LiDAR-based digital outcrops for sedimentological analysis: workflows and techniques

Abstract

Recent developments in workflows and techniques for the integration and analysis of terrestrial LiDAR (Light Detection And Ranging) and conventional outcrop datasets are demonstrated through three case studies. The first study shows the power of three-dimensional (3D) data visualization, in association with an innovative surface-modelling technique, for establishing large-scale 3D stratigraphical frameworks. The second presents an approach to derive reliable geometrical data on sediment-body geometries, whereas the third presents a new technique to quantify the proportions, distributions and variability of sedimentary facies directly from outcrop. In combination, these techniques provide essential conditioning data for geocellular and stochastic facies modelling. Built upon robust, reproducible and quantitative data, the resultant models combine realistic 3D geological architectures with sufficient quantities of reliable numerical data required for stable statistical analysis and establishing uncertainty. Together this new information provides detailed understanding and quantification of the 3D complexity of the sedimentary systems in question, thus offering insights of value for predicting the subsurface anatomy of analogous petroleum systems. As such, use of LiDAR, when combined with conventional field geology, offers a powerful tool for quantitative outcrop analysis, tightly constraining 3D structural and stratigraphical interpretations, and effectively increasing the statistical significance of outcrop analogues for reservoir characterization.

Ground-based and UAV-Based photogrammetry: A multi-scale, high-resolution mapping tool for structural geology and paleoseismology

“…Artificial Intelligence approaches such as Neural Networks, Fuzzy Logic and Evolutionary Algorithms allow the automatic classification of point cloud data, aiding the identification of varying stratigraphy (van Lanen et al, 2009;Rarity et al, 2013) or the extraction and upscaling of fault and fracture populations (e.g. Gillespie et al, 2010;Seers and Hodgetts, 2013), especially when combined with field observations.…”

LiDAR, UAV or compass-clinometer? Accuracy, coverage and the effects on structural models

“…These detailed 3D reconstructions of outcrop geology are applied to a broad range of studies, including sedimentology and stratigraphy (e.g., Hodgetts et al, 2004;Enge et al, 2010;Fabuel-Perez et al, 2010;Eide and Howell, 2014;Rarity et al, 2014;Rittersbacher et al, 2014), reservoir modelling (e.g., Enge et al, 2007;Rotevatn et al, 2009;Buckley et al, 2010), and structural geology (e.g., Seers and Hodgetts, 2014;Bistacchi et al, 2015, among others). Light Detection and Ranging (LiDAR) has been the principal acquisition technique for deriving virtual outcrops in the last decade (e.g., Pringle et al, 2006;Buckley et al, 2008;Jones et al, 2009), though acquiring this type of detailed 3D spatial data requires expensive instrumentation and significant knowledge of processing workflows.…”

Direct Image-to-Geometry Registration Using Mobile Sensor Data

“…Textured surface models are used in a widening range of application domains, such a urban planning (Semmo and Döllner, 2015), cultural heritage (Potenziani et al, 2015), archaeology (Van Damme, 2015) and geological outcrop modelling (Howell et al, 2014, Rarity et al, 2014. After a model has been captured, often by means of terrestrial laser scanning (TLS) or photogrammetry, it may be desirable for domain experts to supplement the model with novel images to make initially-hidden features visible, or to add annotations.…”