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.
Biogenic Sulfur Gases as Biosignatures on Temperate Sub-Neptune Waterworlds
Mark Jessell - The topology of geology
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. 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
5. 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.
6. Chudasama et al., 2016, OGR
Geology Structures Prospectivity
How do we combine these ideas today?
16. 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
25. Strat
Fault
If we include fault contact relationships, this
diagram represents the key topological aspects of
a mineral system
26. 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”
27. 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
28. 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
30. But what if we don’t have enough data to
constrain the model (lack of fault dip information
for example)?
31. 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
32. 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
33. 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
35. 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
38. 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
Notas do Editor
Our approach is to perturb the input observations to allow the automatic calculation of large numbers of models using implicit modelling schemes (geomodeller, leapfrog, SKUA…)