determination of the transition point from open pit to … · · 2016-11-22j chung, m asad, e...

J Chung, M Asad, E Topal, AK Ghosh

Department of Mining Engineering and Metallurgical Engineering

Western Australian School of Mines, Curtin University

Western Australia

The Ninth AusIMM Open Pit Operators’ Conference 2016

2016 Kalgoorlie, Western Australia

Determination of the transition point from open

pit to underground mining

Strategic Mine planning and Optimisation for Combination Mining Method

Curtin University is a trademark of Curtin University of TechnologyCRICOS Provider Code 00301J

Presentation Outline

1. Introduction

2. Problem Definition & Objectives

3. Underground Mining System

4. Modelling the Transition Problem

5. Case Study

6. Conclusions & Recommendations

7. References

Ninth Open Pit Operators’ Conference 2016


Introduction

• Haulage cost and stripping ratio in OP mining will

increase when the pit goes deeper.

• As the stripping cost goes over UG mining cost and

OP mining becomes uneconomical, UG mining

emerges as a viable option.

• Transition from OP to UG required.



Introduction: Combination Mining

4

In combination

mining, all involved

mining strategies need

to be considered

simultaneously in the

mine planning and

optimisation process

to ensure global

optimality achieved.


Introduction

• ‘Transition Problem’ is the determination of the

optimal transition point with the aim of maximisation of

project’s value and resource utilisation.

• ‘Transition Point’ is where the decision has to be

made whether expand the pit or make the transition from

OP to UG.


Problem Definition & Objectives

Conservative/Simplest approach: The transition is considered

near or after the exhaustion (secondary) of the available reserves

inside the ultimate pit (Finch 2012).


Disadvantages:

1. UG mining could have been

the optimal strategy for some

of the OP reserves, but were

planned for OP mining

2. Evaluates OP and UG mining

options separately

3. Ignores the variation in mining

layout from one UG mining

method to the other.

4. Defines the crown pillar (CP)

is an arbitrary location.


Problem Definition & Objectives

Objectives of this study are:

Present an implementation of an integer programming (IP)

based mathematical model

Evaluates possible variations in transition point from OP to

UG mining for sublevel stoping and block caving methods.

Demonstrates the impact of OP to UG mining strategies

and different UG mining methods on the overall value of

the project.



UG Mining System

• Block Caving Mining Method

High production rate and low mining cost

Highly depend on cave-ability of the ore and host rock

Dilution

Costly if caving cannot be maintained

• Stoping Mining Method

Minimum dilution if hanging wall is strong

Stopes can be filled with waste rock, paste fill to recover

pillar

Early production is possible

Safe working environment



Mathematical Modelling for Transition Problem

IP model for OP & UG stoping combined method:

Objective function: Maximises the undiscounted profit

from both OP mining and UG mining.

Constraints:

(i) OP slope or block precedence constraint

(ii) UG mine design constraints

(iii) Reserve restriction constraints

(iv) CP design constraint that ensures the placement of CP is

underneath the pit

(v) The provision of required number of level needed for CP is in

accordance to the geotechnical requirement.




IP model for OP & UG block caving combined method:

Objective function: Maximises the undiscounted profit

from both OP mining and UG mining.

Constraints:

(i) OP slope or block precedence constraint

(ii) UG mine design constraints

(iii) Reserve restriction constraints

(iv) CP design constraint that ensures the placement of CP is

underneath the pit

(v) The provision of required number of level needed for CP is in

accordance to the geotechnical requirement.




Issues:

Size

Big data handling

Computer/Hardware capability

What if they are solved:

Accuracy

Precision

Effectiveness and efficiency

Adapting to Change



Case Study

Case study profile and parameters

Three-dimension (3-D) hypothetical gold deposit.

41,472 blocks with block size of 25𝑚 × 25𝑚 × 25𝑚.

Design stope size 2 × 2 × 2 𝑏𝑙𝑜𝑐𝑘𝑠.

Two levels need to be retained as crown pillar.

IP problem written by Microsoft Visual Basic (VB.net) and solved by using CPLEX solver.



Result Discussions


Scenarios IP model results ($billion)

Scenario 1: OP – UG stoping method 21.657

Scenario 2: OP – UG block caving method 26.020

Scenario 3: OP mining method only 18.396

Scenario 4: UG stoping method only 12.541

Scenario 5: UG block caving method only 13.123


Case Study

• OP-UG stoping and OP-UG block caving methods have the

highest values.

• CP for scenario 1 is at Level 17-18 and scenarios 2 is Level

16-17.

• OP-UG block caving generates a higher value -- low mining

cost, high production rate and economy of scale.

• Proved that if the deposit can be mined through a combination

mining method, optimality can be achieved through strategic

mine planning.



Case Study

• If OP mining is selected for the shallow deposit without

considering the potential transition to UG mining, the ultimate

pit will extend deeper than the final pit generated.

• The IP model

– includes opportunity cost of all available mining strategies.

– Avoid the delays in production during the transition – plan the

development in the early stage.

– Maximised resource and reserve utilisation.



Conclusions & Recommendations

• OP, UG and CP concurrently during the strategic mine

planning strategy is important – global optimisation.

• UG mining method selection plays an important role in

combination method as it will affect the mining layout

and project’s value directly.

• IP models are presented to optimise the mine planning

of combination mining method



Conclusions & Recommendations

• Technical limitations:

– Production rate,

– Equipment requirements

– Variation of labour skills

• Limitations:

– Timing of transition: Production scheduling

– Problem size reduction strategy: Nature of IP model



References1. Alford, C, 1995. Optimization in underground mine design, in Proceedings of 25th International APCOM Symposium 1995, pp 213-218

(Australasian Institute of Mining and Metallurgy,Melbourne: Brisbane, Australia).

2. Asad, M and Topal, E, 2011. Production scheduling of open pit mining operations through cutoff grade optimization. South African Institute of Mining and Metallurgy, 111(11):741-750.

3. Bakhtavar, E and Shahriar, K, 2007. Optimal ultimate pit depth considering an underground alternative, in Proceedings of Fourth AACHEN International Mining Symposium-High Performance Mine Production 2007, pp 213-221 (AIMS: Germany).

4. Bakhtavar, E, Shahriar, K and Mirhassani, A, 2012. Optimization of the transition from open-pit to underground operation in combined mining using (0-1) integer programming. J. South. Afr. Inst. Min. and Metall., 112(12):1059-1064.

5. Brazil, M, Thomas, D A, Weng, J F, Rubinstein, J H and Lee, D H, 2005. Cost optimisation for underground mining networks. Optimization and engineering, 6(2):241-256.

6. Camus, J P, 1992. Open pit optimization considering an underground alternative, in Proceedings of 23th International APCOM Symposium 1992, pp 435-441 (SME: Tucson).

7. Chung, J, Topal, E and Erten, O, 2015. Transition from open-pit to underground - using integer programming considering grade uncertainty, in The 17th annual conference of the International Association for Mathematical Geosciences 5-13 September 2015 2015, (Schaeben, H, Delgado, R T, Boogart, K G and Boogart, R), pp 268-277 (IAMG: Freiberg, Germany).

8. Chung, J, Topal, E and Ghosh, A G, in press. Where to make the transition from open-pit to underground? - using integer programming. South African Institute of Mining and Metallurgy.

9. Dagdelen, K and Traore, I, 2014. Open pit transition depth determination through global analysis of open pit and underground mine scheduling, in Orebody Modelling and Strategic Mine Planning 24-26 November 2014 2014, (Dimitrakopoulus, R), pp 195-200 (The Australasian Institute of Mining and Metallurgy: Perth, Australia).

10. Dimitrakopoulos, R, Martinez, L and Ramazan, S, 2007. A maximum upside/minimum downside approach to the traditional optimization of open pit mine design. Journal of Mining Science, 43(1):73-82.

11. IBM CPLEX Optimization Solver, 2013. Version 12.6. IBM CPLEX ILOG Corp.

12. Johnson, T B, 1968. Optimum open pit mine production scheduling. Berkeley: DTIC Document.

13. Lerchs, H and Grossman, F I, 1964. Optimum design of open-pit mines, in Operations research 1964, pp.

14. Opoku, S and Musingwini, C, 2013. Stochastic modelling of the open pit to underground transition interface for gold mines. Int. J. Min. Reclam. and Environ., 27(6):407-424.

15. Soderberg, A and Rausch, D O, 1968. Pit planning and layout, pp 142-143 (The American Institute of Mining, Metallurgical, and Petroleum Engineers, Inc: New York).

16. Topal, E and Ramazan, S, 2012. Strategic mine planning model using network flow model and real case application. International Journal of Mining, Reclamation and Environment, 26(1):29-37.



Introduction

Mine Planning & Optimisation

Exploration stage

Search mineralization

zone

Block model generation

Geological block model

Economic block model

Determination appropriate mining method

Shallow deposit

Open pit mining method

Deep deposit

Underground mining method

Near surface orebody extend vertically to a considerable depth

Combination mining method

Transition problem

Transition point


determination of the transition point from open pit to … · · 2016-11-22j chung, m asad, e...

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