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By Carsten Rühlemann

Between 2008 and 2013, the German Federal Institute for Geosciences and Natural Resources (BGR) carried out five exploration cruises to the German license area in the eastern Pacific Nodule Belt. The first two expeditions were mainly dedicated to multibeam mapping to obtain an overview of the seafloor topography and acoustic backscatter strength. These data were used to identify ten to fourteen prospective nodule fields for potential future mining, which together cover about 16% of the total license area of 75,000 km2. During the last three cruises, three of these potential mining areas were explored in detail. For this purpose, the BGR developed a suite of exploration methods to map nodule size distributions and nodule abundances. These methods include acoustic surveys with vessel-based multibeam systems as well as near-bottom video mapping complemented by in situ sampling. The economically most valuable field has a size of ca. 2,000 km2, of which 34% is covered by medium to large nodules (> 4 cm long axis of nodules) with an average abundance of 22.4 kg/m2 and 44% is covered by small nodules (< 4 cm) with a mean abundance of 17.5 kg/m2. The total mass of nodules in this field comprises more than 30 million tons wet weight and could sustain deep-sea mining for at least 10 years.

Sep 14, 2011

By Jorge MRS Relvas

Recent research both on active and fossil systems has demonstrated that shallow subseafloor replacement processes are not only viable depositional mechanisms for massive sulfide mineralization, but likely contributed as a major component of the mineralization occurring in large VHMS deposits and in many present-day seafloor hydrothermal systems. In the giant Neves Corvo deposit, as in many others VHMS deposits of the Iberian Pyrite Belt, there is overwhelming evidence for silicate-sulfide replacement processes being largely responsible for the efficiency of the ore-forming systems and huge size of the deposits. Textural evidences at all scales, coupled with a well-constrained mass-balance geochemical analysis, indicate that extensive replacement in the lavadominated volcanic rocks of the footwall sequence, and disseminated replacement mineralization in the volcaniclastic and/or sedimentary units were major mechanisms of ore formation in the Neves Corvo deposit. Shallow metal deposition prior to fluid discharge on the seafloor is likely to play a major role in seafloor massive sulfide mineralization. This premise should be envisaged as critical in evaluating the economic potential of seafloor resources, and should certainly be part of the equation when plans for seafloor mineral exploration missions are drawn.

Sep 14, 2011

By Laurie Meyer

The need for improved, high confidence estimates of nodule abundance to support mine permitting, detailed mine planning and mining and processing equipment design is evident. To date, physical samples represent the ?Gold Standard? for nodule abundance measurement, and are likely to remain as such. However, there are some interesting improvements in the area of 3-D scanning which, if marinized for operations at 6000m, may prove to be reliable alternative methods for mapping abundance over large areas particularly if calibrated or benchmarked with physical sample data. . Features of a high confidence physical sampling device, such as the 0.75m2 (0.86m on a side) box corer developed and successfully used by the Kennecott Group for exploration in the CCZ, take into account not only the accuracy in nodule sample collection but a host of other operability considerations which can mean the difference between a successful exploration cruise yielding high numbers of large area samples and one in which few, inaccurate, often inconclusive samples are collected (or, even worse, the sampler fails to grab any nodules for any number of reasons). The collection of physical samples at appropriate spacing within a mine area combined with more qualitative indications of nodule density such as can be obtained using acoustic backscatter should prove adequate for the near term objectives related to overall abundance appraisal or estimates of ?indicated? resource. Looking ahead, exploration cruises will need to yield increasing amounts of data to support development of higher confidence resource abundance estimates to support issuance of mining permits and detailed design of mining plans and equipment. It is likely

Sep 14, 2011

By G Turner-Saad

An improvement to cut-off grade optimisation theory based on geometallurgy has been completed. The improvement fundamentally consisted of taking into account mineralogical and textural characteristics instead of grades. These characteristics are related to the spatial variability of mineral abundance, association, particle size and liberation properties. Additionally, the improve- ment considered the spatial variability of mineral processing liberation and selectivity properties associated with mineralogy and texture. The enhanced optimisation enables estimation of the economic value of mining operations based on an optimum cut-off policy attributed to liberated and selected ore minerals.The enhanced optimisation was developed as an essential component of a joint cut-and-fill mining and mineral processing methodology based on mixed integer mathematical programming. The formulation considers static and dynamic modifying factors that vary over the projected life of mining. The objective function of the mathematical formulation consists of maximising the realistic expected economic value of concentrates or products of liberated and selected ore minerals, whilst minimises liberated and selected gangue minerals. The optimal solution is obtained when the objective function is subject to geological, mining, processing, marketing, smelting, refining, environmental and financial constraints. The methodology accesses geometallurgical multivariate resource models, which integrate the spatial variability of mineralogical and textural characteristics and mineral processing liberation and selectivity properties.The geometallurgical process concurrently optimises stope geometries, ore reserves, mining sequences, and mining and mineral processing production based on the enhanced cut-off of liberated and selected ore minerals. In addition, the process considers additive and non-additive transfer functions associated to mutually exclusive geometallurgical spatial domains. The transfer functions also take into consideration the blending of mineralogical and textural characteristics with mineral processing liberation and selectivity properties.This contribution presents an example of cut-off grade optimisation via mineralogical and textural characteristic, and liberation and selectivity processing parameter optimisation for a spatially variable orebody.

Sep 5, 2011

By J E. Everett

An essential requirement of product quality control in the mining industry is to be able to reliably predict key quality properties of finished product from the data available before the extraction of the ore. From a production viewpoint, the unit of data collection is generally the input and output data set for each shift of crusher production, but could be any period where mine precrusher data can be reliably matched with product data.This paper demonstrates that linear regression models can be used to predict crush grades from blast grades, even where the crush material is blended from multiple sources or pits for each of which differing regression models might apply. The advantage of using increasingly complex regressions models to match the available data to give increasingly more powerful models is examined. The best model for any application will be a balance between required predictability, available data and the business’ tolerance for complex models.The regression modelling approach has several advantages over the more classic method of run-of-mine (ROM) crusher trials, which will be discussed.The models can use any predictor variable such as grade, geotype and in situ density provided the preextraction data set can be reliably matched with post-crusher data and is significant as a predictor. The models have been used extensively in the generation of the daily crusher plan with the aim of maintaining finished product grade. This approach has also been used associated with exploration drilling and long-term planning.It is acknowledged that there are inherent problems in fitting lump and fines grade to a linear model. However, these problems are minor when they are used for interpolation within the window spanned by the shift blend records used to produce the model. This paper discusses some of the issues limiting linear regression models in this application, and suggests methods enabling consistent models to be formulated

Sep 5, 2011

By R Berry

This paper looks at two ways to estimate the bulk mineralogy of the rocks for assay intervals. The aim is to find an efficient indicator of the most common minerals in the rock. Phase (modal) analysis has traditionally been done using visual methods such as point counting and image analysis. A modern version of this process is the X-ray point counting routine using the SEM-EDS based software. These methods are too slow and expensive for routine analysis of bulk sample mineralogy at the normal assay spacing.Two sources of data were considered that provide information that can be used to determine the mineral abundance in assay samples. The most widely applied method is (semi-) quantitative X-ray diffraction (QXRD). The QXRD method is most applicable to major minerals and has limited application to minerals at low abundance. The nominal detection limit is 0.5 per cent. Values below five per cent have large errors. A second, less common, method is calculation of mineralogy from chemical assay data. Conversion of chemical analyses to mineralogical analyses depends on the unique chemical composition of each mineral. Elements only found in one mineral are easily accounted for, but many compositions are ambiguous. Deciding on the actual mineralogy is not simple. Recalculation of mineral mode from chemical analyses is more accurate than QXRD when the correct minerals, and mineral compositions, are known.Where only a few QXRD analyses are available they can be used to setup a protocol for calculation of mineralogy from assay data. Linear programming works well in this environment. The best results are obtained when both H2O and CO2 are directly measured. Loss-on-ignition (LOI) should be included if these are not available.Where both QXRD and chemical analysis are available for all samples, the best results are obtained using the least squared method to merge the data sets assuming QXRD has much higher analytical errors than chemical assays. The combined method provides more robust results because the high abundance minerals are controlled by the QXRD measurements while the chemical assays improve the precision for low abundance minerals

Sep 5, 2011

By A R. Bye

The mining industry is facing some key challenges that provide a compelling case for geometallurgy initiatives. Over the last 30 years, the average grade of Australian orebodies being mined has halved while the waste removed to access the minerals has more than doubled. In the last eight years, the industry’s energy consumption has increased 70 per cent while multi-factored productivity has fallen 24 per cent. The paper documents a broad range of industry case studies which demonstrate strategies for gaining value from geometallurgy.The mining industry constantly faces the key questions of how significant ore variability is on mine valuation and how would knowledge of the variability change the mining schedule, mine to mill design and operation. Using case studies the paper describes the methods used for incorporating mineral extraction attributes into orebody models and their technical integration into daily operation as well as mine planning optimisation. While pit optimisation from a fully attributed geometallurgical model highlights areas of opportunity and risk it is shown that during the scheduling phase of mine planning that significant value can be added. The benefits from these projects included reducing geotechnical and environmental risk, improving mine to mill performance, option analysis and quantified cash flow risk. There is growing acceptance within the minerals industry that ‘realistically assumed modifying factors’ defined by a competent person/s are not sufficient to mitigate the risk of funding mining ventures. Geometallurgy is moving away from factored ore reserves to data-rich block models providing reliable information for mining, metallurgical and environmental considerations.

Sep 5, 2011

By S C. Dominy

For any gold deposit-based geometallurgical study, the collection and processing of representative samples for gold grade and recovery tests is critical. Sampling protocols should be designed to suit the style of orebody in question. The proportion and size of gold particles has a direct impact on the effectiveness of sampling protocols and metallurgical recovery processes employed. Studies focussing on ore mineralogy and gold particle deportment, size and distribution are required. Key issues are the presence of gold particle clustering (important for sampling optimisation) and proportion of coarse versus fine to refractory gold. X-ray computed tomography (CT) is a radiographic technique that produces high-resolution 3D computerised models of objects based on density distribution. The ‘virtual’ specimens are made up of voxels, the 3D equivalent of pixels each assigned a grey value based on X-ray absorption. This paper presents the results of recent research on the imaging of in situ gold particles in a coarse gold-bearing ore. The technique shows promise as a rapid non-destructive method for preliminary characterisation to facilitate more detailed studies. Early and rapid gold particle determination enables sampling protocol optimisation and metallurgical recovery parameters to be defined prior to detailed feasibility studies

Sep 5, 2011

By L E. Howard

Micro-computed tomography (Micro-CT) is an X-ray imaging technique that produces high-resolution 3D computerised ‘virtual’ models of geological specimens based on the X-ray attenuation of different materials in the specimen. The ‘virtual’ specimens are made up of voxels, the 3D equivalent of pixels, each assigned a gray value based on X-ray absorption. Micro-CT has enormous potential for allowing non-destructive, digital analysis of structure and composition when the mineralogical phases can be digitally separated. However, variation in X-ray flux between scans results in highly variable grayscale values for identical materials. Consequently, materials usually have to be segmented manually, which is subjective, inaccurate, labour-intensive and time consuming. Here we present a protocol and imaging software package that can be used to accurately and precisely extract quantifiable information in a repeatable and objective fashion. The software will allow the separation, visualisation, measurement and analysis of spatial and volumetric distribution of different mineral phases without damaging the specimen. This paper explains the potential use of this protocol and software package to ultimately allow automatic segmentation and quantification of gold in drill core samples, removing subjectivity and inaccuracies from data processing.

Sep 5, 2011

By S C. Dominy

Gravity amenable gold ores are those that after comminution produce liberated particles, composites and/or carriers that can be recovered by gravity separation means. Recovery depends upon mineralisation type and the comminution and concentration method used. Any in situ ore with more than 20 per cent of gold greater than 100 &#181;m in size is likely to have a strong gravity recoverable component. A less traditional approach is where the gold is sulfide-locked and the gold carrier plus any liberated gold is recovered via continuous gravity recovery following fine crushing. Specific tests are undertaken to determine the level of gravity amenable gold within a deposit. The principal methodology is the gravity recoverable gold (GRG) test, which consists of three sequential liberation and recovery stages. For continuous gravity recovery (CGR), the sample is fed over a laboratory Wilfley table to simulate continuous recovery of the gold. Tails from the feed can be progressively re-ground and re-tabled to develop a grade-recovery curve. Primary geology and gold particle size-distribution have a strong effect on the mass of sample required to provide representative results for both tests. Where low-grade ore contains very coarse gold, substantially larger sample masses are required. Experience has shown that GRG and CGR values can vary throughout an orebody, particularly within different geological-grade domains. A testing regime must consider sample frequency and support.

Sep 5, 2011

By M A. Wells

A new approach to more reliably predict the Ni (and Fe, Mg) composition of Ni laterites was tested for RC samples from the (siliceous) oxide–style, Siberia North deposit, Kalgoorlie Nickel Project (KNP), in the north-eastern Yilgarn (WA) using partial least squares regression (PLSR) analysis of diffuse reflectance spectra over the 380 - 2500 nm wavelength range with a multi–element chemistry data set. PLSR cross-validation models were developed to predict FeO, MgO and Ni contents in composite samples with bulk composition limits of &gt;0.08 wt per cent Ni and &lt;6 wt per cent MgO. Calibration and validation models showed a strong, linear trend for predicting FeO and, to a lesser extent, Ni content, whereas PLSR models for predicting Mg content were less reliable. This reflected the prevailing mineralogy and associated element deportment within the oxide laterite profile. For example, Fe and Ni distribution is controlled by relatively few minerals, predominantly goethite and, to a lesser extent, the Fe3+-bearing smectite, nontronite. Magnesium is associated with a range of Mg-bearing minerals, some of which are compositionally complex (eg serpentine, talc, chlorite, smectite and carbonates). Magnesium chemistry alone does not reflect the varied mineralogy of samples with relatively high (5 - 6 wt per cent) MgO contents, which can be spectrally distinct. Hence, samples with similar Mg contents, though comprising Mg-bearing minerals with distinct reflectance spectra, were difficult to model (eg smectite versus Mg-carbonates). The findings of this study demonstrate that characterisation of Ni laterite composition may be achieved as part of routine logging of either drill chips or diamond drill core using PLSR analysis, but that a detailed understanding of the mineral-element association is essential for reliable predictive analysis. This has particular relevance to characterising the geometallurgy of Ni laterites, especially where deposits may be classed as the same type, but have distinct compositional and mineralogical differences.

Sep 5, 2011

By R Hartner

Digital optical microscopy (DOM) and automated SEM-based (ASEM) mineralogy systems (MLA, QEMSCAN) have experienced significant developments within the last decade. However these developments have been independent from each other and the two mineralogical techniques have so far not yet been integrated to combine the strengths and technical benefits of both analytical platforms. This detailed comprehensive mineralogical information is critical support for geometallurgy.Major hardware and software advances in DOM in the last few years have provided important new capabilities with potential applications to automated mineralogy. These technological advances have been largely driven by sectors outside mining (eg medical pathology) and have not yet been widely adopted within the minerals industry. The advent of DOM offers significantly more automated mineralogy capabilities than traditional expert-mineralogist driven optical microscopy. This is based on advances in automated image acquisition, high resolution cameras for digital imaging, imaging of large areas through mosaic options, integration of multiple layers and application of advanced image analysis techniques.Ongoing research involves combining the outputs of DOM and ASEM-based microscopy to create new capabilities for integrated microscopy based on development of advanced cross-platform image fusion and data integration between DOM and ASEM (exploiting the benefits of both analytical platforms). This requires non-linear image registration and transfer of mineralogical identification from ASEM to DOM systems using sophisticated image manipulation and data analysis software.Examples will be given of image fusion and data registration for a range of different ore types. Image fusion techniques are demonstrated using a porphyry copper deposit sample where sulfides and precious metals are classified using the MLA and gangue mineralogy obtained from DOM images. Data integration enables creation of a library containing optical property variability information for minerals identified by the MLA; thus reducing the reliance on skilled mineral identification by supplementing human interpretation

Sep 5, 2011

By J Vann

Geometallurgy is inherently multidisciplinary and it gains its power to deliver improved outcomes for the minerals industry by bridging silos between disciplines. This cross-disciplinary approach unlocks value, identifies (and avoids) value destruction and provides a pathway to better implementation of an energy efficient and sustainable minerals industry. Despite this promise, we argue that the cross disciplinary approach also represents the greatest threat to the success of geometallurgy. Some key cross disciplinary issues identified are:Geometallurgy has so far evolved in the technical sphere, mainly by collaborations of geologists and metallurgists. Consequently, in many cases the business dimensions and value have not been incorporated. Financial and risk evaluation viewpoints need to be assimilated into the geometallurgical paradigm. In fact, until such measures are integrated into practices, the value cannot be fully demonstrated.The historical and current efforts on geometallurgy have been highly focused on improved sampling and measurement of geometallurgical properties or appropriate proxies. This work has been driven by professional and academic geologists and metallurgical engineers. It is notable that mining engineers (who are critical in the value delivery of geometallurgy through changed planning approaches) have so far been at the margins, or absent. The construction of valid three dimensional (3D) geometallurgical models raises some important organisational, mathematical and geostatistical considerations. The enhancement of resource models to account for geometallurgical aspects must be managed carefully if the full value of geometallurgical thinking is to be realised.The use of 3D geometallurgical models to change business decision making and practices is the real nub of the problem. We believe sophisticated scenario based evaluation methods are required if the potential impacts of spatial rock properties on processes further down the mining value chain are to be realistically evaluated. Such changed practices require ‘whole of value chain thinking’ to embed this change into the business in an ongoing way.Because profitable geometallurgy demands changed approaches to business decision-making and also organisation of the firm (radically changed in some cases), the senior executive viewpoint must be incorporated into the language and thinking of geometallurgy. This is unavoidable if the establishment of a geometallurgical approach to project evaluation, development and operation is to be successful and sustained.A powerful analogy for the problem faced by geometallurgy is the transformation of safety culture in the mining industry in the past 20 years. We argue that, as in the safety revolution, explicit models, cultural change and management of the ‘soft’ dimensions of the problem are pivotal to success of geometallurgy. In light of this, we propose a model (‘the Geomet Curve’) that gives a framework and pathway for geometallurgy in seven steps. The implications of this model for technical and organisational steps required at different stages are discussed.

Sep 5, 2011

By R C. A Minnitt

The Witwatersrand Supergroup is host to the world’s largest gold deposits. The location, quantity, grade, continuity and other geological characteristics of a Mineral Resource are either known, estimated from specific geological evidence and knowledge, or interpreted from a well constrained and portrayed geological model. Establishing such a model is an integral part of the evaluation process in the Anglogold Ashanti (AGA) group, and is referred to as a Geoscience Business Model for the mining operations. The geological model established over the years has relied on detailed descriptions of the mineralisation, and understanding of the regional and local geology of the Witwatersrand sediments, in the West Wits and Free State goldfields. The processes of data collection in regard to underground stope and developing mapping, structural and sedimentological mapping, and the geological inputs to mine planning systems are described, together with aspects of drilling, sampling, grade control, and data management. Anglogold Ashanti’s Geoscience Department employs a complex and unique process to generate the Mineral Resource, including a 3D geological structure model of the orebodies which are usually highly faulted, and a robust mineralisation/facies model on which the decisions about domain boundaries are established. A Mineral Resource Inventory System (MRIS) has a dynamic graphic interface to the resource database that is used for compiling the resource statement. It is also used to determine the gold-called-for, as well as short and long-term planning. A unique estimation process using the extensive closely spaced stope face sampling database and the more widely spaced surface drilling information is used in combination in the Macro Co-Kriging estimation. The use of different support sizes in the C0-Kriging process is preceded by the equally unique ‘clusterisation’ and ‘acceptorisation’ procedures by which the data are quality controlled and assured prior to their use in the kriging process. The Mineral Resource and Ore Reserve estimates are classified according to the SAMREC code through a method that ensures that they are compliant, auditable, transparent and reconcilable with previous Mineral Resource and Ore Reserve statements.

Aug 22, 2011

By G Chitombo

Mass mining methods have become the mining industry’s preferred way of extracting most of the world’s most important metal and mineral commodities. Given the rapidly increasing global demand for commodities, the requirement to increase the contribution of some of these (eg copper and gold) from underground sources also continues to grow. In the case of copper this contribution is needed by a number of major producers to supplement production from their ageing deep open pits. Satisfying this increased demand will require the design, construction and operation of more effective, higher capacity and larger scale mines which, in turn, will require enhanced mass underground mining techniques such as block caving (BC), panel caving (PC) and sublevel caving (SLC).It is now widely accepted that future discoveries of orebodies, which will be developed using these methods, are almost certainly to be much deeper than the deposits presently being mined in this way and made more challenging because of the likelihood that the associated grades may be much lower than currently mined. The design and mining of future large-scale cave mines (supercaves) will become crucial in order to extract full value from such deposits. An essential prerequisite of this will be a much improved knowledge of the deposit, ie Total Deposit Knowledge. In this context, Total Deposit Knowledge is the characterisation of the ore deposit and its surrounds at all scales and includes; rock type (lithology), the spatial orientation of a range of geological features or discontinuities, rock mass fabric knowledge, metal grade and distribution data, geometallurgical data (including alteration), geo-hydrology, permeability and porosity. This is the information that will be used, as now, to delineate geological and geotechnical domains and construct models, but with outcomes superior to those presently available. From this information better-informed feasibility study design decisions and performance predictions must be made. In summary more geological information and analysis is required and this needs to be aligned to potential mining and processing requirements much earlier in the project than commonly occurs.

Aug 22, 2011

By D A. Sketchley

The Merlin Zone, a 2008 high-grade Mo-Re discovery, is a part of the Mount Dore Deposit in the Eastern Succession of the Mount Isa Inlier in Queensland, Australia. Hosted by carbonaceous metapelites and phyllites, the Merlin mineralisation comprises molybdenite veins, breccia infillings, stylolitic fracture fillings, and disseminations. Because rhenium is geochemically similar to molybdenum and commonly associated with it, global production of rhenium has been mostly a by-product of molybdenum refining. The high-grade rhenium in the Merlin Zone is an exciting discovery that is expected to become a direct source of rhenium. At the time of discovery, quality assurance (QA) procedures for rhenium were not in place at the Merlin Zone; therefore, they needed to be developed.The Merlin Zone was discovered using reverse circulation drilling, which led to concerns about molybdenite loss due to poor sample recovery. The twinning of the discovery hole with diamond core demonstrated a two-fold increase in molybdenum grade over several tens of metres. Consequently, the resources of the Merlin Zone were defined using assays from diamond drill core.Early analytical work, which was initially done only for molybdenum, comprised geochemical analysis with an aqua regia digestion, which have poor precision and can be biased low. Although initial testing for rhenium used similar procedures to those for molybdenum, a scarcity of commercial rhenium reference materials led to a validation process using neutron activation analyses and different digestions. This resulted in introduction of four-acid digestion assays, development of matrix-matched reference materials, and improvements to the quality of molybdenum and rhenium assays for reporting resources. Coarse and pulp duplicates were used to check for sampling bias and to ensure that levels of precision were adequate for the style of mineralisation and analytical methods. In addition, the direct and consistent geochemical correlation between molybdenum and rhenium provided another method for checking analyses.

Aug 22, 2011

By N Burgio

Block cave mines are often thought of as rock factories where high volumes of production are mined from a fixed area suggesting little requirement for geological input and control. Yet caving operations have peculiar and specific technical requirements from prefeasibility through to post-mining reconciliation. Whilst essential elements such as resource definition, geological interpretation and sampling strategies are common to all mining methods, planning for a block cave requires a different emphasis and philosophical approach in how we deal with these issues. We will examine why a geoscientist’s input is critical towards the successful planning, design and monitoring of a caving operation.

Aug 22, 2011

By C L. McIntosh

The west coast of New Zealand’s south island is host to a large number of placer goldfields that stretch from the Westport area in the north to Gillespies Beach in the south and inland to the foothills of the Southern Alps. This area is host to a large number of alluvial, glacial and strand line deposits ageing in range from Recent to Tertiary. In recent years exploration models have been developed for off shore placer deposits on the continental shelf.Gold mining on the west coast has exploited placer gold resources from the 1860s to present, and with the recent surge in the gold price the industry is currently undergoing a resurgence. The current increase in mining is dominated by small-scale mechanical operations usually involving one to two people at each site; a few larger operations also exist such as the Grey River Dredge.Mining methods range from using floating bucket dredges to small diggers. Some of the mining technologies used are similar to those employed during the great gold rushes of the 19th century. Exploration and grade control techniques can be very rudimentary often relying on previous sampling programs or wide spaced bulk sample drill holes. Some bulk sample drilling is used on the larger operations as a form of grade control, most of the small operations tend not to use any ore control sampling prior to mining. Extraction techniques relying on simple gravity based designs with riffle tables or spirals are the most commonly used. Environmental standards are very high within New Zealand and require operators to return mined areas to preagreed to landforms. The high rainfall experienced on the west coast causes challenges to operators in regard to water quality. Technical issues combined with often limited capital provide for challenges to the operations.

Aug 22, 2011

By J Vann

The philosophical context of many activities in mine geology can be an important lever in adding value to operations. For mine geologists (including resource and grade control geologists) we argue that the tasks of problem formulation, observation and data collection, interpretation and modelling invoke various philosophical considerations whether the practitioner is aware of them or not.Constructing testable models to explain reality is the definitive aspect of any activity claiming to be ‘scientific’. A primary goal of mining geology is to build models that accurately predict reality to an acceptable degree and these include litho-structural, stratigraphic, grade control, resource or reconciliation models. What’s more, in mine geology we are often able collect additional drill samples or access new underground openings, for example, that can provide relatively rapid feedback on how predictive, and therefore useful, our models are. In this paper, we describe the key philosophical frameworks proposed for conducting scientific investigations, including falsification, the method of multiple working hypotheses and structural concepts of scientific theory. The strengths and weaknesses of these approaches are discussed and an attempt is made to relate them to activities undertaken by mine geologists. Common perceptions of what constitutes the scientific method have been dominated by how scientists do experimental physics and chemistry in particular. There are very important differences in the types of problem confronted in these experimental sciences compared to the ‘historical sciences’, such as geology, where the processes studied are unique and only evidential traces of past events are available. The philosophical implications of attempting to validate numerical geological models, such as resource estimates are also briefly considered.Some practical conclusions are drawn about how mine geology activities can be better implemented if practitioners are cognisant of the importance of philosophical considerations when attempting to gain new knowledge through a scientific investigation. We believe that the implications for creating additional value to a project or operation can be very significant when geology is applied by a practitioner with an understanding of the philosophical basis of the activities we think of as constituting a scientific investigation.Remember that all models are wrong; the practical question is how wrong do they have to be to not be useful? (Box and Draper, 1987, 74 p).The demand that theories be highly falsifiable has the attractive consequence that theories should be clearly stated and precise. If a theory is so vaguely stated that it is not exactly clear what it is claiming, then when tested by observation or experiment it can always be interpreted so as to be consistent with the results of the test. (Chalmers, 1999, 67 p).

Aug 22, 2011

By P Hodkiewicz

Recent structural interpretations based on historic stope shapes were used to develop a rapid and innovative method to domain and simulate structurally complex, high-grade gold veins at depth in the Edna May deposit. This involved ‘implicit’ modelling of drill hole data using Leapfrog software, which allows complex wireframe domains to be built and updated rapidly, compared to ‘explicit’ manual wireframing methods that are too subjective and time consuming. Conditional simulation was used for resource estimation, in order to simulate the highly variable gold grades associated with the veins. Similar modelling methods could be used to determine the mining potential of other historic gold deposits that are receiving renewed interest because of the high gold price.Gold at Edna May is hosted in the Edna May Gneiss, which is a WNW-striking tonalitic intrusion along a shear zone that dips approximately 45° towards the NNE. Gold occurs in multiple 0.5 - 5 m thick arcuate quartz veins that plunge steeply towards the west. Two phases of historic underground mining at Edna May (1911 to 1922 and 1935 to 1947) produced 360 000 ounces of gold at an average grade 19.5 g/t from seven ‘reefs’ to a depth of 240&nbsp;m. This established Edna May as one of the highest grade gold mines in Western Australia at the time.Recent drilling by Catalpa Resources confirmed the potential for down-plunge continuity of high-grade veins. New structural interpretations, based on historic level maps and wireframe re-constructions of the arcuate stope shapes, were used as ‘structural trends’ in Leapfrog to model the mineralisation. The resulting wireframes capture the complex distribution of gold in the deposit and were used as domains for resource estimation.Conditional simulation using the Turning Bands method was used to simulate the expected variability of gold grades associated with this mineralisation style and the median of the 100 realisations was used to report an inferred resource. Results of this modelling method are being used to target vein extensions at depth, to consider different underground mining scenarios, and to assess the risks associated with developing and mining this high-grade and high-nugget gold deposit.

Aug 22, 2011