Spatial Scaling of Normal Faults, A-Bomb Canyon, Buckskin Mountains, Arizona

Abstract

Understanding the spatial arrangement of structural features, such as faults, can lead to an understanding of whether the features are randomly located, clustered together, or anti-clustered in space. The objective of this project is to understand the spatial arrangement of normal faults in A-Bomb Canyon, in the Buckskin Mountains of Arizona. Previous spatial arrangement studies have included statistical analyses of nearest neighbor spacings (Priest and Hudson, 1976; Narr and Suppe, 1991) and box counting (Barton, 1995), which have been shown to have limited utility (Gomez and Marrett, in review). The normalized correlation count methodology (Marrett et al., in review) was utilized in this study in order to quantify the spatial organization of faults. In the process of studying the arrangement of these faults, the size distribution, coefficient of variation as well as the normalized correlation count will be examined in order to understand whether or not the faults are clustered or randomly spaced and, if they are clustered, whether those clusters show fractal scaling. Data were collected in the field along three different scanlines. Two of the scanlines are shorter in overall length, considered high resolution and focused on faults with displacements on the centimeter and larger scale. The third scanline, which is considerably longer, focused only on faults with displacements larger than a meter. Scanline collection is done in the field by moving along a linear transect over the area in question and measuring the spacing between each structural feature that appears along the scanline. Data analysis utilizes the Fourier series along with the correlation count technique. Preliminary conclusions show that the size distribution of the faults follows a common power law on both the high resolution and the low resolution scales. The high resolution correlation count indicates that the faults are arranged in regularly spaced fractal clusters and the low resolution correlation count indicates self-organized clustering of faults. Moving forward these analyses, having different resolutions and length scales, will be compared in order to understand how observations on short scales (e.g., well bores) constrain faults on long scales (e.g., oil fields).

AAPG Datapages/Search and Discovery Article #90291 ©2017 AAPG Annual Convention and Exhibition, Houston, Texas, April 2-5, 2017