Abstract
Summary The application of UAV-collected digital outcrop models (DOM) is quantitatively evaluated using a set of fluvial case studies to predict braided fluvial system metrics and build process-controlled reservoir models. Quantifiable accuracies help evaluate common metrics of such deposits, derived from a suite of DOM case studies. Typical data collection methods are largely restricted by ease of access, or to using remote observations with limited accuracy, such as photographic methods. Digital data collection techniques such as Lidar, differential GPS and UAV-mounted Structure from Motion (SfM) photogrammetry allow more rapid, accurate measurements from previously inaccessible locations to be taken of sedimentary architectures. High-density point clouds and photogrammetric models made in Agisoft Photoscan, are analysed in Virtual Reality Geoscience (VRGS). Geobody thicknesses, palaeocurrents, foreset details, architecture and volumes are used to reveal depositional trends. This generates many more measurements from greater outcrop volumes, providing a more meaningful dataset and reducing uncertainty in the final reservoir model.
Published Version
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