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Optimising the Mine Plan
Brian Hall
Principal Mining Engineer
AMC Consultants Pty Ltd
21 / 179 Turbot St
Brisbane Queensland 4000 Australia
bhall@amcconsultants.com
Mine Strategy Optimisation - UQ - Oct 2014 1© AMC Consultants Pty Ltd 2001 - 2014
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Outline – Mine Strategy Optimisation
• Principles of mine strategy optimisation:
Finding the mine plans that deliver the corporate goals
• The strategy optimisation process:
Strategy selection vs strategy optimisation
• Risk management:
Balancing upside reward and downside risk
• Answering misconceptions and objections
• Typical case study outcomes
Mine Strategy Optimisation - UQ - Oct 2014 © AMC Consultants Pty Ltd 2001 - 2014 2
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What is Cut-off Grade?
• Important to distinguish between:
– Definition
• A number separating two courses of action
• In particular, distinguishing ore and waste
– Purpose
• To achieve some economic or financial goal
• e.g., ensure profitability, maximise value etc
– Method of determination
• Break-even calculations
• Lane’s methodology
• Strategy Optimisation
Mine Strategy Optimisation - UQ - Oct 2014 3© AMC Consultants Pty Ltd 2001 - 2014
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How the junior geologist or engineer 
determines the CEO’s bonus!
• The goals implicit in the cut-off derivation process will 
become de facto high ranking corporate goals, whether 
recognised as such or not!
– For example, using a simple “break-even” grade (however 
that’s defined) as the cut-off merely ensures that the 
break-even is achieved
– There is no reason why this should “maximise shareholder 
value” (however that’s defined!)
• The corporate goals must therefore be an integral part of 
the evaluation process!
– But typically they are NOT!
Mine Strategy Optimisation - UQ - Oct 2014 4© AMC Consultants Pty Ltd 2001 - 2014
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Mine Strategy Optimisation
Getting to the best combination 
of cut-off grades and other 
design parameters to achieve 
the corporate goals
Mine Strategy Optimisation - UQ - Oct 2014 5© AMC Consultants Pty Ltd 2001 - 2014
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Where is the industry’s focus?
There is a lot of emphasis in the mining industry 
on improvements in productivity, efficiency, 
unit costs etc 
This is “Doing Things Right”
This is good, but we often miss the more 
fundamental issue:
Are we “Doing the Right Things”?
Ultimately, we should aim to be 
“Doing the Right Things Right”
but logically the first concern must be
“Doing the Right Things”
Mine Strategy Optimisation - UQ - Oct 2014 6© AMC Consultants Pty Ltd 2001 - 2014
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Three types of “big picture” parameters . . .
What is given What we can change
What follows from our strategic decisions
Mine Strategy Optimisation - UQ - Oct 2014 7© AMC Consultants Pty Ltd 2001 - 2014
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The mineral resource
The existing infrastructure and 
environment
Size of Mine
Mining Methods
Production Rate
Sequencing
Knowledge of Resource
Schedules of production and associated activities
Revenue streams
Project capital expenditure
Removing bottlenecks
Enhancing products
Operating and sustaining capital costs
Where are the real drivers of value?
VALUE
Improving efficiencies 
etc here will have 
some impact . . .
. . . but the impact 
may be minimal if the 
operation is not going 
in the right direction!
What is given What we can change
What follows from our strategic decisions
Mine Strategy Optimisation - UQ - Oct 2014 8© AMC Consultants Pty Ltd 2001 - 2014
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The mineral resource
The existing infrastructure and 
environment
Size of Mine
Mining Methods
Production Rate
Sequencing
Knowledge of Resource
Schedules of production and associated activities
Revenue streams
Project capital expenditure
Removing bottlenecks
Enhancing products
Operating and sustaining capital costs
Where are the real drivers of value?
VALUE
What mix of theseWhat mix of these
maximises this?
VALUE
What is given What we can change
What follows from our strategic decisions
Mine Strategy Optimisation - UQ - Oct 2014 9© AMC Consultants Pty Ltd 2001 - 2014
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How do we specify the “size of the mine”?
• Open Pit
– Select one of a number 
of alternative “pit shells”
– Cut-off selection is a 
secondary decision
• Underground
– Select one of a number 
of alternative cut-off-
defined “orebodies”
– Cut-off selection is the 
primary decision
Mine Strategy Optimisation - UQ - Oct 2014 10© AMC Consultants Pty Ltd 2001 - 2014
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There is an optimum cut-off grade . . .
Increasing Cut-off Grade
In
cr
ea
si
ng
 V
al
ue
(For a given mining method, capital plan, 
production rate, and associated parameters)
Cut-off too low, 
unprofitable 
material 
included in 
the reserve
Cut-off too 
high, valuable 
material 
excluded from 
the reserve
Mine Strategy Optimisation - UQ - Oct 2014 11© AMC Consultants Pty Ltd 2001 - 2014
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. . . and an optimum production rate
Increasing Production Rate
In
cr
ea
si
ng
 V
al
ue
(For a given mining method, capital plan, 
cut-off grade, and associated parameters)
Production 
not utilising 
existing 
capacity
Minor 
debottlenecking 
capex
Major 
debottlenecking 
capex
Production 
not utilising 
new capacity
Mine Strategy Optimisation - UQ - Oct 2014 12© AMC Consultants Pty Ltd 2001 - 2014
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What is the optimum combination?
Increasing 
Production 
Rate Increasing Cut-off Grade
Increasing 
Value
For a given mining method, capital plan, and associated parameters, 
value will be a function of both production rate and cut-off grade
Mine Strategy Optimisation - UQ - Oct 2014 13© AMC Consultants Pty Ltd 2001 - 2014
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Finding and Climbing the Hill of Value
Increasing 
Production 
Rate Increasing Cut-off Grade
Increasing 
Value
Typical state of 
current operation:
A long way from 
optimum
OptRate
Ridge
Capex 
Gully
Typical improvement 
proposal:
Arbitrary production 
rate increase; May or 
may not improve value
ValMax 
Hill
Ideal improvement proposal:
Change production rate & 
cut-off grade (& mining 
method?) to maximise value
Similar plots for 
other factors of 
interest, other 
mining methods 
etc, permit informed 
tradeoffs between 
options, for best 
strategy overall
Mine Strategy Optimisation - UQ - Oct 2014 14© AMC Consultants Pty Ltd 2001 - 2014
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Case Study Results –
Various Parameters vs Cut-off Grade
$
$
$ $ $
2 3 4 5 6
Cutoff [g/t Au]
NPV @ 0% NPV @ 5% NPV @ 10%
Avg oz / yr Avg $ / oz$
Mine Strategy Optimisation - UQ - Oct 2014 15© AMC Consultants Pty Ltd 2001 - 2014
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Open Pit Case Study Results –
NPV vs ROM Cut-off & Mining Rate
Increasing ROM Cut-off
• Open pit mining plans are 
often “self-debottlenecking”
– Planned mining rates 
deliver planned ore tonnes 
at planned cut-offs
– The ROM cut-off is 
optimised at those rates
“automatically”
• Faster mining allows a higher 
ROM cut-off
– Higher head grade more 
than covers higher mining 
costs and adds value – up 
to a point
• Access development rates 
underground are analogous
Mining 
Rate as 
% of 
Base 
Case 
Rate
100%
150%
200%
Contour Interval 
$50M PreTax NPV
Higher 
Value 
Case
BaseCase
Mine Strategy Optimisation - UQ - Oct 2014 16© AMC Consultants Pty Ltd 2001 - 2014
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The Mine Strategy Optimisation Process
Mine Strategy Optimisation - UQ - Oct 2014 17© AMC Consultants Pty Ltd 2001 - 2014
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Strategy Optimisation vs 
Typical Strategy Selection
• Typical evaluation processes
– Handle many relationships in external processes to 
generate a limited number of preset strategies for 
evaluation
– Engineering resources generate multiple plans and 
schedules
• Optimisation
– Handles all relationships inside the evaluation model to 
facilitate automated strategy flexing
– Engineering resources generate relationships from limited 
number of plans and schedules
Mine Strategy Optimisation - UQ - Oct 2014 18© AMC Consultants Pty Ltd 2001 - 2014
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The Typical Strategy Selection Process
Base Case Option A Option B
Results Decisions
Corporate goals
Simple 
Model
Project 
Capex
Prodn & Devt 
Schedules
Ongoing capex
Debottlenecking 
options
Operating cost drivers
Met. performance
Closure issues
Revenue dataReserves data
Mine design data
Schedule data
Production targets
Production 
constraints
Mine Strategy Optimisation - UQ - Oct 2014 19© AMC Consultants Pty Ltd 2001 - 2014
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The Mine Strategy Optimisation Process
Results Decisions
Corporate goals
Robust 
Model Ongoing capex
Debottlenecking 
options
Operating cost drivers
Met. performance
Closure issues
Revenue dataReserves data
Mine design data
Schedule data
Production targets
Production 
constraints
Mine Strategy Optimisation - UQ - Oct 2014 20© AMC Consultants Pty Ltd 2001 - 2014
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The Mine Strategy Optimisation Process (1)
• Geology
– Create a reliable model for 
the range of cut-offs to be 
investigated
– Generate “orebodies” at 
each cut-off
– Identify domains which 
may require different
• Mining methods
• Scheduling constraints
• Metallurgical treatment
• etc
• Mining
– Identify suitable methods 
– Open Pit: Create pit shell / 
bench group blocks and 
tonnage / grade data
– U/ground: Identify mining 
blocks; generate reserves 
& devt requirements for 
each cut-off and method
– Identify scheduling rules & 
production constraints
– Produce calibration 
designs and schedules for 
representative cases
Mine Strategy Optimisation - UQ - Oct 2014 21© AMC Consultants Pty Ltd 2001 - 2014
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The Mine Strategy Optimisation Process (2)
• Metallurgy
– Specify recovery 
relationships, for the range 
of cut-offs to be evaluated
– Identify constraints, and 
how to remove them, for
• Ore stream
• Product stream(s)
– Identify the impact of 
debottlenecking on 
recovery, product quality 
etc
• Operating Costs
– Fixed costs
– Variable costs, driven by, e.g.:
Open Pit
• Tonnes mined
Underground
• Development metres
• Ore tonnes
• Backfill tonnes
All Operations
• Truck tonne.kilometres
• Tonnes treated
• Product quantities
– Capacity / step variable costs
Mine Strategy Optimisation - UQ - Oct 2014 22© AMC Consultants Pty Ltd 2001 - 2014
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The Mine Strategy Optimisation Process (3)
• Capital costs
– Sustaining capital
– Fleet replacement
– Debottlenecking & 
project capital
• Impact on future 
maintenance & operating 
costs, & sustaining capital 
– Exploration
• In / near mine
• Regional
• Effect of additional 
discoveries on plans
• End of Life Issues
– Redundancy payments
– Rehabilitation costs and 
commitments
• Social Issues
• Other Financial Issues
– Product prices and 
sales terms
– Taxation
– Discount rates
Mine Strategy Optimisation - UQ - Oct 2014 23© AMC Consultants Pty Ltd 2001 - 2014
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The evaluation process (1)
• Identify all the potential combinations of 
– cut-off grade / ultimate pits
– mining methods
– production rates
– expansion capex projects
– etc etc
• Design and schedule the mine, for each combination
• Calculate the financial etc effects of each scenario
• Identify the scenario that gives the best result
Mine Strategy Optimisation - UQ - Oct 2014 24© AMC Consultants Pty Ltd 2001 - 2014
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The evaluation process (2)
• This process is simple in concept, but daunting in the 
amount of work apparently required
However . . .
• By astute selection of representative options, the 
amount of design work can be reduced to manageable 
proportions, and other scenarios interpolated
• Evaluation models can be constructed in such a way 
as to evaluate all the realistic options in a reasonable 
time frame
Mine Strategy Optimisation - UQ - Oct 2014 25© AMC Consultants Pty Ltd 2001 - 2014
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When should optimisation studies be done?
• Every few years, especially if:
– Economic conditions and / or predictions have 
changed significantly
– Knowledge of the resource has changed significantly
– The previous plan is becoming obsolete
• As an integral and essential part of 
the prefeasibility study
Mine Strategy Optimisation - UQ - Oct 2014 26© AMC Consultants Pty Ltd 2001 - 2014
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Mine Strategy Optimisation - UQ - Oct 2014 © AMC Consultants Pty Ltd 2001 - 2014 27
Typical Timing of Project Stages
Construction
Detailed Design
Final Feasibility
Prefeasibility
Scoping
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Time to Commissioning
En
gi
ne
er
in
g 
Ef
fo
rt
 C
om
pl
et
ed
Engineering 
Effort
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Mine Strategy Optimisation - UQ - Oct 2014 © AMC Consultants Pty Ltd 2001 - 2014 28
Ability to Influence Project Value
Construction
Detailed Design
Final Feasibility
Prefeasibility
Scoping
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Time to Commissioning
En
gi
ne
er
in
g 
Ef
fo
rt
 C
om
pl
et
ed
Engineering 
Effort
Ability to 
Influence Value
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Feasibility study sponsors often specify a 
single cut-off grade to be used for all analyses
• To save TIME
• To save MONEY
• But this can lead to sub-optimal investment decisions!
• What has been shown to be FEASIBLE may still be a 
long way from OPTIMAL
• Post-feasibility “optimisation” studies typically seek 
ways to improve the implementation of the identified 
strategy. They rarely look for better strategies!
Mine Strategy Optimisation - UQ - Oct 2014 29© AMC Consultants Pty Ltd 2001 - 2014
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It’s easy to select an option with a single cut-off!
Cutoff Grade
Va
lu
e 
 o
f 
th
e 
 O
pe
ra
tio
n
Strategy B
Strategy A
Mine Strategy Optimisation - UQ - Oct 2014 30© AMC Consultants Pty Ltd 2001 - 2014
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. . and there may be some upside with Strategy A
Cutoff Grade
Va
lu
e 
 o
f 
th
e 
 O
pe
ra
tio
n
Strategy A
“Upside”
Strategy B
Strategy A
Mine Strategy Optimisation - UQ - Oct 2014 31© AMC Consultants Pty Ltd 2001 - 2014
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But upside available with Strategy B is lost!
Cutoff Grade
Va
lu
e 
 o
f 
th
e 
 O
pe
ra
tio
n
Strategy A
Strategy B
Strategy A
“Upside”
Strategy B “Upside” foregone, through 
failure to do a full investigation
Mine Strategy Optimisation - UQ - Oct2014 32© AMC Consultants Pty Ltd 2001 - 2014
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What’s the real danger?
• Reported reserves derived at a low cut-off become 
“locked in”
• Even if a change from one strategy to another is later 
shown to be technically feasible and financially 
preferable, it may be politically impossible
• Significant shareholder value is irretrievably lost 
because of “cost savings” at the start of the project
Mine Strategy Optimisation - UQ - Oct 2014 33© AMC Consultants Pty Ltd 2001 - 2014
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Knowing just the optimum points for each 
scenario may also be of limited value
Cutoff Grade
Va
lu
e 
 o
f 
th
e 
 O
pe
ra
tio
n
Scenario A
e.g. Base Case 
Price Forecast
Scenario B
e.g. Optimistic
Price Forecast
Optimum policies 
identified by e.g. a 
Lane-style analysis
Which option should 
be selected?
Mine Strategy Optimisation - UQ - Oct 2014 34© AMC Consultants Pty Ltd 2001 - 2014
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Knowing the full curves for various scenarios 
can be a powerful risk management tool !
Cutoff Grade
Va
lu
e 
 o
f 
th
e 
 O
pe
ra
tio
n
Scenario A
Scenario B
Setting up for 
Scenario A 
guarantees this 
range of values
The real benefit 
of setting up for 
Scenario B may 
be small…
… but setting up for 
Scenario B may have 
significant downside 
risk if Scenario A 
then occurs
Mine Strategy Optimisation - UQ - Oct 2014 35© AMC Consultants Pty Ltd 2001 - 2014
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History indicates major strategies are often 
founded on wrong assumptions!
• What price scenario should we plan for, if the “best” predictions 
are consistently wrong?!
Nickel Prices – Actual and Consensus Predictions
Source – JB Were – 4th
Australian Resources 
Conference - 1998
Mine Strategy Optimisation - UQ - Oct 2014 36© AMC Consultants Pty Ltd 2001 - 2014
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If we typically set cut-offs below optimum, 
using optimistic price assumptions . . .
Cutoff Grade
Va
lu
e 
 o
f 
th
e 
 O
pe
ra
tio
n
Actual (Lower) Prices
Predicted Prices
. . . should we be surprised that 
actual returns are often below 
expectations?!
Mine Strategy Optimisation - UQ - Oct 2014 37© AMC Consultants Pty Ltd 2001 - 2014
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Optimisation curves as a
Risk Management tool
• The trade-offs between risk and reward will depend 
on the shapes of the curves
• Making decisions about these trade-offs is not the 
role of junior analysts and technical staff!
• Assessing the impact of cut-off grade can only be 
made with full knowledge of the company’s risk 
profile
• Selecting the cut-off policy is a major corporate 
strategic decision, and can only be properly made 
by (or at least under the fully informed direction of) 
senior executives!
Mine Strategy Optimisation - UQ - Oct 2014 38© AMC Consultants Pty Ltd 2001 - 2014
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Answering Misconceptions
& Objections
Mine Strategy Optimisation - UQ - Oct 2014 39© AMC Consultants Pty Ltd 2001 - 2014
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Answering Misconceptions & Objections (1)
• If costs go down or the metal price rises, the cut-off 
should go down proportionately
– If the cut-off is a break-even, TRUE
– If the cut-off is optimal, FALSE
• The proportional change in an optimum cut-off will typically 
be less than the proportional change in costs or price
• If the cut-off is balancing the capacities of stages of the 
production process, the cut-off will not change at all
• It is also possible for a cost reduction or a price rise to 
cause the optimum cut-off to rise!
Mine Strategy Optimisation - UQ - Oct 2014 40© AMC Consultants Pty Ltd 2001 - 2014
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Answering Misconceptions & Objections (2)
• Value is maximised by producing until Marginal Cost 
equals Marginal Revenue
– In a factory, with unlimited resources and markets, YES
• Successive time periods are essentially independent
– In a mine, with depleting resources, NO
• Choices made in one time period affect reserves, and hence 
strategies, in later periods
• But maybe “TRUE” if Marginal Cost fully accounts for 
downstream effects as well as immediate direct costs 
(as in a Lane-style analysis)
– Value may be maximised by operating various parts of the 
process simultaneously at full capacity. The cut-off that 
results in this is defined by plant capacities and grade 
distribution, and is NOT affected by price and cost
Mine Strategy Optimisation - UQ - Oct 2014 41© AMC Consultants Pty Ltd 2001 - 2014
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Answering Misconceptions & Objections (3)
• A costly detailed study is not required – the best 
strategy can be identified by simple studies and 
intuition
– Intuition (if it exists) has been developed from past 
practices & experience, which are suboptimal
– Intuition (if it exists) is therefore unreliable
Mine Strategy Optimisation - UQ - Oct 2014 42© AMC Consultants Pty Ltd 2001 - 2014
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Answering Misconceptions & Objections (4)
• Reducing mine life reduces the probability of exploration 
making a discovery that could profitably extend the life
– The existing mine plan implicitly has an exploration 
program designed to test all targets before current 
reserves and resources are depleted
Accelerate or slow down that program to fit within the mine 
life required for any cut-off and production rate policy, and 
include these effects in the optimisation analysis
Same probability of discovery then implicit in all options
– For “regular annual expenditure” programmes:
Recognise the loss of value from a suboptimal production 
strategy as a real cost of the exploration programme, in 
addition to its direct drilling etc costs
Mine Strategy Optimisation - UQ - Oct 2014 43© AMC Consultants Pty Ltd 2001 - 2014
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Answering Misconceptions & Objections (5)
• The market will react adversely if a reduced reserve 
is reported
– May depend on the strength of the company
– If this is really true
• Educate senior executives??
• Educate a few key opinion-forming industry analysts??
Mine Strategy Optimisation - UQ - Oct 2014 44© AMC Consultants Pty Ltd 2001 - 2014
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Example Case Studies
All NPVs indexed to the 
NPV before the optimisation study, 
which is given a value of 100
Mine Strategy Optimisation - UQ - Oct 2014 45© AMC Consultants Pty Ltd 2001 - 2014
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Case Study 1 – U/g Gold
– COG Optimisation – Mine-wide & by Area
60
70
80
90
100
110
120
130
140
2.0 3.0 4.0 5.0 6.0
Cutoff [Au g/t]
N
PV
 In
de
x
Potential 
Value Loss
Potential 
Value Gains
25%-30%
GA-optimised 
Mining Area 
Cut-offs
Constant Mine-wide 
Cut-off HoV Curve
Original 
Cut-off
Breakeven 
Grade
Mine Strategy Optimisation - UQ - Oct 2014 46© AMC Consultants Pty Ltd 2001 - 2014
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Optimised Mining 
Block Cut-off Grades
• Identified by use of a 
Genetic Algorithm, 
aiming to maximise NPV
– A GA is a heuristic 
technique for getting 
close to an optimal 
answer when there are 
no analytical methods 
available, and an 
exhaustive search of all 
options is an 
impractically large 
problem
2 g/t
Mine Strategy Optimisation - UQ - Oct 2014 47
3 g/t
4 g/t
5 g/t
6 g/t
© AMC Consultants Pty Ltd 2001 - 2014
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Case Study 2 – U/g Gold
– COG & Production Rate Optimisation
2 3 4 5 6 7 8
0.75
1.00
1.25
1.501.75
2.00
0
20
40
60
80
100
120
140
160
180
N
PV
 In
de
x
Cut-off [Au g/t]
Prod'n
Target
[Mtpa]
160-180
140-160
120-140
100-120
80-100
60-80
40-60
20-40
0-20
Mine Strategy Optimisation - UQ - Oct 2014 48© AMC Consultants Pty Ltd 2001 - 2014
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Case Study 3 – U/g Polymetallic Base Metals
– Grade Descriptor, Mining Method & Cutoff
Changing grade descriptor changed understanding of spatial 
distribution of value, leading to a changed mining method
60
70
80
90
100
110
120
130
140
150
Cutoff Grade
(old grade descriptor values scaled to be numerically similar
to new grade descriptor values)
N
PV
 In
de
x
Old Grade Descriptor, 
Old Mining Method
New Grade Descriptor, 
New Mining Method
Value Gain 
> 40%
Other gains from 
increasing stocks of 
developed ore to 
allow mine to 
produce consistently 
at mill capacity
Mine Strategy Optimisation - UQ - Oct 2014 49© AMC Consultants Pty Ltd 2001 - 2014
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If “True” and “Calculated” Values are 
different, ore and waste are misclassified
Tr
ue
 V
al
ue
Calculated Value
Correctly classed 
as Waste
Correctly classed 
as Ore
Incorrectly classed 
as Waste - LOST
Incorrectly classed as 
Ore - DEGRADATION
(Diagrammatic only)
“Calculated” values from block model 
grades. The spread of “True” values 
is IN ADDITION to estimation errors!
Mine Strategy Optimisation - UQ - Oct 2014 50© AMC Consultants Pty Ltd 2001 - 2014
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Case Study – A wide spread of values . . .
Metal Equivalents
O
re
 V
al
ue
 [ 
$ 
/ t
on
ne
 ]
Equivalence Formula 1
Mine Strategy Optimisation - UQ - Oct 2014 51© AMC Consultants Pty Ltd 2001 - 2014
Note: One increment on Value axis 
= ~50% of unit cost of mining
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. . . was reduced with a better equivalence formula
Metal Equivalents
O
re
 V
al
ue
 [ 
$ 
/ t
on
ne
 ]
Equivalence Formula 1
Equivalence Formula 2
Mine Strategy Optimisation - UQ - Oct 2014 52© AMC Consultants Pty Ltd 2001 - 2014
Note: One increment on Value axis 
= ~50% of unit cost of mining
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Misclassified material can significantly affect 
the reserve used: Which descriptor is best?
Reserve Tonnage
A
ve
ra
ge
 V
al
ue
 [$
 / 
to
nn
e]
Equivalence Formula 2
Equivalence Formula 1
Upgrade of Reserve through 
better grade description and 
reduced misclassification
Mine Strategy Optimisation - UQ - Oct 2014 53© AMC Consultants Pty Ltd 2001 - 2014
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The need for a rigorous approach
• Resource geologists invest a lot of time, effort and 
money attempting to reduce estimation errors
• Inappropriate equivalent value calculations can undo 
all that work
• But there is typically very little science put into the 
derivation of the equivalent value formulas
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100
104
110
118
0 20 40 60 80 100 120
Original Wet & Dry Plant
Capacities, Mining
Sequence & Reserves
Original Wet & Dry Plant
Capacities & Mining
Sequence, Best Value
"Standalone" Reserves
Original Wet & Dry Plant
Capacities, GA-Optimised
Mining Sequence,
Allocation of Concentrators
& Deposit Reserves
GA-Optimised Wet & Dry
Plant Capacities, Mining
Sequence, Allocation of
Concentrators & Deposit
Reserves
NPV Index ==>>
Case Study 4 – Mineral Sands – Multi-deposit
– Sequencing, Selectivity, & Plant Capacity
Mine Strategy Optimisation - UQ - Oct 2014 55© AMC Consultants Pty Ltd 2001 - 2014
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But there’s more . . .
Published by The AusIMM
Available late 
November 2014
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The End
Mine Strategy Optimisation - UQ - Oct 2014 57© AMC Consultants Pty Ltd 2001 - 2014