The document discusses project optimization in the mining industry. It notes that the industry has become more challenging with tighter profit margins. Project optimization can mean the difference between success and failure. A systems approach across the entire mining process from data collection to engineering design is now considered best practice. Sophisticated data collection and geometallurgical modelling is key to optimize different parts of the mining process together.

1. Project Optimisation | Nov 2012| 1
Project Optimisation
Simon Michaux & Andrew Lewis | November 2012

2. Project Optimisation | Nov 2012| 2
• Economic risk mitigation
• More sophisticated prediction & scheduling
• Potential to integrate engineering design steps into a coherent outcome
• More sophistication in ore characterisation and deposit knowledge is required
on a greater scale
• Ability to justify and manage projects on a much bigger scale with a high
capital risk and a longer time period for the start of profit return
• Ability for more accurate decision making in a challenging business
environment
The industry is changing, we must change with it
A systems approach in design across the mining process
is now considered the next generation of engineering

3. Project Optimisation | Nov 2012| 3
Multifactor Productivity: The efficiency in which capital, labour, materials, services, and energy are
utilised to generate a unit of product
The industry business environment is now more
challenging where profit margins are being squeezed
Australian Bureau of Statistics 2011, Experimental Estimates of Industry Multifactor Productivity, 2010-11, ABS, Cat no:
5625.0.55.002, Canberra.
50
60
70
80
90
100
110
Indexed2000-01=100
Topp et al. (2008) ABS (2011)
It now takes 40% more inputs
to generate a single unit of
mineral product
Australian Bureau of Statistics 2011, Experimental Estimates of Industry Multifactor Productivity, 2010-11, ABS, Cat no: 5625.0.55.002,
Canberra.

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Project optimisation can mean the difference between
success and failure in this challenging environment
NPV makes the first few years critical to successful operation
Plant design
capacity
Fast run up
to full
capacity Slow run up
to partial
capacity

5. Project Optimisation | Nov 2012| 5
GeM Model
Economic Models
LS
LC
ROM
Leach
Crushers ProcessMine
LS
LC
ROM
Leach
Crushers ProcessMine
Family of Solutions
Data Collection
Mining Sequences
Mine Plan
Feedback to improve model
Constraints Constraints
LS
LC
ROM
Leach
Crushers ProcessMine
LS
LC
ROM
Leach
Crushers ProcessMine
LS
LC
ROM
Leach
Crushers ProcessMine
LS
LC
ROM
Leach
Crushers ProcessMine
Slope Models
1 1.5 2 2.5 3 3.5 4
x 10
8
0
0.02
0.04
0.06
0.08
0.1
0.12
0.14
0.16
X
Probability Distribution of Expected Cash Flow @ PP-1
2.6 2.7 2.8 2.9 3 3.1 3.2 3.3 3.4 3.5 3.6
x 10
9
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
x
F(x)
Empirical CDF
Cash flow stream
Capital
Investment
CurrentMine
ProjectValue
Production
PeriodMillionof$
V
I
0t 1t 2t 3t 4t
()711tiiitWACCCFR==+
7t5t 6t
1 1.5 2 2.5
x 10
8
0
0.02
0.04
0.06
0.08
0.1
0.12
X
Probability Distribution of Expected Cash Flow @ Last PP
Simulation
Confidence Model
0 5 10 15 20 25 30
-1
0
1
2
3
4
5
6
7
x 10
8
Stochastic Expected Cash Flow
Production Period
CasfFlow
1 1.5 2 2.5 3 3.5 4
x 10
8
0
0.02
0.04
0.06
0.08
0.1
0.12
0.14
0.16
X
Probability Distribution of Expected Cash Flow @ PP-1
1.5 2 2.5 3 3.5 4 4.5
x 10
8
0
0.02
0.04
0.06
0.08
0.1
0.12
0.14
X
Probability Distribution of Expected Cash Flow @ PP-2
1 1.5 2 2.5
x 10
8
0
0.02
0.04
0.06
0.08
0.1
0.12
X
Probability Distribution of Expected Cash Flow @ Last PP
Probability of cash flow can be assessed for each year.
Project Optimisation – Intelligent Engineering
Data transfer technology now makes this
possible early in the design process
• All aspects of the mining process can now be designed to a level of sophistication where the
outputs can be used as inputs into other engineering operations
• All engineering operations can then be optimised together
• The key is to do this in an iterative loop several times to ensure overall operational efficiency

6. Project Optimisation | Nov 2012| 6
Geological Assays Petrophysical Equotip Comminution
Multi-disciplinary data collection
Class
Group
Copper
Domain
Throughput
Domain
Recovery
Domain
Group C Group B
Group B Group C
Group A Group D
Group A Group D
Group C Group A
Group D Group A
Geometallurgical domains in block model
Sophisticated data collection is the key (Geometallurgy)
Process Attribute Ore Domain 1 Ore Domain 2 Ore Domain 3 Ore Domain 4
Ore Value
Valuable metal 1 (Au) grade 0.6g/t - - 1.1g/t
Valuable metal 2 (Cu) grade 1.20% - - 0.50%
Valuable metal 3 (Ag) grade - 2.2g/t 1.3g/t -
Valuable metal 3 (Mo) grade - 0.99% 0.47% -
Valuable metal x (?) grade
Penalty elements Yes (High As content) No No Yes (Low As content )
Ore Charatersiation
Mineral liberation size 75 micron 30 mciron 160 micron 212 micron
Property deportment siganture Yes (Upgrade factor 2.1) No No Yes (Upgrade factor 1.6)
Ore sorting feasible Yes No No No
Energetic conditioning feasible No No No No
Impact breakage energy consumption High High Very High medium
Low energy abrasion energy consumption High High High Low
Bed breakage energy consumption Medium Medium Medium High
Grinding Energy consumption High Medium High Low
Fine grinding energy consumption - Medium High -
Separation Process
Flotation recovery - High Medium -
Flotation kinetics - Medium Medium -
Leaching recovery Medium - - Low
Leaching kinetics Medium - - Low
Gravity Au recovery Yes - - No
Pressure oxidisation required for Au recovery No - - Yes
Engineering Design Request
Valuable metal 1 (Au) grade 0.6g/t - - 1.1g/t
Valuable metal 2 (Cu) grade 1.20% - - 0.50%
Valuable metal 3 (Ag) grade - 2.2g/t 1.3g/t -
Valuable metal 3 (Mo) grade - 0.99% 0.47% -
Valuable metal x (?) grade
Penalty elements Yes (High As content) No No Yes (Low As content )
Ore Charatersiation
Mineral liberation size 75 micron 30 mciron 160 micron 212 micron
Property deportment siganture Yes (Upgrade factor 2.1) No No Yes (Upgrade factor 1.6)
Ore sorting feasible Yes No No No
Energetic conditioning feasible No No No No
Impact breakage energy consumption High High Very High medium
Low energy abrasion energy consumption High High High Low
Bed breakage energy consumption Medium Medium Medium High
Grinding Energy consumption High Medium High Low
Fine grinding energy consumption - Medium High -
Separation Process
Flotation recovery - High Medium -
Flotation kinetics - Medium Medium -
Leaching recovery Medium - - Low
Leaching kinetics Medium - - Low
Gravity Au recovery Yes - - No
Pressure oxidisation required for Au recovery No - - Yes
Engineering Design Request
Floation circuit? - Yes Yes -
Concetrate regrind circuit? - Yes No -
Leach dump? No - - Yes
Leach heap? Yes - - No
Leach tank? No No No No
CiL carbon and leach circuit? Yes - - No
Ore sorting technology? Yes - - No
Energetic conditioning technology? No No No No
Process Attribute Ore Domain 1 Ore Domain 2 Ore Domain 3 Ore Domain 4
Ore Value
Valuable metal 1 (Au) grade 0.6g/t - - 1.1g/t
Valuable metal 2 (Cu) grade 1.20% - - 0.50%
Valuable metal 3 (Ag) grade - 2.2g/t 1.3g/t -
Valuable metal 3 (Mo) grade - 0.99% 0.47% -
Valuable metal x (?) grade
Penalty elements Yes (High As content) No No Yes (Low As content )
Ore Charatersiation
Mineral liberation size 75 micron 30 mciron 160 micron 212 micron
Property deportment siganture Yes (Upgrade factor 2.1) No No Yes (Upgrade factor 1.6)
Ore sorting feasible Yes No No No
Energetic conditioning feasible No No No No
Impact breakage energy consumption High High Very High medium
Low energy abrasion energy consumption High High High Low
Bed breakage energy consumption Medium Medium Medium High
Grinding Energy consumption High Medium High Low
Fine grinding energy consumption - Medium High -
Separation Process
Flotation recovery - High Medium -
Flotation kinetics - Medium Medium -
Leaching recovery Medium - - Low
Leaching kinetics Medium - - Low
Gravity Au recovery Yes - - No
Pressure oxidisation required for Au recovery No - - Yes
Engineering Design Request
Energetic conditioning feasible No No No No
Impact breakage energy consumption High High Very High medium
Low energy abrasion energy consumption High High High Low
Bed breakage energy consumption Medium Medium Medium High
Grinding Energy consumption High Medium High Low
Fine grinding energy consumption - Medium High -
Separation Process
Flotation recovery - High Medium -
Flotation kinetics - Medium Medium -
Leaching recovery Medium - - Low
Leaching kinetics Medium - - Low
Gravity Au recovery Yes - - No
Pressure oxidisation required for Au recovery No - - Yes
Engineering Design Request
Floation circuit? - Yes Yes -
Concetrate regrind circuit? - Yes No -
Leach dump? No - - Yes
Leach heap? Yes - - No
Leach tank? No No No No
CiL carbon and leach circuit? Yes - - No
Ore sorting technology? Yes - - No
Energetic conditioning technology? No No No No
Crushing? Yes Yes Yes Yes
Grinding? No Yes Yes No
HPGR? No No Yes No
Fine grinding? No Yes No No
Process Attribute Ore Domain 1 Ore Domain 2 Ore Domain 3 Ore Domain 4
Ore Value
Valuable metal 1 (Au) grade 0.6g/t - - 1.1g/t
Valuable metal 2 (Cu) grade 1.20% - - 0.50%
Valuable metal 3 (Ag) grade - 2.2g/t 1.3g/t -
Valuable metal 3 (Mo) grade - 0.99% 0.47% -
Valuable metal x (?) grade
Penalty elements Yes (High As content) No No Yes (Low As content )
Ore Charatersiation
Mineral liberation size 75 micron 30 mciron 160 micron 212 micron
Property deportment siganture Yes (Upgrade factor 2.1) No No Yes (Upgrade factor 1.6)
Ore sorting feasible Yes No No No
Energetic conditioning feasible No No No No
Impact breakage energy consumption High High Very High medium
Low energy abrasion energy consumption High High High Low
Bed breakage energy consumption Medium Medium Medium High
Grinding Energy consumption High Medium High Low
Fine grinding energy consumption - Medium High -
Separation Process
Flotation recovery - High Medium -
Flotation kinetics - Medium Medium -
Leaching recovery Medium - - Low
Leaching kinetics Medium - - Low
Gravity Au recovery Yes - - No
Pressure oxidisation required for Au recovery No - - Yes
Engineering Design Request
Flotation recovery - High Medium -
Flotation kinetics - Medium Medium -
Leaching recovery Medium - - Low
Leaching kinetics Medium - - Low
Gravity Au recovery Yes - - No
Pressure oxidisation required for Au recovery No - - Yes
Engineering Design Request
Floation circuit? - Yes Yes -
Concetrate regrind circuit? - Yes No -
Leach dump? No - - Yes
Leach heap? Yes - - No
Leach tank? No No No No
CiL carbon and leach circuit? Yes - - No
Ore sorting technology? Yes - - No
Energetic conditioning technology? No No No No
Crushing? Yes Yes Yes Yes
Grinding? No Yes Yes No
HPGR? No No Yes No
Fine grinding? No Yes No No
Process Attribute Ore Domain 1 Ore Domain 2 Ore Domain 3 Ore Domain 4
Ore Value
Valuable metal 1 (Au) grade 0.6g/t - - 1.1g/t
Valuable metal 2 (Cu) grade 1.20% - - 0.50%
Valuable metal 3 (Ag) grade - 2.2g/t 1.3g/t -
Valuable metal 3 (Mo) grade - 0.99% 0.47% -
Valuable metal x (?) grade
Penalty elements Yes (High As content) No No Yes (Low As content )
Ore Charatersiation
Mineral liberation size 75 micron 30 mciron 160 micron 212 micron
Property deportment siganture Yes (Upgrade factor 2.1) No No Yes (Upgrade factor 1.6)
Ore sorting feasible Yes No No No
Energetic conditioning feasible No No No No
Impact breakage energy consumption High High Very High medium
Low energy abrasion energy consumption High High High Low
Bed breakage energy consumption Medium Medium Medium High
Grinding Energy consumption High Medium High Low
Fine grinding energy consumption - Medium High -
Separation Process
Flotation recovery - High Medium -
Flotation kinetics - Medium Medium -
Leaching recovery Medium - - Low
Leaching kinetics Medium - - Low
Gravity Au recovery Yes - - No
Pressure oxidisation required for Au recovery No - - Yes
Engineering Design Request
Ore Domain 2 Ore Domain 4 Ore Domain 7
Engineering Recommendations for Project Optimisation
So what is the most
cost effective option?

7. Project Optimisation | Nov 2012| 7
Project optimisation for
small and large studies
pit design, production plan & schedule
design criteria, flowsheet, mass balance etc
block model
geomet data (mill, float, leach, geomechanical test data)
option and scenario
analysis
AMDAD/Ausenco LiteO Whittle/Ausenco EO
PFS
FS
best possible
optimised
outcome
Ausenco now has access to this expertise

8. Project Optimisation | Nov 2012| 8
Ausenco Project Optimisation
• When industry is in a growth cycle
o How can we optimise design, construction and production to
help your business make more money most efficiently
• When industry is in a contraction cycle
o How can we optimise design, construction and production to
help your business to survive in a challenging environment
• Flexible decisions can now be made in a defendable
form, fit for purpose to the macro business environment
Engineering expertise merges with
corporate decision making

9. Project Optimisation | Nov 2012| 9
Thank you for your time
Dr Simon Michaux
Senior Process Engineer (Geometallurgy)
Technical Solutions
Minerals & Metals
Simon.Michaux@ausenco.com
Dr Andrew Lewis
Consultant (Optimisation)
Technical Solutions
Minerals & Metals
Andrew.Lewis@ausenco.com