Sampling Broken Ore Residues in Underground Gold Workings: Implications for Reconciliation and Lost Revenue
Abstract
:1. Introduction
1.1. Sampling
1.2. Reconciliation
1.3. What Are Broken Ore Residues?
1.4. Broken Ore Residues—A South African Perspective
1.5. Aim/Focus of This Paper
2. Sampling of Broken Rocks
2.1. Overview
2.2. Theory of Sampling Applied to Mine Residues
2.3. FSE Application
2.4. Optimised Sampling Protocol
3. Case Study
3.1. Introduction
3.2. Preliminary Sampling on the 200 Level Drive
3.2.1. Initial bulk Sample and Granulometry
3.2.2. Segregation in the Residue Pile
3.3. FSE Analysis
3.4. 200 Level Drive Sampling Programme
3.5. 200 Level Drive Field Duplicate Programme
3.6. 200 Drive Residue Reconciliation
3.7. Sampling of the Rest of the South Vein Workings
3.8. Evaluation of the South Vein Workings
3.9. Rest of Mine Reconciliation
3.10. Economic Value of the Programme
4. Sampling, Evaluation, Reporting and Reclamation
4.1. Grade Determination
4.2. Residue Evaluation
4.3. Reporting Residue Resources and Reserves
4.4. Residue Reclamation
5. Conclusions
5.1. General Conclusions
- The underground mining cycle results in some of the metal inventory being left as broken residues within underground mine workings. The mucking process itself can enhance the “milling” of ore yielding liberated fine-ore minerals within the broken rock pile.
- The study of broken ore residues presented here is relevant for both review of reconciliation and evaluation of residue with a view to reclamation.
- It is possible for >5% or more of the original metal inventory to remain as broken residues, which will have a material effect on reconciliation and project economics.
- The residual pile can be strongly gold enriched in comparison to the original in-situ ore. Gold segregation can be observed within the residue pile, where the base is enriched with respect to the upper portion.
- Given that the material in question is already broken, the sampling strategy will be based on digging trenches or pits into the mine floor to extract a pre-determined mass of material for assay. Grab sampling is the only practical method for sampling stopes, given their variable distribution of residues.
- Safety considerations are paramount during both the sampling and reclamation process. If drive/stope access cannot be attained safely, then any estimate may not achieve RPEEE.
- Application of TOS is key to ensuring that sampling is representative. The FSE equation can be used to determine the sample mass required and any subsequent preparation-assay steps at a given DQO.
- If a resource is defined, then a feasibility study is required to evaluate economic viability. If the quantity of gold found is deemed to be economic to extract, vacuum technology enables a cost-effective reclamation method.
- This discussion covers underground operations, though similar loss is also possible during open pit bench blasting. The nature of open pit mining does not allow for residue recovery due to consecutive benching. If some residues are dispersed within the mining area, they will be recovered.
- Other commodities can also be prone to fines loss (e.g., nickel sulphides)and, thus, similar studies may be appropriate.
5.2. Case Study Conclusions
- A preliminary sampling programme involved digging pits into the drive floors and producing a concentrate by panning.
- An initial bulk residue sample of 7.5 t was composited from 7 trenches across a test drive. This was processed through a pilot plant as a series of size fractions to provide a granulometric analysis and head grade. Review of the concentrates indicated that most of the gold was in the 500 µm to 1200 µm size range.
- It was found that 97% of the contained gold was hosted in the −5 cm fraction, representing 90% of the total sample mass. The entire bulk sample displayed a 270% enrichment in gold compared to a bulk sample of primary blasted ore.
- A more detailed sampling programme was undertaken across 4 drives totalling c. 1650 m of strike. This involved collecting 200–250 kg trench samples along each drive (5–6 m separation) to provide a total sample mass of c. 6 t per drive (screened at 50 mm). The 6 t target was an optimised estimate using the FSE equation with the aim of achieving a precision of ±15% at the 90% confidence limit.
- All sample data was combined to estimate an indicated mineral resource of 2650 t at 28.1 g/t Au for 2394 oz Au contained. A feasibility study defined a probable ore reserve of 2600 t at 27.9 g/t Au for 2332 oz Au contained. The study indicated that the project had a pre-tax NPV of US$1.7 M and an IRR of 550% in 2016.
- A reclamation programme of the broken ore residues produced 2412 t at 30.6 g/t Au for 2372 oz Au recovered, which generated a post-tax profit of US$1.4 M.
- The case study presented shows that 22% of the original estimate across the reclaimed area can be attributed to “lost” gold. Reclamation of the residues recovered 18.5% of the original estimate. The additional 3.5% was attributed to gold lost in stopes (not estimated or recovered here), gold lost elsewhere (e.g., in trucks, surface stockpiles, etc.), and sampling/estimation error.
6. Recommendations to the Practitioner
- Characterisation should build a picture of residue tonnes and grade. A first pass programme could include the digging of pits in drive floors or taking grab samples from stope, and panning the samples to identify gold and/or sulphides as appropriate.
- When physically accessible, undertake mini-bulk sampling (100–250 kg samples) and testwork, and integrate with mineralogical and metallurgical needs. Initial assaying programmes should commence with screen fire assaying and/or tabling (e.g., Wilfley or Gemeni tables) after size reduction to identify the presence of coarse gold and/or sulphides.
- It should become clear early on if the grades achieved, and if the likely recovery area will yield a resource. If a mineral resource is defined (assuming RPEEE), then a feasibility study must be undertaken to prove viability.
- Embrace new technologies, such as smart crushers and PhotonAssay, to achieve large volume assays. Any proposed protocol will require validation during initial implementation through the application of sample duplicates where possible. In coarse gold-dominated residues, laboratory-scale or pilot plant facilities, or a sampling tower may be required for grade determination. A QAQC programme will be required for all testwork.
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- Gy, P.M. Sampling of Particulate Materials: Theory and Practice; Elsevier: Amsterdam, The Netherlands, 1982; p. 431. [Google Scholar]
- Minnitt, R.C.A. Sampling: The impact on costs and decision making. J. South Afr. Inst. Min. Metall. 2007, 107, 451–462. [Google Scholar] [CrossRef]
- Dominy, S.C. Importance of good sampling practice throughout the gold mine value chain. Mining Tech. 2016, 125, 129–141. [Google Scholar] [CrossRef]
- Pitard, F.F. Theory of Sampling and Sampling Practice; CRC Press: Boca Raton, FL, USA, 2019; p. 693. [Google Scholar]
- Esbensen, K.H. Introduction to the Theory and Practice of Sampling; IM Publications: West Sussex, UK, 2020. [Google Scholar] [CrossRef]
- Dominy, S.C.; Glass, H.J.; Purevgerel, S. Sampling for resource evaluation and grade control in an underground gold operation: A case of compromise. In Proceedings of the WCSB10 Conference 2022, Kristiansand, Norway, 31 May–2 June 2022; IM Publications: West Sussex, UK; pp. 375–395. [Google Scholar]
- Dominy, S.C.; Platten, I.M.; Glass, H.J.; Purevgerel, S.; Cuffley, B.W. Determination of gold particle characteristics for sampling protocol optimisation. Minerals 2021, 11, 1109. [Google Scholar] [CrossRef]
- François-Bongarçon, D.M.; Gy, P.M. The most common error in applying Gy’s formula in the theory of mineral sampling and the history of the liberation factor. J. South. Afr. Inst. Min. Metall. 2002, 102, 475–479. [Google Scholar]
- Hargreaves, R.; Morley, C. Mining reconciliation—An overview of data collection points and data analysis. In Mineral Resource and Ore Reserve Estimation; Australasian Institute of Mining and Metallurgy: Melbourne, Australia, 2014; pp. 739–748. [Google Scholar]
- Biegaj, K.; Dominy, S.C. Mine floor material recovery must become part of the Life-of-Mine plan. In Proceedings of the International Future Mining Conference Melbourne, Online, 6–10 December 2021; Australasian Institute of Mining and Metallurgy: Melbourne, Australia,, 2021; pp. 358–365. [Google Scholar]
- De Jager, E.J. The Analysis of the Mine Call Factor in Gold Mining with Specific Reference to Western Holdings Mine. PhD Thesis, University of the Witwatersrand, Johannesburgm, South Africa, 1996; p. 112. [Google Scholar]
- Storrar, C.D. South African Mine Valuation; Chamber of Mines of South Africa: Johannesburg, South Africa, 1981; p. 470. [Google Scholar]
- Xingwana, L. Monitoring ore loss and dilution for mine-to-mill integration in deep gold mines: A survey-based investigation. J. South. Afr. Inst. Min. Metall. 2016, 116, 149–160. [Google Scholar] [CrossRef] [Green Version]
- Fourie, A.; Minnitt, R.C.A. Review of gold reef sampling and its impact on the mine call factor. J. South. Afr. Inst. Min. Metall. 2016, 116, 1001–1010. [Google Scholar] [CrossRef] [Green Version]
- Dominy, S.C.; Glass, H.J.; Lam, C.K.; O’Connor, L.; Purevgerel, S.; Minnitt, R.C.A. Integrating the Theory of Sampling into underground grade control strategies. Minerals 2018, 8, 232. [Google Scholar] [CrossRef] [Green Version]
- Dominy, S.C. Grab sampling for underground gold mine grade control. J. South Afr. Inst. Min. Metall. 2010, 110, 277–287. Available online: http://www.scielo.org.za/pdf/jsaimm/v110n6/04.pdf (accessed on 1 April 2022).
- JORC. Australasian Code for Reporting of Exploration Results, Mineral Resources and Ore Reserves, the JORC Code; Joint Ore Reserves Committee of the Australasian Institute of Mining and Metallurgy; Australian Institute of Geoscientists and Minerals Council of Australia: Melbourne, Australia, 2012; 44p, Available online: https://www.jorc.org/docs/JORC_code_2012.pdf (accessed on 1 April 2022).
- PERC. Pan-European Standard for the Public Reporting of Exploration Results; Mineral Resources and Mineral Reserves: The PERC Reporting Standard; Pan European Reserves and Resources Reporting Committee: Brussels, Belgium, 2021; 68p, Available online: https://percstandard.org/wp-content/uploads/2021/09/PERC_REPORTING_STANDARD_2021_RELEASE_01Oct21_full.pdf (accessed on 1 April 2022).
- CIM. CIM Definition Standards for Mineral Resources and Mineral Reserves; CIM Standing Committee on Reserve Definitions: Westmount, QC, Canada, 2014; p. 19. Available online: https://mrmr.cim.org/media/1128/cim-definition-standards_2014.pdf (accessed on 1 April 2022).
- Dominy, S.C. Predicting the unpredictable—Evaluating high-nugget effect gold deposits. In Mineral Resource and Ore Reserve Estimation; Australasian Institute of Mining and Metallurgy: Melbourne, Australia, 2014; pp. 659–678. [Google Scholar]
- Tuck, M. Stope cleaning: Historical methods and future developments. In Proceedings of the Gravity Gold Conference 2010, Ballarat, Australia, 21–22 September 2010; Australasian Institute of Mining and Metallurgy: Melbourne, Australia, 2010; pp. 25–26. [Google Scholar]
- François-Bongarçon, D.M. Theory of sampling and geostatistics: An intimate link. Chemom. Intell. Lab. Syst. 2004, 74, 143–148. [Google Scholar] [CrossRef]
- Minnitt, R.C.A.; Assibey-Bonsu, W. A comparison between the duplicate series method and the heterogeneity test as methods for calculating the sampling constants. J. South. Afr. Inst. Min. Metall. 2010, 110, 251–268. [Google Scholar]
- Dominy, S.C.; Purevgerel, S.; Esbensen, K.H. Quality and sampling error quantification for gold mineral resource estimation. Spectrosc. Eur. 2020, 32, 21–27. [Google Scholar] [CrossRef]
Deposit Type | Coarse Gold | Reserve Grade (g/t Au) | Mined Grade (g/t Au) | Reserve Model Inputs | Estimate of Gold in Residues | Mine Call Factor (Mined/Reserve) |
---|---|---|---|---|---|---|
Vein 1.0–1.5 m low-dip; long-hole | High | 20.2 | 16.4 | Face | 15–20% | 75% |
Sub-vertical 3–5 m vein; long-hole | Med | 9.5 | 7.0 | DDH & Face | 10–12% | 74% |
Sub-vertical 1–2 m vein; long-hole | Low | 10.4 | 9.4 | DDH | 5–10% | 90% |
Vertical 2–4 m vein; long-hole | High | 10.2 | 6.7 | DDH & Face | 20–25% | 66% |
Sub-vertical 1–1.5 m; long-hole & shrinkage | Med | 22.2 | 24.6 | DDH | <5% | 111% |
Sampling Error | Acronym | Error Type | Effect on Sampling | Source of Error | Practical Implication |
---|---|---|---|---|---|
Fundamental | FSE | Correct Sampling Error (CSE) | Random Errors—Precision Generator | Characteristics of the ore type. Relates to constitution and distribution heterogeneity | To achieve a given level of precision, the mass of sample collected will need to be sufficient to reduce the FSE. The Gy FSE equation can be used to optimise the sample mass |
Grouping and Segregation | GSE | Once rock is broken, there will be segregation of rock and mineral particles across the residue. The residue must be sampled across its full depth | |||
Delimitation | DE | Incorrect Sampling Error (ISE) | Systematic Errors—Bias Generator | Sampling method, equipment and materials handling | A consistent trench width is required. Trench depth will vary will residue depth. Residue must be sampled to its full depth |
Extraction | EE | All fragments within the delineated volume must be extracted | |||
Preparation | PE | ||||
Refers to issues during sample transport and storage e.g., mix-up, damage, loss and alteration, preparation (contamination and/or losses), and intentional actions (sabotage and salting), as well as unintentional actions (carelessness and non-adherence to protocols) | |||||
Analytical | AE | - | Analytical process | Relates to all errors during assay and analytical processes, including issues related to rock matrix effects, analytical equipment maintenance, faulty calibration, etc. |
Lot Grade (g/t Au) | Liberation Diameter | |||
---|---|---|---|---|
Very Fine Gold [50 µm] | Fine Gold [100 µm] | Coarse Gold [250 µm] | Very Coarse Gold [1000 µm] | |
5 | 345 kg | 1 t | 3.8 t | 30.7 t |
10 | 170 kg | 0.5 t | 1.9 t | 15.4 t |
20 | 85 kg | 250 kg | 1 t | 7.7 t |
30 | 60 kg | 165 kg | 0.7 t | 5.1 t |
60 | 30 kg | 80 kg | 350 kg | 2.6 t |
Step | Step Action | Stage FSE (68% CL) | Stage FSE (90% CL) | Comments |
---|---|---|---|---|
1 | Crush 250 kg to P90 −4 mm split off 25% | ±12% | ±18% | Post dry, crush entire sample and double riffle split to achieve c. 62.5 kg sub-sample |
2 | Crush 62.5 kg to P90 −1 mm split off 25% | ±8% | ±13% | Crush entire sample and double riffle split to achieve c. 15.6 kg sub-sample |
3 | Pulverise 15.6 kg to P90 −100 µm and split off 2–4 kg for screen fire assay or PhotonAssay | ±2% | ±2% | Pulverize via rod mill or LM5. Batch if required. Rotary sample divide to 2–4 kg sub-sample for SFA or PhotonAssay. If more coarse gold expected, tend toward 4 kg assay charge |
Total FSE | ±14% | ±23% |
Step | Step Action | Primary Lot Mass | Sample Mass | Stage FSE (68% CL) | Stage FSE (90% CL) |
---|---|---|---|---|---|
1 | Collect 12 × 250 kg samples | 260 t | 3 t | ±13% | ±20% |
2 | Crush/split | 3 t | 750 kg | ±3% | ±5% |
3 | Crush/split | 750 kg | 188 kg | ±2% | ±4% |
4 | Pulverise/split for assay | 188 kg | 48 kg | <±1% | <±1% |
Total FSE | ±13% | ±20% |
Size fraction | Fraction Mass (t) | Fraction Grade (g/t Au) | Mass Fraction (%) | Contained Gold (%) |
---|---|---|---|---|
−3 mm | 3.07 | 44.6 | 7 | 25 |
3 to 6 mm | 2.41 | 29.8 | 6 | 13 |
6 to 15 mm | 4.25 | 23.8 | 10 | 18 |
15 to 25 mm | 1.53 | 18.7 | 4 | 5 |
25 to 50 mm | 5.43 | 10.3 | 13 | 10 |
50 to 100 mm | 7.58 | 9.2 | 18 | 13 |
>100 mm | 17.31 | 5.1 | 42 | 16 |
Total | 41.58 | 13.2 | - | - |
Size Fraction | Fraction Mass (t) | Fraction Grade (g/t Au) | Mass Fraction (%) | Contained Gold (%) |
---|---|---|---|---|
−3 mm | 1.97 | 58.6 | 26 | 43 |
3 to 6 mm | 1.77 | 45.8 | 23 | 30 |
6 to 15 mm | 1.14 | 26.7 | 15 | 11 |
15 to 25 mm | 0.76 | 24.3 | 10 | 7 |
25 to 50 mm | 1.13 | 14.6 | 15 | 6 |
50 to 100 mm | 0.56 | 9.2 | 8 | 2 |
>100 mm | 0.16 | 0.2 | 2 | <1 |
Total | 7.53 | 35.6 | - | - |
Layer | Thickness (m) | Fraction (mm) | Mass (kg) | Grade (g/t Au) | Contained Gold (%) |
---|---|---|---|---|---|
L1 (top) | 0.11 | −6 | 55.6 | 34.6 | 11 |
+6 | 70.9 | 22.4 | 9 | ||
Total | 126.5 | 27.8 | 20 | ||
L2 | 0.10 | −6 | 60.2 | 44.7 | 16 |
+6 | 54.8 | 31.6 | 10 | ||
Total | 115.0 | 38.5 | 26 | ||
L3 (base) | 0.12 | −6 | 74.6 | 76.9 | 33 |
+6 | 63.4 | 55.2 | 20 | ||
Total | 138.0 | 66.9 | 54 | ||
Total | 0.33 | 379.5 | 45.2 | - |
Layer | Thickness (m) | Fraction (mm) | Mass (kg) | Grade (g/t Au) | Contained Gold (%) |
---|---|---|---|---|---|
L1 (top) | 0.12 | −6 | 61.2 | 21.7 | 14 |
+6 | 76.8 | 10.5 | 8 | ||
Total | 138.0 | 15.5 | 22 | ||
L2 | 0.13 | −6 | 66.7 | 20.1 | 14 |
+6 | 82.8 | 18.7 | 16 | ||
Total | 149.5 | 19.3 | 30 | ||
L3 (base) | 0.13 | −6 | 84.6 | 42.1 | 36 |
+6 | 63.1 | 18.4 | 12 | ||
Total | 147.7 | 32.1 | 48 | ||
Total | 0.38 | - | 435.2 | 22.4 | - |
Lot Grade (g/t Au) | Liberation Diameter | |
---|---|---|
500 µm Gold | 1000 µm Gold | |
5 | 10.8 t | 30.7 t |
10 | 5.4 t | 15.4 t |
20 | 2.7 t | 7.7 t |
30 | 1.8 t | 5.1 t |
60 | 0.9 t | 2.6 t |
Lot Grade (g/t Au) | Liberation Diameter | |
---|---|---|
500 µm Gold | 1000 µm Gold | |
5 | 0.35 t | 10.8 t |
10 | 0.20 t | 5.4 t |
20 | 85 kg | 2.7 t |
30 | 60 kg | 1.8 t |
60 | 30 kg | 0.9 t |
Measure | Tonnes (t) | Head Grade (g/t Au) | Contained Ounces (Gold) |
---|---|---|---|
Actual mined | 5375 | 14.0 | 2420 |
Actual reclaimed residues | 235 | 36.3 | 274 |
Actual recovered total | 5610 | 14.9 | 2694 |
Probable Ore Reserve | 5712 | 15.8 | 2902 |
Mine call factor (actual/reserve) | 0.98 | 0.94 | 0.93 |
Metric | Tonnes (t) | Head Grade (g/t Au) | Recovered Grade (g/t Au) | Recovered Gold (oz) |
---|---|---|---|---|
Probable Ore Reserve | 2600 | 27.9 | 26.5 | 2215 |
Actual reclaimed residues | 2412 | 32.4 | 30.6 | 2373 |
Difference | −7% | +16% | +15% | +7% |
Metric | Tonnes (t) | Recovered Grade (g/t Au) | Recovered Gold (oz) | Head Grade (g/t Au) | Proportion of Recovered Gold to Reserve |
---|---|---|---|---|---|
Probable Ore Reserve | 25,800 | 15.3 | 12,693 | 16.1 | - |
Actual mined | 22,950 | 13.4 | 9888 | 14.1 | 77.8% |
Actual reclaimed residues | 2412 | 30.6 | 2373 | 32.2 | 18.7% |
Actual total | 25,362 | 15.0 | 12,261 | 15.8 | 96.4% |
Metric | US$ per Tonne | US$ per Ounce Recovered |
---|---|---|
Evaluation cost | 135 | 137 |
Mining/processing cost | 260 | 304 |
Total cost | 395 | 441 |
Post-tax profit | 680 | 573 |
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Dominy, S.C.; Glass, H.J.; Minnitt, R.C.A. Sampling Broken Ore Residues in Underground Gold Workings: Implications for Reconciliation and Lost Revenue. Minerals 2022, 12, 667. https://doi.org/10.3390/min12060667
Dominy SC, Glass HJ, Minnitt RCA. Sampling Broken Ore Residues in Underground Gold Workings: Implications for Reconciliation and Lost Revenue. Minerals. 2022; 12(6):667. https://doi.org/10.3390/min12060667
Chicago/Turabian StyleDominy, Simon C., Hylke J. Glass, and Richard C.A. Minnitt. 2022. "Sampling Broken Ore Residues in Underground Gold Workings: Implications for Reconciliation and Lost Revenue" Minerals 12, no. 6: 667. https://doi.org/10.3390/min12060667
APA StyleDominy, S. C., Glass, H. J., & Minnitt, R. C. A. (2022). Sampling Broken Ore Residues in Underground Gold Workings: Implications for Reconciliation and Lost Revenue. Minerals, 12(6), 667. https://doi.org/10.3390/min12060667