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By J. A. Kinnaird, B. J. Youlton, K. L. Youlton

Methods for treating and processing refractory gold ores are well established. However, what is less well understood is how the formation of the gold-bearing deposits affects gold processing and extraction. In order to evaluate the effect of ore genesis on gold extraction a number of South African gold deposits were studied. These included complex Pilgrim’s Rest samples as well as refractory Fairview, Barbrook, and Consolidated Murchison samples. We found the refractory nature of gold ores is controlled by a limited number of well-understood mineralogical factors. Solid solution gold is linked to low temperature and pressure conditions in fine-grained sedimentary lithologies, while reactive pyrrhotite can form from hydrothermal fluids associated with mafic magmatic rocks. These formational controls can be used to identify and avoid complex deposits at a desktop study phase, or address and reduce complications further along the pipeline using early mineralogical studies.

Jun 1, 2021

By L. Uotinen, M. Rinne, R. Mishra

Underground mining gives rise to geotechnical hazards. A formal geotechnical risk assessment can help to forecast and mitigate these hazards. Frequentist probability methods can be used when the hazard does not have many variables and a lot of data is available. However, often there is not enough data for probability distributions, such as in the case of new projects. The risk assessment is often subjective and qualitative, based on expert judgement. The purpose of this research is to present the use of Bayesian networks (BNs) as an alternative to existing risk assessment methods in underground mines by combining expert knowledge with data as it becomes available. Roof fall frequency forecasting using parameter learning is demonstrated with 1141 sets of roof fall data across 12 coal mines in the USA. The prediction is nearly identical for individual mines, but when multiple mines are evaluated it is difficult to find a single best fit distribution for annual roof fall frequency. The BN approach with TNormal distribution was twice as likely to fit the observed data compared to the Poisson distribution assumed in the past. A hybrid approach using BN combining multiple probability distribution curves from historical data to predict annual roof fall is proposed. The BN models can account for variability for multiple parameters without increasing the complexity of the calculation. BNs can work with varying amounts of data, which makes them a good tool for real-time risk assessment in mines.

Jun 1, 2021

By E. van Steen, G. M. Leteba

Optimizing the catalytic performance of multimetallic nanoparticle (NP) catalysts demands a concrete understanding of their design, while preferentially deploying wet chemical synthesis procedures to precisely control surface structural properties. Here we report the influence of reductants such as hydrogen-rich tetrabutylammonium borohydride (TBAB) and carbon monoxide-rich molybdenum carbonyl (Mo(CO)6) on the shape and morphological evolution of Pt-based binary (PtNi and PtCo) and ternary (PtNiAu and PtCoAu) nanostructures derived from a homogeneous solution of aminebased surface active agents (surfactants) in a high boiling point solvent. We successfully synthesized nanostructures exhibiting well-defined and composition-controlled surfaces deploying a one-pot synthetic approach. The development of the surface properties was, however, observed to be alloyspecific. The resultant highly monodisperse alloy NP with narrow size distributions and facet-oriented surfaces are expected to display enhanced functionality as catalysts for utilization in specific chemical reactions.

Jun 1, 2021

By Q. Liu, S. Liu, Y. Cui

To reduce the frequency of mining incidents and improve safety and production efficiency, it is important to develop technology for the autonomous positioning and navigation of mining equipment, without the assistance of satellite navigation signals. In this study we review the current technological environment for positioning and navigation underground and present several integrated navigation strategies. Existing underground positioning and navigation technology is described, and the performances of different methods based on this technology analysed and compared. The combination types and positioning effects of underground positioning and navigation strategies are discussed. Recent research directions for filtering methods and positioning estimation algorithms for underground positioning and navigation are reviewed. Finally, we summarize the future direction of underground positioning and navigation technology and related algorithms.

Jun 1, 2021

By Eugie Kabwe

The increase in depth of mines due to the depletion of surface deposits leads to unsafe tunnel construction and overall ore extraction. This is due to tunnel instability associated with the surrounding rock mass’s ability to exhibit creep that occurs over time. However, the explicit description of this mechanism using conventional constitutive models has proven to be difficult and inadequate. Hence, this paper presents an integrated viscoelastic viscoplastic visco-damage model with the Duvaut-Lions function. The presented model is calibrated by experimental data to determine the viscoelastic viscoplastic and visco-damage parameters. It is further implemented in a finite volume numerical code and verified on an experimental scale by numerical modeling of a cylindrical specimen. It describes the 3-phase creep mechanism perfectly as compared to the inbuilt conventional integer-order derivative model. Results from the conducted verification show that it can successfully be employed to describe the long-term behavior associated with the creep mechanism.

May 16, 2021

By Omid Asghari, Seyed Reza Ghavami-Riabi, Sajjad Talesh Hosseini

Separation of geochemical anomalies from the background using various methods for identifying areas of higher mineral potential is a critical first step in Greenfield and Brownfield programs. There are several methods for differentiating anomalous regions from the background. The U-spatial statistics is an effective technique that provides the opportunity of reaching this goal by considering the geochemical sample locations in the separation of geochemical anomalies. In this study, a developed form of the U-spatial statistics method is introduced, which not only considers the existence of anisotropic spatial variations in input data but also reduces the computational (CPU) time. While the previous method is based on the isotropic assumption in the study area and a set of search windows at different times, here, the geochemical anomaly is determined by pasting only one ellipsoid window, effectively combining the flexibility of the U-spatial statistics method with the advantages of geostatistical approaches. This paper compares various approaches (the previous and developed version of the U-spatial statistics method, concentrationarea (C–A) fractal model, and probability diagram modeling) for the separation of anomalous areas in the presence of heterogeneous spatial variations. This is done with an application to a Baghqloom porphyry copper deposit located in southeastern Iran. The high potential areas identified via different approaches show an anomalous region in central parts of the Baghqloom area, which partially coincides with an intense potassic alteration area. Compared to other methods, our algorithm separated the high potential areas at a greater spatial resolution.

May 3, 2021

By D. Marcotte, R. V. Dutaut

In most exploration or mining grade data-sets, the presence of outliers or extreme values represents a significant challenge to mineral resource estimators. The most common practice is to cap the extreme values at a predefined level. A new capping approach is presented that uses QA/QC coarse duplicate data correlation to predict the real data coefficient of variation (i.e., error-free CV). The cap grade is determined such that the capped data has a CV equal to the predicted CV. The robustness of the approach with regard to original core assay length decisions, departure from lognormality, and capping before or after compositing is assessed using simulated data-sets. Real case studies of gold and nickel deposits are used to compare the proposed approach to the methods most widely used in industry. The new approach is simple and objective. It provides a cap grade that is determined automatically, based on predicted CV, and takes into account the quality of the assay procedure as determined by coarse duplicates correlation.

May 1, 2021

By W. A. Smith, M. C. Bekker, C. Marnewick

Projects or project-orientated approaches have become a common form of work in nearly all sectors of economies. This has led to concepts such as ‘projectified’ and ‘project orientated’ organizations. By defining projectification of a company, industry, or economy as the share of project work in total work, one can reasonably determine the impact that project management, and by default projectification, has had on that company, industry, or economy in terms of staff optimization and allocation. This paper presents the results for such a projectification study of the South African mining industry. This sector has long been a significant contributor to the country’s economy from a gross value added (GVA) and employment point of view. Understanding the impact of projectification and the project management way of work on this industry may potentially add significant value to both the mining and project management knowledge areas. We show that although the mining industry is considered by some to operate in archaic ways, the level of projectification has increased over time, and now represents approximately one third of all work conducted.

May 1, 2021

By L. Roux

The initial evaluation of a coal deposit often raises uncertainty with regard to the accuracy of the reported Resources and Reserves. Reconciliation of results from mining and beneficiation with the original raw field data highlights deficiencies in original estimations. Credible Resource and Reserve estimation forms the basis on which an entire mining enterprise is motivated, initiated, funded, and established as a commercially viable proposition. This is required for sustainable extraction purposes and to support vital downstream industries such as power generation. Accurate determination of the density of the matrix of the material being evaluated is the key to credible values being obtained for Resources and Reserves. Losses between 15% and 20% of the Resource/Reserve can be realized if incorrect densities are applied to the tonnage derivation. Coal plies and particles have different relative densities, determined by the maceral composition, rank, and mineral and moisture content. These factors in turn contribute to the moisture, volatile matter, ash and carbon contents of a coal, which affect the overall density of the raw coal. More specifically, the relationship of ash to density and the effective matrix porosity were found to be critical in solving the greater majority of the problems in predictive calculations. A major deficiency identified is the inability to determine effective porosity, allowing absorption of adventitious moisture and altering the mass of the core sample. Although the volume of the raw material is altered through crushing, the change in mass after controlled air-drying, used with the original geometrical volume of the raw material, provides a credible air-dry density and allows the determination of the volumetric change related to effective porosity. This parameter can be validated through the evaluation of proximate ash using the ash-adjusted algorithm and a correction for the inherent moisture applied to also give a credible relative density value for an air-dried sample. A combination of theoretical, empirical, and reconciliatory evaluations of the available data, taken from the exploration phase through the mining process to final production, has shown that an integrated approach using the ash-adjusted density (AAD) methodology, in conjunction with other evaluative techniques, provides credible results with a considerably higher degree of accuracy than is currently possible.

May 1, 2021

By Hooman Askari-Nasab, AHLAM MAREMI, EUGENE BEN-AWUAH

In oil sands mining, tailings are voluminous unwanted by-products generated from extracting the desired mineral from the mined ore. Dyke construction and backfilling activities require well-managed techniques to facilitate progressive reclamation at the earliest opportunity. This directly affects the sustainability and profitability of the mining operation. This research introduces a goal programming framework that simultaneously optimizes the (1) production schedule with limited duration stockpiling and directional mining; (2) dyke construction schedule; (3) size, shape, and location of tailings-cells; and (4) mining and processing production targets. The results show that in creating in-pit tailings-cells designs, decreasing the mining-cells volume and increasing the number of mining-cells improve the net present value of the operation due to increased operational flexibility. The model generated a uniform schedule for ore and practical tailings-cells designs for backfilling activities. Integrating tailingscells optimization into oil sands mine planning and waste management ensures the efficient use of in-pit mined-out areas required for sustainable operations.

Apr 14, 2021

By Aldin Ardian, Mustafa Kumral, Jagjit Singh

Risk assessment of mining projects is a requirement in the mineral industries. In this process, many risk variables are timedependent, and the only available data are historical time series. Moreover, in the case of a multivariate scenario, conventional forecasting methods fail to capture conditional dependency across the variables, which is important when there is an underlying causal relationship that needs to be modeled for accurate project evaluation. Thus, we investigated the use of copulas to capture the conditional distribution of the factors involved in a mine risk assessment study. We employed a multivariate copula-based time-series approach to model several uncertain variables. The Autoregressive Fractionally Integrated Moving Average - Generalized Autoregressive Conditional Heteroscedasticity (ARFIMA-GARCH) model was used for the conditional mean and copulas were used to model the error distribution, thus capturing the collective variation and dependence pattern across the variables. The method was implemented to model gold prices, copper prices, and the 10-year US Treasury bond yields and to determine the project’s net present value and probability of being economically feasible. The proposed approach can be used for cases where simulation of multivariate time-series is conducted.

Apr 13, 2021

By Ian Farrell, Josh Stowe, Eric Wingeard

Tailings transport system design is generally based on identifying the minimum and maximum process boundary conditions for pump selection and pipeline sizing. The approach is robust and well-proven. However, the approach has the potential to skew selections to operating scenarios that have a very low likelihood of occurring, such as the combination of high solids throughput and low tailings solids concentration. The approach can result in a tailings transport system design that is overly conservative. A probabilistic method-based approach captures the independent variability of design inputs and the combined likelihood of outcomes. This approach identifies the process conditions that have the highest likelihood of occurrence and are most applicable to equipment and pipeline selections. An outline of a probabilistic-based approach to tailings transport system design and the resulting selections is provided in this article. The probabilistic-based system design is compared to the outcomes from the traditional approach. The benefits and challenges to this approach are discussed and recommendations for utilizing this approach for tailings transport system design are provided.

Mar 31, 2021

By MOHAMMAD R. H. GORAKHKI, Christopher A. Bareither, MANUEL APARICIO, Joseph Scalia IV

The focus of this study was on the evaluation of hydrologic and environmental behavior observed in GeoWaste and waste rock test piles. GeoWaste is a mixture of fast-filtered tailings and waste rock prepared as a tailings-dominated mixture. The two test piles included potentially acid-generating (PAG) waste rock and were operated for 26 months to evaluate whether GeoWaste can suppresses sulfide oxidation and production of metal-rich acid mine drainage relative to PAG waste rock. The test piles were constructed in the shape of truncated 5-m-tall pyramids with 25-m base sides and flat 5-m × 5-m top surfaces. Water content, temperature, electrical conductivity, and oxygen concentration were monitored in four layers and at five locations within each layer in both test piles. In addition, 5-m × 5-m lysimeters were installed at the base of each pile to collect leachate. Approximately 2660 mm of water was added to the surfaces of the test piles via precipitation and irrigation (irrigation ≈ 1050 mm applied at an approximately constant rate for 70 days). The measured saturation, oxygen concentration, electrical conductivity, and temperature in the GeoWaste and waste rock piles suggest more sulfide oxidation occurred in the waste rock pile compared to the GeoWaste pile. Observations from the pile experiments suggest that co-managing mine waste in the form of GeoWaste reduced acid generation compared to waste rock alone due to the lower permeability and unsaturated state of the GeoWaste pile that reduced downward migration of moisture and inhibited drainage.

Mar 31, 2021

By P. K. Kankar, Manoj Khandelwal, Ramesht Shukla

One of the utmost severe mining catastrophes in underground hard rock mines is rock burst phenomena. It can lead to damage to mine openings and equipment as well as trigger accidents or even threat to life as well. Due to this, a number of researchers are forced to study some easy-to-use alternative methods to predict the rock burst occurrence. Nevertheless, due to the extremely multifaceted relation between mechanical, geological and geometric factors of the mines, the conventional prediction methods are not able to produce accurate results. With the expansion of machine learning methods, a revolution in the rock burst occurrence has become imaginable. In present study, three machine learning methods, namely XGBoost, decision tree and support vector machine, are utilized to predict the occurrence of rock burst in various underground projects. A total of 134 rock burst events were gathered together from various published literatures comprising maximum tangential stress (MTS), elastic energy index (EEI), uniaxial compressive strength and uniaxial tensile stress (UTS) that have been used to develop various machine learning models. The performance of machine learning methods is evaluated based on the accuracy, sensitivity and specificity of the rock burst prediction.

Mar 17, 2021

By E Hawkins, S Sheldon

Block caving is becoming a more widely adopted mining method allowing for underground massive low grade orebodies to be extracted economically. Underbreak during cave propagation is difficult to predict in terms of recovery and is not well-researched due to the small number of caving operations. During mining of E26 Lift 2 (E26L2) block cave at CMOC Northparkes Mines, a wedge of high grade material failed to cave, even with the assistance of preconditioning and subsequent attempts to induce caving. The ultimate solution for recovery of the uncaved wedge was the establishment of the E26 sublevel cave (SLC), which commenced mining in 2015, with production following in 2016. The SLC provides approximately 1Mtpa to supplement the lowering grade of the current E48 block cave feed. Applying the sublevel caving methodology to recover block cave underbreak has proven challenging. The impact of the caving stresses and preconditioning of the wedge have caused production limitations requiring continual remediation throughout production of the E26 SLC. The dependence on remediation work created a roadblock to implementing precharging as the prevalence of brow loss raised concerns over the inability to hook up the charged ring. In 2018, a wireless initiation trial was completed in the E26 SLC over 24 rings. The trial showed that precharging was achievable in this environment and greatly improved the safety of charge up personnel.

Mar 15, 2021

By G Balog, T Ormerod, D Sidea

Carrapateena is a copper-gold sub level caving operation located in the Gawler Craton, South Australia. One of Australia’s largest undeveloped copper deposits, the project will be a 4.25 Mtpa underground operation, with an estimated mine life of 20 years (OZ Minerals, 2017). First concentrate production was achieved in December 2019, within the Iron Ore Copper Gold (IOCG) hematite breccia complex. The Carrapateena orebody is overlain by 500 m of barren sediments of the Stuart Shelf, which hosts two aquifers. The cover sequence is dominated by shales, quartzites and sandstones in order of thickness. The cover sequence presented challenges to the mine ventilation system as a result of highly variable rock strengths. On this basis, the site developed the first vent rise, Vent Rise 5 (VR5), earlier than required as a means to test the empirical stability assessment. Assessment for VR5 was completed in 2017, with the mine yet to develop through much of the cover sequence. Due to the geotechnical data available at the time, it was anticipated that break out would occur within the vent rise walls as a function of the low strength Woomera shales. VR5 was developed to 4.5 mᴓ in late 2018. The timing of the VR5 development enabled the site technical team to calibrate empirical stability factors for the assessment of future vent rises. At the time of writing, four additional vent rises have been successfully developed to a diameter of 5.5 m. No significant overbreak has been observed within any of the vent rises. This paper is intended for geotechnical practitioners designing large-diameter vent rises in geological environments similar to the Stuart Shelf where a similar approach to vent rise design may be warranted.

Mar 15, 2021

By T Wettainen, G Shekhar, M Stromsten, B Skawina

The aim of a transportation system in an underground mine is to move the rock masses from one location to another in the most preferable manner by minimising the long and short-term operational costs. A continuous improvement of material transportation systems used in mines generates a need for continuous investigation of the current and new underground transportation systems. In an underground mine, an orepass is a common system used to transfer the material to the lower levels. If this system loses the ability to transport or store the necessary material capacities, it would result in production disturbances. In this paper, discrete event simulation (DES) was utilised to analyse the material inflow and outflow of the orepass systems when subjected to the different conditions. The study presented in this paper is based on the Malmberget mine, the second largest underground sublevel caving (SLC) iron ore operation in the world.

Mar 15, 2021

By D Kilkenny, D Nardini, P Kline

This paper is a case study highlighting learnings and success in two areas challenging underground miners: change management and collaboration. It examines the implementation process of a new automated loading system in the bulk stoping area of Telfer Mine in Western Australia, controlling multiple load haul dump machines. Here, the new technology has brought together different functions and different companies to deliver a well performing automation system in a changing and challenging mining environment. The introduction of a new and different technology on site has driven collaboration between all stakeholders to break down the traditional barriers to achieve the sustained performance required. Historically, different teams have operated within silos and not always aligned to deliver a ‘best for project’ solution. Technical teams focus on the mine design, maintenance teams focus on reliability and operations execute the plan. Mining contractors focus on productivity and cost. Manufacturers focus on supply of goods and service. Optimising each silo individually is not guaranteed to provide an optimal mining solution. Involving elements from each team as seen at Telfer, has resulted in an optimal mining solution for the automated loading system. A change of focus from the technical teams to include automation parameters in the mine design; operability and maintainability built into the system design allowing for collective ownership and responsibility resulting in a more resilient solution. The implementation of the new technology was not only a technical change but more importantly, successful management of change. Elements of successful change management such as communication, vision, leadership and planning, are essential to harness a trusting site culture which is responsive to new technology. Learnings and challenges from this change process will also be discussed with the intent to improve the success rate and timelines of technology implementations in the future.

Mar 15, 2021

By C McCracken, R Landers, B Hesse

Minnovare identified the potential to improve production drilling outcomes in underground long-hole stopes through the adaptation of new technology which was under ongoing development. An approach to Evolution Mining resulted in the companies agreeing to a collaborative agreement to further develop the technology for use on underground long-hole drilling equipment. During a period of six months in FY2018, a series of trials were conducted to compare drilling accuracy using two different methodologies and the subsequent impact this had on ore dilution. Testing was conducted at Cracow underground gold mine in Queensland, Australia. The drill rig’s existing setup/alignment process was compared to the new technology system with the following observations: • Using the existing process only 20% of holes surveyed recorded toe points within the +/ 300mm (11.8in) tolerance blast-hole deviation. • The new technology was proven to limit rig setup/alignment error, reducing average blasthole deviation and increasing the number of holes drilled within tolerance by 160%. The increased accuracy reduced stope dilution by reducing over-break of subgrade ore: • Stopes drilled using the new technology recorded 62.6% less average dilution. • This contributed to an overall reduction in dilution for the full year (FY18) of 5 percentage points compared to FY17 - from 22% to 17% (a net decrease of 22.7%). • With the system implemented as standard practice following results of the FY18 trial and continued success, overall dilution for full year FY19 showed continued reduction to 12% Evolution has continued use of the new technology at Cracow, where the improved accuracy has allowed the extraction of narrower stopes where drilling accuracy is critical. Evolution has also deployed the technology at the Mungari operation and has stipulated that the contractor use the technology at the Mt Carlton operation, which is currently under development. Future implementation of the Development Optimiser system should be verified by commencing additional trials to include a larger data base for validating the initial trial results.

Mar 15, 2021

By B Murphy, N Strong, J Albrecht

Rio Tinto’s Argyle Diamond Mine has a history of underperformance with delivery of ore from the underground operation to the surface for processing with no real clarity in sources of loss and value. In order to increase underground production performance, the basic concepts of the Theory of Constraints model were applied to the Argyle underground production system. This prompted a revised view on bottlenecks and contributors to value loss and ultimately leading to record breaking mine performance. System loss reporting to demonstrate the best opportunity to drive value, departmental detail to develop tools to identify improvement opportunities and clarity across the team to ensure alignment and clear lines of communication were critical to the project success.

Mar 15, 2021