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By J. H. Tonking, O. H. Kuschke

A description is given of the general geology, structure and minerals of economic significance of the Loolekop copper orebody at Phalaborwa. The open pit mining method is described with details of drilling, blasting, loading, hauling and primary crushing operations. A brief description is given of mine planning and its relationship to the control of the mining operation.

By M. M. Oosterveld

Diamonds are mined from ancient raised beach deposits in southern Namibia where complex geological controls have resulted in patchy diamond distribution, largely related to irregularities (trapsites) in the bedrock. The distribution of the number of diamonds per sample is a discrete, reverse- J shape distribution which can be characterized by two parameters. These parameters have been transformed into a Beta and Theta Contribution which can be interpreted as reflecting the 'quantity' and 'quality' of the trapsites. The relationship of statistical parameters, obtained during the sampling of an ore deposit, to the geology of the deposit is an important element of ore reserve estimation. The large-scale regional trends in the contributions have been explained in terms of the geology.

Jan 1, 1987

By M. van Biljon

The possible closure and subsequent flooding of South Deep Gold Mine?s neighbouring Randfontein Estates Limited No. 4 Shaft (REL 4) necessitated the construction of five concrete plugs in the connecting tunnels to prevent the ingress of groundwater into REL4 from flooding South Deep mine. Several technical investigations had been carried out before and during construction of the plugs in order to reduce the probability of groundwater flow through the boundary pillar between the two mines or through the rock mass immediately around the plugs. This paper describes the geological, hydrogeological and stability investigations carried out to evaluate the structural competence of the boundary pillar.

Jan 1, 2006

This paper pays tribute to the pioneers in geomechanics, and addresses some of the most pressing issues of our time related to deep mining, and how to mitigate these issues. Solutions developed by our predecessors seem to have reached their limits as mines continue to go deeper. The International Society for Rock Mechanics (ISRM) guidelines for rock mass characterization for excavation design also require re-thinking to reflect current knowledge and experience. Thus, a whole new approach is urgently required to increase mine safety and productivity. The paper will draw on the challenges and experiences in medicine and science that have been overcome through genuine collaboration, advances in technology, and impressive funding, which can be adopted to provide solutions to contemporary geomechanics challenges for increased safety and productivity as mines continue to go deeper.

Jan 1, 2014

By V-P. Takalo, M. Natsvlishvili, M. Hicks, S. Khizanishvili

"The complexity of copper-gold ores leads to large variations in recoveries and concentrate grades in the processing plant. Detailed chemical and mineralogical studies revealed considerable variation in the ratios of chalcopyrite, chalcocite, and oxidized copper minerals in the ore types studied. The end-member ore types are chalcopyrite-dominated and chalcocite-dominated, while most of the ore types plot between these end-members. In addition, increasing amounts of copper oxide and sulphate minerals result in a decreased response to flotation. Good recoveries and concentrate grades can be achieved from the chalcopyritedominated ore type, while the more altered chalcocite-dominated ore type is more challenging to enrich. IntroductionRich Metals Group (RMG) Copper in Georgia (Figure 1) produces copper-gold concentrates from two open pit mines, Madneuli and Sakdrisi, both located in the Bolnisi mining district in South Georgia. RMG and Outotec began a cooperative project with the aim of improving the recoveries and metal grades in concentrate by gaining an increased understanding of the ore variability and developing more efficient procedures for ore blending, grinding, and flotation. This type of mineralogy-led approach has already been used for other complex ores such as iron oxide copper-gold ores (Hunt, Berry, and Bradshaw, 2011), for iron ores (Lund, Lamberg, and Lindberg, 2013), and for Kupferschiefer ore deposits (Rahfeld et al., 2018).The project started with process audits and mineralogical and chemical characterization of process samples, followed by detailed chemical and mineralogical characterization of six different ore types with simultaneous flotation test work on the same samples. Since neither the recoveries nor the concentrate grades correlate with the head grades of the ores, the modal mineralogical composition, together with the ore hardness, proved to be the most promising approach in developing the geometallurgical classification of these ore types."

Apr 1, 2019

By E. Pizarro, A. Videla, G. Compan

One of the main problems related to mining investment decisions is the use of accurate prediction models. Metallurgical recovery is a major source of variability, and in this regard, the Chuquicamata processing plant recovery was modelled as a function of geomining-metallurgical data and ore characteristics obtained from a historical database. In particular, the dataset gathered contains information related to feed grades, ore hardness, particle size, mineralogy, pH, and flotation reagents. A systemic approach was applied to fit a multivariate regression model representing the copper recovery in the plant. The systemic approach consists of an initial projection of the characteristic grinding product size (P80), based upon energy consumption at the particle size reduction step, followed by a flotation recovery model. The model allows for an improvement in the investment decision process by predicting performance and risk. The final geometallurgical model uses eight operational variables and is a significant improvement over conventional prediction models. A validation was performed using a recent data-set, and this showed a high correlation coefficient with a low mean absolute error, which reveals that the geometallurgical model is able to predict, with acceptable accuracy, the actual copper recovery in the plant.

Jan 1, 2015

By J. Mulenshi, J. Rosenkranz, P. Khavari, S. C. Chelgani

The geometallurgical concept has mainly been applied to primary ore deposits, starting from ore characterisation to the economic optimisation of the mining operation. However, as primary ore resources are becoming depleted and lower in grade, alternative sources need to be explored and a question of adaptability of the geometallurgical approach to the secondary resource repositories arises. The particle size distribution, chemical and mineralogical compositions of the Smaltjärnen historical tungsten tailings from physical separation in Yxsjöberg, Sweden were studied using drill core samples collected from different locations within the tailings repository in order to assess the amenability of the tailings to reprocessing. The tailings are dominated by the –600 to +149 μm particle size fraction. This fraction contains most of the elements of interest (W, Cu, S, Sn, Zn, Be, Bi and F) hosted by scheelite, chalcopyrite, pyrrhotite, cassiterite, danalite (both Zn and Be), bismuthinite and fluorite, respectively. The particle size distribution and mineralogical composition vary across the repository, suggesting a possible existence of geometallurgical domains, which require further assessment to evaluate metallurgical performance. Keywords: Historical tailings, tungsten, scheelite, geometallurgy, characterisation, mineralogy, reprocessing

Jan 1, 2020

The key functions of project evaluation are to assess potential profitability and to develop an effective operational design. For mining projects, design aspects include mining methodology, ore treatment methodology and production rates. All of these characteristics impact on project economics and overall value. Resource models, which form the ultimate basis of project evaluation, typically consist of tonnes above cut-off, grade above cut-off and the spatial distribution (connectivity) of tonnes/grade above cut-off, for one or more variables. Dilution, ore loss and metallurgical recovery are all modifying factors applied to the resource model during evaluation and determination of profitability. A key issue is: how is the value determined? In addition to traditional combination of in situ tonnes/grade, the following merit serious consideration: the concentration of deleterious elements, throughput rates, mining/processing costs and - importantly - metallurgical recovery. Geometallurgy is an emerging field targeted at integrating these issues by identifying either direct measures or proxies for throughput (hardness, grindability), recovery (liberation, mineral shape/texture, etc) and concentrate quality from easily collected macro-, meso- and microscopic data. These 'geometallurgical variables' drive project costs and revenues in a fundamental way. For geometallurgical characterisation to have a real impact on business design, it must enable improved mine planning. When creating spatial estimates for such variables, it is preferable to find proxies that can be measured as close to the intact rock mass as possible. However, spatial estimation of proxies for geometallurgical properties and responses is complex and requires special consideration. Unlike grades, both proxies and absolute measures of geometallurgical variables are not necessarily linear or additive and therefore require very careful geostatistical consideration. In some cases, models must predict extreme values of geometallurgical attributes rather than averages. Incorrect characterisation of metallurgical recovery/throughput can (and has) led to misspecification of the scale of projects, and thus can be seriously value destructive. Aspects of geometallurgy have long been important in iron, bauxite, manganese and coal deposits and are increasingly on the radar for base and precious metal miners. However, as more metallurgically complex deposits are developed and mining of large-scale, low-grade deposits becomes more commonplace, the importance of characterising the metallurgical response in order to generate properly optimised projects will rapidly increase. It is possible that in many `traditional' (ie grades and tonnes) reserve models, the variables that drive the project are missing!

Jan 1, 2007

By M. David

This paper addresses the problem of technological transfer in geostatistics. Expert systems have become popular in certain fields because the needs of the industry are not provided for by traditional concepts and systems of education. The explicit knowledge approach in developing expert systems is presented through two experiments. The first describes a dedicated system written in GOLDEN LISP and the second a shell, using INSIGHT2, which has more general applications. Using expert systems forces on the user a new approach to parameter definition, and as an example an original method for the research of any anisotropy axes is developed which might well be useful in traditional programming. Two examples of application to a coal and a gold deposit are given.

Jan 1, 1987

By R. Cao

Geostatistics was initially developed in the mining sector, but has been extended to other geoscience applications, including forestry, environmental science, soil science, and petroleum science and engineering. This paper presents methods, workflows, and pitfalls in using geostatistics for hydrocarbon resource modelling and evaluation. Examples are presented of indicator variogram analysis of categorical variables, lithofacies modelling by sequential indicator simulation and hierarchical workflow, porosity modelling by kriging and stochastic simulation, collocated cokriging for integrating seismic data, and collocated cosimulation for modelling porosity and permeability relationships. These methods together form a systematic approach that can be effectively used for modelling natural resources.

Jan 1, 2014

By J. M. Ortiz

Mineral resource evaluation requires defining geological domains that differentiate the types of mineralogy, alteration and lithology. Usual practice is to consider the domain boundaries as hard, i.e. data from across the boundaries are disregarded when estimating the grades within a given domain. This practice may hinder the quality of the estimates when a significant spatial correlation of the grades exists across the domain boundaries. In this paper, several geostatistical methodologies to handle soft geological boundaries are compared through a case study on a copper mine in Chile. The estimation methods considered are: ordinary kriging using hard boundaries between geological domains; ordinary kriging omitting the geological boundaries; traditional and standardized ordinary cokriging of the grades assayed in different domains; ordinary kriging within dilated geological domains, that is, incorporating samples from adjacent domains up to a given radius from the boundary of the domain being considered. The estimations are performed using a set of exploration data (drill hole samples) and are validated using a set of production data (blast hole samples collected for grade control). Results indicate that kriging with dilated domains performs better than ordinary kriging using hard boundaries or no boundaries and better than the ordinary cokriging approaches. It therefore appears as a simple alternative to global kriging (without considering the geological domains) and allows accounting for changes in the grade average, dispersion and spatial continuity with the geological characteristics of the deposit, via the use of grade variograms proper to each geological domain. The maximal distance for searching samples from adjacent domains should be chosen according to the spatial correlation of the grades across the domain boundaries, or via a cross-validation at an early stage of the mine or a jack-knife if production data are available. Keywords: Kriging; cokriging; soft boundaries; hard boundaries; geological control; geological domains.

Jan 1, 2006

By F. A. G. M. Camisani-Calzolari

Approximately 850 groundwater samples were collected over a 29 300 km2 region of the semi-arid Northwestern Cape during the site selection phase of the South African radioactive waste disposal project. The purpose of the geostatistical investigation was primarily to delineate metallogenic occurrences and provinces which might exist below the thin veneer of surficial material and could thus interfere with the suitability of the site, and to quantify the distribution patterns of groundwater parameters in order to establish a relationship to local and regional geology. Up to 34 variables were analysed for each sample. Structural analysis revealed that the study area is statistically uniform. The variables have low correlation coefficients, with the exception of major ions, indicating a general poor degree of interrelationship between the spatial distribution patterns of the different variables. On the other hand, the long semivariogram range of the majority of variables, which reaches 70 km in cases, demonstrates their continuity on a regional scale. Kriging, which was repeated for each parameter, reveals that most variables, particularly trace metals, have distribution trends which are not influenced by local geomorphology or surface lithology. A 50 km wide, 220 km long metallogenic province, defined by kriging, could possibly reflect a broad metallogenic imprint on the basement and could represent a target area for prospecting. Kriging also reveals the possible existence of a wrench faulting system which may well have influenced the Namaqualand coastal graben and the western boundary of the Karoo.

Jan 1, 1987

Plurigaussian simulation allows constructing lithofacies or rock type models that reproduce the contacts between facies in accordance with the geologist?s interpretation. Its implementation requires inferring the local facies proportions, but the uncertainty in the true proportions is not accounted for. The simpler model with constant facies proportions may not yield realistic results, due to the possibility of obtaining facies at locations where it is geologically unlikely to find them. This article presents a variation of the plurigaussian model, in which the facies proportions are represented by random fields. The realizations can be made conditional to soft geological informati onto account for local changes in the facies proportions. The model is illustrated via a case study of a porphyry copper deposit where four Gaussian random fields are simulated conditionally to drill hole data and to constraints on the probability of finding a given facies at specific locations (control points) in the deposit. Then the first two fields are truncated using the random thresholds defined by the last two, generating a three-facies model. The proposed random proportion model proves to be simple to use and to account for spatial variations of the geological characteristics and for the uncertainty in the facies proportions. Keywords: categorical variable; lithofacies; truncated plurigaussian simulation; regionalized proportions

Jan 1, 2008

For practical reasons all basic input data for the gold mines of the Anglovaal Group conform to a regular grid of averages of sample values within 25-ft squares in the plane of the ore body; individual sample values with their metric co-ordinates are input and converted by a computer program to the basic 25-ft square averages. At the Prieska copper mine the bore- hole data are forced on to a regular grid of 15-m squares corresponding to the coordinates of the grid points nearest to the actual borehole intersections. As for the gold mines the Prieska ore body, although some 3 to 30 m thick, is also dealt with on a two-dimensional basis (Krige, 1973). On the gold mines the data subjected to geostatistical analysis cover: gold values (in cm g/t), uranium values (cm kg/t), and channel widths (cm). The gold and uranium values are normalised on the basis of log (value plus constant) and all the geostatistical analyses are performed on these transformed values. The channel widths usually conform reasonably well to the normal distribution and are, therefore, not transformed. At Prieska the metal grades analysed cover the two main products, copper and zinc, as well as the impurities lead and bismuth; in addition the specific gravity values and the hanging- and foot-wall deviations from a projection plane are also handled. These were all previously used on an untransformed basis but because of problems associated with the proportional effect the lognormal-de Wijsian model is now used for some of the grade variables. The key computer pro- grams can be summarised briefly as follows:

Jan 1, 1981

By Roger A. Blais, Michel David

"Matheron's geoslalislical method for the estimation of ore reserves has been developed to the point at which real-life problem may be handled effectively. The steps involved in the method are:(i) obtalning the variogram,(ii) fitting a model, and(iii) producing block estimates.All three steps may cause difficulty, and would-be users need a deep understanding of the theory if failure is to be avoided.To illustrate these points, specific cause are considered:(i) two almost equidimensional porpbyry deposits, one drilled randomly and the other regularly; and(ii) two iron formation, one drilled extensively and being mined, while the other is still at the stage of early estimation."

Jan 1, 2014

By J. -M. Chautru

A geostatistical simulation of a typical mining site for polymetallic nodules in the North Pacific Ocean is presented. This is the first stage in the design of an industrial mining system. Two variables which have a major effect on the orebody's economic potential are considered, namely: the maximum slope of the ground inside a mining block of 50 x 100 m; and the average quantity of nodules on the same support. Two geostatistical problems have emerged in this study. The first is due to the lack of a change of support model for the maximum of a variable. A provisional solution, considering an experimentally accessible 'equivalent' support, is proposed. The second is due to a non-linear link between the two variables. To be able to take this into account in the simulation, we propose a new method based on the decomposition: X = E(X/Y) + Residue (X). Satisfactory results were obtained with this approach.

Jan 1, 1987

By M. H. M. von Wielligh

"Brick manufacturers supply a variety of uniquely coloured facebricks to the building industry, which requires a high level of colour consistency in the products. Colour variation in bricks is influenced by the composition and consistency of the white clay raw material. By blending varieties of naturally occurring white clay the manufacturers produce a unique range of facebrick products. Homogeneity of the white clay raw materials mined at Lenasia is crucial for producing bricks of consistent colour. Geostatistical investigations of the major element distributions (SiO2, Al2O3, Fe2O3, and K2O) and loss on ignition (LoI) were conducted. An analysis of the spatial continuity of these variables followed by ordinary kriging indicated that the upper white clay layer at Lenasia is richer in K2O and Fe2O3 than the lower layer. Consistency in the colour of facebricks depends critically on careful management of the variability in the K2O and Fe2O3 content of the clays. The geostatistical approach to understanding the distribution of elements in the clay allows miners to construct clay stockpiles of consistent quality for feeding the brick-making process. Geostatistical investigation of the chemical contents in other clay domains within the deposit is recommended, and could be extended to all facebrick manufacturers to assist in improving the colour consistency of their products. IntroductionMost clay in South Africa is used in the manufacturing of tiles, pipes, bricks, whiteware, refractories, and pottery. Bricks are manufactured from a wide variety of clay types, the behaviour of which during firing depends critically on the the clay mineralogy and chemical composition, but this relationship not well understood (Stein, 1982). The variety among clay deposits is related to the different processes of formation (Deer, Howie, and Zussman, 1992). The geochemical composition of the clay can vary between layers and within the same layer in an individual deposit (Lurie, 1984). The properties of clay minerals are determined by their structures and the different combinations of silicate layers, cations, and hydroxyl ions (Kingery, Bowen, and Uhlmann, 1976). South African clays can be classified as either kaolinite or montmorillonite and are seldom found in a pure form (Lurie, 1984). Different clay minerals affect the drying, forming, firing behaviour, colour, and quality of the brick product in different ways. Laboratory tests (full physical analysis) can indicate the suitability of a clay for the manufacture of ceramic products. The minerals most essential for the manufacturing of clay brick products are kaolinite, illite, and quartz (Stein, 1982)."

Jan 1, 2017

By M. K. Roberts

The approximately 2800 Ma old Ventersdorp Contact Reef is a unique Witwatersrand orebody, from which about 6% of the world?s gold production is derived. A major portion of this production is mined at depths exceeding 2500 m and deepest levels of mining are at about 3600 m. The orebody?s hangingwall consists of volcanic rocks. This differs from the older Witwatersrand orebodies, which have quartzitic hangingwalls. The thickness of the Ventersdorp Contact Reef is generally about 1.20 m, but is highly variable, at an average dip of about 18°. A pronounced unconformity beneath this orebody is also expressed by varying footwall rock type characteristics and frequent rolling of the reef plane. These rolls follow topographic variations of the palaeo-surface. More geological than rock mechanics studies were performed on the Ventersdorp Contact Reef prior to 1992. Recently, however, a multidisciplinary team comprising various rock engineering and geological disciplines has delineated geotechnical areas by a novel technique. Geotechnical areas are defined by distinct footwall/hangingwall rock assemblages. The presence of three footwall and two hangingwall rock types results in the definition of six geotechnical areas across a distance exceeding 60 km, including about 10 gold mines. Distinct rock mass behaviour has been documented in three of the six geotechnically defined areas. Different rock mass behaviour is expressed by features such as mining-induced fracturing, closure rates, fall of ground characteristics and seismic character. Some geological features override the rock mass behaviour as defined for the individual geotechnical areas. These are undulations of the orebody or the frequency, characteristics and attitude of major discontinuities. It is concluded that the concept of geotechnically subdividing orebodies is not only important for facies delineation and the associated grade, but also needs to be considered for safety aspects, in determining factors such as the appropriate support to be employed.

Jan 1, 1999

By M. W. Grodner, J. Maaren, G. Guler, J. K. Schweitzer

The selection of the most suitable mechanized mining strategy has to consider the geotechnical environment in which it will be operating. A mechanized mining method or machine is designed to a given set of specifications to work within an environment. The geological conditions that define this environment are fixed—detailed information of these conditions for design specifications is thus critical. Two major classes of geotechnical parameters are defined—critical and design. The critical controlling factors are a result of mineral composition, size, shape, abundance, assemblage and associated texture, as well as discontinuity type and orientation. Design parameters are specific to each deposit, and their nature cannot be broadly described, as with the critical factors. It is shown that for major deposits in South Africa, namely the Witwatersrand Basin (gold), the Bushveld Igneous Complex (PGEs) and the Karoo Coalfields that by incorporating geological and geotechnical information that appropriate mechanized mining methods can be deduced, and that the performance and design parameters of specific technologies can be determined

Sep 1, 2001

By F. Hees, A. H. Bracken, L. I. Boshoff

"Biological cementation of the Mandena heavy mineral sand deposit in Madagascar was causing difficulty in dredge mining and hence in planning and control of production rates. An investigation was initiated to better evaluate the geotechnical properties of the orebody by defining the distribution and geotechnical properties of the cemented strata, in order to generate a site-specific geotechnical model for the deposit. The geotechnical characterization was developed by an integrated approach using several ground investigation techniques such as piezocone (CPTu) testing, geotechnical drilling, standard penetration testing (SPT), as well as laboratory testing. The final outcomes of the investigation included a 3D geotechnical model showing the distribution and extent of the cemented areas, as well as the typical geotechnical parameter ranges associated with each of the defined geotechnical units. The interpretations developed were incorporated into the mine and production planning to ultimately optimize operational planning and control.IntroductionQIT Madagascar Minerals (QMM) is a heavy mineral sand mining operation at Mandena, near Fort Dauphin in Madagascar. During the final planning and commissioning stages of the project, the need to fully characterize the unusual geotechnical conditions was identified and a geotechnical investigation became necessary.Nature of the problemDuring the commissioning phase it was found that mining production was being hampered by biologically cemented/indurated layers encountered within the sands. Closer inspection of the indurated horizons in the dredging face revealed that these layers contain a high loading of bacteria and fungi. It appears that the bacteria produce an extracellular (outside the cell) polysaccharide (i.e. sugar and carbon salts), which form a gelling biofilm to trap nutrients. There are a number of different bacteria. The fungi, on the other hand, produce a network of fibrous strands that bind the sand grains together. Thus both bacteria and fungi probably contribute to the ‘apparent cohesive’ strength or binding of the indurated sand (Lynn, 2008)."

Jan 1, 2017