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

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

Mar 22, 2022

By P J. Willems, B J. Junor

Blackwater Mine is in the central-southern Bowen Basin, immediately south of the township of Blackwater on the Capricorn Highway. The current open cut operation extracts coal from three main seams, designated Top, Middle and Lower, in the Late Permian Rangal Coal Measures cropping out on the eastern flank of the Comet Ridge. Complex geological structures, dominated by E-W normal faults and N-S reverse faults, have significant detrimental effects on coal mining operations. Historical exploration before 2010 involved several types of drilling only to understand structure, coal quality and washability. Hence, although drilling data was combined with limited pit mapping and observation, unknown structures were still often encountered during excavations and led to mining surprises. In 2010 BHP completed 200-line km of closely spaced 2D seismic survey to capture gross and detailed structures followed by fit for purpose structural drilling to confirm major structures in the northern part of the mine. In 2018 a high density 9.2 km2 3D seismic survey was completed in the southern part of the mine. Subsequently, a 17.2 km2 survey was completed in 2020 to cover the northern active mining area. It allowed geoscientists to successfully map previously unknown major faults and seam splits, which could potentially impact the mineability of the area. It is important to note, that faults interpreted using modern high-density 3D data can be interpreted with dramatically higher confidence in the fault dip and azimuth orientation in comparison to the legacy 2D data. Along with targeted drilling, pit mapping and structural interpretation, the outcome adds value to mine planning and operations. This paper outlines recent successful seismic 3D data acquisition and interpretation. In detail, the paper presents case studies on how the data can be incorporated into a structural model to improve geological knowledge, enable geotechnical assessment, and support safe and efficient coal mining in a large and structurally complex mine.

Mar 22, 2022

By M Haest, S Sandler, R Botha, H Lang, K Hume

Benchmark practices in the mining industry include the establishment of Quality Programs — Quality Assurance and Quality Control (QAQC) — to monitor the correct execution of sampling protocols and control each stage of the ‘Sample Cycle’: Sample Collection, Preparation (comminution) and Analysis. QAQC reports commonly include statistical-numerical results that quantify performance of QAQC controls (field duplicates, preparation duplicates, blanks, standards etc). Graphics such as scatter plots, QQ plots, histograms and cumulative frequencies are used to represent the results. Statistical values including relative difference, absolute difference, relative variance, averages, T-test, and Zscores are used to quantitatively express the relationship between duplicate pairs ... but is an effective quality program just a statistical exercise? This paper aims to highlight the concept of ‘Quality Management’ (QM) as the precursor of continuous monitoring (ideally in real time) of QAQC results on Exploration, Production, Processing and Port samples, determined by trend analysis performed on a time and/or grades basis. Currently, there is a paradigm in the process of quality assurance that if individual data points fall within a predetermined acceptance limit then they are ‘acceptable’ and therefore suitable for informing operational and investment decisions. However, what is stated with respect to QM is that sometimes results found within the acceptance limits can indeed be internally biased, or show material deviations over a period of time, thereby impacting reconciliation results and/or potentially creating discrepancies with the final buyers. QM refers to the proactive detection of these ‘anomalous tendencies’, the approach and communication with the source of the information, the understanding of the reasons that cause the deficiencies, and the generation of agreed action plans to remediate the situation and ensure the consistency of results, in other words: continuous improvement on proactive manners.

Mar 22, 2022

By A Kleinitz, J Halilovic, K Trappitt

Mine operators use grade control to determine the destination of each block of material in the mine. In polymetallic mines, grades are best expressed in dollars: the Net Smelter Return, NSR, per tonne. To estimate NSRs, geologists working on grade control develop models for each geometallurgical domain in the mine. These models may incorporate observations on the mineralogy and grain sizes of the material being examined. The site’s mill operators contribute to the models by providing geologists with statistical analyses that relate assay results and mineralogical compositions to metallurgical parameters, such as the rates of recovery of each economic metal to each of the concentrates produced, and the compositions of those concentrates. The team responsible for sales and marketing of the site’s products contributes to the NSR models by providing details of the costs of shipping concentrates to smelters and refineries; and by providing figures that are specified in the smelter contracts, such as the payability of the metals in each concentrate and the fees charged by the smelter. The mill operators also provide, for the NSR models, equations to estimate the rates of recovery of deleterious materials to each concentrate. Deleterious materials comprise mostly halogens and amphoteric elements, both of which reduce the efficiency of smelters. Furthermore, deleterious materials such as antimony and arsenic may be poisonous to people and to the environment. The sales and marketing team provide specifics of the penalties that smelters impose upon deleterious materials. These penalties may reduce NSRs by tens of percent, possibly to levels below the cut-off grade. Thus, in the blocks that are subject to grade control, mine geologists monitor not only the concentrations of economic metals, but also the presence and abundance of deleterious materials. The preparation and maintenance of models, to estimate NSRs and to assess changes in the levels of potentially toxic materials to be mined, requires close and continuing consultation between corporate departments. There must be strong communication of mine geologists with the mill operators; with the people who market the mine’s concentrates; and, should there be a risk of encountering toxic levels of deleterious materials, with the mine’s health, safety and environmental officers. This co-operation could require radical changes in the structure of many organisations. However, experience suggests that such changes can significantly improve the profitability of a mine.

Mar 22, 2022

By M Forbes, R Jeuken

Brownfields geoscience measurement such as drilling and surface geophysics can be costly and it is often difficult to weigh the cost of data collection and processing against the value it unlocks at the time of extraction. This makes it difficult to prioritise geoscience expenditure and find the optimum intensity of geoscience activity across competing assets. There are multiple options for managing resource uncertainty and spatial variability through mine planning and resource engineering such as varying marketing strategy, adjusting stockpile or other infrastructure design and product blending. Consideration of these alongside increased data collection further complicates finding a comparable value of geoscience programs to determine the right blend of geoscience measurement and engineering controls. Concepts similar to Value of Information (VOI) analysis which is applied to strategic planning can be used to estimate the value of geoscience measurement and pit sequencing at tactical planning and operational timescales. This involves the quantification of resource uncertainty and prediction of how it will affect resource extraction. This paper outlines this process and demonstrates its use to prioritise geoscience at BHP Coal Assets. The value of infill drill programs in enabling operational stability is quantified and compared the value of engineering controls like increased stockpile capacity. This study supports that idea that the application of VOI methods to bulk mining at tactical time horizons has potential to inform geoscience planning and resource engineering not just separately, but as part of a unified strategy for managing resource uncertainty.

Mar 22, 2022

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 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 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 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 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 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

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 Pranoto, E Lawell, T Dean, M Grant

The Goonyella Riverside Mine is located 30 km north of Moranbah in Central Queensland, Australia. Recent mining activities have exposed the north–south striking Kenya and Zimbabwe thrust Faults. These faults vertically offset coal seams by up to 25 m and locally thicken coal packages through imbrication of coal seams. The presence of back-thrusts add to the geotechnical complexity of maintaining highwall stability. The Kenya and Zimbabwe Faults have provided multiple challenges to the mining operation, with an unplanned additional 240 kt of coal tonnes being mined from imbrication of coals seams or from the refinement to local scale geological models. These additional coal tonnes have been either identified during the mining of the coal seam or just prior to overburden removal above the coal seam. These faults can also negatively impacted highwall stability with highwall failures, lowering the overall slope angle for pit designs and increasing stand-off distances for hazardous highwall conditions. Unmanned Aerial Vehicles are used to scan exposed highwalls and enable geological mapping via high-quality 3D images. Measure while drill data from drill and blast rigs can provide local-scale intersections of the faults and coal seams. Mine Geologists utilise these and other data sets to create localised geological models refined position of the fault planes and coal seams. These models are utilised by relevant mine site teams to ensure the safe and efficient mining of coal around these faults.

Mar 22, 2022

By H S. Pescini

A material aim when feeding ore blends into a processing facility is to reduce the variability of the properties of the feed material and to maximise the output, or throughput. At the Mining Geology conference of 2019, we presented a paper on optimal blending of coking coal given geological variability. The paper introduced integer-programming techniques to both maximise value and minimise feed or product variability. We discussed an application where the geological uncertainty is characterised using a normal distribution and exact solutions are readily obtainable using second order conic constraints in the mathematical model. Geological uncertainty is not always normally distributed, many properties will be characterised as log normal or some other skewed distribution. For example, copper can be some form of lognormal and Fe in Iron ore has a left skewed distribution. In this paper, we discuss some distribution free techniques to optimise the blends of plant feed or output given a quantified geological uncertainty. We discuss the sample average approximation method and how to set-up and apply the method to an ore blending problem. Evaluating a case study demonstrates that the explicit use of non-normally distributed geological uncertainty can better optimise feed into an ore processing facility and potentially add significant value. The approach is equally applicable to all mining and processing operations that blend material into a processing facility or directly into a saleable product.

Mar 22, 2022

By R J. Goldie

The Monty Copper Gold Deposit is an ultra-high grade mine in Sandfire Resource’s Doolgunna region which was completely drilled out and developed within two years of commencing mine development. During this period, a total of 986 grade control diamond drill holes were completed, assayed, and validated, 15 levels developed, and 3136 faces mapped. The aggressive schedule meant a high flow of geological data was produced, validated, and incorporated into regular geological model updates. To process this data at a rate which allowed for timely use, more robust data processing methodologies needed to be generated. A new validation system was implemented which required two levels of validation being applied to any diamond drilling update. Step one was the validation of initial physical data including survey pick-ups and logging. This was done prior to new drill data being added to the geological model. Step two was the validation of assay data which was required prior to resource estimation. The implementation of Seequent’s Leapfrog Geo modelling software also allowed for a more seamless and efficient modelling workflow. The use of the Leapfrog Geo vein systems allowed for more rapid generation of geological models which then afforded more time for stringent assessment of the mineralisation system. An example of this was the introduction of cross-shift peer reviews in which opposing rosters of geologists would rigorously evaluate the previous rosters work prior to reporting. This additional level of validation resulted in more robust geological models and the identification of new ore trends. This presentation will detail the evolution of the Monty Geological model from a simple tabular indicated resource into a complex highly refined measured resource. Themes will include how the model was produced using workflows developed and optimised to meet key deliverables.

Mar 22, 2022

By M Akop, G Phillips, L Elliott

An estimation geologist has many tools in their kit and using the correct one for the job is vital for creating a useful model. Reconciliation is a key step to monitor the performance of a resource model and to ensure the correct tools have been selected and appropriate parameters are set. This paper presents an example of refining the estimation methodology for a Channel Iron Deposit (CID), resulting in an improved model. Rio Tinto Iron Ore (RTIO) CIDs are unique iron ore deposits located in the Pilbara region of Western Australia and contribute a significant volume to the world’s seaborne iron ore market. A problematic feature of these deposits is the irregular dispersion of clay pods that cannot be delineated with confidence within the resolution of the exploration drilling. Resource to grade control reconciliation showed an over-prediction of high-grade material in the resource model. A fresh approach was required to improve grade and tonnage predictions. Historically, clay pods were delineated using traditional wireframing techniques and estimated using ordinary kriging with hard boundaries. The new method utilised indicator kriging to estimate the probability of clay. Probabilities generated from the indicator kriging estimate were used as an additional weighting following the ordinary kriging of grades. Results showed indicator kriging improved global high-grade tonnes reconciliation, however, as expected, it did not improve the spatial prediction of clay. Based on improved reconciliation results indicator kriging has now been adopted as a suitable alternative for analogous CIDs at RTIO. These improvements benefit the mine planning process, but do not replace grade control models.

Mar 22, 2022

By W Patton, I Minniakhmetov, H Talebi, U Mueller

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

Mar 22, 2022