Evaluating roughness scaling properties of natural active fault surfaces by means of multi-view photogrammetry

Abstract

(2017) 'Evaluating roughness scaling properties of natural active fault surfaces by means of multi-view photogrammetry. ', Tectonophysics., Further information on publisher's website: Use policyThe full-text may be used and/or reproduced, and given to third parties in any format or medium, without prior permission or charge, for personal research or study, educational, or not-for-prot purposes provided that:• a full bibliographic reference is made to the original source • a link is made to the metadata record in DRO • the full-text is not changed in any way The full-text must not be sold in any format or medium without the formal permission of the copyright holders.Please consult the full DRO policy for further details. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. A C C E P T E D M A N U S C R I P T AbstractFault roughness is a measure of the dimensions and distribution of fault asperities, which can act as stress concentrators affecting fault frictional behaviour and the dynamics of rupture propagation.Studies aimed at describing fault roughness require the acquisition of extremely detailed and accurate datasets of fault surface topography. Fault surface data have been acquired by methods such as LiDAR, laser profilometers and white light interferometers, each covering different length scales and with only LiDAR available in the field. Here we explore the potential use of multi-view photogrammetric methods in fault roughness studies, which are presently underexplored and offer the advantage of detailed data acquisition directly in the field. We applied the photogrammetric method to reproduce fault topography, by using seven dm-sized fault rock samples photographed in the lab, three fault surfaces photographed in the field, and one control object used to estimate the model error.We studied these topographies estimating their roughness scaling coefficients through a Fourier power spectrum method. Our results show scaling coefficients of 0.84±0.17 along the slip direction ACCEPTED MANUSCRIPTA C C E P T E D M A N U S C R I P T 2 and 0.91±0.17 perpendicularly to it, and are thus comparable to those results obtained by previous authors. This provides encouragement for the use of photogrammetric methods for future studies, particularly those involving field-based acquisition, where other techniques have limitations.

Analysis of Fracture Roughness Control on Permeability Using SfM and Fluid Flow Simulations: Implications for Carbonate Reservoir Characterization

“…As a measure to define the error of the model, we follow the methodology established by Corradetti et al [19]. This calls for modeling a piece of graph paper under the same condition as fracture imaging (same light, relative distance, and number of photos).…”

“…Various approaches have been reported in the literature for mapping the surface of fractures and faults in the field or laboratory involving the use of Lidar [14,15], laboratory profilometers [16][17][18], and SfM photogrammetry (e.g., [12,19]). Corradetti et al [19] applied SfM photogrammetry for mapping fracture surfaces obtaining 3D reconstructions with point-cloud densities of equal quality to Lidar-derived data. Among these methods, SfM photogrammetry shows great promise as it is inexpensive (photo-camera and processing software) and extremely flexible regarding the scales and conditions (applicable in the field and laboratory).…”

“…Among these methods, SfM photogrammetry shows great promise as it is inexpensive (photo-camera and processing software) and extremely flexible regarding the scales and conditions (applicable in the field and laboratory). For example, SfM photogrammetry has been successfully used as an analytical tool to gather geologic data from outcrop studies [20][21][22][23], as well as at smaller scales on fault surfaces [19] and fossilized human footprints [24].…”

“…Evaluation of fracture roughness is achieved by implementing the power spectral density (PSD), which provides a more objective description based on the frequency distribution of the asperities in the Fourier domain. This approach has been successfully applied by previous authors for describing the roughness of fractures (e.g., [25]) and fault surfaces [14,15,18,19]. To increase the statistical significance of the results, approximately 2000 fractures were modeled using the software SYNFRAC [25][26][27] creating computer-generated synthetic fractures, using input parameters of the fractal dimension, fracture roughness (an output of the PSD analysis of real fractures), and the standard deviation of the asperities height.…”

Focus stacking photogrammetry for micro‐scale roughness reconstruction: a methodological study

“…Wickens and Barton (1971) proposed that photogrammetry could be used as a method of roughness measurements for rock fractures. With the advance of digital cameras, photogrammetry has been successfully applied in both laboratory assessments (Lee and Ahn, 2004;Fujii et al, 2007;Nilsson et al, 2012) and field measurements (Fujii et al, 2007;Haneberg, 2007;Bistacchi et al, 2011;Corradetti et al, 2017a) of fault and fracture wall roughness at different length scales. It has also been recently applied to surface tracking in analogue experiments (Heng et al, 2010;Galland et al, 2016), fold analysis (Vollgger and Cruden, 2016;Corradetti et al, 2017b), fault or fracture spatial analysis (Lato and V€ oge, 2012;Vollgger and Cruden, 2016), stratigraphy (Nieminski and Graham, 2017) and palaeontology (Lockley et al, 2016).…”