Putting the “GEO” back in front of GEOmetallurgy
A “Cradle to Grave” unifying link across the exploration and mining value chain
Warren Potma
Scott Halley, Andrew Scogings, Serik Urbisinov,
Carl Brauhart, Nikita Sergeev, Angela Escolme
Thanks, also, to Hot Chili Ltd.
22/02/2018 www.csaglobal.com
CSA Global is a leading mining, geological, technology and management consulting
company which provides high quality solutions to our clients in the global minerals
industry. Our staff include geologists, mining engineers, project managers, data
management professionals and technical personnel.
About CSA Global
www.csaglobal.com
Case for early implementation
W. Potma: RIU Explorers Conference 22/2/2018 www.csaglobal.com
Inputs
Inte
gra
ted
GE
Om
eta
llu
rgy
&
3D
Min
era
l S
yst
em
Mo
de
llin
g
4 Acid ICP-MS Geochemistry
Alt’n-Pathfinder-Litho-Geochem
Calculated Mineralogy
Mineralogy: Spectral, Petro & XRD
Appropriate Quantitative Mapping & DH logging data capture
Structure, MagSus, Density, pXRF, Acid Fiz, Hardness, quality photography...
High quality data management
Live (implicit) 3D models
Simplified fit-for-purpose 3D models Lithology – Mineralogy –
Payable/Deleterious Elements -Weathering – Rock Mass
Applications
Exploration
Greenfields – brownfields – mine - shoot
3D Modelling
Litho-structural – Alteration - Resources
Metallurgy
Quantitative 3D Mineralogy
Truly Representative Met. Composites
Mine Design
Rock Mass Classification – Geotech –Blasting - Scheduling
Process Design
Optimisation – Scheduling - Blending
Environmental
Acid Mine Drainage – Mine Closure
Ground Selection
Quantify strategic decisions
Impact
Cradle to Grave Unifying link across Mining Value Chain
Philosophy: to provide critical
knowledge EARLY in project
lifecycle for maximum value
Costs savings at every stage from
improved decision making
Early warning of fatal flaws and opportunities
Informed Observational Geology
Open-minded working hypotheses
Geophysics/Petrophysics
GEOmet Value Proposition
Can you afford NOT to do it? (from the earliest stage)
• 4A ICP-MS Geochem, Spectral, quantitative logging:
– Surface sampling & mapping stage: <10% of total project cost
W. Potma: RIU Explorers Conference 22/2/2018 www.csaglobal.com
Blind VMS example:
Value of low level
multi-element
pathfinder geochem.
If assays were
limited to Cu, Pb, Zn
this target would
have been missed.
(Halley 2016)VMS stringer zone. Cu is in chalcopyrite;
restricted to sparse veinlets.
Sb is in the lattice of the pyrite.
Maps the footprint of the stringer zone.
Projected position of
massive sulphide
VMS
horizon
Hangingwall
stratigraphy
Footwall
stratigraphy 1km
Outcropping
Porphyry Cu
Blind Porphyry Cu
Phyllic Alteration HaloPhyllic
Alteration
Halo
GEOmet Value Proposition
Can you afford NOT to do it? (from the earliest stage)
• 4A ICP-MS Geochem, Spectral, quantitative logging:
– Surface sampling & mapping stage: <10% of total project costs
– Exploration drilling stage: <2% of total project costs
www.csaglobal.com
(Halley 2016)
SWIR Spectral Mineralogy
1km
Outcropping
Porphyry Cu
deposit
Bismuth assays by ICP-MS, detection limit 0.01ppm
Blind Porphyry Cu deposits
300m below surface
Bi_ppm ICP-MS
0.01ppm Det. Limit
Bismuth assays by ICP-AES, detection limit 5ppm
Bi_ppm ICP-AES
5ppm Det. Limit
GEOmet Value Proposition
Can you afford NOT to do it? (from the earliest stage)
• 4A ICP-MS Geochem, Spectral, quantitative logging:
– Surface sampling & mapping stage: <10% of total project costs
– Exploration drilling stage: <5% of cumulative project costs
– Resource Definition stage: <<0.5% of cumulative project costs
• Optimised drill design & sampling protocols - reduced costs
• Better 3D geological and mineralisation models – increased confidence
• Better discovery/Resource extension outcomes – more ore
• Improved MRe confidence & Resource classification outcomes
• GEOmet model available pre-Scoping Study – time saving
• Early warning of any fatal flaws (and opportunities)
W. Potma: RIU Explorers Conference 22/2/2018 www.csaglobal.com
GEOmet Value Proposition
Can you afford NOT to do it? (from the earliest stage)
W. Potma: RIU Explorers Conference 22/2/2018 www.csaglobal.com
Productora Chilean Coastal Range Cu-Mo-Au example:
• Integrated GEOmet approach delivered 3D mineral
system model which:
– identified problems with existing geological model
– changed exploration focus, and targeting rationale
– led to 3 new discoveries & Resource increases from ~100Mt to
~260Mt, 90 Mt maiden Reserve
– Ultimately led to maiden porphyry copper discovery (Alyce
PCD) 500m west of Productora breccia in 2014 & identification
of 7km long porphyry geochem trend
– Directly impacted PFS outcomes
East-dipping Habanero discovery
W. Potma: RIU Explorers Conference 22/2/2018 www.csaglobal.com
Habanero Discovery
Productora Central Pit Area
Section 6822215mN
Preliminary
Central Pit Design
+0.3% Cu mineralisation
+0.1% Cu mineralisation
OPEN
Early 2013
Alt’n model indicated there should be more Cu, and it looks like its East-dipping?!
72m@ 0.7% Cu,
36ppm Mo
East-dipping Habanero discovery
W. Potma: RIU Explorers Conference 22/2/2018 www.csaglobal.com
Habanero Discovery
Productora Central Pit Area
Section 6822215mN
Preliminary
Central Pit Design
+0.3% Cu mineralisation
+0.1% Cu mineralisation
100m@ 1.0% Cu,
0.3g/t Au, 108ppm Mo
181m@ 1.0% Cu, 0.3g/t Au, 173ppm Mo
(open to end of hole)
including:
71m@ 1.6% Cu, 0.4g/t Au, 229ppm Mo
OPEN
Oct 3 2013
181m @ 1.0% Cu, 0.2g/t Au, 173ppm Mo!
49m@ 1.0% Cu,
0.1g/t Au, 207ppm Mo
www.csaglobal.comwww.csaglobal.com
Potassic Tourmaline Breccia Cu-Au-Mo Ore:
• Majority of ROM ore
• Variable hardness, density & abrasiveness
• K-spar cement dominant - dense and hard
• Tourmaline breccia - soft, friable, abrasive
• Highly variable weathering – ox-trans-fresh?
• Strong localised structural/breccia controls (GC
complexity)
Metallurgist:
“I want a representative bulk sample….. please”
Feasibility Study Time…..
BOCO
TOFR
www.csaglobal.com
Habanero Ore Zone:
• Anomalously E-dipping (Mining)
• Very high Cu grade (Mill feed variability)
• Locally high pyrite content (AMD)
• Relatively soft (Low BWI)
• Sericite + Clays (Float sliming?)
• Clay-rich shears & foliation (Geotech)
GEOmet domain considerations
BOCO
TOFR
www.csaglobal.com
Advanced Argillic Domain:
• Silica-Clay (+/- sericite/pyrite)
• Dominantly waste – Pit high-wall
• Sharp E-dipping contact with HG ore (Mining)
• Deep weathering – highwall geotech
• Localised clay-rich shears/foliation (Geotech)
• Very hard silicification (Blasting/Drilling)
• Abundant cavities in oxide zone (Water!)
GEOmet domain considerations
BOCO
TOFR
GEOmet Value Proposition
Can you afford NOT to do it? (from the earliest stage)
• 4A ICP-MS Geochem, Spectral, quantitative logging:
– Surface sampling & mapping stage: <10% of total project costs
– Exploration drilling stage: <5% of cumulative project costs
– Resource Definition stage: <<0.5% of cumulative project costs
– Feasibility Study stage:<<0.01% of cumulative project costs with
massive advantages:
• Reduced Risk: Infinitely more representative, accurate & precise
• Reduced Cost: well characterised remnant ½ core available for Met test
work
• Minimised risk of rework or surprises
• Reduced Time: All the GEOmet characterisation & modelling is complete
before Feasibility, thus well informed Met test work can commence
immediately
W. Potma: RIU Explorers Conference 22/2/2018 www.csaglobal.com
GEOmet of a complex skarn
Client Requirements:
Deliver the “least complex 3D geometallurgical domain model possible” for a complex Sn-fluorite-Cu-W Skarn deposit that:
• is representative of the critical domains affecting processing, including:
lithological, alteration and ore mineralogy; oxidation and weathering-
related mineralogy; hardness; abrasiveness; grainsize and textural
characteristics
• has quantitative constraints sufficient to underpin confidence in an
“Indicated” classification for the fluorite MRe• adequately informs metallurgical sampling strategy
• A reliable, quantitative, 3D GEOmet model is “required to underpin
confidence in the Feasibility Study for this perceived marginal Resource”
W. Potma: RIU Explorers Conference 22/2/2018 www.csaglobal.com
GEOmet Protolith vs Logging
W. Potma: RIU Explorers Conference 22/2/2018 www.csaglobal.com
Calcareous-
Sediments
Mg Dolomitic-
Sediments
Granite
Mafic
Dykes
ORIG-TIRR
WCR-RUBB
WCR-CLY
SANCLY
LOAM
GRN
WCR_GRN
MTS_GL_3_1
MTS_AND
MTS_MG
Simplified Protolith
Model: based on
quantitative
lithogeochemistry
focused on mineralogy
that might impact
processing
Clients Geological Model:
based on detailed logging
NW SE
150m
150m
www.csaglobal.com
Gangue Mineralogy Classification (alteration mineralogy)
Point Density
K-spar or Biotite
Muscovite
Kaolinite
Least Altered Granite
Least Altered Sediments
& Mafics/Andesites
16W. Potma: RIU Explorers Conference 22/2/2018
www.csaglobal.com
Relationship between Gangue Mineralogy & Sn grade
Sn%
Mineralogy_SH
• Highest-grade Sn mineralisation is
spatially correlated with Quartz-
Topaz-Kspar (and/or Biotite)- Mt
Skarn +/- Muscovite
• Lower grades occur with Sericite-
Chlorite-Magnetite Skarn
• Gangue Mineralogy requires
further simplification for GEOmet17W. Potma: RIU Explorers Conference 22/2/2018
www.csaglobal.com
Simplified 3D GEOmet Domain Classification
The simplified GEOmet Domain
Classification is based on gangue
mineralogy characterisation (using ICP-
MS, XRD, SWIR, petrography and logging
data), and is simplified to focus on
critical attributes that potentially impact
processing and mining.
18
www.csaglobal.com
Simplified 3D GEOmet Domain Model
GEOmet
Domains
Note the steeply plunging shoot geometry
of the Qtz-Topaz Domain (right)
Enveloped by the magnetite-rich Fe-Skarn
Domain which also dominates the north-
eastern end of the pit (below)
The remaining volume comprises Calc-
Silicate Domain rocks (not represented)
19
www.csaglobal.com
Client’s detailed Geol. Model vs CSA GEOmet Domains
Calc-Silicates
Granite
ORIG-TIRR
WCR-RUBB
WCR-CLY
SANCLY
LOAM
GRN
WCR_GRN
MTS_GL_3_1
MTS_AND
MTS_MG
Qtz-Topaz
Fe-Skarn
Simplified GEOmet Domains
that impact processing & mining:
based on quantitative gangue
mineralogy
NW SE
150m
150m
20W. Potma: RIU Explorers Conference 22/2/2018
Client’s Geological Model:based on detailed logging
www.csaglobal.com
Client’s Geol. Model vs Quantitative Weathering Domains
Transitional-Oxide Domain
Sulphide Domain
ORIG-TIRR
WCR-RUBB
WCR-CLY
SANCLY
LOAM
GRN
WCR_GRN
MTS_GL_3_1
MTS_AND
MTS_MG
Quantitative Weathering Domain Model
Clients Geological Model
Intense Supergene Clay Domain
NW SE
150m
150m
21W. Potma: RIU Explorers Conference 22/2/2018
www.csaglobal.com
Estimating Fluorite Grade using Ca:F ratios (fluorite stoichiometry)
Fluorite constitutes ~20% of Resource value, but there is a problem…
22W. Potma: RIU Explorers Conference 22/2/2018
Fluorite (CaF2) = 51.3wt% Ca, 48.7wt% F
Any point above the black line
exceeds the maximum possible
fluorite content based on Ca
content
Fluorite + Carbonate/Amphiboles
Clie
nt’s
estim
ated
flu
ori
te p
ct(a
ll F
in
flu
ori
te)
Calc. max fluorite pct from fusion XRF F & Ca values
Flu
ori
tep
ctfr
om
sem
i-q
ua
nti
tati
veX
RD
Calc. max fluorite pct from fusion XRF F & Ca values
www.csaglobal.com
Relative abundance of (Acid Insoluble) Cassiterite vs Stannite (Acid Soluble)
Cassiterite (blue) dominates the
proximal high grade ore zones.
Relative abundance of Stannite:Cassiterite
increases away from the main ore, usually
coincident with very low Sn grades.23
GEOmet Impact
Characterise more, characterise earlier & test less
• High value exploration outcomes
• Saves time & money throughout the project life cycle
• Improves spatial representivity & confidence in models
• Provides early warning of threats and opportunities
• Reduces risk, minimises errors & rework
• Skarn GEOmet work positively impacted fluorite MRe, Met test work
programmes, plant design, pit optimisation and scheduling
• and “demonstrated that most of the preliminary metallurgical test work (predating the GEOmet project) was essentially wasted” (Client’s independent consultant metallurgist)
W. Potma: RIU Explorers Conference 22/2/2018 www.csaglobal.com
www.csaglobal.com
Cassiterite (blue) dominates the
proximal high grade ore zones.
Relative abundance of Stannite:Cassiterite
increases away from the main ore, usually
coincident with very low Sn grades.25
Inputs
Inte
gra
ted
GE
Om
eta
llu
rgy
&
3D
Min
era
l S
yst
em
Mo
de
llin
g
4 Acid ICP-MS Geochemistry
Alt’n-Pathfinder-Litho-Geochem
Calculated Mineralogy
Mineralogy: Spectral, Petro & XRD
Appropriate Quantitative Mapping & DH logging data capture
Structure, MagSus, Density, pXRF, Acid Fiz, Hardness, quality photography...
High quality data management
Live (implicit) 3D models
Simplified fit-for-purpose 3D models Lithology – Mineralogy –
Payable/Deleterious Elements -Weathering – Rock Mass
Applications
Exploration
Greenfields – brownfields – mine - shoot
3D Modelling
Litho-structural – Alteration - Resources
Metallurgy
Quantitative 3D Mineralogy
Truly Representative Met. Composites
Mine Design
Rock Mass Classification – Geotech –Blasting - Scheduling
Process Design
Optimisation – Scheduling - Blending
Environmental
Acid Mine Drainage – Mine Closure
Ground Selection
Quantify strategic decisions
Impact
Cradle to Grave Unifying link across Mining Value Chain
Philosophy: to provide critical
knowledge EARLY in project
lifecycle for maximum value
Costs savings at every stage from
improved decision making
Early warning of fatal flaws and opportunities
Informed Observational Geology
Open-minded working hypotheses
Geophysics/Petrophysics
Integration – Communication - Collaboration
W. Potma: RIU Explorers Conference 22/2/2018
For more information
please contact:
Follow Us On:
W. Potma: RIU Explorers Conference 22/2/2018 www.csaglobal.com
Putting the “GEO” back in front of GEOmetallurgy:
Can you afford NOT to do it?
CSA Global GEOmet Team:
Warren Potma Scott Halley
Andrew Scogings Serik Urbisinov
Carl Brauhart Nikita Sergeev
Travis Murphy Fede Cernuschi
Jamie Robinson
+ many additional specific commodity experts