3d Model And Feature Evidence Visualisation In The

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3D Model and Feature Evidence Visualisation in the Integrated Exploration Platform Jason C. Wong, Eun-Jung Holden, Daniel Wedge, David Nathan, Klaus Gessner, & Ruth Murdie Geoscientific Data Interpretation Challenges  Large volumes of geoscience data (e.g. collected by the Geological Survey of Western Australia - GSWA).  Introduces a time bottleneck as interpretation is timeconsuming, and outcomes are often not consistent within and between individuals.  Inattentional blindness is problematic for geological interpretation due to human biases.  Introduces subjectiveness as an interpreter is unlikely to identify features that are not expected or looked for.  Geological features may appear in subtle contrast to the surrounding.  Introduces uncertainty, as features are not easily visible. Integrated Exploration Platform Overview A component of a major research initiative between Geological Survey of WA (GSWA) and CET through WA Exploration Incentive Scheme (EIS) phase 2 Australian Research Council (ARC) linkage (LP140100267) Interpretation platform to promote full utilisation of GSWA data for explorers operating in WA: 1. Visualisation tools to support multiple 2D and 3D data. 2. Feature evidence – confidence feedback on interpretation lines. Intelligent support tools for computer-assisted & user-driven interpretation. Integrated Exploration Platform 1. Visualisation tools to support multiple 2D and 3D data (A suite of image blenders) Thomas, J., Cook, K.: Illuminating the Path: Research and Development Agenda for Visual Analytics. IEEE-Press (2005) 2. Feature Evidence Analysis – Confidence feedback. 2D Visualization Tools in IEP Human Perception Sensitive Colour Maps A default rainbow colour map Vs Perception friendly map 2D Visualization Tools in IEP Blenders Barycentric Triangle Blender Circle Blender Clique Blender Linear Blender Bilinear Blender Kovesi, P. 2012. Phase Preserving Tone Mapping of Non-Photographic High Dynamic Range Images, Digital Image Computing: Techniques and Applications (DICTA), 2012 International Conference on, pp.1-8. [Dynamic Range Compression tool available in the CET Grid Analysis Plugin for Geosoft Oasis Montaj] Kovesi, P. 2012. Phase Preserving Tone Mapping of Non-Photographic High Dynamic Range Images, Digital Image Computing: Techniques and Applications (DICTA), 2012 International Conference on, pp.1-8. [Dynamic Range Compression tool available in the CET Grid Analysis Plugin for Geosoft Oasis Montaj] Kovesi, P. 2012. Phase Preserving Tone Mapping of Non-Photographic High Dynamic Range Images, Digital Image Computing: Techniques and Applications (DICTA), 2012 International Conference on, pp.1-8. [Dynamic Range Compression tool available in the CET Grid Analysis Plugin for Geosoft Oasis Montaj] Kovesi, P. 2012. Phase Preserving Tone Mapping of Non-Photographic High Dynamic Range Images, Digital Image Computing: Techniques and Applications (DICTA), 2012 International Conference on, pp.1-8. [Dynamic Range Compression tool available in the CET Grid Analysis Plugin for Geosoft Oasis Montaj] 3. Kovesi, P. 2012. Phase Preserving Tone Mapping of Non-Photographic High Dynamic Range Images, Digital Image Computing: Techniques and Applications (DICTA), 2012 International Conference on, pp.1-8. [Dynamic Range Compression tool available in the CET Grid Analysis Plugin for Geosoft Oasis Montaj] 2D Visualization Tools in IEP 3D Visualization Tools in IEP  Visualization tools for 2.5D and 3D data, utilizing the concept of interactivity.  Prototype visualization combining plan-view and cross-section datasets.  Prototype comparison visualization of two 3D volumetric datasets. 3D Visualization Tools in IEP Cross-section Data Blender Single Volume Blender: Sphere Data Mode Dual Volume Blender: Slice Similarity Mode 3D Visualization Tools in IEP Integrated Exploration Platform 1. Visualisation tools to support multiple 2D and 3D data (A suite of image blenders) Thomas, J., Cook, K.: Illuminating the Path: Research and Development Agenda for Visual Analytics. IEEE-Press (2005) 2. Feature Evidence Analysis – Confidence feedback. Structural Interpretation of Magnetic Data • For structural interpretation, interpreter seeks discontinuities (edges, ridges, valleys) • CET Grid Analysis extension for Geosoft Oasis Montaj (2010-) GSWA magnetic data (RTP-DRC) from West Kimberley Ridges (Phase Symmetry) Magnetic data Ridges CET Grid Analysis Extension (for Geosoft Oasis Montaj) http://www.geosoft.com/pinfo/partners/CETgridanalysis.asp Valleys (Phase Symmetry) Magnetic data Valleys CET Grid Analysis Extension (for Geosoft Oasis Montaj) http://www.geosoft.com/pinfo/partners/CETgridanalysis.asp Edges (Phase Congruency) Magnetic data Edges CET Grid Analysis Extension (for Geosoft Oasis Montaj) http://www.geosoft.com/pinfo/partners/CETgridanalysis.asp Checking Feature Evidence on Structure Interpretation using Visualisation Structure interpretation by Mark Lindsay 2015  Visual feedback on data evidence  Quantitative measure of feature evidence Feature Evidence Visualisation On-going Development  Improved integration and visualisation of MT and seismic data.  Improved process of ‘spell checker’ on structural interpretation - using multiple datasets.  Introduce lithology interpretation support.  Public release in early 2016. Thank you. Questions?