Automated prospectivity analysis for
intrusion-related mineral systems
in the Charters Towers-Ravenswood region
Arianne Ford
Outline
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Aims and scope
Mineral system models
Data
Prospectivity mapping
2
Aims and Scope
• Evaluate available data
• Develop targeting criteria for intrusionrelated mineral systems
– Specific focus on geochemistry
• Generate prospectivity maps
• Develop a method for ranking existing
targets
Study Area
Mineral Systems
• Deposits are focal points of much larger mass flux and energy
systems
• Focus on critical processes that must occur to form a deposit
• Allows identification of mineralization processes at all scales
• Not restricted to particular geologic settings/deposit type
Charters Towers-Ravenswood
Mineral Systems
• Siluro-Devonian
– Intrusion-hosted orogenic gold system
– Mineralization hosted in Silurian granites
– Mineralization dates are Devonian
– ?Source?
• Permo-Carboniferous
– Intrusion-related gold system
– Mineralization related to sub-volcanic intrusions
of Kennedy Igneous Association
Data
• Geochemistry
• Geology
• Geophysics
Geochemistry
• Terra Search/GSQ data
– SSS; RC; Soils
– Lots of data points
• limited multi-element analysis
• Patchy spatial distribution
– Works well for mapping out the Ravenswood
Batholith using automated methods
• Carpentaria Gold (Resolute) data
– RC and Soils have good sample density over
Ravenswood district
– Good multi-element geochemical analysis
Geochemistry maps
Carpentaria Gold Geochem
Geochemistry – data analysis
• Focus on the data provided by Carpentaria
Gold
– Best distribution of sample points over
Ravenswood district (soil and rock chip)
– Comprehensive multi-element analysis
• Data levelled for geology
• Determine element associations for each
camp
• Produce anomaly maps for district-scale
prospectivity mapping
Geochemistry – PCA results
• Assess element associations
– Within camp
– Regionally
• Limitations
– Needs sufficient sample density and distribution
– Interpolating between sparse points
– Requires multi-element analysis for each
sample -> hence use of Carpentaria Gold data
Regional PCA (soil)
[As Au Bi Mo Pb Sb] +/[Ag Cu Te W]
Geochemistry - zonation
• Only works in camps with sufficient data
points
• Inconsistent zonation trends between camps
– No characteristic zonation, each IRG camp is
different
Geology
• 1:100,000 scale mapping
– Surface geology
– Solid geology interpretations
– Structures
• Camp scale mapping
– Variable resolution: ~1:5,000
– Detailed, but patchy and limited spatial extent
– Geology and structures
Geology - maps
Geophysics
• GSQ and GA
– Magnetics
– Gravity
– Radiometrics
• Data reprocessed to create derivative
products
• New interpretations
– Revised structural maps
– Intrusion mapping
Geophsyics maps
Intrusion detection
• Automated tool in Geosoft for mapping
intrusions from aeromagnetic data
Human expert at best
Automated detection
Ground truth
• Limitations
– Resolution of data
– “Circularity”
– Age?
Images: Geosoft; Holden et al., 2012
Intrusion detection
Statistical Correlations
• Statistically assess relationship between
targeting criteria and known IRG occurrences
Layer
Max. Contrast*
% Deposits
% Total Area Favourable
CG soil geochem PCA
1.6098
36%
96%
CG RC geochem PCA
1.8018
25%
92%
Dyke density
1.425
17%
6.5%
Permo-Carb intrusions
No statistically significant result
* Contrast ≥ 0.5 is meaningful
• Results need to be statistically significant
AND geologically meaningful to be useful for
exploration
Prospectivity Analysis
• Integrating what worked for finding major
deposits
– Permo-Carb sub-volcanic intrusions
• Mapped and interpreted from geophysics
– Mapped dykes
– Principle component analysis using Carpentaria
Gold geochemistry data
Prospectivity map
Campoven
Three Sisters
Conclusions
• Tried lots of things that didn’t work
– Data needs to be fit for purpose
• Resolution of geophysical surveys
• Geochemical survey sample density and elements
analysed in the lab
– This can be seen as a positive outcome
• We need to know what works, but we also need to
know what doesn’t work; this is rarely discussed
Conclusions
• Highlights that even with expert data
analysts working on the problem, a purely
data-driven or automated approach doesn’t
work here
– Needs expert opinions to drive the model
– We welcome input from industry
• If you want to get involved in a round-table
discussion, we are tentatively planning a
meeting for October/November in Townsville
– Please email Arianne Ford or Vladimir Lisitsin
– [email protected] or [email protected]
Acknowledgements
Geological Survey of Queensland
Resolute Mining Ltd.