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By B. Simser, T. Butler, A. Hall

The longterm future of Glencores’ mining operations in the Sudbury basin area of Ontario, Canada likely depends on mining deposits at depths below two kilometres. To gain a better insight into the rockmass response to mining, a geological scouthole program has been implemented at Glencores’ Nickel Rim Deep and Onaping Depth Project to gain insight into rockmass conditions ahead of the devel-opment face. The scouthole program involves drilling long (up to 600 m) subhorizontal boreholes drilled ahead of the development end and collecting data about the rockmass conditions from various geophysi-cal and mechanical tools (in addition to conventional core logging). Once all data has been collected and the borehole is available, seismic sensors are installed up to 450 m down the hole as part of the micro-seismic monitoring program with the leading sensor always located ahead of the development end. The recorded seismic data is used to provide realtime insight into the rockmass response to mining. On May 20, 2017 a flurry of seismicity with a maximum moment magnitude (Mw) of 0.7 occurred causing damage to the ramp heading. Data from the microseismic monitoring system had indicated that conditions at the development end were changing prior to the rockburst. A back analysis of the scouthole data indicated a clear anomaly in the rockmass at the location of the rockburst. The scouthole data also provided sufficient information to suggest that once this anomalous zone was exited, mining conditions would improve. With the microseismic monitoring system providing realtime information from the rockmass, the area was re-habilitated and ramp development continued successfully. Details of the rehabilitation and adjustments to the ramp development are discussed. Some correlations between the scouthole data and recorded micro-seismicity are also presented.

Apr 26, 2022

By Mirjana Boskovic

LKAB’s Kiirunavaara Mine is a sublevel caving iron-ore mine located above the polar circle in northern Sweden. The mine has been proclaimed seismically active since 2008 after a magnitude 3 seismic event, according to Swedish National Seismic Network (SNSN). At that time the Kiruna Mine did not have mine-wide seismic system. Since then, the Kiruna Mine experienced several damaging seismic events of which the largest one on the May 18, 2020. The magnitude, based on the moment tensor inversion results on data from the SNSN as well as seismic stations in Finland and Norway, is estimated to 4.2 ± 0.2 moment magnitude. The seismic event on the May 18, 2020 was located in the middle of the one of the productions areas and caused the major damage in the mine, damaging several kilometres of drifts on six mining levels, some of them beyond the practical repair. These damages affected four of ten production areas on several levels, some more some less. Luckily, no person got injured from the seismic event and the very long aftershock series. An important part in the whole process after the seismic event was information flow and decision-making process. It was very important to keep workers and community informed as that contributed transparency of decision-making and decreased the speculations. Resuming the production in the damaged areas in the safe manner, very soon become main focus for the mine management. It was obvious that not only rehabilitation of the areas is needed to resume the production. It was A MUST to understand the factors behind the seismic event and its mechanism to be able to avoid same situation and prevent seismic event of similar size. Mine engineers had to think outside the box to find the solutions to ‘rescue’ every drift that they could to be able to make good enough base for continued mining of the area. The paper describes actions taken in a very complex process of recovering the area that we from the beginning thought need to be abandon. Seismological analyses of the event on May 18, 2020 and past activity in the area, damage mapping, detailed studies of structures and geology, numerical modelling as well as engineering judgement were used as base for all our decisions how to proceed in attempt to restore mining of the area heavily damaged by 4.2 moment magnitude seismic event, in a safe way.

Apr 26, 2022

By D Lucato, B Haase, R Saha, S Limberger-Forte, J Lishman

Cadia East Mining operations have employed geometallurgical techniques to advance the understanding of the in situ rock hardness variability across existing Panel Caves (PC). Geometallurgy advances the understanding of variability across an orebody through the integration of geology, mineralogy and processing response and therefore enhances spatial mapping of comminution or separation properties. Spatially extensive geometallurgical measurements are necessary so that continuous rock properties can be generated and used for the development of comminution and processing domains using geostatistical modelling. Standard testing protocol across geological and mineralogical domains is vital to understand the variability in deposit wide comminution and separation properties. The high cost and large sample requirements associated with metallurgical test work typically results in insufficient data density and distribution, making it difficult to model and map deposit scale variability. Quantitative hardness proxy tools are useful to measure in situ rock hardness, however this data is typically either sparse or missing within advanced mining operations. In recent years, mineralogy and multi-element assay data has often been collected as part of the standard geological data set and is generally coincident with metallurgical test work. In this paper relationships between mineralogy and comminution parameters have been applied to multi-element assay data with coincident measured Bond Work Index (BWi) data to generate a predicted BWi using linear regression. The predicted BWi is intended to supplement existing measured BWi data to enable better extrapolation across the deposit. Geostatistical Conditional Simulation methods have then used the predicted and measured BWi data to produce a BWi variable as a new input to the resource model. The simulated BWi can be used as an input for specific energy models to predict required grinding energy consumption across a deposit.

Mar 22, 2022

By A Purton, C Taylor, E Conroy

The spatial modelling of geometallurgical domains is an important step in the characterisation of an ore deposit allowing for the quantification of various rock types, their differing rock properties and the overall value of a project. The traditional approach to modelling such features is through the use of deterministic models, where a single estimate of the extents and structure of the ore deposit is mapped out by geologists based on available data and their interpretation of the geological processes. Any uncertainty in the layout of different domains is not accounted for and heterogeneities of chemical and physical properties of the orebody are likely underestimated. Spatial machine learning techniques can be used to derive geometallurgical categories, or classes, from multiscale, multiresolution and high dimensional measured rock properties. Subsequently, geostatistical simulations of these classes can be applied to obtain multiple equiprobable realisations that define the layout of the geometallurgical classes at unknown locations between boreholes, or domains. In-turn these realisations can be used quantify the uncertainties in the location of boundaries between different domains. The development of a workflow for defining geometallurgical domains and later geostatistically simulating them across the Orebody H; a complex stratabound Bedded Iron Ore deposit located in Western Australia’s Pilbara region is demonstrated. This could be used to identify zones of high uncertainty where collection of additional data might help mitigate or minimise risks and in turn improve forecast production performances.

Mar 22, 2022

By S L. Martin, M Wimberger

The binary indicator coding of assay and lithological data according to a single criterion or multiple criteria is a powerful technique for representing mineralised shapes through the modelling of probabilities. This can be as simple as using a single indicator to model the probability of occurrence of a condition, usually a grade threshold or a lithology, but it can also be used with a number of categories. Case studies are presented to show the power of this approach, where the geological controls on mineralisation or on the distribution of a rocktype or alteration, often coupled with mineralisation, are unclear. The categorical approach is often used as a de facto grade filter in disseminated or stockwork mineralisation. The ultimate expression of the indicator formalism is in multiple indicator kriging (MIK), where a conditional distribution of probabilities is generated for each estimation panel. This has applications in recoverable resource estimation, as the input for continuous or categorical simulation, where the distribution of sample grades is multimodal, or when there are superimposed mineralisation events with different orientations. However, in some cases, MIK is being used as an excuse for ignoring a quality geological interpretation. Examples from the public domain show the abuse of the categorical and MIK approaches to modelling probabilities, together with a plea for greater consideration of the geology.

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 A Whaanga

The use of photogrammetry has greatly increased the accuracy of 3D mapping underground. However, this has not reduced the need or desire for geologists to produce plans and sections showing an interpretation of the mapped geology. At the Waihi Underground Gold Mine, a hybrid solution has been developed that utilises the accuracy of photogrammetry and mapping onto face photos with the CAD-based Deswik.MappingTM functions to create plan and section maps. These have the benefit of looking like traditional paper maps but are more spatially accurate and richly attributed with metadata that can be filtered and exported to downstream processes. Deswik.MappingTM is a tablet-based solution that allows the geologist to map digitally with a stylus. Automation is utilised for the updating of survey as-builts, approved designs, drill holes, geological mapping, vein interpretations and mine work areas, reducing the requirement to print out maps at various locations and scales. Having 3D mine software on a tablet device provides a wealth of features not available when using paper: scaling is a problem of the past; information can be turned on and off; features can be viewed in 3D; and measurements between points of interest can be calculated in 3D space, for example, between vein wireframes and drill hole sample information. A suite of custom scripts has been developed that take the spatially accurate, registered and attributed polyline data from photogrammetry scans and converts them to a geological mapping legend with vein textures, structural information, and lithological boundaries. These 3D maps can be plotted in plan or section view and satisfy the requirements of the most ardent paper map supporter.

Mar 22, 2022

By J Ashford, Minniakhmetov

Geostatistical simulations are the best practice for uncertainty quantification in non-linear systems. Simulations are currently undertaken on an ad hoc basis in the mining industry due to high requirements in computing environments and advanced geostatistics. In contrast to the estimation process, multivariate simulations can be performed using different methods, tools, and computational environments, similar to data science. For large companies with multiple commodities it is important to have a standard framework to test, build, and run workflows using different methods, applications and computational environments. This work presents an auditable, modular and scalable framework to create geostatistical simulation workflows where the workflow is abstracted from the implementation. Key aspects: automation – workflows should be able to run automatically given updated data (if hands on modelling is not required); auditability – workflows should document key considerations and parameters; modularisation – workflows should permit swapping out components, for example substituting domaining in Leapfrog software with automated domaining using machine learning scripts; scalability – easy, repeatable, portable deployments on diverse infrastructure (for example, experimenting on a laptop, then moving to an on premise cluster or to the Cloud); reproducibility – parameters should be archived to permit re-running and reproduction of workflows in future years; and sensitivity analysis – any component of a workflow should be able to run with multiple scenarios of parameters and data to enable global uncertainty quantification and sensitivity analysis. The presented framework can be used to create different workflows for geostatistical simulations in multiple assets to quantify uncertainty in the value chain for resource categorisation, reserves uncertainty, value of information and robust mine planning amongst others.

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 Jared Winkler, Jon A. Hummer, Aleksandar D. Bugarski, Shad Peters, Steven E. Mischler, Steve Cochrane, Shawn Vanderslice, Teresa Barone

The case study assessed submicron aerosols at a continuous miner (CM) section, diesel aerosol concentrations at the longwall (LW) section, and elemental carbon (EC) and total carbon (TC) exposures. Aerosols at CM sections were a mix of freshly generated and those from main drifts. Low ambient concentrations and personal exposures suggest effective control strategies, with further reductions possible by curbing emissions from high-emitting light-duty vehicles.

Mar 16, 2022

By K. Luxbacher, D. T. Hristopulos, S. Schafrik, J. Diaz, Z. Agioutantis

Big data is generated from both surface and underground mining operations. Such data contain a wealth of information concerning safety and health in the workplace and production parameters. This paper will discuss the progress towards developing an accurate forecasting model for methane gas concentration based on the analysis of data collected from Atmospheric Monitoring Systems in underground coal mines employing time series models. Several procedures need to be applied to raw data, such as data cleaning and filtering for outlier removal, data homogenization and segmentation, and exploratory statistical analysis. The data analyzed were retrieved from two coal operations in the Eastern US. A negative correlation between barometric pressure and methane gas concentration was established, at least for certain data segments. Such correlations raise the possibility that barometric pressure data can predict variations of gas concentration in the mine. The datasets will be further investigated to establish the robustness of barometric pressure and gas concentration correlation and explore the dependence of gas concentration on other factors related to mine design and operations

Mar 2, 2022

By J. Scheepers, P. Smith, G. (Yunfei) Qiao

High pressure acid leach (HPAL) and pressure oxidation (POx) or pressure leaching extraction processes occur in autoclave vessels operating at elevated temperature and pressure, acidic conditions with abrasive mineral slurries. The harsh process conditions require specialized severe service metal seated ball valves to support operation of the vessels. Over several decades thermally sprayed titanium dioxide (TiO2) and chrome oxide (Cr2O3) coatings have been applied to extend the service life of the ball valves and other high wear critical components. Variability in the coating application quality control and severe process conditions can result in spalling, coating failure and premature failure of the component resulting is decreased autoclave circuit availability. In 2012 MOGAS, together with BRENCO, initiated research and development for ML-381, metallurgically bonded coating. This paper includes the historical development of severe service ball valve coatings, success of the trials and increasing industry adoption of the ML-381 coating for ball valves and other critical autoclave circuit components.

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

By T. Kretschmer, F. Villwock

Conveyor systems are an essential part of many material movements in all conceivable areas of application. They are used to transport goods in raw materials extraction, agriculture, and even articles for daily use. In the process, not only distances of several kilometers but also differences in altitude of several hundred meters are bridged. The layout of the conveyor usually follows the topography at the respective installation site. Particularly in the case of large height differences, safety devices must be provided to prevent uncontrolled movement. Backstops can take over this task in predominantly ascending overland conveyors and are used either as a primary or as a secondary safety system in conjunction with a service brake. They are always used when the system comes to an unplanned standstill, whether due to a power failure, an emergency stop or a defect. When designing backstops, it must be ensured in any case that all conceivable circumstances are taken into account so that failure is ruled out without the product being unnecessarily large in size. Various safety factors are applied, some of which are even prescribed by authorities. One example is the Australian standard on machine safety for bulk material belt conveyors (AS/NZS 4024). This stipulates a redundant acceleration safety device that can absorb at least 150% of the maximum load. ALTRA Industrial Motion with its sister companies Marland and Stieber manufacture backstops for a wide range of applications. With more than 85 years of business activity in freewheeling and backstop applications, they are among the most known and experienced companies and provide a great know-how.

Mar 2, 2022

By Y. Wang, G. Xu, N. A. Amoah, A. Kumar

Mining-induced coal dust causes various respiratory diseases to mine workers, such as coal workers’ pneumoconiosis (CWP). Current available underground monitors are expensive, heavy and only measure mass concentration. These disadvantages limit them for regulatory sample monitoring purposes only while personal exposure levels for most miners remain unknown, risking miners to potential overexposures. Low-cost light scattering PM sensors offer a potential solution to this problem with capability of high spatio-temporal resolution PM characterization. However, these sensors require careful calibration before they can be applied in mining environments. There is basically no comprehensive study in the literature using a standard protocol assessing these sensors for coal dust monitoring. With the aim of calibrating the PMS5003 sensors for coal dust monitoring, we design the calibration method and system to calibrate these low-cost PM sensors coal dust monitoring. Working principles of present coal dust monitor and low-cost sensors are presented in detail. The linear regression calibration model which is used for the sensor calibration is further described. Sensor calibration and evaluation protocols are comprehensively compared and discussed. This investigation reveals the feasibility of low-cost sensors for real-time personal coal dust monitoring in underground coal mines.

Mar 2, 2022

By K. S. Fraser, R. Frischmuth

High temperature pressure oxidation (>190°C) is a wellrecognized and versatile metallurgical oxidative pre-treatment process commonly used to liberate gold from refractory sulfide ores and concentrates. The pressure oxidation of refractory gold ores was first commercially applied in 1985, at Homestake Mining Company’s McLaughlin mine in the United States. Since that time numerous refractory gold and other high temperature pressure oxidation facilities have been built throughout the world. The design of each facility was met with unique challenges and opportunities which have led to an array of plant configurations, pressure oxidation autoclave sizes, and sulfide oxidation capacities. This paper presents a historical review of high temperature pressure oxidation operations and current projects in execution with a focus on the autoclave vessel design, circuit configuration, and unit sulfide oxidation capacity as a basis for characterization and comparison.

Mar 2, 2022