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GMEX Introduction
1. Geomechanical Modelling for
mining and exploration
Dr John McLellan
Principal Geoscientist
GMEX – Geological Modelling for Exploration
Email: john@gmex.com.au
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2. Background
GMEX: Established in 2012
Core business: Structural Geology and Geomechanical Modelling for exploration
Modelling: Finite Element and Discrete Element Techniques
Why? To better understand deformation events, associated fluid flow and to enable predictive targeting
based on geological ‘processes’
Dr John McLellan: Completed a PhD in Economic Geology 2004
Specialities: Structural Geology and Geomechanics
Current Position: Principal Geoscientist, GMEX
Previous Positions: Senior Geoscience Consultant, A/Business Manager, Rockfield 2010-2012
Senior Research Fellow, James Cook University 2004-2010
Experience: 12 years of geomechanical modelling and related prospectivity analysis, 7 years involvement
with the Predictive Mineral Discovery CRC.
Academic: Over 40 peer reviewed articles, current Adjunct Senior Research Fellow at James Cook
University.
Awards: Prospectors Suppliers Award 1997, AGSO Jubilee Prize 1998, Geological Society of Australia Gold
Medal 1999, AUSIMM Bursary 1999, Australian post-graduate Award (APA) 2001, Pmd*CRC Scholarship
2003, Australian Post-Doctoral Fellowship 2009, Townsville Regional Resources Excellence Awards –
Resources Professional of the Year 2011, Resources Project of the Year 2011.
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3. Why Geomechanical Modelling?
Advantages:
1. Provides insight into the formation of structurally controlled mineral deposits
2. It explores the geological processes (i.e. deformation and associated fluid flow) rather than simply
collecting and presenting empirical data
3. Provides a better understanding of the interactions between the mechanical response of the crust
to deformation events and fluid migration
4. Can simulate the partitioning of both stress and strain during deformation and highlight the most
likely or favourable areas for fluid focussing
5. Predictive capacity for targeting from within mine extensions to regional exploration
6. Provides quantitative results which can be incorporated into prospectivity analysis in both two and
three dimensions
Methodology:
1. A 2d or 3d conceptual model is derived from known data (e.g. lithology, structural data)
2. Models are then built and meshed and an applied stress or deformation condition simulates the
deformational events
3. After deformation has been simulated models are interrogated to highlight stress and strain
partitioning/anomalies, effects of competency contrasts, fault systems and fluid migration
4. These anomalies are then used to highlight favourable predictive targets
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4. Predictive Capacity
-To find mineral deposits we need to know the areas in the crust that will facilitate the fluids responsible
for that mineralisation
- We use ‘empirical data’ to test geological processes
- The geomechanical response of the crust can indicate shear zones, faults and breccias, all of which can
be important fluid conduits
- We can identify target areas that have a higher likelihood of hosting mineralisation
- Identifying not only favourable areas, but also areas of low favourability will reduce your exploration
target area, reducing costs and increasing the chances of discovery
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5. Techniques
There are two main modelling techniques employed:
1. Finite Element Analysis (FEA): a full 3-dimensional geological model is built and subjected to a
simulated deformation event. We can then interrogate the model and examine the geomechanical and
fluid flow response to the deformation.
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Conceptual Geological Model
Numerical Mesh with
applied deformation
Volumetric strain outputs
6. Techniques
2. Discrete Element Modelling (DEM): a 2-dimensional geological model is built and subjected to a
simulated deformation event. We can then interrogate the model and examine the geomechanical and
fault/fluid related response to the deformation.
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Conceptual Geological Model
indicating fault architecture and
lithological boundaries
Results can be integrated into most GIS
environments and can be easily viewed
in Google Earth for better clarity for the
exploration team
Example of model results from applied
stress conditions. We can clearly define
areas of stress anomalies as a function
of fault block movement
7. Validation Case Studies
Archaean Granite-Greenstone Au Deposit (Sunrise Dam Gold Mine):
- Structurally controlled mineralisation
- Poor within mine targeting due to nugget effect, deformation styles and limited deep drilling
- Aim was to highlight areas within the mine sequence that were most likely to contain both shear and
fracture hosted gold mineralisation using a 3D FEA analysis
Outcome: Target areas defined based on geomechanical modelling predictions
Target areas followed up by deep drilling
Targeting successful, discovery of the new Vogue 12 million tonne orebody
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Example of SW plunging trend in numerical models
Mark Cutifani – CEO presentation June 2011
This brownfield discovery is significant
And a potential game-changer for Sunrise Dam
8. Validation Case Studies
Volcanogenic System, Ben Lomond U-Mo Deposit:
- Structurally controlled mineralisation
- Limited exploration within the tenement
- Aim was to highlight areas within the tenement that had the highest likelihood of structurally
controlled mineralisation, compare with known XRF data and generate priority geomechanical targets.
This was done using both 3D FEA and 2D DEM analysis
Outcome: Target areas defined based on geomechanical modelling predictions of a combination of rock
failure plots and stress variations
Target areas have a good correlation with known XRF geochemical data
Future targeting planned around the main geomechanical targets
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3D conceptual model and volumetric strain/flow outputs
2D DEM outputs and comparison with known occurrences
9. Validation Case Studies
Fe-Oxide Cu-Au systems, Eastern Fold Belt, Mt Isa:
- Structurally controlled mineralisation
- Fault controlled system with competency contrasts
- Aim was to highlight areas within the region that had the highest likelihood of structurally controlled
mineralisation, using competency contrasts of metasediments/granites/mafics and regional
deformation events. This was done using a 2D DEM analysis.
Outcome: Target areas defined based on geomechanical modelling predictions of a combination of rock
failure plots and stress variations have a good correlation with known mineral occurrence data
Fault architecture and competency contrasts have been the controlling structural components
of mineralisation in the Eastern Fold Belt
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2D Conceptual model for the EFB 2D DEM outputs and comparison with known occurrences. Selwyn high strain zone very evident.
10. Validation Case Studies
Geita Gold Mine, Tanzania:
- Structurally controlled mineralisation
- Fault controlled system with competency contrasts
- Aim was to validate structural models and propose the most likely orientation of sigma1 responsible for
mineralisation. Also, highlight areas within the region that had the highest likelihood of structurally
controlled mineralisation in both plan and cross sectional view using a 2D DEM analysis.
Outcome: Structural model validated with the most likely orientation of sigma 1 responsible for
mineralisation identified
New targets defined as a result of stress anomaly combinations and fault aperture opening
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Fault movement and aperture opening Cross sectional differential stress outputs and joint
displacement.
11. Geomechanical Modelling of the
Geological Process
-Both FEA and DEM are very powerful tools for mineral exploration
- This type of analysis allows us to examine the mechanical geological process that has formed the
mineralisation instead of simply relying on gathered empirical data and how we combine this to
formulate the best targets
- It can provide quick reliable data that can be used in a targeting prospectivity program in both two and
three dimensions
- Incorporating this data into a GIS platform can greatly enhance WOFE analysis as it provides an
understanding of the mechanical process, which is the key to structurally controlled mineralisation
Understanding the process makes the ‘where’ easier to solve because you know the ‘why’
These techniques can be applied to most structurally controlled mineral deposits or regions. If you would
like to discuss these techniques further contact Dr John McLellan at john@gmex.com.au
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