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integrate
introduce
Economic Benefits and Technical Complexities of Grade Engineering® in Strategic Mine Planning
of Metalliferous Projectswww.crcore.org.au
Carlos Espejel Mine PlanningEngineer
PhD Advisors: Dr Micah Nehring, Professor Peter Knights, Dr Brett King
CRC ORE has developed a novel approach to improving productivity and based on a system value approach referred to as Grade Engineering®
Involves increasing head grades to process by the early physical rejection of non valuable material through pre-concentration techniques;
Differential blasting
for grade by size
2
Sensor based
particle sorting
4
Coarse gravity
separation
5
Preferential grade
deportment by size
1
Sensor based bulk
sorting
3
Grade Engineering Pre-concentration Techniques
GRADE ENGINEERING
The extent and magnitude of some ore types to preferentially deport mineralogy/grade into specific size fractions during coarse breakage generates outcomes which can profoundly change operational decisions.
Exam
ple
of m
iner
alis
atio
n st
yle
at c
ore
scal
e
GRADE BY SIZE – NATURAL DEPORTMENT
0
0.05
0.1
0.15
0.2
0.25
0 5 10 15 20 25 30
Fre
qu
en
cy
Fragmentation Size (mm)30025020015010050
1.0
0.8
0.6
0.4
0.2
00
Finely Concentrated Ore
Conventional Blast
Coarse Waste
Differential blasting involves changing energy designs for a blasting bench, through powder factors, stemming, and/or different drilling blasting designs, following its grade heterogeneity.
The objective/aim is to induce different size distributions to valuable material and non valuable material, to then be screened to separate the upgraded material (undersize).
DIFFERENTIAL BLASTING – INDUCED DEPORTMENT
Detect Identify Quantify
Surfa
cePe
netra
te X-ray transmission
NIR/SWIR spectral LIBS/LIFS
3D shape XRF
Optical (VIS)
Neutron activation
UV fluorescence
Microwave thermal
ElectromagneticMagnetics Magnetic resonance
Gamma activation
Optical (colour)
CR
C O
RE
focu
s
SENSOR BASED SORTING – BULK AND PARTICLE
Technique where valuable material is separated from non valuable material through the use of Sensors (Optical, Electromagnetic, Laser). Sensors are used as the telemetry method, together with mechanical, hydraulic or pneumatic separators.
Sensor based bulk sorting based on mass diversion (shovel, truck, belt scale …) is an attractive concept
Magnetic resonance involves radio frequency excitation of mineral phase lattice structures resulting in a distinctive frequency response for some minerals – it is penetrative and capable of rapid quantification
SENSOR BASED SORTING – MAGNETIC RESONANCE
CRC ORE has developed a novel approach to improving productivity and based on a system value approach referred to as Grade Engineering®
Involves increasing head grades to process by the early physical rejection of non valuable material through pre-concentration techniques;
Differential blasting
for grade by size
2
Sensor based stream
sorting
4
Coarse gravity
separation
5
Preferential grade
deportment by size
1
Sensor based bulk
sorting
3
Grade Engineering Pre-concentration Techniques
GRADE ENGINEERING
GRADE ENGINEERING BENEFITSGRADE ENGINEERING – SHORT AND LONG TERM BENEFITS
IMPROVEMENT OF RESERVES
IMPROVEMENT IN METAL PRODUCTION
IMPROVEMENTS IN NPV FROM 3% TO 15%
RESILENCE TO METAL PRICE CHANGE
IMPROVES CASHFLOW
IMPROVES SELECTIVITY AND DESTINATION OF MATERIAL
THROUGHPUT IMPROVEMENT & ENERGY SAVINGS (DB FRAGMENTATION)
IMPROVES METALLURGICAL RECOVERIES
HEAD GRADE IMPROVEMENTS TO PROCESS
REDUCES AMOUNT OF WASTE FROM ORE STREAMS
ST Benefits
LT Benefits
Grade Engineering Techniques
Differential
blasting
for grade
by size
2
Sensor based stream sorting
4
Coarse
gravity
separation
5
Preferentia l
grade depor tment
by s iz e
1
Sensor
based bulk
sorting
3
GE Resource Evaluation GE Final Pit Optimization Push Back Opt/Dsg GE Production Schedule Optimization
Project Strategic Targets (NPV)
GE Cost Model
STRATEGIC MINE PLANNING – WITH GRADE ENGINEERING
Grade Engineered Strategic Mine Plan (GE SMP)
CO
ST M
OD
EL
Capital Costs (CAPEX)
Operational Costs (OPEX)
Initial Investment
Sustaining
Mining
Processing
Admin
Selling
Refining
Variable • Mill ($/t)• Leaching ($/t)
Variable• Hauling ($/t)• Loading ($/t)• Drill & Blast ($/t)• Rehandling ($/t)• Ancillary ($/t)
Fixed Costs ($/hr)
Grade Eng.
Market Costs
Variable• Screening ($/hr)• Diff Blast ($/hr)• Sensor BS ($/hr)• Rehandling ($/hr)
GE STRATEGIC MINE PLANNING (SMP) – COST MODELLING
GE
CRC ORE 11
GE SMP RESOURCE EVALUATION – BLOCK MODELLING
GE Geometallurgical Attributes: Ranking Responses (RR)• Grade Variability• Separation Properties per GE Technique
Geological Parameters
Metallurgical Parameters
CU @ 0.5
20% @ 0.95 + 80% @ 0.39 = 0.5
30% @ 0.80 + 70% @ 0.35 = 0.5
50% @ 0.70 + 50% @ 0.30 = 0.5
0.95
0.39
0.80
0.35
0.70
0.30
70% @ 0.60 + 30% @ 0.28 = 0.5
0.60
0.28
Selects Highest Economic Value: $/t
CRC ORE 12
GE SMP RESOURCE EVALUATION - RANKING RESPONSE & MASS PULL
CU @ 0.5
Grade Engineering Plant Waste Dump
Leaching Pads
Stock Pile
Process Plant
Best Economic Destination
LG Stream
HG Stream
GE Economic Optimum Combination
Mine
GE Technique
CRC ORE 13
GE SMP RESOURCE EVALUATION – BLOCK VALUE & DESTINATION
𝑪𝑪𝑪𝑪𝑪𝑪𝒎𝒎 =ℎ
𝑃𝑃 − 𝐾𝐾 𝑦𝑦
𝑪𝑪𝑪𝑪𝑪𝑪𝒉𝒉 =(ℎ + (𝑓𝑓 + 𝐹𝐹)
𝐻𝐻 )𝑃𝑃 − 𝑘𝑘 𝑦𝑦
𝑪𝑪𝑪𝑪𝑪𝑪𝒌𝒌 =ℎ
𝑃𝑃 − 𝑘𝑘 − (𝑓𝑓 + 𝐹𝐹)𝐾𝐾 𝑦𝑦
Ken Lane Value and Cut-Off Grade Equations
𝑉𝑉𝑚𝑚 = 𝑃𝑃 − 𝑘𝑘 𝑥𝑥𝑦𝑦𝑥 − 𝑥𝑥ℎ −𝑚𝑚 − (𝑓𝑓+𝐹𝐹)𝑀𝑀
𝑉𝑉ℎ = 𝑃𝑃 − 𝑘𝑘 𝑥𝑥𝑦𝑦𝑥 − 𝑥𝑥ℎ − 𝑚𝑚 −(𝑓𝑓 + 𝐹𝐹)𝑥𝑥
𝐻𝐻
𝑉𝑉𝑘𝑘 = 𝑃𝑃 − 𝑘𝑘 𝑥𝑥𝑦𝑦𝑥 − 𝑥𝑥ℎ − 𝑚𝑚 −(𝑓𝑓 + 𝐹𝐹)𝑥𝑥𝑦𝑦𝑥
𝐾𝐾
CRC ORE 14
GE SMP RESOURCE EVALUATION – LANE’S CUT-OFF GRADES
Grade Engineering - Value and Cut-Off Grade Equations
CRC ORE 15
GE SMP RESOURCE EVALUATION – GE CUT-OFF GRADES
V- Mine Limiting
𝑉𝑉𝑉𝑉𝑉𝑉𝑚𝑚 = 𝑃𝑃𝐻𝐻 − 𝐾𝐾𝐻𝐻 𝑥𝑥𝑀𝑀𝑝𝑝𝑦𝑦𝐻𝐻𝑥𝐻𝐻 + 𝑃𝑃𝐿𝐿 − 𝐾𝐾𝐿𝐿 𝑥𝑥(1 −𝑀𝑀𝑝𝑝)𝑦𝑦𝐿𝐿𝑥𝐿𝐿 − 𝑥𝑥𝑀𝑀𝑝𝑝ℎ𝐻𝐻 − 𝑥𝑥(1 −𝑀𝑀𝑝𝑝)ℎ𝐿𝐿 − 𝑥𝑥𝑀𝑀𝑝𝑝𝑉𝑉𝐻𝐻 − 𝑥𝑥(1 −𝑀𝑀𝑝𝑝)𝑉𝑉𝐿𝐿 − 𝑚𝑚 −(𝑓𝑓 + 𝐹𝐹)𝑀𝑀
GE Cut-Off Grade - Mine Limiting
𝑉𝑉𝑉𝑉𝐺𝐺𝐺𝐺𝑉𝑉𝑚𝑚 =𝑀𝑀𝑝𝑝 ℎ𝐻𝐻 − 𝑉𝑉𝐻𝐻 + 1 −𝑀𝑀𝑝𝑝 ℎ𝐿𝐿 − 𝑉𝑉𝐿𝐿
𝑃𝑃𝐻𝐻 − 𝐾𝐾𝐻𝐻 𝑀𝑀𝑝𝑝𝑦𝑦𝐻𝐻𝐼𝐼𝑓𝑓 + 𝑃𝑃𝐿𝐿 − 𝐾𝐾𝐿𝐿 𝑦𝑦𝐿𝐿(1 − 𝐼𝐼𝑓𝑓𝑀𝑀𝑝𝑝)
CRC ORE 16
GE SMP RESOURCE EVALUATION – BEST PROCESSING DESTINATION
Only - Direct Feed
Grade Engineered Feed + Direct Feed
?Grade Engineered Final Pit GE Economic Block Model
Grade Engineering• GE Parameters• Pre-C Independent Processing
Destination• Pre-C $/t
Base Case
CRC ORE 17
GRADE ENGINEERED SMP – FINAL PIT OPTIMISATION
5% Improvement in Reserves
CRC ORE 18
GE SMP RESOURCE EVALUATION – VALUE CURVES & COG
-10
-5
0
5
10
15
20
25
30
0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90 1.00
SEC MILL SEC LCH WASTE
MILL
LEACH
WASTE
Cut-Off Grades0.36 Cu%
0.15 Cu%
Unit Value ($/t)
CRC ORE 19
GE SMP RESOURCE EVALUATION – VALUE CURVES & COG
-10
-5
0
5
10
15
20
25
30
0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90 1.00
SEC MILL SEC LCH GE Grade by Size WASTE
MILL
LEACH
WASTE
0.24 Cu%
0.15 Cu%
GRADE BY SIZE
0.50 Cu%
CRC ORE 20
GE SMP RESOURCE EVALUATION – VALUE CURVES & COG
Cut-Off Grades
0.62 Cu%
0.10 Cu%
Unit Value ($/t)
-10
-5
0
5
10
15
20
25
30
0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90 1.00
SEC MILL SEC LCH GE Differential Blasting WASTE
MILL
WASTE
DIFFERENTIAL BLASTING
CRC ORE 21
GE SMP RESOURCE EVALUATION – VALUE CURVES & COG
Cut-Off Grades 0.78Cu%
0.10 Cu%
Unit Value ($/t)
-10
-5
0
5
10
15
20
25
30
0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90 1.00
SEC MILL SEC LCH GE Sensor Sorting WASTE
MILL
SENSOR BASED SORTING
WASTE
0
20
40
60
80
100
120
140
0.1
0.3
0.5
0.7
0.9
1.1
1.3
1.5
0
20
40
60
80
100
120
140
160
SBS
DB
ND Natural Deportment
Differential Blasting
Sensor Based Sorting
GE
GE
GE G
E GE
GE
GE
GEG
E
GE
GE
GE G
E
GE G
E
GE
GE G
EGE
HG GE HG CASH FLOW GE CASH FLOW
Mt Cu %
CRC ORE 22
GE SMP – PRODUCTION SCHEDULE OPTIMISATION FOR NPV
0.0
1.0
2.0
3.0
4.0
5.0
6.0
7.0
0
20
40
60
80
100
120
140
16020
16
2017
2018
2019
2020
2021
2022
2023
2024
2025
2026
2027
2028
2029
2030
2031
2032
2033
2034
2035
2036
2037
Mas
s [M
t]
Sensor Based Sorting Only 20% of Total Material Movement goes to GE Plant. 20% of Mill Feed comes from Grade Engineering Plant. Improvement on base case NPV – 9.1%
Material to Grade Engineering Plant
Direct Feed to Waste
Direct Feed to Mill
Direct Feed to Dump Leach
CRC ORE 23
CASE STUDY RESULTS – GE PRODUCTION SCHEDULE OPTIMISATION
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0
5000
10000
15000
20000
25000
30000
35000
2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 2037
Grade Engineering Plant - Capacity: 30 Mtpa
GE Feed Average Grade: 0.42 Cu% Upgraded to Mill at 0.67 Cu% 41% of GE Material Marginal to Dump Leach at 0.36 Cu% 56% of GE Material Downgraded to Waste Dump at 0.28 Cu% 3% of GE Material
Upgraded Material to Mill
Dowgraded Material to Dump LeachGE FEED
GE TO MILL
GE TO DUMP LEACH
GE TO WASTE DUMP
0.42 Cu%
0.36 Cu%
0.67 Cu%
0.28 Cu%
CRC ORE 24
CASE STUDY RESULTS - GE SS SEPARATION & DESTINATION SCHEDULE
0.40
0.50
0.60
0.70
0.80
0.90C
u %
Sensor Based Sorting Only Overall LOM Cu% Head-grade increased by 6.7% Produced 8% more in Cu concentrate
CASE STUDY RESULTS - HEAD GRADE IMPROVEMENT
CRC ORE 25
Base Case Head Grade Cu%
GE SS Head Grade Cu%
Grade Engineering Amenability Every Deposit is Different Every Deposit will have different heterogeneity, grade variability. Every Project will be amenable to different Grade Engineering Techniques and at different
scales.
GE Full Mine Planning Optimisation aids to reach and improve Strategic Goals. NPV Improvement of 3% to 15% achieved through GE fully optimised mine plans Improvement of Reserves by 5% Head Grade Improvement from 3% to 10%, per year and for LOM. Head in TPH from 5% to 10%, per year and for LOM. Improvement in Metal in Cu concentrate
CRC ORE 26
GRADE ENGINEERED STRATEGIC MINE PLANNING – CONCLUSIONS
integrate
introduce
Economic Benefits and Technical Complexities of Grade Engineering® in Strategic Mine Planning
of Metalliferous Projectswww.crcore.org.au
Carlos Espejel Mine PlanningEngineer
PhD Advisors: Dr Micah Nehring, Professor Peter Knights, Dr Brett King