343
Options analyses performed using both HoV and the SOT demonstrated that the deposit
was amenable to a “two pass” approach with respect to the mine planning. In other words,
high grade sub-zones can be mined first to maximize NPV, with the subsequent mining of
lower grade ore in the later years to improve free cash flow. This two-pass approach was
applied to the stope-profit attribute, with SOT configured to target high-value stopes in the
early years (typically stopes with high gold grades and favorable geochemistry), with lower
value stopes targeted in the later years of the mine.
3 DISCUSSIONS AND CONCLUSIONS
This paper summarized a mine planning optimization workflow implemented for an underground metal mining project. The main contribution of this paper is that it demonstrated a
complete and practical underground mine planning optimization process aiming to improve
values and reduce risks, with the latest software and analysis tools.
The project has a wide range of metal grades and geochemistry distributions, which makes
the mining planning process complicated but also provides flexibility for blending and schedule optimization.
Software tools played a critical role during the mine planning process. Conditional simulation produced a large number of simulation models to validate the resource model. Simulation
models after running through Stope Optimizer suggested that there was a fewer number of high
grade stopes than the resource model predicted. MSO and PUNO were used for the rapid mine
designs, which produced a large amount of data for the HoV strategic mine planning and optimization. HoV analysis identified the value range and provided guidance to cut-off grade and
production rate for more detailed scheduling. To improve the project economics and reduce
risks, SOT and OMP were applied for schedule optimization with multiple layers of constraints.
A “two pass” mine planning opportunity was recognized with the HoV study. Mining high
grade ore in the first seven years to improve NPV, and mining lower grade ore in the later
years to maximize free cash flow. This “two-pass” approach was realized with the detailed
tactical mine planning.
REFERENCES
[1] PRIMO, AMIRA, Stope Optimization and Stope Layout, 2011
[2] G. Davis, A. Newman, Modern Strategic Mine Planning, 2008, CRC Mining Conference.
[3] A. Jewbali, H. Wang, C. Johnson, Resource Model Uncertainty Analysis and Stope Optimizer
(MSO) Evaluation for an Underground Metal Mine Project, APCOM 2015.
[4] Hall A. and Hall B., 2006. Doing the Right Things Right – Identifying and Implementing the Mine
Plan that Delivers the Corporate Goals, in Proceedings International Mine Management Conference 2006 (The Australian Institute of Mining and Metallurgy: Melbourne).
[5] C. Alford, M. Brazil, and D. Lee, Stope Optimization, 2007, Optimization in Underground Mining, Handbook of Operations Research In Natural Resources, pp. 561–575.
[6] Fast Level Designer, Decline Optimization.
[7] Schedule Optimization Tool
[8] B. Hall, Cut-off Grades and Optimising the Strategic Mine Plan, 2014, Spectrum Series 20 (The
Australian Institute of Mining and Metallurgy: Melbourne).
[9] A.B. Szwilski, Advantages of strategic mine planning, 1987, Mining Science and Technology Volume 5, Issue 3, pp. 309–317.
[10] Resource Leveling.
[11] L. Fava, Heuristic optimization of scheduling scenarios for achieving strategic mine planning targets, MIRARCO Mining Innovation, 2013, 23rd World Mining Congress, Montreal, Canada.
[12] Munoz, G.; Espinoza, D.; Goycoolea, M.; Moreno, E.; Queyranne, M.; Rivera, O., A study of
the Bienstock-Zuckerberg algorithm, Applications in Mining and Resource Constrained Project
Scheduling, Computational Optimization and Applications. Volume 69, Issue 2, pp. 501–534.
March, 2018.
Options analyses performed using both HoV and the SOT demonstrated that the deposit
was amenable to a “two pass” approach with respect to the mine planning. In other words,
high grade sub-zones can be mined first to maximize NPV, with the subsequent mining of
lower grade ore in the later years to improve free cash flow. This two-pass approach was
applied to the stope-profit attribute, with SOT configured to target high-value stopes in the
early years (typically stopes with high gold grades and favorable geochemistry), with lower
value stopes targeted in the later years of the mine.
3 DISCUSSIONS AND CONCLUSIONS
This paper summarized a mine planning optimization workflow implemented for an underground metal mining project. The main contribution of this paper is that it demonstrated a
complete and practical underground mine planning optimization process aiming to improve
values and reduce risks, with the latest software and analysis tools.
The project has a wide range of metal grades and geochemistry distributions, which makes
the mining planning process complicated but also provides flexibility for blending and schedule optimization.
Software tools played a critical role during the mine planning process. Conditional simulation produced a large number of simulation models to validate the resource model. Simulation
models after running through Stope Optimizer suggested that there was a fewer number of high
grade stopes than the resource model predicted. MSO and PUNO were used for the rapid mine
designs, which produced a large amount of data for the HoV strategic mine planning and optimization. HoV analysis identified the value range and provided guidance to cut-off grade and
production rate for more detailed scheduling. To improve the project economics and reduce
risks, SOT and OMP were applied for schedule optimization with multiple layers of constraints.
A “two pass” mine planning opportunity was recognized with the HoV study. Mining high
grade ore in the first seven years to improve NPV, and mining lower grade ore in the later
years to maximize free cash flow. This “two-pass” approach was realized with the detailed
tactical mine planning.
REFERENCES
[1] PRIMO, AMIRA, Stope Optimization and Stope Layout, 2011
[2] G. Davis, A. Newman, Modern Strategic Mine Planning, 2008, CRC Mining Conference.
[3] A. Jewbali, H. Wang, C. Johnson, Resource Model Uncertainty Analysis and Stope Optimizer
(MSO) Evaluation for an Underground Metal Mine Project, APCOM 2015.
[4] Hall A. and Hall B., 2006. Doing the Right Things Right – Identifying and Implementing the Mine
Plan that Delivers the Corporate Goals, in Proceedings International Mine Management Conference 2006 (The Australian Institute of Mining and Metallurgy: Melbourne).
[5] C. Alford, M. Brazil, and D. Lee, Stope Optimization, 2007, Optimization in Underground Mining, Handbook of Operations Research In Natural Resources, pp. 561–575.
[6] Fast Level Designer, Decline Optimization
[7] Schedule Optimization Tool
[8] B. Hall, Cut-off Grades and Optimising the Strategic Mine Plan, 2014, Spectrum Series 20 (The
Australian Institute of Mining and Metallurgy: Melbourne).
[9] A.B. Szwilski, Advantages of strategic mine planning, 1987, Mining Science and Technology Volume 5, Issue 3, pp. 309–317.
[10] Resource Leveling
[11] L. Fava, Heuristic optimization of scheduling scenarios for achieving strategic mine planning targets, MIRARCO Mining Innovation, 2013, 23rd World Mining Congress, Montreal, Canada.
[12] Munoz, G.; Espinoza, D.; Goycoolea, M.; Moreno, E.; Queyranne, M.; Rivera, O., A study of
the Bienstock-Zuckerberg algorithm, Applications in Mining and Resource Constrained Project
Scheduling, Computational Optimization and Applications. Volume 69, Issue 2, pp. 501–534.
March, 2018.