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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 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 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 A D. Wulfse, C M. D Barton

Underground fractured aquifers in the Ernest Henry deposit are to a large extent controlled by deposit scale brittle structures. The underground mine has been subdivided into nine water zones based on hydrogeological characteristics, including conductivity and connectivity, within the mining areas bound by these structures. The nine water zones and the hydrological characteristics of the associated structures are utilised for risk assessing mine development and for targeting diamond drilling dewatering activities. Wireline and conventional underground diamond drilling techniques have been used throughout the network of underground aquifers with the aim of dewatering areas within the mining footprint. These dewatering drilling campaigns have historically been highly successful at lowering aquifer water levels throughout the underground workings. As part of recent mine expansion activities, diamond drilling has intersected high pressure (>507 psi), high temperature (>50°C) and high flow water (>3 L/sec) in as yet unconstrained underground aquifers. Groundwater is typically conducted through rubble and clay rich faults, further hampering progression of drilling. Drilling through fractured aquifers at depth presents both mine planning as well as safety challenges. Recent drill holes have been delayed or abandoned when aquifers hosting this high pressure, high flow water have been intersected, risking mine planning deadlines. Recent technological innovation developed to control groundwater outflows from the diamond drill hole whilst drilling has been trialled at the Ernest Henry Mine. This case study focuses on the utilisation of alternative drill methodologies to allow the current drilling campaign to continue without delay, whilst also improving safety conditions encountered on the drill site.

Mar 22, 2022

By K L. Silversides, A Chlingaryan, A Melkumyan

Multiple data sources can be fused to improve boundary modelling in stratified deposits such as the banded iron formation (BIF) hosted deposits in the Pilbara Region of Western Australia. Accurate boundaries are essential to produce high quality geological models. Initial models are based on the widely spaced exploration hole data. This creates a high level of uncertainty in areas between the holes, with different interpretations of the boundary equally probable. Including directional information collected in these holes in the models can reduce the number of possibilities. Including data collected during mining, such as blastholes and bench measurements, can further guide the model. This research demonstrates a Gaussian Processes based method of fusing these disparate data sources to better inform the boundaries. Our results demonstrate that when only exploration points are used the model creates a smooth boundary with minimal variation between the holes. Each additional data source refined the model and added additional detail to the boundary. For the blast data, the new detail projects down to the bench below the current bench to allow for a better prediction before mining commences on that bench.

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 J Taylor, M Smith, A Tunnadine, D Nikolakopoulos

As Olympic Dam rapidly expands into the Southern Mine Area (SMA) the Mine Geology team has concurrently ramped up underground diamond drilling to sustain rates of above 175 km/a. With >10 underground rigs double-shifting, traditional paper sections used for the management of drill programs were no longer optimal due to scale of operations. An opportunity was identified to modernise monitoring of all underground diamond drill programs, through the integration of logged copper sulfide estimates with Olympic Dam’s first-fully integrated deposit-scale geological model in Leapfrog Geo. This paper describes the transition within the Mine Geology team from reliance on 2D paper sections, towards near-real time 3D geological modelling for optimising end-of-hole decisions in the field. This transition was enabled by innovative database solutions informing locally constrained implicit models, limited by a distance buffer around active underground fan drilling. Due to the high volume of historic drilling, there were significant computational challenges with the implementation of daily production style implicit models at Olympic Dam and initial testing of regular updates to implicit gradeshells and sulfide domains required in excess of 12 hrs to run. The enabling solution was to optimise the interfaces between the AcQuire database, Deswik MDM and Leapfrog Geo to create a dynamic, streamlined workflow that was easily completed by Mine Geologists in accordance with daily production duties. Geologists are now building rapid implicit models for a range of variables from an integrated data set of logged sulfide estimates and existing assays, spatially constrained by 150 m buffers around active drilling using a unique drill fan identifier flagged during the planning phase. Once the live-implicit models are updated, they are exported for visualisation on field tablets to be used during logging and core checks at the start and end of every shift. To manage the risk of ‘going digital’ interpretation remains at the forefront of the drill section close-out process, with Mine Geologists critically reviewing the finished sections on a standardised template with new learnings wireframed and communicated to stakeholders. The Live Field Model has enabled a step-change in the geological effectiveness of diamond drilling, reducing over – and under-drilling ore-waste at Olympic Dam continuing to push drilling effectiveness towards 20 per cent of intercepts >2 per cent Cu. In addition, upside or risk identified during the proactive management of drilling execution can be rapidly capitalised or mitigated.

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 S Sullivan

A recent review of resource reports lodged to statutory bodies found geological models with oversmoothed or unrealistic lithological boundaries, many of which do not represent geological appearance in the field, pit or underground drive. The underlying data is often too complex or messy to be incorporated into the resource model and is thus a simplification of reality, to the detriment of the mining operation and its shareholders. Volumes can be over- or underestimated and subsequent grade predictions can be misplaced, combining to cause over- or understatement in resource reporting to stakeholders and statutory authorities. Domain models can be improved with new modelling techniques such as machine learning. However, with poor data or improper use of machine learning techniques, the conclusions can be just as misleading as with current techniques. Machine learning rarely offers a single ‘right’ outcome, rather a range of possible outcomes from the data provided. But importantly it can take advantage of the full richness of data for more informed models. Machine learning also provides confidence in its predictions so that uncertainty in the resultant models can be quantified and passed through for risk assessment during mine planning and operation. This paper will discuss the factors accentuating complexity in deposit modelling: data diversity, structural controls, chemistry, data volumes, process workflows and external non-geological constraints. A case study illustrates the risk of reducing or ignoring complexity, which can result in an overly simplified geological model.

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 A. Juganda, H. PINHEIRO, J. Brune, N. SANDOVAL, G. Bogin, K. Gallagher, F Wilson

The present work discusses the nuances of scaling and flow similarity to develop a 1/40th scale version of a longwall coal mine. Details on the geometric, kinematic, and dynamic scaling of the physical model are presented and discussed. This works also discusses using a 30% CO2 – 70% He gas mixture as a surrogate for methane. It also presents the implications of various Reynolds numbers (ranging from 7,000 to 140,000) and rotation of the shearer drums in the dynamic representation of the airflow and gas mixtures in the physical scaled model.

Mar 19, 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

By Qingwen Shi, Brijes Mishra

The abstract discusses the use of numerical simulations to investigate roof fall in underground mines. It highlights the advantages of the discrete element method (DEM) in simulating large strain problems and fracturing processes, while acknowledging its computational limitations for large-scale problems. The study presents a 3D numerical model coupling the finite difference method (FDM) and DEM to simulate laminated roof failure in a coal mine. The model represents the laminated roof with bonded particles and discontinuities, while the surrounding rock is represented by continuum zones. The research analyzes the fracturing of the laminated roof as the entry advances, demonstrating the coupled method's ability to reproduce laminated roof failure.

Mar 17, 2022

By ETHAN FUSTER, Richard Ray Jr, STEPHEN LEE

The abstract states that horizontally-mounted jet fans are commonly used to ventilate vehicular tunnels due to their space and cost savings compared to fully ducted systems. It highlights the successful use of vertically-mounted jet fans in exhaust ventilation shafts for a passenger rail overbuild in New York City. The paper compares shaft dimensions, jet fan placement, and measured airflows, also comparing these measurements to predictions from computational fluid dynamics (CFD) simulations.

Mar 16, 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