Extraction of three-dimensional fracture trace maps from calibrated image sequences

Abstract

The routine application of digital survey technologies such as terrestrial lidar and photogrammetry to the characterization of fault and fractures in outcrop over the past decade has resulted in major advances in terms of the efficiency of discontinuity data acquisition. However, the reliance upon meshand point-cloud-based analysis approaches means that data sets obtained from these sources commonly offer heavily abstracted views of the measured fracture network due to the limited resolution of the input model. Here, we pre sent an alternative approach that combines conventional two-dimensional (2D) image analysis with ray-tracing techniques to extract three-dimensional (3D) fracture trace maps from photogrammetrically calibrated image sequences. These 3D trace objects may be interrogated to obtain fracture network properties (trace length, intensity, and connectivity), with probabilistic methods used to estimate fracture orientation for high collinearity traces.Our approach possesses a number of advantages over existing digital surface reconstruction-based methods, with the use of a 2D pixel-based approach allowing established image-processing routines (e.g., edge detection/ connected components analysis) to be applied to the characterization of fracture and fault properties. Moreover, the innately high resolution of the input images results in practically lossless 3D fracture trace representation, limiting truncation effects. As a result, the method is capable of resolving local variability in higher-order fracture properties such as fracture intensity, which are difficult to derive using existing approaches. We demonstrate the approach on pervasively faulted Permian age exposures of the Vale of Eden Basin, UK.

Rapid, semi-automatic fracture and contact mapping for point clouds, images and geophysical data

“…These traces cannot be detected using facet-based techniques and require a different approach. Seers and Hodgetts (2016) demonstrate one such approach and automatically extract 3-D structural traces by applying image-based edge detection techniques (phase congruency) to a set of images and then projecting the identified traces into 3-D using depth information derived from photogrammetric reconstructions or associated laser scan data. This approach uses multiple images to overcome issues associated with out-of-plane geometry; however, as with other fully automated methods, a variety of parameters and thresholds require careful calibration and the results must be manually vetted to remove false positives.…”

“…There has recently been significant effort to develop automatic or computer-assisted methods for digitising structural data, in particular from orthorectified photographs or image sequences (Seers and Hodgetts, 2016;Vasuki et al, 2014;Jones et al, 2009). Achieving satisfactory automated digitisation is challenging for the mapping of geological structures due to intrinsic variables such as geometry, soft linkage…”

“…1242 S. T. Thiele et al: Rapid, semi-automatic fracture and contact mapping and segmentation over multiple scales and extrinsic variables such as natural variations in colour, shadows, glare and/or incomplete geological exposure. Due to this complexity, fully automatic methods often require significant manual adjustment and vetting to remove false positives while retaining real geological features (Vasuki et al, 2014;Seers and Hodgetts, 2016).…”

A Nonparametric Approach for Assessing Precision in Georeferenced Point Clouds Best Fit Planes: Toward More Reliable Thresholds

“…Several manual, semiautomated, and unsupervised procedures have been developed for structural data reduction, allowing three-dimensional representations of structural traces (Lato et al, 2009;Li et al, 2016;Seers & Hodgetts, 2016a;Vasuki et al, 2014), as well as points of near-planar geological surfaces (Chen et Key Points:…”

Quantitative analysis of folds by means of orthorectified photogrammetric 3D models: a case study from Mt. Catria, Northern Apennines, Italy

“…The user‐friendly nature of this rapidly improving technique is, in fact, allowing a large community of geoscientists to construct detailed digital models of geological exposures (for example, Pringle et al., ; Sturzenegger and Stead, ; Bistacchi et al., ; ; Favalli et al., ; Massironi et al., ; Tavani et al., ; Reitman et al., ; Thiele et al., ; Vollgger and Cruden, ). More specifically, the application of this technique is becoming widely accepted in dealing with the characterisation of geological structures and related structural elements (fractures and folds) from digital outcrop data (for example, McCaffrey et al., ; Pearce et al., ; Bemis et al., ; Vasuki et al., ; Seers and Hodgetts, ; Vollgger and Cruden, ; Corradetti et al, ). The photogrammetric method (Remondino and El‐Hakim, ) is an estimative technique through which the metric data of a 3D object (shape, position and size) are obtained by estimating the spatial coordinates of each point in the photographs.…”