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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 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 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 C B. Smith, G L. Boxer, S W. Moss, A L. Jaques, V Lorenz, M J. Rayner

The Ernest Henry Iron Oxide Copper Gold deposit is hosted in a large dilation between two moderately dipping shear zones found in the footwall and hanging wall of the deposit. These shears are controlled by a large diorite intrusion to the north-east and south-west of the deposit, formed ~1660 Ma. A shear zone dubbed the ‘Interlens’ uncovered through underground workings truncates the main orebody into two lenses, and is hypothesized to have formed in conjunction with the Hanging Wall Shear Zone and Footwall Shear Zone. All three shears dip moderately to the SSE (50–140) from open cut exposures through to the current mining horizon approximately 800 m below the surface. Routine geological work and a capital drilling campaign has identified a significant flexure in these sub parallel ore bounding shears with increasing depth. A shift in shear orientation in the Interlens over approximately 100 m vertically from ~50° to the SSE to a steep, easterly trend (~85° to the east) is observed in both drill core and exposures in the underground workings. It is hypothesized the diorite intrusive to the south-west of the deposit controls the shear zone geometries at depth. The geometry of the Interlens mirrors the surface expression of the Proterozoic package of the orebounding shears to the south-west of the deposit, suggesting the surface geometries of the shear zones are consistent with depth. Additional drilling to explore the validity of this hypothesis is planned for the near future to better understand the structural controls on the Ernest Henry mineralisation with increasing depth.

Mar 22, 2022

By P C. J Blackney, I M. Glacken

Spotted Quoll is a massive sulfide nickel deposit located in the Forrestania greenstone belt in the Archaean Yilgarn block in Western Australia. Discovered in October 2007, mining has progressed from open pit to underground and currently uses longhole open stoping with paste fill as the primary stoping method. Immediately prior to 2019, the Mineral Resource estimate (MRE) was defined by a single grade domain of nickel greater than or equal to 0.8 per cent, irrespective of the host lithology, a legacy of the original ore wireframe being built using explicit methods. While a number of obvious structural offsets were honoured in this nickel grade domain, only one modelled fault was used to undertake domaining of arsenic. From 2019 onwards, implicit modelling in Leapfrog Geo™ was used to construct a mine-scale geological model, which triggered the definition of a high-grade core of massive/matrix nickel sulfides surrounded by a low-grade halo of stringer/disseminated nickel sulfides in the surrounding rock. As part of the evolution of the geological model and with the aid of Seequent Central™ to allow collaboration between site-based mine geologists, Perth-based resource geologists and Melbourne-based consultants, a detailed review of the structural mapping was carried out as additional information from underground development became available. This allowed numerous faults and shears to be identified – particularly in the lower half of the mine. These were used to define further structural domains and to refine the understanding of the nickel and arsenic grade distributions in the mineralised envelope. The increased definition to the domains provided by the geological model resulted in a significant improvement in the accuracy of the Mineral Resource estimate, as measured by reconciliation using voids of the mined stopes determined from the cavity monitoring survey (CMS).

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

Resource characterisation is critical for informed decisions in both strategic and operational space. The sources of information for resource characterisation are limited by: direct measurement of resource attributes, such as grades, rock-types, mineralogy, and are available only from sparse locations, ie drill holes; or indirect geophysical measurements such as seismic, gravity or electro[1]magnetic survey. Data collection tools, methods, and processing technologies are constantly improving providing a broad spectrum of options for data collection strategies. The cost of each data survey varies from thousands to millions of dollars with the value of each additional data having diminishing return for a particular business decision. The value of information analysis provides the optimal decision on data collection strategy within a limited available budget. This work presents an example of value of information analysis for new Blast Hole Assay Tool (BHAT) and Reverse Circulation Grade Control (RCGC) data used in addition to the wider spaced exploration data. The value of information is quantified in terms of reduction of grade uncertainty, ore loss and dilution by comparing different combinations of data collection methods. Four different strategies were considered: exploration samples in addition to 50 per cent of blastholes surveyed with BHAT, exploration samples in addition to 33 per cent of blastholes surveyed with BHAT, exploration with wide-spaced RCGC data, and exploration without additional grade control. For each strategy the observed values have been simulated using advanced multivariate geostatistical simulations and compared with simulated ground truth models. The calculated uncertainty, ore loss and dilution informed the optimal data collection strategy. Opportunity to reduce sample density from the nominal 50 per cent of drill holes was evaluated.

Mar 22, 2022

By A Boucher, M Baudin, P Androszczuk, I Minniakhmetov, A Rigby, P Machado, M Wright, B Van Dijken

IGO Ltd’s (IGO’s) Nova Operation (Nova), which is 160 km east-north-east of the town of Norseman in Western Australia (WA), mines and processes nickel-copper-cobalt (Ni-Cu-Co) sulfide ore from the magmatic Nova-Bollinger Deposit (Nova-Bollinger), which is hosted by the Mesoproterozoic age high-grade metamorphic rocks of the Albany Fraser Orogen. Over its 56-month life-of-mine (LOM) operations to 31 December 2020, Nova has processed 5.63 Mt of ore grading 2.04 per cent Ni, 0.86 per cent Cu and 0.07 per cent Co from its underground mine. At the end of 2020, both the Nova-Bollinger JORC Code reportable Mineral Resource estimate (MRE) and Ore Reserve estimate (ORE) were >90 per cent classified in the highest JORC Code confidence categories of Measured Mineral Resource and Proved Ore Reserve respectively. The high JORC Code classification confidences assigned to the Nova-Bollinger MRE and ORE results from the 386 km of surface and underground diamond drill testing of the deposit to a nominal 12.5 by 12.5 m pierce point spacing in mineralisation. The close spaced high-quality drilling and bulk mining method employed at Nova has effectively removed the need for any grade control modelling outside of the MRE process. Importantly, having only the one fully drilled out deposit being mined and only the one process plant, Nova’s reconciliation process is in the fortunate situation of not being confounded by issues such as external ore sources and constant updates as new grade control information becomes available. IGO’s Nova reconciliation processes are focused on reconciliation ratios that quantify operational period differences between the MRE and ORE head grade and tonnage forecasts and the process plant head actuals. These metrics have been used to identify key reconciliation issues and have initiated several studies into the causes for specific reconciliation results, which are discussed in the paper. In late 2020, a period of sustained poor reconciliation results led to the recognition that increasing the understanding of risk between the MRE and ORE should be investigated. To assist with modelling stope level risk within the mine plan and subsequent reconciliation, an attempt was made to develop a formula to quantify ‘stope risk’ from MRE metrics such as sample spacing, kriging efficiency and so on

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 T Walton, C Perring, M Pepper, G Gerber

The Yandicoogina Channel Iron Deposit (CID) is an accumulation of iron pisolites cemented by a goethite-rich matrix. The Yandicoogina CID’s are found in a palaeochannel that meanders within a broad structural basin of the Yandicoogina Syncline in Pilbara region of Western Australia. RTIO Yandicoogina Mine Geology team contributed to a number of strategies maximising the iron ore reserves mined by Rio Tinto. Two strategies are discussed: the replacement of the Batter-Berm final pit walls by contour dozing; and upgrading the lower grade material to crusher feed. 1. Contour dozing – traditional Batter-Berm pit final wall configuration left kilometre long wedges of ore sterilised around bench margins. Contour dozing final walls (ie dozing of ore down the ore-waste contact) as internally defined by RTIO Yandicoogina Mine Geology (Mine Geology), enabled recovery of additional crusher feed. 2. Upgrade of lower grade material – the lower ore domain (GVL) within the Yandicoogina orebody contains numerous clay pods. Contaminant Al2O3 inherent within clay pods can result in CID material outside of crusher feed grade specifications, causing it to be flagged as ‘internal waste’ in mining models and permanently lost to waste dumps. In 2011, after multiple tests, Mine Geology demonstrated that this material could be upgraded to crusher feed via wet processing. With the support of the RTIO Metallurgical Development team new grade specifications were defined. The resulting material has been used to supplement higher grade ore. While increasing the mining ore output, these ongoing value-adding strategies also promote more sustainable mining via better use of the non-renewable iron ore commodity. The initiatives extend mine life, reduce waste movement, improve strip ratio and increase productivity

Mar 22, 2022

By O Dominguez

Mine value chain reconciliation (MVC) is a necessary procedure to evaluate a mine’s performance against the assumptions and models used to plan mining and processing operations. Using nomenclature from Parker (2012), F2 reconciliation is the ratio between material received at the mill, compared with material sent to the mill, commonly reported in terms of tonnes, grade and metal. Measurements of material sent to the mill can be estimated in many ways, including: fleet management system (FMS) records, truck counts, or volume reduction. Most time-based reconciliations (for example, month-end reconciliation) use short-term model depletions of in situ rock measured by periodic topographic scans or surveys.

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

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

Mar 22, 2022

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

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

Mar 22, 2022

By N Anderson

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

Mar 22, 2022