The Influence of Resolution on Scale-Dependent Clustering in Fracture Data

Abstract

Fracture spacing data is widely studied as its application allows for characterizing fractured reservoirs and identifying preferential flow paths. Such data can be acquired from scanlines, cores and well-logs (e.g., dip meter, OPTV) at various resolutions. However, the influence of resolution of the data obtained from various methods on the results is not well-known. Lacunarity is a parameter that quantifies the scale-dependent clustering of spatial patterns. It has been previously used for delineating differences between a set of nested fracture networks with similar fractal dimensions but collected at different resolutions. Recently, lacunarity has also been used for identifying scale-dependent pattern changes from scanline data. The current research illustrates the application of this technique for delineating differences between scale-dependent clustering attributes of data collected at various resolutions along the same scanline. Specifically, data was collected from outcrop exposures (i.e., road-cuts and dip slopes) of the Cretaceous turbititic sandstones of the Chatsworth Formation widely exposed in southern California (USA) at various resolutions. The same scanline at low (aerial photograph) and high resolution (ground measurement) is analyzed for its scale-dependent clustering attributes. It is found that while the coefficient of variation indicates an overall near random arrangement for the low-resolution data, lacunarity curves of high-resolution data identify clusters at the meter-scale. This observation is consistent with the findings from an earlier study that analyzed scale-dependent fracture clustering in maps from a different location.

AAPG Datapages/Search and Discovery Article #90216 ©2015 AAPG Annual Convention and Exhibition, Denver, CO., May 31 - June 3, 2015