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By S A. McManus

With the advances in software speed and capability, many of us now are running multiple scenarios on entire models rather than just testing small areas or a few blocks. In the authors experience both the geological and geostatistical academic theory and our rules of thumb, often prove un-useable or incorrect in the real world we work in. The only way to truly validate and tune our models is to complete the entire model and ‘see if it works’. If it lacks some property we were expecting, then we need to find out why and/or run different scenarios to see what changes. This is not always possible with tight project timelines but we find ourselves doing more and more of this sort of thing, and in so doing, understand that every deposit is different and requires its own ‘rules’ to get valid and useful results. For the purposes of this paper, this process is termed Empirical Geostatistics. Take Clayton Deutsch’s ‘all realisations all of the time’ concept a step back. Before you even think of simulating, test the alternate realisations generated by alternate parameters such as different domaining, varying search neighbourhood parameters etc.

Mar 22, 2022

By D Kentwell

IGO Ltd’s (IGO) Nova Operation (Nova) is 160 km east-north-east of the town of Norseman in Western Australia (WA). Discovered by Sirius Resources NL (Sirius) in 2012 and acquired by IGO in 2015, the Nova-Bollinger Deposit (Nova-Bollinger) occurs within the Fraser Zone of the AlbanyFraser Orogen. Nova-Bollinger is a complex nickel-copper-cobalt (Ni-Cu-Co) magmatic intrusive sulfide deposit, which is characterised by high-grade folded and undulating breccia lodes that host the bulk of the payable metals. Significant sulfide mineralisation is also found in several magmatic intrusive styles including net-textured, disseminated and blebby styles. A smaller but material volume of sulfides has also been remobilised into the deposit’s footwall rocks as ‘stringer’ bands in metasediments, or as discrete massive sulfide lenses. When interpolating Mineral Resource estimate (MRE) block grades in the presence of locally varying grade connectivity trends, such as folds or undulations, the sample search neighbourhood, which is used to identify the composites subset that is used for each block estimate, should be oriented to match the local trends. In theory, the most robust method of estimation where locally varying angles (LVAs) are applied to search neighbourhoods, are techniques where the composites and the blocks to be estimated are transformed to an unfolded coordinate system (UCS). However, UCS methods can be tedious to implement and require subjective decisions to be made that cannot always be fully defended. An alternative LVA method commonly used in the industry is dynamic anisotropy (DA), which is much simpler to implement and is often assumed (but not that often demonstrated) to result in similar results to UCS-style estimation. In 2018, Nova’s Mine Geology team (MGT) estimated the grades and density of the Nova-Bollinger MRE using the UCS approach. For the 2020 MRE update, Nova’s MGT tested and compared the USC grade interpolation method with the DA approach. As applied to the Nova-Bollinger’s 2020 MRE, the comparison, advantages and disadvantages of the two estimation methods are the subject of this paper

Mar 22, 2022

By A Whaanga, W Vigor-Brown

IGO Ltd’s (IGO’s) Nova-Bollinger Deposit (Nova-Bollinger) is a magmatic nickel-copper-cobalt (NiCu-Co) sulfide deposit found 160 km east-north-east of the town of Norseman in Western Australia (WA). The deposit is hosted by the Mesoproterozoic rocks of the Fraser Zone, which is part of the Albany Fraser Orogen (AFO). Since mining commenced in 2016, IGO’s Nova Operation (Nova) has mined and processed to 31 December 2020, 5.63 Mt of ore grading 2.04 per cent Ni, 0.86 per cent Cu and 0.07 per cent Co. Nova’s mine geology team (MGT) has used commercially available implicit modelling (IM) and general-purpose resource modelling (RM) industry software systems, to prepare the 31 December 2020 (CY20) update of Nova-Bollinger’s JORC Code reportable Mineral Resource estimate (MRE). This CY20 MRE update was predominantly based on ~386 km of diamond core drilling, with the drill holes having a nominal grid spacing of 12.5 by 12.5 m throughout the mineralised zones of the deposit. Using IM tools, Nova’s MGT interpreted and modelled 22 separate domains from the drill hole logging, assaying results, and the MGT’s underground mapping. These IM closed volumes were then used to control the estimation of MRE variables into conventional industry digital block models using RM and other ancillary software systems. During 2021, a commercial machine learning (ML) software was trialled by Nova’s MGT for preparing block models of Nova-Bollinger’s MRE domains. The motivation for the trial was that the ML process could expedite modelling through the direct creation of a domain coded block model from the drill hole logging. Compared to the industry standard approaches of wireframing or IM, where the modeller usually makes many subjective choices to produce the domain model, ML offers a more objective ‘hands-off’ process for determining the connectivity of domains defined in drill holes. Additionally, the ML process provides a quantitative confidence metric associated with its output that may have utility in mine production and resource classification. In this paper, the results of the Nova-Bollinger ML modelling trial are compared to the MGT’s current workflow for MRE work. The MGT’s conclusions as to the advantages and disadvantages of the IM and ML methods for preparation of MRE domains are discussed. The ML software was also tested as a method of rapidly interpreting geology outside the principal zones of MRE interest. These testing results are also presented in this paper.

Mar 22, 2022

By P Micale

Geological data provides the foundations for the mining value chain. It is used to underpin the modelling and planning and consequently optimise downstream business decisions. However, it is often forgotten or taken for granted. End users often assume the data to be sound without verification. Geological data can be considered a company’s number one asset. Subsequently, the storage, use and management of this data need careful curation and time invested in preserving and protecting it. An established polymetallic mine with 20 000 drill holes could have a data replacement value in excess of $500M at 2020 prices, excluding labour and salary costs. The Australasian Code for Reporting of Exploration Results, Mineral Resources and Ore Reserves (the ‘JORC Code’) provides guidelines for Public Reporting. Within the code, Table 1 requires discussion around the different types of geological data, its collection and use. What is needed is additional details regarding the validation and integrity of the geological database. A comprehensive guideline specifying minimum geological standards for geological databases has been developed. This expands on the critical points outlined in Table 1 of the JORC Code. This guideline can be used by companies where geological databases are managed in-house or used to assess these services’ outsourcing. This guideline will ensure that geological data is reliable and unadulterated and can be used with confidence. Using this guideline will assist in preserving the investment of geological data in the mining value chain

Mar 22, 2022

By R Hargreaves, T Elkington, W J. Shaw, G W. Booth

Every day, around the world, thousands of tons of ore are loaded onto ships completing the miningproduction process and starting a multimillion-dollar economic transactions process. These transactions are based on the supply of tons of a commodity with certain specifications of assays of the main element (or physical properties) and concentration of contaminants, which are finally verified and evaluated by buyers, and also are considered ‘as true’ during Reconciliation process. On Sample Stations, this ‘true’ is based on a few kilograms of sample, often representing thousands of tons, that are sent to laboratories for further sample preparation and chemical analysis, where finally assay information is obtained from a few grams of pulverised sample, and are used for further production, planning, operational and financial-marketing decisions. Different International Standards (depending on the commodity) are used to establish the methodology to be followed, to set-up and obtain samples from the Sample Stations, and the specifications are visually inspected to give an estimation on the performance of the sampling point. This paper seeks to highlight with examples, the importance of the implementation of a continuously monitored Quality Program (QAQC and QM) on Sample Stations, focused on the parameters that directly affect the quality and representativeness of the samples. By this implementation, a proactive approach and better-informed decisions can be taken for mining companies to: a) quantify/improve production and reconciliation results, and b) to supply the right specifications of shipped ore, increasing the value of the Resources. Finally, laboratory results are normally used as an indication of the quality of the information applied for the economic transaction, but it should be considered, clarified and highlighted that the laboratory will only process and analyse a sample obtained from a Sample Station, and potential problems on bias or precision may occur in stages prior to the laboratory reception. Hence the importance of the implementation of a quality assurance program that protects multi-million dollar decisions.

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

Consultants in the mining industry have the opportunity to visit interesting deposits all over the world. Each deposit has its own set of challenges to face when it comes to defining and understanding the deposit geology and the economics to make it viable for extraction. Some of the challenges can include appropriate data capture, sampling techniques, structural characteristics, geochemistry, geophysics, lithology definition, and economic boundaries. It is essential that the practices used at each deposit (eg drilling, sampling, geological modelling, resource estimation etc) are documented and the results obtained are robust and defensible. The Competent Person is not always aware of instances where their resource estimation practices have not been substantiated. ‘You don’t know what you don’t know’ is a phrase frequently used during a mineral resource audit. Technical work to substantiate drilling, sampling, density, assaying, geological modelling and estimation processes is not always completed. Audited Competent Persons often comment: • ‘I was unaware that this was required.’ • ‘I have not had training in this area and do not know how to complete the checks required.’ • ‘This is how we’ve always done it.’ Examples of audits where it was found that geological practices were not substantiated are examined here. A discussion is included on why substantiation of these practices is important, and potential reasons as to why there are instances of unsubstantiated processes and practices are discussed.

Mar 22, 2022

By D Espinoza, I Rees, J Pocoe, P Collier

P Collier, I Rees, J Pocoe and D Espinoza

Mar 22, 2022

By E Philippa, B Miller

Material characterisation, ore sequencing and process capability are commonly regarded as the key parameters to consider in designing and operating an effective pit to plant supply chain. Therefore, an understanding of rock mass properties is the starting point for controlling the presentation of problematic material to the ore handling plant and optimising process utilisation. There are different methodologies for characterising problematic material and ore handleability which exist across a spectrum of sophistication. At one end of this spectrum are simple indices built using first principles geology and at the other are complex algorithms developed using advanced analytical methods, machine learning and ore traceability. Regardless of the method, without an integrated process for careful management of problematic ore, material handling delays (ie blocked, bridged, blinded and buried events) will interrupt the stable flow of production. The ability of the ore control geologist to mitigate these delays is central to the ore handleability challenge. This paper describes a quick and easy solution that links the presentation of ore to the operating window at the crusher. This operating window is based on material characterisation, using the physical, textural and mechanical properties of the rock mass, and crusher performance. It also describes how a basic problematic ore index (POI) can be developed using ore tracking to the production face, petrographic studies of ore texture and mineralogy, and existing variables in the geological model. Finally, this paper will demonstrate that by coding the POI into the geological model for mine planning, together with performance monitoring through compliance to plan routines, material handling delays at the crusher can be reduced, unlocking significant resource value.

Mar 22, 2022

By H Kurth

Oyu Tolgoi copper and gold mine in the southern Mongolia holds mineral resources that make it one of the largest known copper and gold deposits in the world. The project is operating an open pit mine on the near surface of Southern Oyu deposit and developing underground block-caving mine at the Hugo Dummet North where 80 per cent of total resources exists. Oyu Tolgoi (OT) commenced open pit mining in 2011 and implemented an industry standard blasthole sampling, and ordinary kriging grade control estimation with block-out process. Since 2017, grade control improvement projects have successfully completed that have led to the implementation of current, improved grade control system. Geological model is updated by blasthole logging on Leapfrog® and used for daily grade estimations. GC estimation is proceeded solely on Vulcan® by running Lava script and integrating with a relational database. Combination of block-out procedure produces GC model which is updated in Vulcan® and as well as in the database simultaneously. Switching to the integrated database eliminated many manual processes such as importing and exporting data and enabled access to the database anytime, anywhere and from any device. Thereby, these improvements allowed to increase an efficiency, create a comprehensive reconciliation system and reduce operational risks. We are looking forward to expanding applications of integrated grade control data stored in the database. This paper outlines how the grade control system was developed at OT’s open pit mine, and how it is integrated into the short range mine planning, mine reconciliation workflow and ultimately enabled development of various automated reporting systems.

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 W Patton, I Minniakhmetov, H Talebi, U Mueller

The sustainability of mining projects is linked to informed investment decisions based on public reporting of exploration and mineral resource estimation results. In Australia, public reporting guidelines are established by the Joint Ore Reserves Committee reporting code through the JORC Code (2012). Although the assessment of uncertainty in the results reported is a requirement, this is often communicated qualitatively and evaluated subjectively. This can become a liability particularly in the early stages of mining projects when spatial domains of geological interpretation and mineralisation envelopes inform resource estimations’ reliability. A recent review of JORC reports found no reports used quantitative assessments of the geological interpretation or mineral resource estimation envelopes, and 27 per cent of reports did not address the question of quality of geological interpretation. Reports that did address the quality used 19 different terms to communicate quality. This work presents methodologies for quantitative uncertainty assessment and communication and explores how they could be applied in public reporting practice. Quantitative uncertainty reporting would benefit mine planning and financial modelling as they normally assume the geology is 100 per cent right (since no error is reported or only a single deterministic model is provided). The complexity, cost, and additional work of doing a quantitative assessment could hinder a straightforward implementation. This could be overcome if mining companies budget for quantitative uncertainty assessment and associated professional development. A compulsory requirement for the inclusion of uncertainty assessments in public reporting or adopting standardised subjective language would improve industry practice.

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 I Minniakhmetov, J Ashford

Orebodies constitute naturally occurring, commonly highly variable concentrations of minerals in the earth’s crust formed through varying and highly unpredictable processes. Orebody knowledge is a core foundation of a mining company’s asset base underpinning all decisions about Mineral Resource and Ore Reserves, future production, development and ultimately the profitability and competitiveness of a mining enterprise. The decision to invest in a mineral project is usually based upon a techno-economic evaluation of the project and having clear approval pathways to gain local community support and address social and environmental impacts. The main objective of the techno-economic evaluation is to determine the optimum development sequence for the particular orebody in question and to estimate the economic viability of the project and the future return on investment to its stakeholders, balancing the inherent value of the mineral in the ground against the costs of development and market pricing. With the exception of market-driven commodity prices, virtually all revenue and cost estimates fundamentally stem from the understanding and subsequent modelling of the orebody. A reliable estimate of the ore deposit grade and other geological value-drivers is the foundation upon which the business case for future mine development and operation is intricately dependent. Orebody knowledge is, therefore, the fundamental driver of the mineral project cycle, influencing the progression of studies and consequently, the resource company’s ability to declare Exploration Results, Mineral Resources or Ore Reserves which govern the source and cost of funding available to the project. Drilling provides a ‘vector’ to the true nature of the orebody and effectively buys time to manage the technical risk associated with the orebody. Despite its perceived high cost, in both time and money terms, drilling is the only available technology for acquiring the necessary orebody knowledge to support technical and economic studies and to minimise orebody-driven cash flow uncertainty and volatility. However, like all costs, pressure to minimise drilling budgets is ubiquitous across the minerals industry. Paired with inappropriate key performance indicators, drilling is often regarded as a cost to be minimised, rather than an investment to be optimised. Furthermore, as future deposits get deeper and more complex, the collection of orebody knowledge is increasingly on the critical path for project development. The increasing cost of data collection pertaining to these deposits increases the temptation to minimise orebody knowledge gathering at the cost of long-term value as the reduction or postponement of drilling results in greater orebody knowledge risk at all stages of the value chain. Indeed the true cost of the decision to drill less is rarely known until the mine is in operation, well after the mine project evaluation team has moved on. This paper aims to promote orebody knowledge as the fundamental source of endogenous project financial risk and, consequently, its critical importance in project financial evaluation. Furthermore, the report documents experimental research into the development of an econometric model for valuing orebody knowledge. Using the density of drilling data as a proxy measure of orebody knowledge, the proposed approach integrates well-established stochastic grade modelling techniques with the mathematical mechanics of Decoupled Net Present Value (DNPV) which, combined with stochastic grade modelling (conditional simulation), lends itself to the financial International Mining Geology Conference 2022 | Brisbane, Australia and Online | 22–23 March 2022 3 assessment of orebody knowledge risk. Based on this approach, a metric is formulated, representing the minimum value of the orebody knowledge added by additional drilling

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 Jessica M. Wempen, William G. Pariseau, Dallan J. Coons, Michael K. McCarter, Erik C. Westman

The abstract discusses the importance of proper pillar sizing in underground mining for safety and efficiency. It highlights the use of theoretical models, geotechnical measurements, and numerical modeling in predicting pillar behavior. The research focuses on using seismic tomography to image stress changes in a yield pillar at a longwall mine as the longwall face approaches. The study aims to compare the stress distribution imaged using tomography with theoretical models, geotechnical measurements, and numerical models.

Mar 18, 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