last three arc newly proposed in this study. Thewell-structured semivariograms of fracture spacing and length indicate that both the location of thefractures and the length distribution within their structure domains are not random. The results ofthis study also suggest that semivariograms can provide useful information in terms of spatialcorrelation distance for fracture location and fracture length. These semivariograms can also beutilized to design more efficient sampling schemes for further surveys. as well as to define thelimits of highly probable extrapolation of a structure domain.
