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Special Issue "Geometallurgy"

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A special issue of Minerals (ISSN 2075-163X).

Deadline for manuscript submissions: closed (28 September 2018) | Viewed by 88927

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Special Issue Editors

Dr. Simon Dominy

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Guest Editor

Camborne School of Mines, University of Exeter, Penryn, Cornwall TR10 9FE, UK
Interests: economic geology; mineral exploration; orebody knowledge; geometallurgy; mining geology
Special Issues, Collections and Topics in MDPI journals

Dr. Louisa O’Connor

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Guest Editor

Western Australian School of Mines, Curtin University, Perth, WA 6102, Australia
Interests: ore characterisation; process mineralogy; comminution; geometallurgy; critical metals; in-situ leaching; microwave comminution; ore strength reduction

Dr. Anita Parbhakar-Fox

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Guest Editor

ARC Transforming the Mining Value Chain (TMVC) Industrial Transformation Research Hub, University of Tasmania, Hobart, Tasmania 7001, Australia
Interests: environmental geochemistry and mineralogy; environmental geometallurgy; mine waste characterisation; acid rock drainage prediction

Special Issue Information

Dear Colleagues,

Geometallurgy has reached maturity, beyond its early simplistic “geology + metallurgy” conception. It is recognised as an approach that can both maximise value and predict the risks associated with resource development. Modern geometallurgy seeks to integrate geoscientific disciplines with minerals and mining engineering. It aims to understand grade, geoenvironmental, metallurgical and mining variability based on information, such as geochemistry, mineralogy and lithology, obtained from spatially-distributed samples or sample points. Multiple spatially-distributed small-scale tests are used as proxies for grade, mineralogy, process parameter and rock mass variability. These data allow 3D block modelling across relevant parameters, that can then be fed into the mine plan. Geometallurgy vastly increases stakeholder collaboration and communication, creating an environment for knowledge sharing and improved data acquisition and interrogation, with the end result being the integration of such data into mine planning and scheduling. This Special Issue aims to bring together all aspects of geometallurgy; we particularly welcome case studies.

Dr. Simon Dominy
Dr. Louisa O’Connor
Dr. Anita Parbhakar-Fox
Guest Editors

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Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Minerals is an international peer-reviewed open access monthly journal published by MDPI.

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Keywords

Sampling and Theory of Sampling
Ore and waste characterisation
Geometallurgical test work
Deterministic and probabalistic modelling
Mine planning and optimisation
Financial analysis
Risk assessment
Acid mine drainage forecasting
Reprocessing of waste rock and tailings
Value drivers of geometallurgy
Geometallurgical programme design and management
Tactical and strategic geometallurgy
Case studies

Published Papers (15 papers)

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Research

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Open AccessFeature PaperArticle

Incorporation of Geometallurgical Attributes and Geological Uncertainty into Long-Term Open-Pit Mine Planning

and

Minerals 2019, 9(2), 108; https://doi.org/10.3390/min9020108 - 13 Feb 2019

Cited by 25 | Viewed by 7877

Abstract

Long-term open-pit mine planning is a critical stage of a mining project that seeks to establish the best strategy for extracting mineral resources, based on the assumption of several economic, geological and operational parameters. Conventionally, during this process it is common to use deterministic resource models to estimate in situ ore grades and to assume average values for geometallurgical variables. These assumptions cause risks that may negatively impact on the planned production and finally on the project value. This paper addresses the long-term planning of an open-pit mine considering (i) the incorporation of geometallurgical models given by equiprobable scenarios that allow for the assessing of the spatial variability and the uncertainty of the mineral deposit, and (ii) the use of stochastic integer programming model for risk analysis in direct block scheduling, considering the scenarios simultaneously. The methodology comprises two stages: pit optimization to generate initial ultimate pit limit per scenario and then to define a single ultimate pit based on reliability, and stochastic life-of-mine production scheduling to define block extraction sequences within the reliability ultimate pit to maximize the expected discounted value and minimize the total cost of production objective deviations. To evaluate the effect of the geometallurgical information, both stages consider different optimization strategies that depend on the economic model to be used and the type of processing constraints established in the scheduling. The results show that geometallurgical data with their associated uncertainties can change the decisions regarding pit limits and production schedule and, consequently, to impact the financial outcomes. Full article

(This article belongs to the Special Issue Geometallurgy)

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Open AccessArticle

A Hybrid Approach for Joint Simulation of Geometallurgical Variables with Inequality Constraint

Yerniyaz Abildin

Nasser Madani

and

Erkan Topal

Minerals 2019, 9(1), 24; https://doi.org/10.3390/min9010024 - 04 Jan 2019

Cited by 17 | Viewed by 3684

Abstract

Geometallurgical variables have a significant impact on downstream activities of mining projects. Reliable 3D spatial modelling of these variables plays an important role in mine planning and mineral processing, in which it can improve the overall viability of the mining projects. This interdisciplinary paradigm involves geology, geostatistics, mineral processing and metallurgy that creates a need for enhanced techniques of modelling. In some circumstances, the geometallurgical responses demonstrate a decent intrinsic correlation that motivates one to use co-estimation or co-simulation approaches rather than independent estimation or simulation. The latter approach allows us to reproduce that dependency characteristic in the final model. In this paper, two problems have been addressed, one is concerning the inequality constraint that might exist among geometallurgical variables, and the second is dealing with difficulty in variogram analysis. To alleviate the first problem, the variables can be converted to new variables free of inequality constraint. The second problem can also be solved by taking into account the minimum/maximum autocorrelation factors (MAF) transformation technique which allows defining a hybrid approach of joint simulation rather than conventional method of co-simulation. A case study was carried out for the total and acid soluble copper grades obtained from an oxide copper deposit. Firstly, these two geometallurgical variables are transferred to the new variables without inequality constraint and then MAF analysis is used for joint simulation and modelling. After back transformation of the results, they are compared with traditional approaches of co-simulation, for which they showed that the MAF methodology is able to reproduce the spatial correlation between the variables without loss of generality while the inequality constraint is honored. The results are then post processed to support probabilistic domaining of geometallurgical zones. Full article

(This article belongs to the Special Issue Geometallurgy)

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Open AccessArticle

Automated Acid Rock Drainage Indexing from Drill Core Imagery

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Minerals 2018, 8(12), 571; https://doi.org/10.3390/min8120571 - 04 Dec 2018

Cited by 7 | Viewed by 3244

Abstract

The automated classification of acid rock drainage (ARD) potential developed in this study is based on a manual ARD Index (ARDI) logging code. Several components of the ARDI require accurate identification of sulfide minerals that hyperspectral drill core scanning technologies cannot yet report. To overcome this, a new methodology was developed that uses red–green–blue (RGB) true color images generated by Corescan^® to determine the presence or absence of sulfides using supervised classification. The output images were then recombined with Corescan^® visible to near infrared-shortwave infrared (VNIR-SWIR) mineral classifications to obtain information that allowed an automated ARDI (A-ARDI) assessment to be performed. To test this, A-ARDI estimations and the resulting acid-forming potential classifications for 22 drill core samples obtained from a porphyry Cu–Au deposit were compared to ARDI classifications made from manual observations and geochemical and mineralogical analyses. Results indicated overall agreement between automated and manual ARD potential classifications and those from geochemical and mineralogical analyses. Major differences between manual and automated ARDI results were a function of differences in estimates of sulfide and neutralizer mineral concentrations, likely due to the subjective nature of manual estimates of mineral content and automated classification image resolution limitations. The automated approach presented here for the classification of ARD potential offers rapid and repeatable outcomes that complement manual and analyses derived classifications. Methods for automated ARD classification from digital drill core data represent a step-change for geoenvironmental management practices in the mining industry. Full article

(This article belongs to the Special Issue Geometallurgy)

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Open AccessArticle

Forecasting Geoenvironmental Risks: Integrated Applications of Mineralogical and Chemical Data

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Minerals 2018, 8(12), 541; https://doi.org/10.3390/min8120541 - 22 Nov 2018

Cited by 20 | Viewed by 3807

Abstract

Management of solid mine wastes requires detailed material characterisation at the start of a project to minimize opportunities for the generation of acid and metalliferous drainage (AMD). Mine planning must focus on obtaining a thorough understanding of the environmental properties of the future waste rock materials. Using drill core obtained from a porphyry Cu project in Northern Europe, this study demonstrates the integrated application of mineralogical and geochemical data to enable the construction of enviro-geometallurgical models. Geoenvironmental core logging, static chemical testing, bulk- and hyperspectral mineralogical techniques, and calculated mineralogy from assay techniques were used to critically evaluate the potential for AMD formation. These techniques provide value-adding opportunities to existing datasets and provide robust cross-validation methods for each technique. A new geoenvironmental logging code and a new geoenvironmental index using hyperspectral mineralogical data (Hy-GI) were developed and embedded into the geochemistry-mineralogy-texture-geometallurgy (GMTG) approach for waste characterisation. This approach is recommended for new mining projects (i.e., early life-of-mine stages) to ensure accurate geoenvironmental forecasting, therefore facilitating the development of an effective waste management plan that minimizes geoenvironmental risks posed by the mined materials. Full article

(This article belongs to the Special Issue Geometallurgy)

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Open AccessArticle

Simulation of a Mining Value Chain with a Synthetic Ore Body Model: Iron Ore Example

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Minerals 2018, 8(11), 536; https://doi.org/10.3390/min8110536 - 18 Nov 2018

Cited by 10 | Viewed by 9027

Abstract

Reconciliation of geological, mining and mineral processing information is a costly and time demanding procedure with high uncertainty due to incomplete information, especially during the early stages of a project, i.e., pre-feasibility, feasibility studies. Lack of information at those project stages can be overcome by applying synthetic data for investigating different scenarios. Generation of the synthetic data requires some minimum sparse knowledge already available from other parts of the mining value chain, i.e., geology, mining, mineral processing. The aim of the paper is to describe how to establish and construct a synthetic testing environment, or “synthetic ore body model” for data integration by using a synthetic deposit, mine production, constrained by a mine plan, and a simulated beneficiation process. The approach uses quantitative mineralogical data and liberation information for process simulation. The results of geological and process data integration are compared with the real case data of an apatite iron ore. The discussed approach allows for studying the implications in downstream processes caused by changes in upstream parts of the mining value chain. It also opens the possibility of optimising sampling campaigns by investigating different synthetic drilling scenarios including changes to the spacing between synthetic drill holes, composite length, drill hole orientation and assayed parameters. A synthetic deposit model can be a suitable tool for testing different scenarios for implementation of geometallurgical programs and also an educational tool for universities and companies. Full article

(This article belongs to the Special Issue Geometallurgy)

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Open AccessArticle

A Geometallurgical Approach to Tailings Management: An Example from the Savage River Fe-Ore Mine, Western Tasmania

Anita Parbhakar-Fox

John Glen

and

Bonita Raimondo

Minerals 2018, 8(10), 454; https://doi.org/10.3390/min8100454 - 15 Oct 2018

Cited by 29 | Viewed by 4855

Abstract

At the Old Tailings Dam (OTD), Savage River, Western Tasmania, 38 Mt of pyritic tailings were deposited (1967 to 1982) and have since been generating acid and metalliferous drainage (AMD). Mineral chemistry analysis confirmed high concentrations of refractory cobalt in pyrite (up to 3 wt %). This study sought to determine, through a series of bench scale tests, if Co could be liberated using biohydrometallurgical techniques. Four bulk tailings samples were collected across the OTD, from up to 1.5 m depth, targeting three sulphide-bearing facies. The study was conducted in four stages: (1) bacterial adaption using BIOX^® bacteria; (2) biooxidation optimization with pH, temperature and Fe medium parameters tested; (3) flotation test work to produce a sulphide concentrate followed by biooxidation; and (4) Fe and Co precipitation tests. The BIOX^® culture adapted to the bulk composite (containing 7 wt % pyrite) in ~10 days, with biooxidation occurring most efficiently at pH 1.5–1.6 and 40 °C whilst the Fe medium concentration was identified as a less-controlling parameter. Flotation produced a 71% pyrite concentrate with total oxidation occurring after 14 days of biooxidation with 99% of Co leached. At pH 3, Co was effectively separated from Fe, however Ni and Cu were also present in the pregnant liquor solution and therefore required refining before production of cobalt hydroxide, the intermediate saleable product. This study shows that adopting a geometallurgical approach to tailings characterisation can identify if mine waste has commodity potential and how best to extract it therefore unlocking the potential for unconventional rehabilitation of AMD affected sites. Full article

(This article belongs to the Special Issue Geometallurgy)

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Open AccessArticle

Rock Classification Using Multivariate Analysis of Measurement While Drilling Data: Towards a Better Sampling Strategy

Veena S. Vezhapparambu

Jo Eidsvik

and

Steinar L. Ellefmo

Minerals 2018, 8(9), 384; https://doi.org/10.3390/min8090384 - 04 Sep 2018

Cited by 21 | Viewed by 4291

Abstract

Measurement while drilling (MWD) data are gathered during drilling operations and can provide information about the strength of the rock penetrated by the boreholes. In this paper MWD data from a marble open-pit operation in northern Norway are studied. The rock types are represented by discrete classes, and the data is then modeled by a hidden Markov model (HMM). Results of using different MWD data variables are studied and presented. These results are compared and co-interpreted with optical televiewer (OTV) images, magnetic susceptibility and spectral gamma values collected in the borehole using down-the-hole sensors. A model with penetration rate, rotation pressure and dampening pressure data show a good visual correlation with OTV image for the studied boreholes. The marble class is characterized by medium penetration rate and medium rotation pressure, whereas the intrusions are characterized by low penetration rate and medium to high rotation pressure. The fractured marble is characterized by high penetration rate, high rotation and low dampening pressure. Future research will use the presented results to develop a heterogeneity index, develop an MWD-based 3D-geology model and an improved sampling strategy and investigate how to implement this in the mine planning process and reconciliation. Full article

(This article belongs to the Special Issue Geometallurgy)

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Open AccessArticle

Geometallurgical Flowsheet as a Tool for Designing and Communicating Geometallurgical Programs

Aleksandra Maria Lang

Steinar Løve Ellefmo

and

Kurt Aasly

Minerals 2018, 8(9), 372; https://doi.org/10.3390/min8090372 - 28 Aug 2018

Cited by 6 | Viewed by 4573

Abstract

This paper introduces the concept of using a geometallurgical flowsheet as a tool to design, visualize and communicate a geometallurgical program. The development of the concept is carried out using a case study of an industrial mineral mining operation. A modified Integration Definition for Function Modeling (IDEF0) technique is proposed as a methodology to develop the geometallurgical flowsheet. The geometallurgical program is defined as a summary of the operations necessary to develop and validate the geometallurgical model. The geometallurgical model is defined as the function that links georeferenced in-situ geological characteristics and a georeferenced measure of performance in a processing plant. The geometallurgical flowsheet in this study is developed both as a general concept as well as a case-specific illustration based on the example of the Verdalskalk AS industrial mineral operation. Full article

(This article belongs to the Special Issue Geometallurgy)

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Open AccessArticle

Geometallurgical Approach to the Element-to-Mineral Conversion for the Nabbaren Nepheline Syenite Deposit

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Minerals 2018, 8(8), 325; https://doi.org/10.3390/min8080325 - 29 Jul 2018

Cited by 6 | Viewed by 4693

Abstract

Nabbaren nepheline syenite, a silica-deficient intrusive rock with low Fe content, was the industrial mineral deposit study case in this study. The quality of industrial mineral products are generally based on their bulk chemistry, which are directly related to their modal mineralogy and mineral chemistry; however, these are costly and time-consuming to determine. A geometallurgical-based methodology, known as element-to-mineral conversion (EMC), was applied to estimate its modal mineralogy based on its given bulk and mineral chemistry. EMC is a convenient and cost-effective technique, which can be used to quickly estimate modal mineralogy. Two EMC methodologies were applied: one least square based, LS-XRD, and one regression based, R-XRD. Additionally, average and specific mineral chemistries were used during estimations. The R-XRD method, a method not yet used for EMC purposes, gave better modal mineralogy estimations than LS-XRD. Considering the restrictions in the method, R-XRD shows potential for improvement and implementation at operational scale, making it a valuable geometallurgical tool for increasing resource performance, easing decision-taking processes, and reducing risks. The use of different mineral chemistries did not influence the modal mineralogy estimation, unlike the method used for it. Full article

(This article belongs to the Special Issue Geometallurgy)

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Open AccessArticle

Reprocessing of a Southern Chilean Zn Tailing by Flotation—A Case Study

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Minerals 2018, 8(7), 295; https://doi.org/10.3390/min8070295 - 11 Jul 2018

Cited by 17 | Viewed by 5310

Abstract

The reprocessing of tailings can have economic and environmental benefits compared to the processing of primary ore deposits. In this paper we present the characterization of a tailings dam in southern Chile by means of mineralogical and geochemical investigations, focusing on sphalerite and trace elements with the aim to investigate a potential reprocessing. The assessment is followed by a flotation study, focusing on the recovery of sphalerite with a high selectivity towards sulfidic and non-sulfidic gangue minerals. An in-depth analysis of a selected test based on mineral liberation analysis data is used to refine the liberation, concentration and flotation weighting function for future investigations. Full article

(This article belongs to the Special Issue Geometallurgy)

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Open AccessArticle

Near Real-Time Classification of Iron Ore Lithology by Applying Fuzzy Inference Systems to Petrophysical Downhole Data

Maria C. Kitzig

Anton Kepic

and

Ashley Grant

Minerals 2018, 8(7), 276; https://doi.org/10.3390/min8070276 - 28 Jun 2018

Cited by 7 | Viewed by 4409

Abstract

Fluctuating commodity prices have repeatedly put the mining industry under pressure to increase productiveness and efficiency of their operations. Current procedures often rely heavily on manual analysis and interpretation although new technologies and analytical procedures are available to automate workflows. Grade control is one such issue where the laboratory assay turn-around times cannot beat the shovel. We propose that for iron ore deposits in the Pilbara geophysical downhole logging may provide the necessary and sufficient information about rock formation properties, circumventing any need for real-time elemental analysis entirely. This study provides an example where petrophysical downhole data is automatically classified using a neuro-adaptive learning algorithm to differentiate between different rock types of iron ore deposits and for grade estimation. We exploit a rarely used ability in a spectral gamma-gamma density tool to gather both density and iron content with a single geophysical measurement. This inaccurate data is then put into a neural fuzzy inference system to classify the rock into different grades and waste lithologies, with success rates nearly equal to those from laboratory geochemistry. The steps outlined in this study may be used to produce a workflow for current logging tools and future logging-while-drilling technologies for real-time iron ore grade estimation and lithological classification. Full article

(This article belongs to the Special Issue Geometallurgy)

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Open AccessArticle

Towards Representative Metallurgical Sampling and Gold Recovery Testwork Programmes

Simon C. Dominy

Louisa O’Connor

Hylke J. Glass

Saranchimeg Purevgerel

and

Yuling Xie

Minerals 2018, 8(5), 193; https://doi.org/10.3390/min8050193 - 04 May 2018

Cited by 15 | Viewed by 7201

Abstract

When developing a process flowsheet, the risks in achieving positive financial outcomes are minimised by ensuring representative metallurgical samples and high quality testwork. The quality and type of samples used are as important as the testwork itself. The key characteristic required of any set of samples is that they represent a given domain and quantify its variability. There are those who think that stating a sample(s) is representative makes it representative without justification. There is a need to consider both (1) in-situ and (2) testwork sub-sample representativity. Early ore/waste characterisation and domain definition are required, so that sampling and testwork protocols can be designed to suit the style of mineralisation in question. The Theory of Sampling (TOS) provides an insight into the causes and magnitude of errors that may occur during the sampling of particulate materials (e.g., broken rock) and is wholly applicable to metallurgical sampling. Quality assurance/quality control (QAQC) is critical throughout all programmes. Metallurgical sampling and testwork should be fully integrated into geometallurgical studies. Traditional metallurgical testwork is critical for plant design and is an inherent part of geometallurgy. In a geometallurgical study, multiple spatially distributed small-scale tests are used as proxies for process parameters. These will be validated against traditional testwork results. This paper focusses on sampling and testwork for gold recovery determination. It aims to provide the reader with the background to move towards the design, implementation and reporting of representative and fit-for-purpose sampling and testwork programmes. While the paper does not intend to provide a definitive commentary, it critically assesses the hard-rock sampling methods used and their optimal collection and preparation. The need for representative sampling and quality testwork to avoid financial and intangible losses is emphasised. Full article

(This article belongs to the Special Issue Geometallurgy)

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Open AccessArticle

Geometallurgical Study of a Gravity Recoverable Gold Orebody

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Minerals 2018, 8(5), 186; https://doi.org/10.3390/min8050186 - 29 Apr 2018

Cited by 21 | Viewed by 5892

Abstract

Sheeted vein gold deposits are often characterised by multiple sub-parallel veins and free-milling coarse gold. Inherent mineralisation heterogeneity results in grade and process parameter variability, which increases project risk if not quantified. Measured grade variability is often exacerbated by poorly designed sampling and testwork protocols. Protocols that are optimised within the framework of the Theory of Sampling (TOS) to suit the ore type, together with quality assurance/quality control systems, will reduce variability and provide fit-for-purpose results. Geometallurgy can be broadly split into two key approaches: strategic and tactical (or operational). The strategic approach focuses on the whole orebody and long-term life-of-mine view, whereas tactical geometallurgy relates to a more short- to medium-term view during mining. The geometallurgical approach requires spatially distributed samples within a deposit to support variability modelling. Diverse attributes from core logging, mineralogical/textural determination and small-scale tests are used to measure variability. This contribution presents a case study that emphasises an early-stage strategic geometallurgical programme applied to a gravity recoverable gold (GRG) dominated deposit. It exemplifies how data can be acquired from a well-designed and planned programme to support resource estimation, a pre-feasibility study, trial mining and fast-track to production. A tactical geometallurgical programme is embedded into the mine operation. Full article

(This article belongs to the Special Issue Geometallurgy)

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Open AccessArticle

Quantification and Prediction of Bulk Gold Fineness at Placer Gold Mines: A New Zealand Example

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Minerals 2017, 7(11), 226; https://doi.org/10.3390/min7110226 - 19 Nov 2017

Cited by 7 | Viewed by 5036

Abstract

This study documents the bulk Au fineness (Au parts per thousand) of the bullion from a placer gold mine in southern New Zealand. The compositions of doré bars produced approximately every 10 days over nearly three years is compared to the range of compositions of gold particles which have been extracted. Silver is the principal impurity in the gold, and the doré bars contained 2–3 wt % Ag over the period examined. At the scale of a typical individual 0.5 mm gold particle, there are three different types of gold: an Ag-bearing core (2–9 wt % Ag), a 10–50 µm wide Ag-poor rim (typically <1 wt % Ag), and micron scale overgrowth gold (0% Ag). The overgrowths are volumetrically negligible, and the average Ag content of a gold particle is controlled principally by the proportions of core and rim gold. The rims have been formed by recrystallisation of deformed core gold, with associated leaching of the Ag from the recrystallised gold. The volumetric proportion of cores has decreased with increasing flattening of gold particles, and highly flattened and folded flakes have little or no remnant cores. The bulk Au fineness of doré bars from the mine has decreased from ~980 to ~970 as the mine progressed upstream in a Pleistocene paleochannel because the upstream gold has been less flattened than the downstream gold. Full article

(This article belongs to the Special Issue Geometallurgy)

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Open AccessReview

Geometallurgy—A Route to More Resilient Mine Operations

and

Saranchimeg Purevgerel

Minerals 2018, 8(12), 560; https://doi.org/10.3390/min8120560 - 01 Dec 2018

Cited by 45 | Viewed by 12520

Abstract

Geometallurgy is an important addition to any evaluation project or mining operation. As an integrated approach, it establishes 3D models which enable the optimisation of net present value and effective orebody management, while minimising technical and operational risk to ultimately provide more resilient operations. Critically, through spatial identification of variability, it allows the development of strategies to mitigate the risks related to variability (e.g., collect additional data, revise the mine plan, adapt or change the process strategy, or engineer flexibility into the system). Geometallurgy promotes sustainable development when all stages of extraction are performed in an optimal manner from a technical, environmental, and social perspective. To achieve these goals, development of innovative technologies and approaches along the entire mine value chain are being established. Geometallurgy has been shown to intensify collaboration among operational stakeholders, creating an environment for sharing orebody knowledge and improving data acquisition and interpretation, leading to the integration of such data and knowledge into mine planning and scheduling. These aspects create better business optimisation and utilisation of staff, and lead to operations that are more resilient to both technical and non-technical variability. Geometallurgy encompasses activities that utilise improved understanding of the properties of ore and waste, which impact positively or negatively on the value of the product, concentrate, or metal. Properties not only include those that impact on processing efficiency, but also those of materials which will impact on other actions such as blasting and waste management. Companies that embrace the geometallurgical approach will benefit from increased net present value and shareholder value. Full article

(This article belongs to the Special Issue Geometallurgy)

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