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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 D Clarke, I Minniakhmetov

This paper describes the application of the SBRE framework to model the Olympic Dam deposit, one of the largest copper and uranium deposits in the world. Geostatistical simulations are the best practice for quantifying uncertainty in the mineral value chain and estimating resources. However, these simulations are currently undertaken on an ad hoc basis in the mining industry due to the high requirements in computing resources and capabilities in advanced geostatistics. The SBRE project provides a standard framework to test, build, and run conditional simulation workflows, which has been applied to the Olympic Dam deposit. Conventional geostatistical methods face challenges when modelling the Olympic Dam deposit, such as non-stationarity, non-linear correlations, and a large number of grid blocks to simulate. To address these challenges, a combination of methods was used, including projection pursuit multivariate transform, trend-residual decorrelation, pluri-Gaussian simulations, and turning-bands simulations. Various tools and applications were used to build the model, including in-house developed applications, Autovariogram software (Varify), and the RMSP python library. All computations were accomplished on the AWS cloud using the EC2-Batch service. The final set of simulations was validated using various methods, such as grade-tonnage curves, histograms, swath plots, and variogram reproductions, as well as validation using historical samples back-testing. The study highlights the importance of an automated, modular, and scalable framework in the development of conditional simulation workflows and describes the learning gained from trials of different combinations of methods and software

May 24, 2023

By C Artica

Two quantitative methods for Mineral Resource classification have been applied to a copper skarn deposit beneath a large open pit that is mining a world-class porphyry complex. A drill hole spacing study (DHSS) using the single block kriging method (SBK) and a conditional simulation method (CS) were applied to the skarn deposit and the results compared. Inputs to both processes included the proposed mining rate and stope designs to estimate the likelihood of achieving grade and metal production targets. Mineral Resource classification of the deposit considers the relative precision of tons, grade and metal predictions over quarterly and annual production periods. These relative precision estimates are calculated at 90 per cent confidence interval (CI). The SBK method represented the production period as a single large block. Kriging estimates were performed in the large block for various synthetic drill hole grids, and the estimation errors derived. The error was assumed to be normally distributed due to the large block size and quantity of samples, allowing CIs to be deduced. The CS method followed a conventional sequential Gaussian simulation workflow where grades were simulated with a 5 ft × 5 ft × 5 ft grid node spacing inside mineralisation domains. Each realisation was then averaged up to monthly production volumes represented by a combination of designed stopes, and the coefficient of variation (CV) for the averaged grade was calculated. CI on the relative precision of grade predictions were then deduced from the CVs. The two methods produced similar results; despite being calculated independently. CS results were used to report uncertainty in the proposed life-of-mine plan and highlight areas for additional drilling. SBK results were used as the basis for Mineral Resource classification as this method has been previously applied to the skarn deposit.

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 M Bond, R R. Hargreaves, G W. Booth

There are numerous causes of speculative mineral resource and reserve inflation. Traditionally, these are linked to issues of data accuracy or misinterpretation, the use of overly optimistic estimation parameters or assumptions, an absence of independent expert verification, or the simple pressure to increase company value, covert or otherwise. Owing to its subjective nature, classification of resources and reserves remains an opaque process. Of necessity, Competent Persons rely on personal heuristic interpretations, ideally underpinned by appropriate estimation and classification experience across commodity and deposit types. Whereas independent verification of individual resource and reserve statements remains impractical, publicly available data can be interrogated for potential category inflation, particularly when viewed with exploration expenditure statistics included in annual company reports. Abrupt changes in category tonnages and market capitalisation without concomitant expenditure can aid in outlier detection. Consequently, a comparison of common exploration and resource reporting parameters offers a basis for risk assessing classification robustness, over time. In this introductory study, an analysis of globally listed companies was undertaken over a multi-year period, examining base and precious metal projects in both preproduction and operational asset classes. From these, a series of exploratory decision tree trigger points were generated against which target companies were anonymously identified and risk-ranked.

May 24, 2023

By P Dowd, A Adeli, C Xu, X Emery

Geometallurgical modelling is increasingly being incorporated into mineral resource modelling and estimation as a means of increasing efficiency, decreasing operating costs and reducing risk in mining operations. Traditional geostatistical workflows for geometallurgical modelling face several difficulties, in particular, related to the non-additivity of process response variables, to highly heterotopic data sets and/or to preferential sampling designs, all of which may explain why most attempts to estimate geometallurgical response variables from assay data and mineralogy are still based on statistics and machine learning. The aim of the work presented here is to demonstrate the applicability of geostatistics to estimate copper recovery from copper sulfide ores at the Prominent Hill Iron Oxide Copper-Gold (IOCG) deposit in Australia. As recovery is non-additive, the preferred workflow is the joint estimation of the masses of metal in the feed and in the concentrate, both of which are additive variables. While the mass of metal in the feed can be estimated from abundant online assay analyses, the mass of metal in the concentrate can only be estimated from a very limited number of laboratory-scale batch flotation tests. Traditional approaches to estimating the masses of metal in the feed and in the concentrate, such as simple and ordinary co-kriging, are described and discussed. A modified version of co-kriging is introduced, which incorporates linear relationships between the mean values of the input variables, in addition to a spatial correlation model. Co-kriging with related means is shown to outperform traditional simple and ordinary co-kriging in terms of precision, accuracy and consistency of the estimates, and offers a practical and efficient tool to deal with highly heterotopic and preferential sampling designs.

May 24, 2023

By J Levett, O Rondon, I Glacken

Reporting Codes are not prescriptive on methodologies to report or classify Mineral Resource Estimation results, but the assessment of risk and uncertainty is required, and is likely to be increasingly important in future Code updates. The 2012 JORC Code indicates that relative confidence in tonnage-grade estimations should be considered for classification, and that there should be a discussion of relative accuracy and confidence levels in the Mineral Resource Estimate. These considerations are also relevant to the drill hole spacing required for various classification categories, along with other geological and data quality criteria. This paper summarises the theory, principles and current practice of various drill hole spacing analysis techniques for both achieving a desired level of resource categorisation and for optimising grade control or resource drill-out costs. The authors provide practitioners with a guide in their use to assess uncertainty and relative accuracy, as illustrated by a number of case studies. While all drill hole spacing studies rely on the assumption of consistency of the continuity model from current to future drilling, the range of methods available provide much more objective outcomes than previously adopted ‘rules-of-thumb’.

May 24, 2023

By A Jewbali, L Allen

At Newmont Corporation drill hole spacing studies are done to support the business in understanding the cost of collecting additional information (with a specific focus on drill hole sampling density) versus the value of additional drilling in terms of resource risk reduction. For the last 20 years drill hole spacing studies have been executed in an effort to answer the following question: What spacing should the deposit be drilled at to achieve a certain level of resource confidence so that when mining occurs the resource model delivers as predicted ie what is the optimal sampling density? The optimal sampling density supports a resource model that provides a sound foundation for mine planning purposes and resource/reserve reporting. At Newmont Corporation drill hole spacing studies are now a requisite for understanding drill data density needs for new deposits and near mine expansions. This paper details the evolution of drill hole spacing studies at Newmont Corporation in terms of methodology and usage.

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 Son Hoang Nguyen, Thanh‑Hai Pham, Duoc Van Tran, Dung Thi Kim Nhu

Apatite ore plays a critical and irreplaceable role in fertilizer production and is being upgraded in quality in northern Vietnam. The old tailing of the Bac Nhac Son beneficiation plant (Vietnam) has a significant apatite amount in the form of coarse unliberated particles. These millions of tons of tailing ore have 6–8% of P2O5 content, which can be retreated to provide fertilizer factories. This work presents the results obtained in recovering apatite from this tailing in the laboratory. By the combination of the processes of classification, preliminary flotation, re-grinding and cleaning in the flotation column, an apatite concentrate of 30.68% P2O5 can be obtained with the total recovery of 37.76% from the initial tailing of 7.56% P2O5. The study results not only provide an appropriate technical solution for recovering the apatite ore from tailing ore but also have outstanding meaningness in the recovery of mineral resources under the context of a circular economy.

May 24, 2023

By Guodong Li, Chenlin Wang, Zibiao Yu, Bo Xu

Abandoned coal mines have many underground space resources, such as roadways, shafts, and gobs. Among them, abandoned roadways are the best gas storage space for underground compressed air energy storage (CAES). However, CAES caverns have high air pressure and strict sealing requirements. Therefore, the stability and sealing of abandoned roadways under high internal pressure must be analyzed. Afterward, the suitability of abandoned roadways used for CAES caverns should be evaluated. In this study, the numerical simulation software FLAC3D was used to calculate the stress, deformation, plastic zone volume, and pore pressure of surrounding rock in an abandoned roadway under 10 MPa internal pressure. The influence of buried depth, surrounding rock grade, and in situ stress state on roadway stability and the effect of surrounding rock permeability on roadway sealing were analyzed. Results showed that the stress, displacement, and plastic zone volume of surrounding rock were affected by high internal pressure when the buried depth was less than 300 m, but high internal pressure had little effect on them when the buried depth was more than 300 m. The suitable range of buried depth was more than 300 m. The optimal choice of surrounding rock grade was I and II, followed by grades III, IV, and V. The optimal choice of in situ stress state was σH > σh > σv, followed by σH > σv > σh and σv > σH > σh. The sensitivity of the stability evaluation parameters was ranked in descending order as follows: buried depth, surrounding rock grade, and in situ stress state. When the surrounding rock permeability was less than 1 × 10− 14m2, the 24-h air leakage rate of the roadway was less than 1%. The suitable range of surrounding rock permeability was less than 1 × 10− 14m2.

May 23, 2023

By Abhishek Kumar, T. G. Sitharam, Surender Singh

The height of tailings pond (TP) embankments is frequently raised to accommodate the ever-increasing volume of tailings released by the mining industries. Excess pore water pressure (EPWP) may develop during the height-raising operations, which can affect the overall stability of TP. This article presents a detailed stability analysis for the embankments of an existing TP, the height of which was increased twice utilizing downstream (D/S) and upstream (U/S) construction techniques. A rigorous two-dimensional transient fully coupled-stress-pore pressure analysis is performed in the finite element-based package RS2 to examine the build-up of EPWP during different stages of construction. Furthermore, an attempt is made to investigate the feasibility of future height raising, with due consideration given to the influence of embankment raising rates. Results from the analysis show a development of higher EPWP within the tailings deposit in comparison to the embankments of TP, indicating the development of an undrained-like condition. The study further reveals that the development of EPWP is highly affected by the rate at which embankments of TP are being raised. A higher rate of embankment-raising results in the development of greater EPWP in comparison to a lower embankment-raising rate, which may lead to the ultimate collapse of TP. Furthermore, based on the stability analysis, the height of existing TP can be further raised by 4 m (two lifts of 2 m height) utilizing the U/S construction technique. A thorough cost and benefit analyses are however required before implementing the results of the current analysis since the storage capacity of TP is reduced while raising by the U/S method.

May 16, 2023

By Vhutali Carol Madanda, FHATUWANI SENGANI, François Mulenga

The first introduction of fuzzy theory in the nineteenth century created room for continuous research and application in various fields. Fuzzy set theory has been globally applied in geotechnical engineering, and research in this field continues to date. The fuzzy inference system is considered to be one of the most popular techniques adopted to resolve some of the geomechanical challenges faced in both surface and underground excavations. This paper unpacks fuzzy theory-based approaches in mine geomechanics with the aim of expanding the innovative application of the same approach specifically in tunnel geomechanics. This aim was achieved by conducting a review of recent successful and unsuccessful applications of fuzzy inference systems in underground excavations/tunnelling geomechanics. Indeed, this review has outlined some cardinal points associated with the ability of the technique to solve complex geomechanics problems. However, the success of the technique was accompanied by a few limitations associated with the methodology. Finally, a future outlook associated with the technique has been established.

May 15, 2023

By Jon Pocock, Ashma Singh

The traditional approach for the beneficiation of South African siliceous sedimentary phosphate ores has been reverse cationic flotation. The robustness of this approach, however, has been a concern due to its sensitivity to parameters such as slimes content, headgrade ( P2O5 and SiO2 content), reagent dosages and conditioning times. The phosphate mineralisation for the ore body under investigation is predominantly carbonate fluorapatite composed of mainly quartz and apatite and minor amounts of chlorite, ilmenite and carbonates. Beneficiation of low grade sedimentary ores containing calcareous impurities, such as calcite and/or dolomite in addition to siliceous gangue, is required to meet the increasing demand; therefore, much research has been carried out to find an alternative technique to beneficiate this material. This paper investigates traditional flotation approaches versus the currently adopted ‘Crago Process’. Comparative results are presented in terms of upgrade potential for the production of concentrate rock for downstream applications. The novelty of the ‘Crago Process’ lies in its double stage approach, i.e. direct fatty acid flotation followed by reverse cationic amine flotation. The Crago process was able to achieve higher upgrades reporting at 32.1% P2O5 compared to conventional cationic flotation only achieving grades of 18.5% P2O5. Furthermore, the recovery gain was 3%.

May 13, 2023

By Carla Da Corte, Kagisego Letsoalo, Ashma Singh

Banded Iron Formations (BIF) are sedimentary rock formations ranging in age from 0.8 to 3.8 billion years and consist of alternating layers of silica and iron. The thickness of the alternating layers varies between and within deposits, with this lithology forming approximately two-thirds of South Africa’s future low-grade hematite resources. The production costs for South African iron ore producers are approximately double that of the largest iron ore producers, namely, Brazil and Australia. This in conjunction with volatile commodity prices, necessitated a cost-sensitive beneficiation strategy for low-grade hematite to sustain the industry and extend life of mine. A BIF sample grading at 44% Fe and comprising predominantly of hematite and quartz with minor amounts of magnetite and goethite was subjected to three fines gravity processing routes to establish the amenability of this sample to beneficiation. To provide flexibility for iron ore producers who still have high-grade resources available, two product grades were considered, namely a 60% Fe product for further blending or a 63% Fe product for direct sales.

May 12, 2023

By H. Y. Sohn

Considering the two most important issues the ironmaking industry faces today, i.e., energy consumption and greenhouse gas emissions, it would be advantageous to utilize the concentrate-size raw materials directly without pelletizing or sintering, especially without the use of coke. This plenary lecture describes two such processes developed at the University of Utah. One is the Flash Ironmaking Technology (FIT) and the other is a moving-bed process for continuous ironmaking with gaseous reduction of iron ore concentrate (MBIT). These technologies are designed to produce iron directly from iron concentrate without requiring pelletization/sintering and cokemaking in two significantly different temperature ranges. They take advantage of the high reactivity of the concentrate particles and will considerably reduce energy consumption and carbon dioxide emissions compared with the current processes. The process of the development from the conception of the idea, to kinetic feasibility establishment, to laboratory flash furnace, and finally to the operation of a prototype facility for the development of the FIT is discussed. The development of the MBIT also started with the formulation of the process concept, followed by kinetics feasibility establishment, and the design of a potential industrial reactor. The results of economic analyses on the FIT are briefly described.

May 12, 2023

By Andreas Dietrich

The development of new techniques in mineral exploration seems to reduce the need of geological field work and mapping: Data collection can now be done remotely by satellites, drones, and tablet-equipped field assistants, while the geologist assembles data sets with 3D software. The interpretation of complex data sets can be assisted by machine learning and artificial intelligence (ML, AI). Instead of loosing relevance, geological mapping and logging are now even more essential to provide the interpretive framework essential for the correlation, validation, and integration of huge amounts of data, but will not be replaced by new technologies. Geological truthing lies in the field, with experienced geologists conducting this work while training and mentoring young professionals.

May 10, 2023

By Robert Gordon, Leduar Ramayo

This paper reviews the application of the magnetotellurics method for deep earth imaging, specifically its recent use to better understand original mineral emplacement processes. Resistivity information from newer innovative applications of the technology for nearer surface imaging also provides valuable insights into near surface structure, which in some cases has led directly to new discoveries.

May 10, 2023