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Mark Jessell - The topology of geology

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Mark Jessell from the Centre for Exploration Targeting at the University of Western Australia presents his latest work on using geological relationships to improve our 3D modelling and mineral systems analyses.

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Mark Jessell - The topology of geology

  1. 1. The Topology of Geology, a work in progress… Mark Jessell, Sam Thiele, Vitaliy Orgarko, Mark Lindsay, Evren Pakyuz-Charrier, Florian Wellmann • What do I mean by topology… and what I don’t. • 2D • 2D->3D • 3D
  2. 2. Energy Sink Energy Source Potential Energy Gradient Self-Organized System Entropy (exported to environment as diffuse heat) Energy Flux – fed into system at a slow rate Energy Flux – Released in transient “Avalanches” Threshold Barrier A B Framing of new paradigms
  3. 3. Giant ore deposits are zones of focused mass and energy flux
  4. 4. Giant ore deposits are zones of focused mass and energy flux So as geologists (and explorers) we need to understand spatial and temporal relationships: • Fluid pathways & barriers • Thermal, structural, chemical overprinting relationships • Neighbourhood relationships … we know this, and these concepts are already partially captured in prospectivity mapping as proximity buffers etc.
  5. 5. Chudasama et al., 2016, OGR Geology Structures Prospectivity How do we combine these ideas today?
  6. 6. = topologySpatial and temporal relationships Egenhofer (spatial) relationships
  7. 7. K. L. Burns 1975 Analysis of Geological Events. Mathematical Geology, Vol. 7, No. 4, Kerry Burns, 1975
  8. 8. Non-overlapping spatial topology
  9. 9. What I don’t mean: Map topology
  10. 10. No topology control 2D topology control What I don’t mean: Mesh topology Pellerin et al., 2011
  11. 11. Analysis of spatial topology Adjacency Matrices Network Diagrams Hive Diagram
  12. 12. 2D map analytics • What do maps tells us about pathways, spatial relationships, stratigraphic variation? Geology Polygons 1:500 000 GSWA Geology Layer (Mount Bruce sub-set)
  13. 13. Potential for data mining (see EJ… )
  14. 14. UNITNAME GROUP MAX_AGE_MA MIN_AGE_MA Ashburton Formation Wyloo Group 1806 1799 Duck Creek Dolomite Wyloo Group 2010 1799 Mount McGrath Formation Wyloo Group 2010 1799 Beasley River Quartzite Shingle Creek Group 2208 2208 Cheela Springs Basalt Shingle Creek Group 2208 2208 Boolgeeda Iron Formation Hamersley Group 2445 2208 Kazput Formation Turee Creek Group 2445 2208 Koolbye Formation Turee Creek Group 2445 2208 Kungarra Formation Turee Creek Group 2445 2208 Turee Creek Group Turee Creek Group 2449 2208 Woongarra Rhyolite Hamersley Group 2449 2445 Weeli Wolli Formation Hamersley Group 2451 2450 Brockman Iron Formation Hamersley Group 2494 2451 Mount McRae Shale and Mount Sylvia Formation Hamersley Group 2541 2501 Wittenoom Formation Hamersley Group 2597 2504 Marra Mamba Iron Formation Hamersley Group 2629 2597 Jeerinah Formation Fortescue Group 2715 2629 Bunjinah Formation Fortescue Group 2718 2715 Maddina Formation Fortescue Group 2718 2713 Pyradie Formation Fortescue Group 2730 2718 Boongal Formation Fortescue Group 2745 2730 Hardey Formation Fortescue Group 2766 2749 Mount Roe Basalt Fortescue Group 2775 2772 Fortescue Group Fortescue Group 2780 2629 Milli Milli Inlier metagranitic unit 3500 2830 Rocklea Inlier metagranitic unit 3500 2830 Milli Milli inlier greenstones 3520 2930 Rocklea Inlier greenstones 3520 2930
  15. 15. Stratigraphic Relationships Fault Relationships Geology polygon & fault shapefiles converted to WKT format for easy of analysis
  16. 16. Need to distinguish between fault contacts and stratigraphic contacts
  17. 17. A is younger than B Line width ∝ to contact length Stratigraphic Contact Relationships
  18. 18. Example unconformable contact relationships Offlap? Onlap?
  19. 19. Wyloo Turee Shingle Ck Hamersley Fortescue Basement Full Group topology of Mt Bruce sheet UNITNAME topology of each group
  20. 20. Formation-level regional analysis Formation-level polygon analysis Marra Mamba Iron Formation
  21. 21. SW SE NW NE Formation-level Sub- regional analysis
  22. 22. Fault network 1:500 000 GSWA Geology Layer
  23. 23. Strat Fault If we include fault contact relationships, this diagram represents the key topological aspects of a mineral system
  24. 24. 2D->3D With the harmonisation of digital geological data available via delivery systems such as GeoVIEW, we can imagine a world where 3D models are available “on-demand”
  25. 25. 2D->3D Current Workflow Insert data into geomodeller 1. Topography 2. Stratigraphic contacts, with structural orientation data 3. Faults with structural orientation data 4. Stratigraphy 5. Fault-Fault age relationships 6. Fault-stratigraphy age relationships 3D model and/or cross-sections
  26. 26. Data availability? 1. Topography  SRTM 2. Stratigraphic contacts, with structural orientation data Map + WAROX 3. Faults with structural orientation data Map + WAROX 4. Stratigraphy ? 2D Map Analytics 5. Fault-Fault age relationships  ? 2D Map Analytics 6. Fault-stratigraphy age relationships  2D Map Analytics
  27. 27. + + + = 3D
  28. 28. But what if we don’t have enough data to constrain the model (lack of fault dip information for example)?
  29. 29. Original Inputs Perturbed Inputs 1 Perturbed Inputs 2 Perturbed Inputs 3 Perturbed Inputs 4 Perturbed Inputs N • • • Implicit Modelling Engine Wellman et al., 2010, 2011 Jessell et al., 2010 Lindsay et al., 2012,2013 Geological Topological Uncertainty & MC Simulation: Multiple Hypotheses 45 Could be uncertainty wrt orientation, position, nature, age relationship… So now, instead on ONE model, we have as many models as our patience allows… and the challenge changes from perfecting THE MODEL, to analysing the comonalities and differences between suites of geological models
  30. 30. Triple Domain Inversion J Giraud Depth(km) Geological Uncertainty Density true model Magnetic – true model  Colour scale: likelihood  Contour lines: petrophysical distribution Petrophysical Uncertainty Unconstrained single inversion Petrophys constrained single inversion Petrophys + geol constrained single inversion Petrophys constrained joint inversion Petrophys + geol constrained joint inversion
  31. 31. 3D Model topology a) Connectivity • Flow simulations • Electrical measurements Massively reduced dimensionality (>4000 x for this example) b) Litho-structural contacts form the limiting containers for property simulations c) Geophysical inversions often assume fixed topology to constrain the model space d) Proxy for plumbing of mineral system Thiele et al., 2016a,b 350,000 voxels 82 elements
  32. 32. Mount Painter Inlier Armit et al., Geophys. J. Int. (2014) 199, 253–275 50,000,000 voxels
  33. 33. Unique topologies (overall, structural and lithological) can be identified by comparing graphs using the Jaccard coefficient j (Jaccard, 1901; 1912). Graphs are considered to be equivalent when the set of arcs defining each graph (A and B) are identical, and hence j=1 𝑗(A, B) = A  B / A  B
  34. 34. Thiele et al., 2016a,b J Struct Geol accepted
  35. 35. Spot the difference
  36. 36. Conclusions • Spatial and temporal topology have the potential to provide essential insights in to minerals systems • We can extract topology from 2D (maps) and 3D models • In map view we can use the extracted topology to better understand scaling and spatial variation in lithostratigraphic and fault systems ( key Mineral System components) • We can potentially use the map analytics to help automate the 2D map to 3D model transformation • 3D model topologies are highly sensitive to small variations in input data and can be used to classify distinct topological classes