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Relationship between Aperture and Spatial Arrangement of Opening-Mode Fractures: Preferential Positioning of Large Fractures Inside Clusters

Leonel A. Gomez and Randall Marrett
The University of Texas at Austin, Austin, TX

The permeability of a Previous HitfractureNext Hit network is dominated by the few largest aperture fractures and influenced by how fractures are spatially arranged. Therefore, understanding how the largest fractures of a Previous HitfractureNext Hit array are arranged in space is vital to increase the understanding of the behavior of fractured reservoirs. In addition, there is very little published research on the relationship between aperture and spacing of opening-mode fractures. Qualitative field observations on dolostones and sandstones in the Sierra Madre Oriental, Mexico, seem to indicate that on some arrays, fractures with large apertures are more abundant inside clusters than between clusters.

Every Previous HitfractureNext Hit data set measured, regardless of the scale, has typically an aperture Previous HitthresholdNext Hit bellow which Previous HitfractureNext Hit aperture cannot be reliably measured. We compared the spatial arrangement of the same Previous HitfractureNext Hit array at different values of aperture Previous HitthresholdNext Hit to study the spatial preferential positioning of a particular aperture fraction of the array. For the quantitative analysis of the spatial arrangement of selected Previous HitfractureNext Hit arrays we used a recently developed analytical technique, called normalized correlation count (NCC). NCC analyses indicate that in arrays that are harmonically arranged in clusters, large fractures are, statistically speaking, preferentially located inside clusters, more so than small fractures. When the same analysis is performed on Previous HitfractureNext Hit arrays that do not display clustering distinguishable from random or on arrays where the Previous HitfractureTop positions are randomized, large fractures do not display a preferential location inside clusters.