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

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0 5 10 15 20 25 30

Fre

qu

en

cy

Fragmentation Size (mm)30025020015010050

1.0

0.8

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0.4

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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