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By J Q. Shi, M Karakus, Y Liu

Predicting the spatial distribution of rock mass properties in cave mining is a critical challenge. In this study, we introduce a novel machine learning-based model to advance our comprehension of rock behaviour. This model specifically focuses on the spatial distribution of rock mass and mechanical properties, a crucial aspect of our understanding of rock mechanics. Our model is inspired by the recognition that neighbouring information serves as crucial prior knowledge for predicting the spatial distribution of these properties, wherein closer neighbours are likely to exhibit similar characteristics. To effectively capture and model these neighbour relationships, we design a neural network-based model to map the spatial locations within the data set into a new highdimensional space. Within this transformed space, we utilise Euclidean distance to identify N neighbours. Leveraging these neighbours, we introduce a straightforward yet highly effective approach—label propagation—to construct a graph that illustrates neighbour relationships. This graph not only facilitates the prediction of the spatial distribution of rock mass properties but also offers a measure of uncertainty for these predictions. We validate the proposed method using a real rock data set and showcase its efficacy in capturing intricate relationships and distributions within rock properties, enabling precise predictions across diverse spatial scales. Our results underscore the potential of machine learning-based approaches to revolutionise the field of rock mechanics, providing valuable insights applicable to geotechnical engineering, mining, and other sectors where an accurate understanding of rock properties is paramount. This model has direct practical implications, offering a new tool for geotechnical engineers and mining professionals to enhance their understanding and prediction of rock properties, thereby improving safety and efficiency in their operations.

Sep 1, 2024

By A Specht, A Müller, V Montenegro, S Winkler, E Klaffenbach, A Schmidt

In the process of primary copper smelting in flash smelting furnace (FSF), the ratio of iron to silica (Fe/SiO2 mass ratio) primarily determines the slag viscosity and magnetite formation. Viscous slag does not only cause difficulties in daily operation, such as in tapping, it also increases the copper losses to slag. Thus, keeping the Fe/SiO2 mass ratio at the desired level is an important aspect of FSF and slag cleaning furnace (SCF) operation. In this study, the improvement of the Fe/SiO2 mass ratio was conducted in two steps: First, the optimal Fe/SiO2 mass ratio was derived based on thermodynamic data. Based on this analysis, appropriate control limits were determined. Second, this range of favourable Fe/SiO2 mass ratios was implemented into operation by an advice-based control system, which suggests the addition of silica based on the analysis of SCF slag. As this approach was successful, the same advice-based control system principle was adapted for the coke addition to the SCF. After testing the new advice-based control for several months, the production data confirm the predictions by thermodynamics: since the prediction was implemented as an advisor, the copper and magnetite content in SCF slag is significantly reduced and viscous slag is reported less often by operations.

Aug 21, 2024

By G R. F Alvear Flores

Mineral resources are becoming more complex in composition and structure making it more difficult to produce clean concentrates for primary metal smelting. In parallel, providing technological solutions to the recycling and recovery of end-of-life materials is becoming more important in moving towards the goal of increasing circularity. The availability of fundamental thermodynamic data and advanced thermodynamic tools greatly assists in evaluating these complexities and their impact on existing and new processes. In addition, it is fundamental to support the economic performance of smelters. This paper describes several examples on how fundamental work can be applied to industrial processing..

Jun 17, 2024

By K M. Cook, D Clark

Fatality prevention and zero harm are key focus areas for resource companies. However, they remain an ongoing challenge for high hazard industries, including the mining sector. As one example the latest International Council on Mining and Metals (ICMM) Safety Performance Report shows that, while there is generally a declining fatality trend since the organisation commenced publishing data in 2012, there were still 33 fatalities across member companies in 2022 (ICMM, 2023b). Every fatal incident brings significant pain and suffering to the colleagues, friends and family of those involved, however the failures and causal factors leading to each incident are frequently very familiar to people working in the industry, particularly those tasked with managing risk and safety. In the words of Dame Judith Hackitt, Grenfell Tower Fire Investigator, ‘there are no new accidents – just different people making the same mistakes because they haven’t learned’ (Hackitt, 2022). The recurring themes in terms of the nature of fatal hazards and their associated causes across the mining sector show that, despite improvements evidenced by the favourable declining fatality trends over the long-term (in general and outside of catastrophic multiple fatality events), changes are required to achieve fatality elimination and the aspiration of zero harm. This extended abstract and the accompanying presentation apply a mining frame of reference to the idea that there are no new accidents, examining how this applies within the industry and why the lessons from past failures are not always well understood or applied to prevent the reoccurrence of material unwanted events. Many contemporary mining and resources organisations have extensive internal incident history data and a wide variety of information on fatality incidents is publicly available, including the annual ICMM Safety Performance Report. This extended abstract and the accompanying presentation explore how this existing data can be used effectively to learn from the past and proposes practical ideas regarding strategies for successful knowledge transfer to the workforce as a key component of preventing history repeating and improving safety performance across the industry. As noted by ICMM, ‘sharing lessons from failure is vital to improving health and safety, but it’s not enough’ (ICMM, 2023a).

Apr 16, 2024

By L Nicholls, A Parbhakar-Fox

Reprocessing Queensland’s historical copper tailings for critical minerals is an opportunity to circularise the state’s mining industry by converting waste liabilities into assets. Mine waste valorisation enables economic rehabilitation of legacy mining sites, improves environmental outcomes, and can establish a secondary resources sector that produces a sustainable supply of critical minerals to supplement growing global demands (Australian Government, 2023). The North-West Queensland Minerals Province (NWQMP) hosts numerous copper mines with known cobalt mineralisation (Degeling, 2020). Cobalt is a critical metal essential for green energy and battery technologies, however its global supply is at risk due to geopolitical and ethical concerns (Rachidi et al, 2021). Historically mining in the NWQMP has focused on copper, leaving cobalt to theoretically accumulate in the mine waste. First-pass geometallurgical characterisation of waste repositories by the Sustainable Minerals Institute identified Capricorn Copper as a key site for further investigation into cobalt deportment and recovery potential.

Aug 2, 2023

By L Bertoss, D Carvalho

In the last decade, the use of advanced implicit modelling software/algorithms in mineral resource workflows has become a best practice in the mining industry. In most cases, these workflows can easily replicate the level of detail of explicitly modelled geometries, even for very complex deposits. These techniques are flexible and can produce fast results since software is responsible for generating 3D surfaces and solids based on geological and interpretation data. Nevertheless, depending on how unique and complex some deposits are, intense manual editing and input are required to honour the geological context and produce the desired outcome. The current geological modelling workflow at George Fisher Mine (GFM) is based on the semi-automatic built-in tool that generates stratigraphic sequences (stacked lithology layers) based on logging and mapping data. This tool (stratigraphic sequence from Leapfrog Geo™) works for the majority of areas in the mine but fails to capture observed mineralisation pinch-outs in operational areas and at extrapolated boundaries of the deposit. These pinch-outs have the potential to negatively impact grade forecasts if not resolved manually. Using built-in software tools only, the alternative for a more accurate model is to generate each individual layer and adding tens of thousands of manual interpretation points to honour pinch-outs (based on the amount of existing drilling in the mine and number of layers). This approach would require an estimated minimum of two to four years of a full-time employee (FTE) to be exhaustively completed. This study presents an automated approach to generate pinch-out points using a set of Python scripts that only take a few minutes to run. The newly generated points are then combined into the commercial software workflow as interpretation points, honouring observed pinch-outs. The remarkable time difference between approaches removes chance of manual errors and allows mine geologists to spend valuable time in validation and testing of scenarios, ensuring they are more representative of the deposit’s geology.

May 24, 2023

By D Clarke, I Minniakhmetov

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

May 24, 2023

By J Levett, O Rondon, I Glacken

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

May 24, 2023

By D Clarke, I Minniakhmetov

The Olympic Dam deposit is truly a world-class IOCG-Ag deposit, the world’s fourth largest deposit of copper and the world’s largest known single uranium deposit. Traditional and non-traditional methods have been used to accurately model the geology and mineralisation of the Olympic Dam deposit. Conditional simulation models have long been used as the most robust method for estimating risk and uncertainty in mine planning decisions at other mines around Australia and the world. There are many challenges associated with simulating the Olympic Dam deposit at a selective mining unit size sufficient for underground mine planning purposes. These include the size of the deposit, resulting in hundreds of millions of grid blocks; the disseminated nature of the zoned sulfide mineralisation. And lastly the direct relationship of the relative abundances of the sulfide mineral species that are crucial to the Olympic Dam smelter performance. Several geostatistical techniques have been utilised in the workflow for the Olympic Dam Conditional Simulation model to address these challenges. The key techniques are: • Projection Pursuit Multivariate Transform to de-correlate the main elements before simulation. • Pluri-Gaussian implicit boundary simulation method to simulate the mineralisation domains. • Spectral simulation method of de-trended and de-correlated attributes with account of local varying variance. The resulting conditional simulation models have been validated against histograms, grade-tonnage curves, cross-plots and assessed for variogram reproduction. This paper presents how the final conditional simulation models compare to benchmarking models created using alternate estimation techniques of ordinary kriging and local uniform conditioning. It also presents a validation process using historical samples to test final estimate accuracy of the simulation models.

May 24, 2023

By J P. Evert

Didipio gold-copper mine operation is situated in the island of Luzon, approximately 270 km north of Manila in the Philippines, in an area of high seasonal rainfall. The hydrogeological water flow model implied that there would be high connectivity between regional structures and underground operations. This model predicted that underground mine groundwater inflows were expected to quickly rise as the decline progressed to a peak of 510 L/s. Designing a capital pump station to deal with 510 L/s has its own challenges, however developing the decline down to the required level, always dealing with 300 L/s of water and constructing the pump station is extremely challenging and required a robust water management plan and mine design. When dealing with expected high volumes of water, underground mine design and scheduling plays a key role in protecting electrical infrastructure, equipment, secondary pumps, and the decline from flooding. A good drainage system and controlled dewatering plan is essential for safety and progress. This paper details the dewatering techniques and mine designs required to accomplish decline development with high water inflows as used in the Didipio project. It will describe the learnings and outcomes that are achievable with a flexible design, as new structures are mapped, and water intersections are increased. It also highlights the potential for adaptability in mine planning to provide evolving improvements or to evade problems that are expected from the constant reconciliation of data recorded during development.

Mar 29, 2023

By E Kabwe, M Karakus

Deep hard rock underground mines tend to experience high stress as such drives exhibit dynamic responses attributed to a rock burst variant (strainburst). This dynamic behaviour is difficult to predict, and every effort is made to devise the appropriate dynamic support system for its associated failure restraint. This paper outlines the back analysis and the support scheme design for an underground decline that exhibited damage from a dynamic strainburst occurrence. It employs a decline section that experienced a dynamically loaded strainburst that initiated rock fragment ejections. The procedure involves a preliminary structural analysis, a seismic intensity measure, and a rock mass simulation to determine the static stress concentration and ground support system response. The numerical simulation is conducted in FLAC3D which employs the advanced strain-softening IMASS constitutive model governed by two Hoek–Brown (HB) bounding yield surfaces. To account for the post-peak brittleness response associated with strainburst the plastic strain multiplier () is adjusted to 0.0 < < 1.0. The back-analysis shows that the occurrence was initiated by a low-intensity seismic wave that superimposed an extra stress component to the initial static stress which triggered rock fragment ejections. Additionally, the appropriate support scheme comprised of Weldmesh, Fibrecrete, static (split set) and yieldable (Kinloc) reinforcements is recommended and implemented. Thereafter, the bolt’s efficiency is evaluated based on the axial force and elongation capacities and then compared with the published bolt performance data. The evaluation results show that the maximum bolt axial force (0.1 per cent) and elongation (0.006 per cent) are below the designed capacity and rupture strain.

Nov 29, 2022

By N Barnett, M Dello-lacovo, J Oh, S Saydam, T Pelech

In-Situ Resource Utilisation and Off-Earth mining require the application of horizontal drilling. The stability of such openings is challenging when excavating in the lunar regolith. Excavations on the Moon will encounter unconventional operational conditions such as different material properties, low gravity, and a moonquake. Micro-tunnelling or drilling to support lunar exploration and development of infrastructure on the Moon requires stability analysis to ensure its desired performance. The discrete element method (DEM) modelling technique has been utilised to investigate the optimum opening sizes on the lunar soil. From the literature, the mechanical properties of the lunar regolith have been reviewed and used for numerical model development. The model has been calibrated by simulating numerical triaxial tests with the Mohr–Coulomb failure criterion. Then, detailed parametric studies have been performed to investigate the influence of confinement, opening dimensions and moonquakes on the stability of openings. The findings have led to the development of a simple stability chart of the relationship between unsupported opening sizes and lunar regolith properties at different depths.

Nov 29, 2022

By C Zhang, G Si, J Oh, X Zhu

The presence of rock joints has a huge impact on the strength, deformability, and permeability of fractured rock masses by providing surfaces of weakness on which further deformation are more prone to occur, and by serving as the major channels of water flow due to low matrix permeability. In earlier studies, water flow-through rock joints is often assumed as laminar flow between two ideal smooth parallel plates, and the well-known cubic law was derived and widely used to characterise the hydraulic behaviour of rock joints. However, natural rock fractures are irregular and of spatially varied aperture. Thus, the concept of equivalent hydraulic aperture was introduced to modify the cubic law. Numerous works have been conducted on the relation between hydraulic aperture and mechanical aperture incorporating various geometrical parameters. The surface roughness is one of the most sensitive factors for water flow-through rock joints. The aperture distributions are irregular in natural roughed fractures relative to the parallel plates. Barton et al (1985) and Olsson and Barton (2001) incorporated the joint roughness coefficient JRC in evaluating hydraulic aperture and proposed an empirical equation based on fluid flow tests. However, their equations do not conform to the dimensional consistency. Many other researchers (Zimmerman and Bodvarsson, 1996; Xiong et al, 2011; Li et al, 2019) considered aperture distributions in their equations. But the aperture distributions change during shear was always neglected. The contact of rock joints also has a significant impact on the hydro-mechanical behaviour of rock joint, since fluid tends to flow-through a rough joint along connected channels while bypassing the contact obstacles with tortuosity. Nonetheless, previous research mostly considered joint roughness or aperture changes based on 2D joint profiles, while the contact and tortuosity based on 3D surfaces were often overlooked. Only a few works have been made on quantifying the effect of contact area on flow behaviour (Walsh, 1981; Zimmerman et al, 1992; Zimmerman and Bodvarsson, 1996; Yeo, 2001), and mostly ignored contact area change induced by shearing and the associated impact on flow behaviour. Summarily, the quantification of fracture geometry effects on water flow in single rock joints still needs further investigation, especially when considering coupled shear-flow processes. This paper, therefore, aims to study the impacts of contact area and aperture distributions of the single rock joint on the flow behaviour. The evolutions of contact area and aperture distributions induced by shear are considered. Then, an improved model for estimating the hydraulic aperture with the mechanical aperture incorporating the above factors is developed. Finally, a series of shear and shear-flow tests are conducted on artificial joint samples and the model performance is verified by comparing against the results of experimental tests.

Nov 29, 2022

By T Wang, D Wang

Photogrammetry-based techniques supported by traditional mapping tools are more frequently used for open pit geotechnical mapping. It fundamentally involves the collection of geological, structural and rock mass data from pit batters when safe to do so. These are essential components for refining and implementing continuous improvements to geotechnical models. The geotechnical model is used to review bench performance, optimise geotechnical design parameters, interpretation and analysis of pit slope stability. This paper is a case study of implementing different pit mapping methods at Mount Carlton gold mine, North Queensland. It critically reviews the tools required, including the Brunton compass, mobile application Clino, geotechnical data mapping software CloudCompare (2015) and Sirovision software. The review compares the image precision, structural measurements and data analysis. The review also underlines mine site management philosophy for safe geotechnical data collection to identify in-pit geotechnical hazards and the mitigation of potential slope instability. Sirovision is a remote sensing system for site geology mapping and interpreting geotechnical characteristics of exposed mining faces. The system utilises off-the-shelf digital SLR cameras to capture stereo photographs of the rock face and uses the latest image processing technology to generate accurate 3D models. These 3D models are digitally analysed using computational geometry to extract unbiased and accurate geological and geotechnical data. CloudCompare processes high accuracy 3D dense cloud rock surfaces reconstructed with photogrammetry software to extract the geological planes using the FACET or Compass plugins. The major discontinuity sets can be observed and the orientation (dip/dip direction) obtained from the algorithm is accurate and reliable for geotechnical assessment, including kinematic and rock slope stability analysis.

Nov 29, 2022

By R W. Henley, L Knuefing, M Turner, Y Zhang, M Saadatfar, A Limaye, R Cruikshank, M A. Knackstedt, A Kingston, L Beeching, N Francois

A better understanding of ore fragmentation and the textural features of ore is a key to the energy efficient extraction of targeted minerals from low-grade ore deposits. In this study, X-ray microcomputed tomography (micro-CT) is employed to study mineral liberation during the tensile failure and onset of fragmentation of a copper ore. Our results show that X-ray micro-CT could inform new studies of ore micromechanics and fragmentation at the laboratory scale and may offer new avenues to address current challenges in the design of efficient comminution processes. We present the results of experiments based on a high-pressure apparatus enabling micromechanical studies to be carried out in situ (inside a micro-CT scanner). This platform produces high-quality 3D images of the evolution of a sample of porphyry copper ore during an in situ fragmentation test. A sequence of tomographic images enables mapping in 3D of both the deformation of mineral phases and the fragmentation process. The fragmentation occurs quasistatically through multiple stages starting with an initial tensile fracture splitting the ore diametrically, followed by tensile-activated nucleation and growth of multiple fractures producing a complex fracture network. Coupling breakage with microstructural information enables quantitative determination of the impact of ore texture heterogeneity on fracture patterns and mineral liberation. This microstructural information can be compared to key measurements of the ore mechanical behaviour such as the global deformation energy, strain deformation field and the stress relaxation response. The latter allows one to identify interesting precursor signals of the tensile failure. The copper liberation, fragment size distribution and breakage patterns are statistically characterised and related to comminution mechanisms which are clearly identified in the sequence of tomographic images. The two dominant mechanisms are rock-rock friction/compression induced by fracture closing and compression-driven fragmentation at rock-crusher contact points.

Aug 24, 2022

By T Perera, B Fan, S Thang, T Hsia

The mining industry is currently focusing to develop and adopt sustainable collector chemistry that can efficiently recover valuable minerals from their natural state. However, a limited number of research can be seen on the design and synthesis of polymeric flotation collectors. The focal objective of this research is to synthesise a more effective polymeric collector with advanced architecture to utilise in the mineral processing industry. Reversible Addition-Fragmentation Chain Transfer (RAFT) co-polymers with cardanol derivatives have the potential to selectively trap valuable metals in the flotation process in a more efficient way. Cardanol exhibits amenability to chemical modification for making tailor-made monomers that can further produce polymers with high value. The synthesis of a series of fit for purpose copolymers in this study was accomplished by RAFT polymerisation. The ability to design complex architecture is a significant advantage in engineering polymeric collectors by RAFT polymerisation. Initially, commercially available cardanol was converted to a cardanol based monomer and copolymerised with commercially available monomers to synthesise a series of novel cardanol based copolymers with predetermined molecular weights. The side groups of the copolymer were chemically modified to incorporate functionality that can be selectively adsorbed on the chalcopyrite surface.

Aug 24, 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 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 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 J R. Ruiseco, D La Rosa, L Julian, W Hunt

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

Mar 22, 2022