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By J R. Ruiseco, D La Rosa, L Julian, W Hunt

The DeGrussa copper-gold deposit is located 900 km North of Perth. Copper-gold bearing massive sulfide lenses occur in lower greenschist facies meta-sedimentary and mafic volcanics of the Bryah Basin. Regional folding, faulting, and tilting of the stratigraphy primarily occurred during the Capricorn Orogen (Johnson, 2013). The Shiraz Fault and Merlot Fault are regional oblique-sinistral faults that offset the DeGrussa massive sulfides lenses into three fault blocks by ~350 m and ~120 m, respectively. A network of deposit-scale brittle-ductile faults splay from, and in one example are cut by, the Shiraz and Merlot faults. This results in localised ore displacement, selvage alteration and degradation of the rock mass integrity. Historically, only the Shiraz and Merlot Faults were modelled and validated during mining and grade control. The requirement for a comprehensive structural model became more relevant as mining became advanced and confining stresses on local rock mass became more complicated. The DeGrussa Structural Model has been developed to delineate areas of structural complexity and is an important tool in mitigating rockfall risk through well informed technical design. During this process, every accessible excavation was walked and structurally mapped. New workflows in Leapfrog Geo and new technology, including an app that runs on mobile phones streamlined the validation process. Drill hole orientation was a limiting factor during validation. At the time of writing this submission, the DeGrussa Structural Model consists of 34 faults, and is now an important tool for the Technical Service team when developing mine plans and schedules. Applied structural geology is often seen as exclusive to those with a PhD in the field. Faults at DeGrussa have been modelled and reconciled by a Mine Geologist and Geotechnical Engineer, using first principles geological characterisation. This is a simple process that demonstrates any geologist can contribute to a structural model, provided they understand the fundamentals of unbiased structural measurements and consistent record of observation

Mar 22, 2022

By M Watson, A V. Engelbrecht, E Murray-Hayden

Whereas mine reconciliation is a well-established month-end process for most modern mining operations, the resource sector has yet to endorse uniform reporting factors against which model accuracy and metal recovery can be formally assessed. Logically, any comprehensive reconciliation framework should facilitate comparison between period reserve, mine and mill and production figures. Historically, Parker’s F Series ratios (Parker, 2012) are often used in some form by mine operators, although they are rarely shared externally, as formal definitions have yet to be accepted. This paper presents a structural extension to the reconciliation process, wherein resource ratios (R Series factors) are used to quantify the long-term impact of the information effect, together with dilution and ore loss. A case study from the El Limón Guajes (ELG) Mine Complex in Mexico is used to demonstrate how an R Factor Series can be implemented to facilitate operation optimisation, over and above conventional F Series reconciliation treatments. This approach is applicable to any mining operation.

Mar 22, 2022

By N Anderson

The world-class Golden Mile gold deposit in the Eastern Goldfields of Western Australia is part of the Kalgoorlie Consolidated Gold Mines (KCGM) operation, which is wholly owned by Northern Star Resources Limited. Current mining operations across the Golden Mile is dominated by the large Fimiston Open Pit, which is over 4 km long, 1 km wide and 600 m deep. It is part of a larger mineralised system that stretches over 8 km and includes the Mt Charlotte Underground Mine, which is also operated by KCGM, as well as numerous historical open pit and underground mines. This mineralised system has been continuously mined for over 125 years and is set to continue well into the future. The Golden Mile deposit is in the Norseman Wiluna Greenstone Belt which is made up of a series of mafic volcanic and sedimentary rocks that have been structurally deformed and intruded by granitic rocks. There are two main styles of mineralisation across the Golden Mile. Firstly, the Fimiston style, which consists of shear hosted Golden Mile lodes with abundant sulfides and tellurides and secondly, the Charlotte style that comprises younger stockwork veins. Fimiston style mineralisation is the primary style of mineralisation within the Fimiston Open Pit. Historically, in excess of 3500 m of underground development and over 755 stopes were mined prior to the consolidation of the area and the commencement of Fimiston Open Pit operation. Old underground workings, known as voids, are either empty or backfilled and extend to more than 1.2 km below surface. Although they are a routine part of mining operations at KCGM, voids pose a significant challenge for the geology team in terms of planning and executing exploration and grade control drilling, geological modelling, grade and tonnage estimation, drill and blast design and execution, marking up ore block designs, mining, and reconciliation. This paper will discuss the various challenges faced by the geology team due to the presence of voids, solutions used to overcome some of these challenges and the results of these activities.

Mar 22, 2022

By N Pranoto, E Lawell, T Dean, M Grant

The Goonyella Riverside Mine is located 30 km north of Moranbah in Central Queensland, Australia. Recent mining activities have exposed the north–south striking Kenya and Zimbabwe thrust Faults. These faults vertically offset coal seams by up to 25 m and locally thicken coal packages through imbrication of coal seams. The presence of back-thrusts add to the geotechnical complexity of maintaining highwall stability. The Kenya and Zimbabwe Faults have provided multiple challenges to the mining operation, with an unplanned additional 240 kt of coal tonnes being mined from imbrication of coals seams or from the refinement to local scale geological models. These additional coal tonnes have been either identified during the mining of the coal seam or just prior to overburden removal above the coal seam. These faults can also negatively impacted highwall stability with highwall failures, lowering the overall slope angle for pit designs and increasing stand-off distances for hazardous highwall conditions. Unmanned Aerial Vehicles are used to scan exposed highwalls and enable geological mapping via high-quality 3D images. Measure while drill data from drill and blast rigs can provide local-scale intersections of the faults and coal seams. Mine Geologists utilise these and other data sets to create localised geological models refined position of the fault planes and coal seams. These models are utilised by relevant mine site teams to ensure the safe and efficient mining of coal around these faults.

Mar 22, 2022

By H S. Pescini

A material aim when feeding ore blends into a processing facility is to reduce the variability of the properties of the feed material and to maximise the output, or throughput. At the Mining Geology conference of 2019, we presented a paper on optimal blending of coking coal given geological variability. The paper introduced integer-programming techniques to both maximise value and minimise feed or product variability. We discussed an application where the geological uncertainty is characterised using a normal distribution and exact solutions are readily obtainable using second order conic constraints in the mathematical model. Geological uncertainty is not always normally distributed, many properties will be characterised as log normal or some other skewed distribution. For example, copper can be some form of lognormal and Fe in Iron ore has a left skewed distribution. In this paper, we discuss some distribution free techniques to optimise the blends of plant feed or output given a quantified geological uncertainty. We discuss the sample average approximation method and how to set-up and apply the method to an ore blending problem. Evaluating a case study demonstrates that the explicit use of non-normally distributed geological uncertainty can better optimise feed into an ore processing facility and potentially add significant value. The approach is equally applicable to all mining and processing operations that blend material into a processing facility or directly into a saleable product.

Mar 22, 2022

By C Laming, P M. Hetherington, F A. Pym, M P. Murphy, K E. Crook

Reconciliation is a powerful tool used by mining operations to compare the mass and grade of ore produced with what was estimated before mining. The primary objective of reconciliation is to verify that the estimated planned metal production is achieved during processing, allowing issues to be identified for which adjustments can be made throughout the mining value chain to improve recovery and maximise efficiency. Traditionally, the mine plan is based on estimated mine grades using sampled exploration drill hole or blasthole grades. Reconciliation discrepancies between the mine plan and mill are common due to such factors as insufficient or non-representative sampling, poorly conceived models, or unrecognised blast movement. MineSense Technologies Limited® (MTL) has developed an X-ray fluorescence (XRF) sensor-based ore classification system that is installed on mining equipment to provide real-time grade estimates of run-of-mine material at bucket, truck, or belt-scale. Bucket level grade estimates provide insights into grade variations at the mine face that were never before available. This data set eliminates some of the leading causes of reconciliation discrepancies and enables tracking of tonnages and grades from the mine face to the processing plant at bucket resolution with confidence. Bucket-by-bucket grades at the mine face enable dynamic optimisation of the mine plan to stabilise the mill feed grade through blending of mine and stockpile loads. Beyond stabilising feed grade, Mine to Mill reconciliation combined with the full XRF spectrum response can generate proxy relationships to ore characteristics like hardness and recovery. These properties can then be predicted at the mine face, enabling further optimisation of the downstream mill feed, not only for grade, but also for power and water consumption, reagent addition, and recovery. This paper presents the benefits of MTL technology for grade reconciliation and mill performance optimisation at a Cu Mine in BC (Canada).

Mar 22, 2022

By N Anderson

With traditional grade control processes, geological models are created by geologists at the completion of the data collection stage and wireframe construction is closed off at a set date to allow for time to complete the estimation process. Any issues identified at earlier stages or the addition of new data requires the estimation process to be started again. Alternative interpretations are explored only if time allows and often in a limited fashion. An alternative workflow has been developed at the Waihi Underground Gold Mine utilising Leapfrog Edge and Seequent Central. Geological and grade control models are created, dynamically linked, and saved as separate branches. A project geologist is able to work on the grade control model and a mine geologist on the geological model simultaneously. This allows for a non-linear modelling workflow with continual review and feedback. The introduction of new data can occur right up to the model due date, with data collection, validation, alternate interpretation, and review happening incrementally. Models are categorised and stored in Seequent Central according to project status. An approved version of the geological model and grade control estimate are uploaded at the time of release and transparently capture all data used at a point in time, as well as the review process. Dynamically updating models for grade control has reduced turnaround time while increasing accuracy and quality. Estimates of individual domains are vastly improved from being able to rapidly evaluate the effects of model parameter changes in real time and 3D. Development and stope design directly benefit from these streamlined processes, with higher quality, timely production occurring as a result.

Mar 22, 2022

By D Reid, J McKibben, M Noppe

International mineral disclosure standards and guidelines aligned with the CRIRSCO (Committee for Mineral Reserves International Reporting Standards) template were developed to inform stakeholders about the relative accuracy and confidence levels of publicly reported information and to support investment decisions, particularly when advancing projects through different development stages. The traditional stages range from early to advanced exploration, through pre-development (with Mineral Resources and pre-feasibility and/or feasibility levels of study) before the final development stages, where a decision to proceed with construction or production (or both) is made. The traditional definition of Mineral Resource and Ore/Mineral Reserve classification categories and techno-economic study levels (including Preliminary Economic Assessment (PEA), Scoping Study (SS), Pre-Feasibility Study (PFS) and Feasibility Study (FS)) were defined with pre-development project assessment in mind. As such, these definitions are not necessarily well aligned to the reporting structures required by operating mines which need to consider a range of timelines spanning short to long-term operating conditions. However, the same terminology and definitions are used, or expected to be used, by both project developers and mine operators when reporting resources, reserves and techno-economic study outcomes. This paper discusses how various stakeholders in the minerals industry (including competent/qualified persons, mining company leaders, investors, lenders and regulators), generally interpret the definitions of Mineral Resource and Ore Reserve categories in terms of the relative accuracy of the estimates, their link to techno-economic study levels and their contribution to life-of-mine (LOM) schedules. The paper examines the degree to which mining companies recognise, and apply, enhanced operational knowledge to reflect short-term views of the relative accuracy and confidence levels associated with publicly reported Mineral Resource and Ore Reserve estimates and forecasts. Furthermore, this paper explores how this knowledge is applied to support ongoing Mineral Resource, and particularly Ore Reserve, generation and reporting. This paper is informed by public data and responses to an internal survey prepared by the authors and completed in 2021 by several mining companies.

Mar 22, 2022

By F Faraj, M Pal, M Haest, M Bradshaw, H Lang, K Hume

MineSense Technologies Ltd. is revolutionising grade control at mining operations by installing ShovelSense® sensors on buckets that measure the grade of every load before it is dumped in the truck. This allows the mine to exploit grade variations at a resolution that was not available before, reducing the amount of ore loss to the waste stream and removing waste from material destined for processing. These changes dramatically improve the profitability and sustainability of mining operations. ShovelSense relies on X-ray fluorescence analysis of the rocks as they flow in the bucket and is integrated with fleet management to direct the trucks to the right destination. Lab simulations of ShovelSense measurements on porphyry copper ores show correlations between predictions and lab measurements at 0.98 r-squared with a coefficient of variation of 10 per cent. Visualisation of copper grade predictions in three dimensions shows a reasonable match with the dig plan, but with local changes in the ore-waste contact due to more accurate contact identification, related to blast movement and other mining factors. Correct delineation of these contacts ensures ore trucks are not sent to the waste dump and waste trucks are diverted from the crusher, creating enormous value for the operation and the environment.

Mar 22, 2022

By B Haase, R Saha

Conditional simulation (CS) has been extensively used in metal industry to assess uncertainty of geo metallurgical variables to build robust distributions around grade tonnages across different time horizons. Coal’s entry to nonlinear stochastic modelling is relatively new and this paper summarises the work done at BHP to enable its practical usage from production time frames to Life of Asset planning. CS in coal using Sequential Gaussian Simulation (SGS) is used to understand resource confidence around specific variables within pre-defined boundaries of spatially continuous domains for each coal seam. The variation between simulations for a given parameter reflects uncertainty. This paper demonstrates the use of CS to profile resource based upon agreed seam/parameter uncertainty thresholds which affect planning, forecasting, extraction and inform identification of key production risks and defining mitigation strategies. The end goal is to de-risk long-term plans by optimising infill data collection and improve stability in short-term planning through increased understanding of confidences locally rather than at global resource definition stages. The paper also briefly discusses the use of automated workflows and systems to minimise the time spent on the process to enable use in decision-making.

Mar 22, 2022

By E J. Hill, F Huang, A Otto

Geochemical data from drill core samples is used in mineral exploration to enable geologists to understand subsurface geology. However, it is challenging to analyse these data sets rigorously and consistently. Manual data interpretation relies on the knowledge and experience of logging geologists. When multiple geologists are involved, it is possible to introduce inconsistencies in logged lithology type and scale of logging (‘splitters’ versus ‘lumpers’). Machine learning (ML) is a powerful tool for analysing high dimensional data (ie data with many variables) and large data sets (ie data with many samples). However, ML methods applied to drill hole samples do not incorporate spatial information and this can result in high misclassification rates and small-scale ‘noisy’ results. We demonstrate the use of multiscale spatial analysis (wavelet tessellation) as a pre-ML step to analyse spatial information. This step helps reduce misclassification and filter out unwanted small-scale variation in the data. In an experiment, we used wavelet tessellation and supervised ML to predict litho-geochemical rock types from geochemistry data. The data set is from the Valhalla uranium deposit near Mount Isa, northern Queensland. First, geochemical knowledge and statistical analysis was used to select appropriate geochemical elements for litho-geochemical classification. Second, the elements were processed using multiscale spatial analysis. Third, we trained a Random Forest model with the data set and found that the model performs worse in predicting rare rock samples than common ones. We applied over-sampling and down-sampling methods in aim to overcome this issue. As a conclusion, the combination of multiscale spatial analysis (to define rock unit boundaries) and Random Forests (to classify rock units) is a good method for rapid and accurate analysis of drill hole geochemistry.

Mar 22, 2022

By J. R. R. Bowling, A. McFadden, M. Francoeur

The abstract discusses the increasing use of extensive duct-fan systems in underground hard-rock mine development. It highlights the challenges of designing these systems, particularly the risk of partial vacuum and the need for careful booster fan positioning. The paper explores factors influencing the design of these systems, including component limitations, operational wear margins, and power constraints. It also defines the concept of partial vacuum and its impact on ventilation ducts. The authors propose an algorithmic approach for specifying the location and blade pitch of in-line booster fans to prevent system failure.

Mar 17, 2022

By Brian Y. Lattimer, Kray D. Luxbacher, Jonathan L. Hodges, Manuel J. Barros-Daza

The abstract discusses the importance of predicting fire response time (the time before conditions become untenable for firefighters) in underground coal mines. It introduces a data-driven approach using artificial neural networks (ANNs) to predict response time and fire size based on measurable parameters like CO concentration, mine geometry, air velocity, and time since fire detection. The approach was tested using simulations from fire models (FDS and FSSIM), showing promising results for real-time predictions during mine fires.

Mar 6, 2022

By T. Doshi, S. Ennis

The interactions of mineralogy, chemistry and mechanics in an ore concentrator are highly complex, so it can be particularly hard to measure the impact of a specific plant change. This paper describes a method for modeling a baseline metal recovery so that the value of a major process improvement can be measured. This method only considers variables that cannot be optimized, such as mineralogy or equipment availability. Linear regression, random forests, extreme gradient boosting (XGB), and simple two-layer neural network models of process value were tested as candidate baseline model types to assess the impact on throughput and recovery in a copper concentrator. XGB performed the best in terms of accuracy for both throughput and recovery models. Using an XGB model of nonoptimizable process variables provides an accurate, dynamic baseline that can be compared with continuous production data to determine the value added by major concentrator improvements in real time.

Mar 2, 2022

By Y. Chen, D. He, J. H. Potgieter

The demand for rare earth elements (REE) is increasing rapidly owing to the emergence of new cleanenergy and defense-related technologies. China’s dominates the world production of REE. In this paper, we review the ore characteristics of four typical REE deposits in China and discuss the conventional beneficiation techniques, including gravity and magnetic separation, flotation, and hydrometallurgical processing of these ores. Some of the latest laboratory findings and industrial applications, as well as the development of novel reagents for REE processing in China are presented. The REE beneficiation technologies developed and employed in China could constitute a good case study for many other emerging projects being explored around the world.

Mar 2, 2022

By L. Schernikau, W. H. Smith

Oil, coal, and gas account for approximately 80% of global primary energy, but only a portion of total airborne CO2 eq (approx. 35% at GWP20 to 65% at GWP100), even though they account for 95% of total measured CO2 emissions. The benefits of these energy sources, as well as their related costs, are not all incorporated in current energy policy discussions. Global greenhouse gas policies must include documented changes in measured airborne CO2 eq to avoid spending large amounts of public funds on ineffective or sub-optimal policies. The authors examined airborne CO2, which is less than half of emitted CO2, as well as reported CH4 emissions and the global warming potential of CH4 as published by the IPCC for coal and natural gas. The surprising conclusion is that surfaced-mined coal appears ‘better for the climate’ than the average natural gas, and all coal appears beneficial over LNG. Therefore, current CO2-only reduction policies and CO2 taxes are leading to unintended consequences and the switch from coal to natural gas, especially LNG, will not have the desired impact of reducing predicted future global warming; in fact, quite the contrary. A large portion of anthropogenic global warming is attributed by the IPCC and IEA to CH4, but it must be noted that CH4 emissions from natural sources and from agriculture account for approximately 40% and 25% of annual global CH4 emissions respectively. Energy accounts for about 20% of documented CH4 emissions. CO2 contributes only approximately 35% of annual airborne anthropogenic GHG emissions after accounting for CH4, over a 20-year horizon. At a 100-year horizon, the contribution of CO2 increases to approximately 60%. Energy policies that do not consider all GHG emissions along the entire value chain will lead to undesired economic and environmental distortions. All carbon taxation and CO2 pricing schemes are incorrect and need to be revised. At IPCC’s GWP20 an approximately 2%1 higher loss of CH4 across the value chain prior to combustion of natural gas versus coal will lead to ‘climate parity’ of coal with natural gas. According to public data, natural gas value chains have high CH4 and undocumented CO2 losses. On a global average, using only IEA-documented CH4 data, natural gas emits approximately 15% more CO2 eq than surface-mined coal, over a 20-year horizon. This difference will increase as the use of shale gas and LNG expands. Investors should support all energy systems in a manner that avoids an energy crisis, including intermittent renewable energy systems where they make sense. If CO2 emissions need to be reduced, one of the most effective ways would be to install ultra-supercritical power plants with CCUS technology. However, the undisputed benefits of increased CO2 concentrations in the atmosphere because of its promotion of photosynthesis and plant growth effects (fertilization) need to be considered in energy policy decisions as well. The authors suggest that future research and development should concentrate on reducing net emissions from fossil fuel power plants and providing cost-effective and reliable new conventional power generation capacity, utilizing clean coal and clean natural gas technology.

Mar 2, 2022

By T. Fernandez, V. Juchen, C. Petter, F. Cantini, V. Lenz, V. I. Araújo, R. Petter, R. Darrigo, A. Young, I. G. da Costa, J. Oppermann

There are many methods to estimate costs quickly. One of these is the Parametric Method, where costs are estimated from general algorithms (or curves). Derived from an original tool based on the O’Hara model, a software called MAFMINE was developed. MAFMINE is based on parametric models to estimate investment and operational costs in mining. The software itself is based on the use of a computer model known as client-server. However, the model needs new inputs from advances made by the mining industry, mainly in terms of electrification, automation, digital transformation and preconcentration to face Environmental, Social and Governance (ESG) concerns. Thus, this work was to prepare a new core module ready to incorporate the new technologies aiming to deliver operation and capital costs associated with environmental impact mitigation. The tool generates an order of magnitude estimate for CAPEX and OPEX to establish a very first Discounted Cash Flow (DCF) in a mining venture. For quick evaluations, at a preliminary level, the results are very promising.

Mar 2, 2022

By S. S. Klima, A. L. Mazzella, J. S. Driscoll, T. W. Beck

Previous testing was performed by researchers at the National Institute for Occupational Safety and Health (NIOSH) to improve longwall dust control using underside shield sprays with a longwall directional spray system. This testing provided encouraging results toward respirable dust exposure reductions for longwall personnel, achieving as high as 99% dust reduction at some sampling locations along the longwall personnel walkway. Additional laboratory testing was conducted to test these underside shield sprays in conjunction with a shearer-clearer spray system located on the longwall shearer body. The purpose of this testing was to determine if the underside shield sprays interacted positively or negatively with the shearerclearer sprays. Results from this testing indicate that while the shearerclearer system influences where the respirable dust particles are directed, underside shield sprays can still lower respirable dust exposure for longwall personnel.

Mar 2, 2022

By K. Anim, C. Calderon-Arteaga

Located in Mojave, CA, The Soledad Mountain mine is an Open pit Heap-Leach gold Mine, which is operated by Golden Queen Mining Company LLC. under private capital. Open pit mining began in 2015 while full production was reached in 2016. The open pit mine feed a processing plant that can process more than 13K tons per day of ore which is sent to a heap leach pad. The Soledad Mountain project is a poly metallic deposit with Au and AG being recovered as payable metals. As the mine became bigger after moving to the east pit phases, Golden Queen was facing new challenges to control the production and accurately determine KPIs to improve/increase the production. To maximize returns and asset value, a new fleet management system (FMS) was adopted and implemented. The new FMS has enabled the mine to interconnect the different stages of the mining, as well as to recognize issues and implement the necessary corrections. With the associated increase in complexity in the process, the requirement of the ore control system to accurately predict ore feed characteristics is critical to maximizing metal recovery. Implementation of new daily and weekly plans were needed to ensure the ore delivery and meeting the tonnage goals, while allowed the equipment operators to better geolocate and to maximize the equipment production. These conditions alongside with Golden Queen’s drive to increase profitability and maximize net asset value has created challenges. These challenges are numerous and multifaceted. However, the ability to accurately route the material from the mine, is critical to site success and some of these challenges have been overcome by the adoption of the new FMS, the implementation of daily and weekly plans and upgrades in the ore control workflow. Examples of how the integration of the new systems allowed golden Queen to improve production strategy, are discussed in this article.

Mar 2, 2022

By J. Kretschmann, O. Drusche, S. Krause

Mining companies are caught between the growing international relevance of ESG (Environmental, Social and Governance) investments and the need to secure their “social license to operate” by considering the needs of their stakeholders. In the search for sustainable business models, the concept of the circular economy (CE) is gaining momentum among practitioners and scholars, as it enables the creation of shared value and thus strengthens the trust of investors and stakeholder relationships. However, there is a lack of a sectorspecific CE framework providing guidance to decision-makers in evaluating promising activities. A gap, which this contribution aims to address.

Mar 2, 2022