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https://hdl.handle.net/2440/83339
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Type: | Journal article |
Title: | LiDAR-based digital outcrops for sedimentological analysis: workflows and techniques |
Author: | Rarity, G. Van Lanen, X. Hodgetts, D. Gawthorpe, R. Wilson, P. Fabuel-Perez, I. Redfern, J. |
Citation: | Geological Society Special Publication, 2014; 387(1):153-183 |
Publisher: | Geological Society Publishing House |
Issue Date: | 2014 |
ISSN: | 0305-8719 0072-1085 |
Statement of Responsibility: | F. Rarity, X. M. T. Van Lanen, D. Hodgetts, R. L. Gawthorpe, P. Wilson, I. Fabuel-Perez, & J. Redfern |
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. |
Rights: | © The Geological Society of London 2013 |
DOI: | 10.1144/SP387.5 |
Published version: | http://dx.doi.org/10.1144/sp387.5 |
Appears in Collections: | Aurora harvest Australian School of Petroleum publications |
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