3D Mineral Potential Modelling and Greenfields Exploration in Queensland Prepared by Matthew Greenwood Greenfields Prospectivity Unit Geological Survey of Queensland Department of Natural Resources and Mines

1. 3D Mineral Potential Modelling
and Greenfields Exploration
in Queensland
Matthew Greenwood
Greenfields Prospectivity Unit
Geological Survey of Queensland
Department of Natural Resources and Mines

2. Quamby Project Area
• Project area covers an
area of 95km long by
80km wide. Located
immediately north of
Cloncurry
• Includes the major
operating Ernest Henry
copper - gold mine as
well as significant copper
and gold projects such as
Rocklands and Roseby,
and the Dugald River
Silver – Lead – Zinc
deposit

3. Mineralisation Potential
• Recent sediments cover >70% of
the area with most cover depths
interpreted to be less than 200m.
Consequently, much of the area
has been under-explored
• Quamby area is prospective for
multiple styles of mineralisation
including Cu±Au±iron oxide
deposits, sediment-hosted Cu
deposits, sediment-hosted Ag-Pb-
Zn deposits, Au and Cu veins and
Cu skarns
• Known mineralisation mostly
confined to outcropping areas. But
some large systems discovered
under shallow cover. High
potential for greenfields discovery

4. 3D Weights of Evidence (WoE)
Targeting
• Jar of 1000
marbles
• 1/1000 chance
of randomly
picking the right
one
• But what if you
had more
information?
• Statistical evaluation of relationships between known mineral
occurrences and exploration datasets (such as rock type, structure,
geochemistry)
 used to define mineral potential probabilities

5. 3D Weights of Evidence (WoE)
Targeting
• Statistical evaluation of relationships between known mineral
occurrences and exploration datasets (such as rock type, structure,
geochemistry)
 used to define mineral potential probabilities
• Previous studies identified geological objects and properties
(exploration criteria) believed to be associated with Copper - Gold
mineralisation in area
• Exploration criteria represented in the model and tested against
known mineral occurrences (How strong is the association?)
• Mineral Potential index is a combination of the statistically significant
exploration criteria. Highlights locations with similar sets of these
properties to known mineral occurrences

6. 3D Weights of Evidence
• Weights assigned from correlation
between mineral occurrences and
evidential properties.
• Continuous properties converted to binary
properties (favourable region and non-
favourable region)
• 23 evidential properties tested
• Two different model areas were tested due
to different styles of mineralisation in these
areas
Distance to Crustal Scale Faults
Distance to Granites

7. 3D Weights of Evidence
• Weights assigned from correlation
between mineral occurrences and
evidential properties.
• Continuous properties converted to binary
properties (favourable region and non-
favourable region)
• 23 evidential properties tested
• Two different model areas were tested due
to different styles of mineralisation in these
areas
Distance to Crustal Scale Faults
Distance to Granites

8. Mineral Potential Index – Constantine Domain
• Targeting mainly Copper – Gold
mineral systems
• Most important exploration
criteria
– Geochemical anomalies
– Geophysical anomalies
– Proximity to faults
– Uranium anomaly
• Weighted criteria combined to
create Mineral Potential Index

9. Mineral Potential Index – Constantine Domain
• Targeting mainly Copper – Gold
mineral systems
• Most important exploration
criteria
– Geochemical anomalies
– Geophysical anomalies
– Proximity to faults
– Uranium anomaly
• Weighted criteria combined to
create Mineral Potential Index
Copper Geochemistry
Density inversion
Distance to Faults
Uranium Anomaly

10. Mineral Potential Index – Constantine Domain
Horizontal slice at 100m (outcrop - ~100m cover)
Red Spheres are known mineral occurrences

11. Mineral Potential Index – Constantine Domain
Horizontal slice at -100m (~200 - ~400m cover)
Red Spheres are known mineral occurrences

13. • Targets include
– Copper-Gold mineralisation
– Copper only
• Most important exploration
criteria
– Geochemical anomalies
– Geophysical anomalies
– Proximity to faults
– Potassium anomaly
• Different strengths of
association
• Less variation in 3D than in
Constantine Domain
Mineral Potential Index – Mary Kathleen Domain

15. Conclusions
• The creation of 3D models, geophysical inversion and mineral
potential modelling is value-adding to the large set of pre-
competitive data available to explorers from the GSQ
• These products will
– Attract exploration interest and investment
– Reduce risk and improve efficiency exploration
– Improve exploration strategies and landuse decisions
– Encourage new greenfields exploration
• Greenfields exploration will lead to new discoveries and
ensure a healthy resource future for Queensland