Authors: Hocking, R; Smith, M


DOI https://doi.org/10.36487/ACG_repo/2435_A-12

Cite As:
Hocking, R & Smith, M 2024, 'Caving resources and reserves: Defining a process for understanding variability and appropriate classification across global codes through project life ', in Daniel Johansson & Håkan Schunnesson (eds), MassMin 2024: Proceedings of the International Conference & Exhibition on Mass Mining, Luleå University of Technology, Luleå, pp. 132-141, https://doi.org/10.36487/ACG_repo/2435_A-12

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Abstract:
Caving Ore Reserves have unique modifying factors, including cave growth and material mixing, that need to be considered above and beyond the typical factors for other deposits. In this paper, we look at the confidence of Resource classification process based on that outlined by Parker (2014). With increased computing power and conditional simulation, Resource estimation can now simulate multiple block models based on the same drill holes, allowing the variability of the Mineral Resource to be estimated. However, there was no process available to discuss how to apply modifying factors of block cave and sub level caves. A process for estimating some of the applicable modifying factors by using simple macros in mine planning software, so that conditional simulation can be added to mixing models to determine the variability across these mixing models, is proposed. The Resource can then be classified based on this resource estimation technique. As the mine sources more data from markers or flow calibration, the error from the Mineral Resource model can be separated from the error in the mine planning flow models – this paper discusses an application of the f factors defined by Parker (2014). We explore the intricacies of the different Codes for reporting in Canada (NI43-101), the USA (S-K 1300), SAMREC and Australia (JORC). We look at the treatment of Reserves at different stages of a cave's life from the planning phase (PFS and FS), through to cave ramp-up, and finally during the production phase. The key considerations of each phase of a cave's life in terms of Reserve reporting, the key differences in each reporting Code for each phase of a cave's life, and a method for communicating variability through time between the resource and reserve model are discussed.

References:
Brunton I., Lett, J. L., Sharrock G. B., Thornhill T. & Mobilio B. (2016). Full-scale Flow Marker Experiments at the Ridgeway Deeps and Cadia East Operations, Massmin 2016, Sydney pp 142-150.
Burgio, N. (2020). Block cave ore reserves: Are we reporting a reserve or potential inventory? in R Castro, F Báez & K Suzuki (eds), MassMin 2020: Proceedings of the Eighth International Conference & Exhibition on Mass Mining, University of Chile, Santiago, pp. 1039-1047.
Campbell, A. D. (2017). A simple and accurate method for Ore Reserve estimation and Mineral Resource depletion in caving mines, in Proceedings 13th AusIMM Underground Operators’ Conference 2017, pp 253-259 (The Australasian Institute of Mining and Metallurgy: Melbourne).
Campbell A. D. (2018). Full-scale experiments and numerical modelling to improve ore recovery in sublevel cave mines, PhD thesis, University of Queensland.
Castro, R., Arancibia, L., Guzman, D. & Henriquez, J. P. (2018). Experiments and simulation of gravity flow in block caving through FlowSim', in Y Potvin & J Jakubec (eds), Caving 2018: Proceedings of the Fourth International Symposium on Block and Sublevel Caving, Australian Centre for Geomechanics, Perth, pp. 313-322, .
Diering T. (2007). Template mixing: an alternative depletion engine for block cave scheduling. in Proceeding APCOM 2007, Santiago pp 313-320.
Garces D., Viera E., Castro R. & Melendez M. (2016). Gravity Flow Full scale Tests at Esmerelda Mine’s Block – 2 El Teniente, Massmin 2016, Sydney, pp349-357.
Hargreaves R. & Morley C. (2014). Mining Reconciliation – An Overview of Data Collection Points. Mineral Resource and Ore Estimation – The AusIMM Guide to Good Practice, Second Edition, Monograph 30 pp 739-748.
Hocking, R., Balog, G., Ormerod, T. & Pearce, H. (2018). Early cave management at the Carrapateena sublevel cave', in Y Potvin & J Jakubec (eds), Caving 2018: Proceedings of the Fourth International Symposium on Block and Sublevel Caving, Australian Centre for Geomechanics, Perth, pp. 421-432.
Hocking, R., Fargher, M. & Chester, C. (2020). Marker design and calibration for Carrapateena sub level and block cave with a focus on fines migration an far field flow', in R Castro, F Báez & K Suzuki (eds), MassMin 2020: Proceedings of the Eighth International Conference & Exhibition on Mass Mining, University of Chile, Santiago, pp. 489-504.
House, M. & Secis, R. (1997). Draw parameters and reserve estimation using PC-BC at the E26 Block Cave Mine, Northparkes NSW, in Proceedings Mining Geology Conference, pp 81-92 (The Australasian Institute of Mining and Metallurgy: Melbourne).
Jamieson M. (2012). Development of sub level cave draw optimisation at Newcrest mining. Proceedings of the 6th International Conference and Exhibition on Mass Mining, 10–14 June. Sudbury: Canadian Institute of mining, Metallurgy and Petroleum.
JORC, (2012). Australasian Code for Reporting of Exploration Results, Mineral Resources and Ore Reserves (The JORC Code) [online]. Available from: <> (The Joint Ore Reserves Committee of The Australasian Institute of Mining and Metallurgy, Australian Institute of Geoscientists and Minerals Council of Australia).
Laubscher D. H. (2000). A practical manual for block caving pdf accessed at on 10 March 2024.
Parker H. (2014) Reconciliation Principles for the Mining Industry, Mineral Resource and Ore Estimation – The AusIMM Guide to Good Practice, Second Edition, Monograph 30 pp 721-738.
Parker H. & Dohm C. (2014), Evolution of Mineral Resource Classification from 1980 to 2014 and Current Best Practice, Finex 2014 Julius Wernher Lecture power point.
Power, G. R. (2004). Modelling granular flow in caving mines: large scale physical modelling and full scale experiments. PhD Thesis, Julius Kruttschnitt Mineral Research Centre, The University of Queensland.
Power, G. (2004). Full Scale SLC Draw Trials at Ridgeway Gold Mine. Proceedings of MassMin 2004, Chilean Engineers Institute, Santiago, Chile.
Power G. (2012). Optimizing caving recovery using comparative draw planning strategies and PGCA flow modelling software massmin 2012.
StephensonP. R. & Stoker P. T. (2014). Review of 2012 JORC code and comparison with National Instrument 43-101 Mineral Resource and Ore Estimation – The AusIMM Guide to Good Practice, Second Edition, Monograph 30 pp 779-792.
Talu, S., van As, A., Seloka, W. & Henry, R. (2010). Lift 2 North extension cave performance', in Y Potvin (ed.), Caving 2010: Proceedings of the Second International Symposium on Block and Sublevel Caving, Australian Centre for Geomechanics, Perth, pp. 407-421
Van Hout, G., Taylor K. & Van As A. (2023). A novel methodology for verifying height of draw in a cave mine through draw point sampling and geological observations, 26th World Mining Congress (WMC 2023).
Wilson, M. L., Van Hout, G. J. & Dean, F. F. (2018). Testing the suitability of radio frequency identification cattle tags for tracking block cave progression', in Y Potvin & J Jakubec (eds), Caving 2018: Proceedings of the Fourth International Symposium on Block and Sublevel Caving, Australian Centre for Geomechanics, Perth, pp. 713-724.
Whiteman D., Talu S., Wilson, M., Wall, G., van As A. & Kuiper P. (2016). Cave Tracker Flow monitoring system installation at Argyle Diamond Mine Massmin 2016.
Yeates G. & Hodson D. (2006). Resource Classification – Keeping the End in Sight. 6th International Mining Geology Conference Darwin NT.




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