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By K. Woodward, Y. Potvin, B. McFadyen, M. Grenon

Open stoping has become a popular mining method in hard rock mines, not only due to the safety of the method as a non-entry approach, but also because of the high extraction rate and low costs. At mine sites, stope performance is evaluated by calculating stope overbreak using the stability chart. However, limitations of the stability chart regarding the precision of the predictions, nonconsideration of factors such as the influence of blasting, and the exclusion of underbreak have led to non-optimal designs. The capabilities of today's computers have increased the amount of data being collected and the power of models being built. This article presents a step towards a new stope design approach where stope overbreak and underbreak are measured and georeferenced using octrees at an approximately cubic metre resolution and predicted using multivariate statistical models (partial least square, linear discriminant analysis, and random forest). Results show that overbreak and underbreak location along the design surface and their magnitude are predicted with good precision using a random forest model. These predictions are used to build the expected geometry of the open stope. The resolution of the data and the use of multivariate analysis has enabled the prediction of variation in stope performance along the design surface, going well beyond the simple qualitative per stope face prediction provided by a traditional stability chart approach.

Jun 5, 2023

By B. Genc, C. Gous

Spontaneous combustion during coal mining operations is a major problem that affects the health and safety of workers and causes environmental problems. The phenomenon is associated with the presence of coal, coal shale, and pyrite. In 2020, a premature detonation incident occurred at an iron ore mine where the waste material contains black carbonaceous shale units known to be associated with pyrite. The spontaneous combustion propensity and properties of samples of the black carbonaceous shales from the mine were examined and compared with samples from the Witbank Coalfield. The spontaneous combustion liability indexes of these samples were correlated with X-ray fluorescence (XRF) and proximate and ultimate analyses using linear regression. The Wits-Ehac Index classification results show that the samples were between medium and high risk. The linear regression analysis showed very poor correlations between the Wits-Ehac Index results and the XRF and proximate and ultimate results. The most valuable relationship found is between the presence of relatively high sulphur (greater than 3%) and ground reactivity with nitrate-bearing explosive emulsion.

Jun 5, 2023

By Kyle A. Perry, Ethan A. Steward

The mining of underground coal presents several hazards for miners, including the risk of an explosion fueled by methane gas and coal dust. Methane gas, produced during coal formation, can continuously leak into old workings and build up through its lower explosive limit. Underground coal mines are required to maintain safe conditions, either by ventilating old workings or sealing them off using approved methods. Seals must be designed to withstand instantaneous pressures for a minimum of four seconds. A design strength of at least 50 pounds per square inch (psi) is required for atmospheres monitored and maintained inert, 120 psi for non-inert or not monitored, and greater than 120 psi for special cases. Due to the high cost and testing environment availability, most mine seals are designed through calculations and computer modeling and not subjected to full-scale testing in a representative environment. High pressure is not the only threat that mine seals may be exposed to. During an underground explosion, pressure waves and gas expansion may propel common mine items and objects to a high velocity, generating enough energy to damage mine seals and reduce their strength. Damaged mine seals may fail to contain their rated pressure, allow high pressure gas and fumes to vent through the seal during an explosion, or allow gasses to leak through the seal later after an explosion has occurred. This paper examines the effects of high velocity impacts of common mine materials and items on a reinforced mine seal rated to 120 psi.

Jun 2, 2023

By Wei Victor Liu, Na Zhang, Chengkai Fan, Bei Jiang

This study used artificial neural networks (ANNs) coupled with Gaussian mixture modeling (GMM) to analyze truck haulage data from openpit mines. The proposed weighted ensemble models performed better than benchmark models in predicting truck productivity, providing a new means of solving complex data and improving mine planning and decision-making.

Jun 1, 2023

By Irina Chernyshova, Erik Larsen, Hanumantha Rao Kota, Vladislav Slabov, Garima Jain

The mining industry faces pressure to provide metals for the green digital shift using sustainable technologies. This study evaluates biosurfactants as collectors for ultrafine and coarser particles of hematite and malachite, aiming to improve the flotation of ultrafine particles.

Jun 1, 2023

By Yueyue Ding, Yuanhui Li, Zhengrong Li, Pengfei Yu, Kunmeng Li, Zhipeng Xiong

The overburden responses in gently inclined orebody mining are different from those in horizontal orebody affected by the orebody dip angle. In particular, the mining-induced stress presents asymmetrical distribution characteristics spatially, resulting in stress concentration and large-scale pressure relief phenomenon in the surrounding rock. As a result, frequent ground pressure disasters such as roof collapse and barrier splitting occur frequently. Moreover, the ground pressure evolution law and the interaction between stopes in multistope mining are complex. The effective ground pressure control measures cannot be taken due to unclear understanding of the evolution of stress and displacement fields, justifying the investigation of the distribution and evolution of underground pressure for safe and efficient mining.

Jun 1, 2023

By Ihsan Berk Tulu, Haochen Zhao, Deniz Tuncay

The process of designing pillars and selecting support measures in underground coal mines relies highly on the accurate assessment of mining-induced loads and the load-bearing capacities of the supports. This study proposes a new method to estimate the percentage of load carried by the gob in underground coal mines using a new parameter that introduces the site-specific overburden geology.

Jun 1, 2023

By Aixiang Wu, Minjie Zhang, Zhuen Ruan, Yiming Wang

This paper combines theoretical and experimental analysis to conduct relevant research to improve the accuracy of predicting paste yield stress by slump flow. The analytical model of slump flow for yield stress is derived based on a mini-cylindrical mold with a height-to-diameter ratio of 1. It shows that the dimensionless slump flow is a monotonic decreasing function of the dimensionless yield stress and is independent of the material type (specific gravity), which provides a theoretical basis for quantifying the rheological properties of paste with slump flow. Three different tailing-prepared pastes were tested for their slump flow and implemented rheological tests simultaneously. The yield stress is obtained based on the Bingham model fit, as the measured value of the yield stress is substituted into the derived theoretical model. The studied pastes yield stresses range from 34.78 to 524.08 Pa, with corresponding dimensionless slump flow of 3.43 to 1.09. The results showed that the calculated slump flows were generally greater than the measured values. The analysis showed that this was mainly due to the thixotropy of the paste, with minor deviations ranging from − 1.5 to 5.8% for the less thixotropic pasted prepared from tailing C. An approximate analytical solution for yield stress as a function of slump flow is obtained using Taylor’s formula. However, it is unsuitable for predicting the yield stress because the yield stress calculated by this function is much higher than the measured value. The empirical yield stress model was constructed and experimentally verified. The results show that the empirical formula has high accuracy and good generality. The deviation of the studied pastes is between − 15 and 5%, which provides a practical method for rapid and accurate prediction of paste yield stress in mine sites.

Jun 1, 2023

By Brendan Demich, Brendan Macdonald, Timothy J. Orr, Jonathan K. Hrica, CASSANDRA L. HOEBBEL, Jason Navoyski, Jennica L. Bellanca

Haul truck fatal accidents and injuries continue to be a significant concern for the mining industry. However, the availability of high-quality training materials continues to be limited. Near-miss incident accounts, if packaged well, could help fill this gap, because for every fatality, there are hundreds of reportable accidents and thousands of undocumented near misses. Researchers from the National Institute for Occupational Safety and Health (NIOSH) collected detailed accounts of 21 near-miss incidents in virtual interviews with mineworkers at surface mining operations across the country. From these interviews, researchers created four simulation videos using the Unity game engine. The simulation videos bring these events to life through first-person retelling and various visual perspectives of actual events. Each video exemplifies a critical safety message and a common haul truck hazard. This paper describes the process of taking narratives and turning them into impactful visual stories using graphic simulation. NIOSH plans to co-release these simulation videos with the Mine Safety and Health Administration (MSHA) to the mining industry to raise awareness and ultimately help reduce haul truck-related accidents and fatalities in mining.

Jun 1, 2023

By Amar Prakash, V. M. S. R. Murthy, VIVEK KUMAR HIMANSHU, Sufal Mehrotra, Ashish Kumar Vishwakarma

Raises are vertical or inclined openings made to connect two levels of an underground metalliferous mine. They are developed using drilling and blasting-based technique or by mechanical means. Raise boring machines (RBM) have evolved in recent years, which provide quicker and safer raise excavation. The penetration rate using RBM has influenced applied thrust. The required thrust to enhance penetration rate with optimal use of energy would be different under varying geological and geotechnical conditions. In this study, the influence of applied thrust on penetration rate using RBM has been investigated. The investigation has been made for two different rock types, amphibolite (AMP) and garnet-biotite-sillimanite-gneiss (GBSG). The numerical simulation model was developed for this purpose using Ansys-Explicit Dynamics. The induced tensile stress under different conditions of applied thrust has been analysed in the calibrated numerical model. The model output shows the power trend between the parameters. The experimental data on penetration rate was also collected along with the respective operational parameters. A statistical analysis has been carried out for the gathered data. The analysis of data also shows a power trend between thrust per cutter and penetration rate in both rock types and hence validates the numerical simulation-based output. Based on the outputs of the numerical simulation and empirical study of the experimental data, the optimum thrust per cutter for excavation in both rock types is in the range of 12–14 tons. The approach used in this study can be helpful for predicting the optimal operational parameters of raise boring machines under different geological/geotechnical conditions.

May 29, 2023

By D Hope, D K. Mukhopadhyay, J D. Harvey

South32 (S32), a globally diversified mining and metals company, is listed on securities exchanges around the world (ASX, JSE, LSE), with its primary listing being on the Australian Securities Exchange (ASX). Chapter 5 of the ASX Listing Rules (Australian Securities Exchange (ASX), 2019b) requires a mining entity to provide a summary of governance arrangements and internal controls with respect to its estimation processes, estimates and reporting of Mineral Resources and Ore Reserves annually. As a global company, it is also important to design and implement all governance processes and internal controls which can be used consistently across the organisation. The three lines model (previously known as the ‘three lines of defense’ model) is employed across South32 to manage risk where the first line (Practitioners) designs, implements and executes processes and controls to manage risk; the second line (Stewardship) identifies material gaps and improvement opportunities in the first line by monitoring conformance with the group requirements, legislative and regulatory obligations. Second line also assists with the development and improvement of core fundamentals based on industry good practise. The third line (Group Assurance) provides independent and objective assurance over the Group’s system of risk management and control. The estimation of resources and reserves for most of the operations within South32 is managed by the Planning function. The estimation process is part of the annual Life of Operation Plan (LoOP). The LoOP identifies and assesses the strategic alternatives for the development of an operation and recommends the preferred pathway based on value and risk. The LoOP starts with opportunity framing and the updated resources as an input and ends with the short-term plan and annual budget (the outputs). Ore Reserves estimates are one of the outputs from the LoOP. All the inputs and outputs follow internal standards and procedures which includes peer review and performance reconciliation. Stewardship (Second line) which is a centralised function has standards in place to ensure compliance to internal controls and external regulatory requirements. This includes assessment of the competence of Competent Persons, technical reviews, independent audits and training in the relevant chapters of the ASX Listing Rules, Guidance Notes and Appendices. Group Assurance (Third line) which reports to the Risk and Audit Committee of the Board of Directors ensures the design and operating effectiveness of the processes, standards and procedures associated with the estimation and reporting of resources and reserves. While the level of scrutiny has a different intent for each line in the three lines model, the overall purpose is to achieve a consistent outcome across the organisation

May 24, 2023

By D A. Sims

This paper outlines the contributing factors to a series of erroneous Mineral Resource estimates which led to considerable loss, including significant reduction of mine life and consequently a large write-down of asset value. The error prompted divestment of the mineral asset in the short-term by the owners, a major mining company. There were multiple and complex contributions to the result: • The mine was undergoing a transition in the deposit geology with increasing depth that was not accommodated in the models. Early indications of the geological transition in initial drilling were generally unrecognised in resource modelling. The shortcomings of the models became apparent with increasing infill drilling and subsequent production reconciliation. • There was a lack of recognition of, and confidence in, site-based input and skills by corporate technical management. The site had a reputation internally for over-delivery to plan early in its life and that supported the anticipation of ongoing metal delivery into the mine plan by management. • A corporate lack of confidence in site being able to adequately domain the mineralisation led to the use of a CIK domaining process, rather than one which was geologically based. This domaining process led to gross over-statement of mineralisation trends reflected in the subsequent OK estimate. • Timelines on the outsourced estimation process were so short that validation was not possible. Obvious errors in the estimate versus data were not able to be used to correct the issues and the site’s Competent Person sign-off occurred without adequate checks. This case study is presented to reinforce the concept that Mineral Resource estimates are not solely based on the ability of the Competent Person to satisfactorily guide the process. There are usually multiple complex issues in the estimation process which need to be recognised and considered in judging reconciliations of model to actual.

May 24, 2023

By W Patton

Investment decisions in the mineral resources sector are made on the basis of an assessment of the economic potential for a mineral deposit. Given the supporting information for the location, scale, and quantity of the commodity of interest, miners and investors aim to make risk-informed decisions when considering further investment. The objective of resource classification is the synthesis of various types and quantities of geologic information used in resource model construction to assign confidence categories to the estimated mineral resources, which can then be used to support informed economic decisions. In this paper a risk-based classification scheme for iron ore mineral resources using conditional simulations is presented. The method involves categorisation of each block according to a confidence level, considering expected recoveries from a kriging model over mining production volumes. The realisations of the simulated model are used to assign risk-based confidence categories to zones of the ore deposit. One motivation for this work is to assess the sensitivity of the scheme to geologic uncertainties. Specifically, that which uncertainty in the layout of mineralising alterations and weathering overprints influence variabilities of associated rock properties and the likelihood of obtaining expected ore recoveries. It is shown these risks have material implications for a project’s economic potential. How the scheme can be extended to the grade control context and the value subsequent grade control activities is also quantified.

May 24, 2023

By L Bertoss, D Carvalho

In the last decade, the use of advanced implicit modelling software/algorithms in mineral resource workflows has become a best practice in the mining industry. In most cases, these workflows can easily replicate the level of detail of explicitly modelled geometries, even for very complex deposits. These techniques are flexible and can produce fast results since software is responsible for generating 3D surfaces and solids based on geological and interpretation data. Nevertheless, depending on how unique and complex some deposits are, intense manual editing and input are required to honour the geological context and produce the desired outcome. The current geological modelling workflow at George Fisher Mine (GFM) is based on the semi-automatic built-in tool that generates stratigraphic sequences (stacked lithology layers) based on logging and mapping data. This tool (stratigraphic sequence from Leapfrog Geo™) works for the majority of areas in the mine but fails to capture observed mineralisation pinch-outs in operational areas and at extrapolated boundaries of the deposit. These pinch-outs have the potential to negatively impact grade forecasts if not resolved manually. Using built-in software tools only, the alternative for a more accurate model is to generate each individual layer and adding tens of thousands of manual interpretation points to honour pinch-outs (based on the amount of existing drilling in the mine and number of layers). This approach would require an estimated minimum of two to four years of a full-time employee (FTE) to be exhaustively completed. This study presents an automated approach to generate pinch-out points using a set of Python scripts that only take a few minutes to run. The newly generated points are then combined into the commercial software workflow as interpretation points, honouring observed pinch-outs. The remarkable time difference between approaches removes chance of manual errors and allows mine geologists to spend valuable time in validation and testing of scenarios, ensuring they are more representative of the deposit’s geology.

May 24, 2023

By I Sucholutsky, D M. First, D Mogilny, F Yusufali

Machine learning is creating value in all facets of the mining industry, from exploration to production. The authors provide an accessible, high-level introduction to artificial intelligence (AI), machine learning (ML), and deep learning (DL); the latter being widely recognised as one of the most powerful forms of ML. In particular, the authors will introduce deep learning models known as convolutional neural networks (CNNs), how they are applied, and the economic considerations necessary for determining when DL may be the right solution to de-risking complex block modelling problems. The authors present preliminary results from the mineral resource modelling study of the Jundee orogenic gold deposit, Yandal belt/gold province, Western Australia. The primary goal was to identify the direction and location of the narrow gold veins more accurately and demonstrate how non-linearly correlated elements are used as direct inputs to the resource model to assist with the target element’s grade prediction. This demonstrates that: (1) existing techniques for finding correlations between assayed elements do not adequately reflect the complex geology of the asset, (2) nonlinear correlations that are difficult to model as simple mathematical functions are representative of geological patterns in a deposit, and (3) non-linearly correlated assayed data, fed as inputs, increase the performance of the resource model as reconciled through blind tests. To conclude, the authors hypothesise that the patterns represented by the DL block models may be revealing the results of overprinting geological processes that generated mineral deposits. For example, the primary hydrothermal processes that deposited metals created depositional patterns that become particularly complex as a result of being overprinted, in part or in whole, by secondary physicochemical processes. This may explain why non-linear geochemical relationships have the capacity to generate more accurate block models of mineral deposits.

May 24, 2023

By A A. Latscha, D O’Connor

Increasing orebody complexity, restrictions in ground access, and longer lead times for disturbance approvals, have generated the need for the Resource Development Team within Rio Tinto Iron Ore (RTIO), to explore optimised drill design techniques that deliver resource conversion value while maximising program outcomes. In response to this challenge, the Team initiated a case study to produce an AI assisted/designed drill program using a non-machine learning AI. The case study involved the assessment and implementation of an AI generated drill program at one of RTIO’s Pilbara iron ore deposits, located in the Hamersley Province of Western Australia. The Mineral Resource is currently classified as 100 per cent Inferred. Access constraints inherent to topography, and the presence of exclusions zones have prevented adequate drilling coverage, resulting in lower resource confidence and a poor definition of the orebody extents and geometry. The drill campaign, planned in Q1 2023, needs to consider access constraints, complex topology and the limitations related to additional ground clearance, while addressing the requirement of improving orebody knowledge. The drill plan had to address two objectives. The first and main aim of drilling was to upgrade the Resource Classification to allow for possible conversion to Ore Reserve. The input for this objective was a volumetric representation of the areas currently not meeting pre-defined quantitative Resource Classification upgrade criteria. The second objective was to better define the orebody extents and geometry. For the second objective, the input to the drilling optimiser was a volumetric representation (blocks) of the areas of high uncertainty in the mineralisation/waste boundary, which were defined using an indicator conditional simulation technique. The drilling optimiser output was a range of compliant drill plans. A set of KPIs based on economic and orebody knowledge criteria were used to assess the plans and to select the most optimal drill design to be drilled in 2023. The geology and management teams were able to make better informed, objective decisions using the trade-off between cost and orebody knowledge gained. As part of the assessment, the AI generated plans were compared to our current planning practises. The AI assisted plans, when gauged against the project KPIs, showed clear and measurable improvements in both meeting project objectives and in managing operational risk.

May 24, 2023

By H Arvidson, V Chamberlain, J Joughin, N Pollock, F Cessford, T Flitton, T Rowl

Environmental, social and governance issues (ESG) have become a defining feature in the marketplace to differentiate preferred investments. With the sustainability commitment and reporting landscape anticipated to evolve exponentially, it is now imperative to rapidly develop the approach taken by mineral companies to adequately identify and address ESG risks and opportunities in the reporting of Mineral Resource and Mineral Reserve (MRMR). MRMR cannot be effectively reported as technically and financially assured and realistically executable, if ESG is not integrated into the strategy, business model, input assumptions and process that defines and drives robust MRMR public reporting. Regulatory reporting codes across the globe are presently in various stages of being updated and modified to ensure ESG factors are appropriately covered as a key part of diligent and transparent disclosure. Security exchanges are making it clear that companies must not omit ESG risks from reports to investors. This paper discusses associated challenges for MRMR reporting and suggests avenues for improvement. Key themes include: the importance of procedure rather than prescription and checklists; how ESG criteria impact Modifying Factors and determination of Reasonable Prospects for Economic Extraction (RPEE); the need for financial models to account for material ESG commitments; the uniqueness of each mineral asset; the need for education, upskilling and accreditation of both ESG experts about MRMR reporting and equally Competent Persons in ESG matters; and the need for clear and balanced reports that meet the needs of end users. (RPEE is adopted here for simplicity and consistency, recognising that some reporting codes still include ‘Eventual’ in the term (ie RPEEE). Whilst RPEE and RPEEE are subtly different the intent is to point to the process of assessing ESG factors in determining reasonable prospects.) The principles of transparency, materiality and competence remain paramount when considering the impact of ESG matters on MRMR reporting, and this necessitates an inclusive, cohesive, and integrated approach to assessing ESG issues to ensure the necessary expertise and diligence is applied.

May 24, 2023

By D Clarke, I Minniakhmetov

The Olympic Dam deposit is truly a world-class IOCG-Ag deposit, the world’s fourth largest deposit of copper and the world’s largest known single uranium deposit. Traditional and non-traditional methods have been used to accurately model the geology and mineralisation of the Olympic Dam deposit. Conditional simulation models have long been used as the most robust method for estimating risk and uncertainty in mine planning decisions at other mines around Australia and the world. There are many challenges associated with simulating the Olympic Dam deposit at a selective mining unit size sufficient for underground mine planning purposes. These include the size of the deposit, resulting in hundreds of millions of grid blocks; the disseminated nature of the zoned sulfide mineralisation. And lastly the direct relationship of the relative abundances of the sulfide mineral species that are crucial to the Olympic Dam smelter performance. Several geostatistical techniques have been utilised in the workflow for the Olympic Dam Conditional Simulation model to address these challenges. The key techniques are: • Projection Pursuit Multivariate Transform to de-correlate the main elements before simulation. • Pluri-Gaussian implicit boundary simulation method to simulate the mineralisation domains. • Spectral simulation method of de-trended and de-correlated attributes with account of local varying variance. The resulting conditional simulation models have been validated against histograms, grade-tonnage curves, cross-plots and assessed for variogram reproduction. This paper presents how the final conditional simulation models compare to benchmarking models created using alternate estimation techniques of ordinary kriging and local uniform conditioning. It also presents a validation process using historical samples to test final estimate accuracy of the simulation models.

May 24, 2023

By M P. Murphy, C M. D Barton

When developing a new underground mine, the geological interpretation that guides the mineral resource is crucial to the preparation of a reliable ore reserve. In preparing a robust geological model to underpin a resource estimate, practitioners must weigh the comparative risk of accepting a relatively wide-spaced drill hole pattern, versus a more close-spaced pattern that ensures a high local geological confidence for mine planning but may have an exponentially increased time and monetary cost. This paper details the authors’ investigations into the geological uncertainty of IGO’s Odysseus Deposit, which is approximately 645 km north-east of Perth, Western Australia. At Odysseus, the komatiitic nickel sulfide mineralisation is irregularly cross-cut by nickel-barren pegmatites that have intruded and offset its thick ultramafic orebodies. These pegmatites generate significant uncertainty in the precision of Odysseus’ resource volume and tonnage estimates, as well as the subsequent quantification of pegmatite mining dilution in its ore reserve. To quantify the geological uncertainty in the pegmatite interpretations, IGO’s mineral resource practitioners prepared several geological risk studies over the Odysseus North lode, which is the lode most affected by the pegmatites. These studies included categorical conditional simulation of the pegmatites, preparing implicit geological models with alternative algorithms, trialling a machine learning application to prepare a maximum likelihood geological model, and finally assessing the early results of the pre-production close-spaced drilling to these different models. To assess the precision of the different single-outcome models, the authors’ compared the estimated pegmatite content of each model to the range of possibilities modelled by categorical conditional simulation within the planned stopes at Odysseus North. An estimation confidence score for each modelling method was then prepared for each alternative single-outcome modelling method. From these studies IGO concluded that a close-spaced drill pattern is essential at Odysseus, supporting the view of the Competent Person in 2017 who proposed a 25 m drill spacing in areas affected by pegmatite which had been partially classified as Inferred.

May 24, 2023

By Mustafa Kumral, Yu Cheng Yang, Zhixuan Shao, Young Bin Moon

Since the discoveries of favorable deposits are becoming increasingly difficult, mining operations shift to lower grade and deeper deposits. The viability of these operations is sensitive to many factors, such as commodity prices and operating costs. Given that a mining corporation has no power to set prices, the focus is directed on minimizing the operating costs. Underground mining operations require a network infrastructure, including shaft, ramps, declines, levels, cross-cuts, raises, winzes, and adit. The design of this network is a costly process. As such, it has a significant potential to reduce development and haulage costs. Furthermore, network design is a continuous process along with development, production, and maintenance throughout mine life. Under the constraints of the turning radius, the gradient, and the obstacle avoidance for haulage network of underground mines, this paper first demonstrates network design and optimization approaches using Dubins path combined with the Hierarchical Density-Based Spatial Clustering of Applications with Noise (HDBSCAN) algorithm. A threshold-based model is developed, providing viable solutions to the network design when the number of declines is high. Furthermore, a three-dimensional Rapid-exploring Random Tree (RRT) algorithm combined with Dubins path is employed as a heuristic solver for obstacle avoidance purposes in the network. Various case studies are conducted to show the applicability of the proposed methods.

May 24, 2023