Application of risk assessment to improve sustainability in bauxite mining

ABSTRACTGeostatistical modelling of grades in mineral deposits often requires the simulation of multiple related variables that have sum and fraction constraints. Sum constraints occur when the sum of some variables may not exceed or must equal a given constant. Fraction constraints occur when a variable may not exceed another variable. In this case, the geostatistical simulations should reproduce the histograms, variograms, multivariate relationships and honour the constraints. We present a methodology for the geostatistical simulation of multiple related variables that considers sum and fraction constraints. The methodology is illustrated in a case study. The data were obtained from a bauxite deposit. First, the original variables were re-expressed as ratios. Second, the variables were transformed using the Projection Pursuit Multivariate Transform (PPMT). Then the PPMT transformed variables were simulated independently using sequential Gaussian simulation and back-transformed. The simulations reproduced the histograms, variograms and bivariate relationships and honoured the sum and fraction constraints.

Nuwaifa Formation is a part of sequence stratigraphy that belongs to the Jurassic system exposed in the western desert of Iraq. The Jurassic system consists of Ubaid, Hussainiyat, Amij, Muhaiwir, and Najmah formations. Each formation is composed of basal clastic unit overlain by upper carbonate unit. Nuwaifa karst bauxite was developed in fossil karsts within the Ubaid Formation in areas where maximum intersection of fractures and faults exist. This bauxitization process affected the upper surface of the Ubaid limestone formation, which directly underlies the Nuwaifa bauxite Formation. Nuwaifa Formation represents karst-filling deposit that consists of a mixture of allochthonous (sandstone, claystone, and mudstone) and autochthonous lithofacies (bauxite kaolinite, kaolinitic bauxite, iron-rich bauxite, and flint clay). Most bauxite bodies occur within the autochthonous lithofacies and are lenticular in shape with maximum thickness ranges from few meters to 35 m and in some place up to 100 m. Petrographically, the bauxite deposit exhibits collomorphic-fluidal, pisolitic, oolitic, nodular, brecciated, and skeletal textures indicative of authigenic origin. Mineralogy boehmite and gibbsite are the only bauxite minerals; the former is dominant in the upper parts of the bauxite profiles, whereas the latter is dominant throughout the lower and middle part of the bauxite. Kaolinite, hematite, goethite, calcite, and anatase occur to a lesser extent. The study bauxites are mainly composed of Al2O3 (33–69.6 wt.%), SiO2 (8.4–42 wt.%), Fe2O3 (0.5–15.9 wt.%), and TiO2 (0.7–6.1 wt.%) with LOI ranging from 13.5 to 19.1 wt.%. Geochemical investigations indicate that the immobile elements like Al2O3, TiO2, Cr, Zr, and Ni were obviously enriched, while SiO2, Fe2O3, CaO, MgO, Zn, Co, Ba, Mn, Cu, and Sr were depleted during bauxitization process. The results of this study strongly suggest that the bauxite deposits of the Nuwaifa Formation are derived from the kaolinite of the Lower Hussainiyat Formation.

Guinea is known as a geological scandal due to the importance and diversity of its mineral resources. Experts use superlatives to highlight the country's bauxite potential, regardless of the assessing system. Several geological surveys agree that Guinea contains 33% of the world's known bauxite reserves. There is inconsistency in the way the content of a deposit is defined, and the concepts and definitions are mixed up in different statistical data.  As a result, an expert comparing various bauxite deposits must recognise the terms in use and adjust them in his assessment for consistency. The vast bauxite potential presents a serious opportunity for the country to become a forerunner in the bauxite and aluminium industries, as well as to develop red mud valorization opportunities. This article discusses the bauxite potential and the local alumina industry in Guinea, as well as the technologies used to value the resulting red mud. The bauxite and alumina sector is responsible for the largest direct contribution to GDP in Guinea.

Mineral resources are estimated to establish potential orebody with acceptable quality (grade) and quantity (tonnage) to validate investment. Estimating mineral resources is associated with uncertainty from sampling, geological heterogeneity, shortage of knowledge and application of mathematical models at sampled and unsampled locations. The uncertainty causes overestimation or underestimation of mineral deposit quality and/or quantity, affecting the anticipated value of a mining project. Therefore, uncertainty is assessed to avoid any likely risks, establish areas more prone to uncertainty and allocate resources to scale down potential consequences. Kriging, probabilistic, geostatistical simulation and machine learning methods are used to estimate mineral resources and assess uncertainty, and their applicability depends on deposit characteristics, amount of data available and expertise of technical personnel. These methods are scattered in the literature making them challenging to access when needed for uncertainty quantification. Therefore, this review aims to compile information about uncertainties in mineral resource estimation scatted in the literature and develop a knowledge base of methodologies for uncertainty quantification. In addition, mineral resource estimation comprises different interdependent steps, in and through which uncertainty accumulates and propagates toward the final estimate. Hence, this review demonstrates stepwise uncertainty propagation and assessment through various phases of the estimation process. This can broaden knowledge about mineral resource estimation and uncertainty assessment in each step and increase the accuracy of mineral resource estimates and mining project viability.

Estimations of mineral resources and ore reserves have been recently widely used by mining engineers and investors. The classification framework based on the prepared code by the Joint Ore Reserves Committee of The Australasian Institute of Mining and Metallurgy, Australian Institute of Geoscientists and Minerals Council of Australia (JORC code), which is one of the international standards for mineral resource and ore reserve reporting, provides a template system that conforms to international society requirements. Recent research has shown that an existing fault risk can affect the mineral resource and ore reserve estimation. According to this research, the faulted area that is involved in the effect on the estimated region is so extensive that it is not distinguishable. In this research, a new method called FGT (F for fault, G for grade and T for thickness) is introduced and presented for the estimation of mineral resources. The proposed method can provide an error map of a particular aspect of the combination of coal accumulation (G), fault risk (F) and thickness (T), and its output would categorise the mineral resources. This method was implemented in the Parvadeh Ш coal deposit, which is located in the eastern portion of Central Iran. The deposit contains five seams named B1, B2, C1, C2 and D; of these, C1 was selected as the most important seam in the exploratory grid analysis. Thus, C1 alone can reflect the properties of the Parvadeh Ш deposit. In this study, we compared the conventional method and the FGT method. This comparison indicated that the areas that should be rejected from the region in the FGT method are less and more distinguishable than those determined with the conventional method. Therefore, the inferred resources can be completely differentiated from the indicated and measured resources with a high resolution. The conventional method cannot distinguish between these three categories at this level of resolution. Therefore, the FGT approach has high precision in classifying the coal resource compared to the conventional method.

Mining contributes to the life quality of contemporary society, but can generate significant impacts, these being mitigated due to environmental controls adopted. This study aimed to characterize soil physical properties in high-altitude areas affected by bauxite mining, and to edaphic factors responses to restoration techniques used to recover mined areas in Poços de Caldas plateau, MG, Brazil. The experiment used 3 randomized block design involving within 2 treatments (before mining intervention and after environmental recovery), and 4 replicates (N=24). In each treatment, soil samples with deformed structures were determined: granulometry, water-dispersible clay content, flocculation index, particle density, stoniness level, water aggregate stability, and organic matter contend. Soil samples with preserved structures were used to determine soil density and the total volume of pores, macropores, and micropores. Homogenization of stoniness between soil layers as a result of soil mobilization was observed after the mined area recovery. Stoniness decreased in 0.10-0.20 m layer after recovery, but was similar in the 0-0.10 m layer in before and after samples. The recovery techniques restored organic matter levels to pre-mining levels. However, changes in soil, including an increase in soil flocculation degree and a decrease in water-dispersible clays, were still apparent post-recovery. Furthermore, mining operations caused structural changes to the superficial layer of soil, as demonstrated by an increase in soil density and a decrease in total porosity and macroporosity. Decreases in the water stability of aggregates were observed after mining operations.

It has long been recognized that the largest mineral deposits contain most of the known mineral endowment (Singer and DeYoung, 1980). Sometimes called giant or world-class deposits, these largest deposits account for a very large share of historic and current mineral production and resources in industrial society (Singer, 1995). For example, Singer (1995) shows that the largest 10 percent of the world’s gold deposits contain 86 percent of the gold discovered to date. Many mineral resource issues and investigations are more easily addressed if limited to the relatively small number of deposits that contain most of the known mineral resources. An estimate of known resources using just these deposits would normally be sufficient, because considering smaller deposits would not add significantly to the total estimate. Land-use planning should treat mainly with these deposits due to their relative scarcity, the large share of known resources they contain, and the fact that economies of scale allow minerals to be produced much more cheaply from larger deposits. Investigation of environmental and other hazards that result from mining operations can be limited to these largest deposits because they account for most of past and current production.The National Mineral Resource Assessment project of the U.S. Geological Survey (USGS) has compiled a database on the largest known deposits of gold, silver, copper, lead, and zinc in the United States to complement the 1996 national assessment of undiscovered deposits of these same metals (Ludington and Cox, 1996). The deposits in this database account for approximately 99 percent of domestic production of these metals and probably a similar share of identified resources. These data may be compared with results of the assessment of undiscovered resources to characterize the nation’s total mineral endowment for these metals. This database is a starting point for any national or regional mineral-resource or mineral-environmental investigation.

Laterite-type bauxite deposits typically exhibit a highly irregular boundary between the bauxite and underlying ferricrete units. This irregularity cannot be accurately modeled using data collected from sparsely spaced drillholes (e.g., 76.2×76.2 m or 250×250 ft). Geological models that assume a sharp and nearly horizontal bauxite/ferricrete contact can result in significant errors when calculating the in situ bauxite resource (in volume) and in misclassifying ore and waste during mining operations. Two primary sources of uncertainty must be addressed when modeling lateritic bauxite deposits: (1) grade uncertainty associated with variations in Al2O3 and SiO2% concentrations, and (2) geometric uncertainty related to lateral variations in the bauxite/ferricrete contact. Among these, geometric uncertainty is more critical, as accurately estimating bauxite ore tonnage depends on the precise modeling of the lateral variation in the boundary between the bauxite and underlying ferricrete units. This study evaluates the uncertainty of the bauxite resource within a selected mine area in northern Queensland, Australia, particularly in cases where experimental data are sparse and limited. To address this, the position variable (bauxite floor elevations) and the thickness of the bauxite unit are jointly simulated under two scenarios. In the first scenario, the histograms, variogram model parameters, and the estimated trend of the variables of interest are assumed to be known with certainty; that is, parameter uncertainty is not considered in the modeling process. In the second scenario, the histograms, variogram model parameters, and the estimated trend are considered uncertain, and parameter uncertainty is explicitly incorporated into the modeling process using the multivariate spatial bootstrap procedure. The methodology is applied to both scenarios, showing that incorporating parameter uncertainty in geostatistical modeling results in greater dispersion of the uncertainty associated with the in situ bauxite resource. The results show that the 95% confidence intervals for the in situ bauxite ore volume, derived from bauxite thickness realizations, vary depending on whether parameter uncertainty is considered. When parameter uncertainty is incorporated, the interval is (390,123 m3 and 393,223 m3), whereas without parameter uncertainty, it is (382,332 m3 and 384,373 m3). This comparison highlights that incorporating parameter uncertainty provides a more realistic assessment of resource risk in the modeling process.

Data from a mineral deposit are commonly obtained by core drilling. This kind of sampling involves high costs, limiting the number of drill holes. Additional holes should be located to bring the maximum benefit. The benefit can be evaluated by various ways and must take into account the goals of sampling. This article presents a case study where the deposit has been sampled and the new drillings must be added to reduce the uncertainty about a transfer function, Net Present Value (NPV) of the mining project. There are basically two ways to choose locations where new drillings should be placed for cases where the aim of sampling is to reduce uncertainty about a global function: the addition of new drillings outlining a quasi regular grid with previously collected drillings or the addition of new drillings on the locations of high uncertainty about the attribute of interest (or the attribute that is considered most influential in the transfer function). The performances of these patterns on reducing the uncertainty measured by the function selected are compared. The results point out that the most efficient pattern relates to the distribution (histogram) of the uncertainty about the attribute of interest. Thus, the choice of which sampling pattern should be adopted varies depending on data distribution and its influence on the transfer function.

The full potential of geostatistical simulation as a tool for planning, designing and optimising production is only realised when it is integrated within the entire design and production cycle. In the planning and design stages this involves the simulation of components of the production cycle that depend on (simulated) grades and geology. In the production stage it involves integration with the mining method and the type and use of equipment. This paper explores the general concepts of integrated geostatistical simulation and illustrates them with particular reference to blast design, equipment selection and the associated quantification of ore loss, ore dilution and the ability to select ore on various scales. The critical component of most metalliferous open pit mining operations is ore selection, i.e. the minimisation of ore loss and ore dilution during extraction. In general, extraction comprises drilling, blasting and loading, all of which are planned and designed on the basis of uncertain models of geology and grade. The application describes the integration of geostatistically simulated grade, geological and geomechanical models with blast modelling to provide a link between the estimated in situ characteristics of the orebody and the locations of the same (displaced) characteristics following the blast. This approach provides a means of evaluating different types of selection and thereby enables planners to optimise the selection process in terms of blast design, type and size of loading equipment, maximisation of ore recovery and minimisation of ore loss and dilution. This conversion of the in situ/block model resource to a realistically recoverable reserve may, in many instances, be the most significant source of uncertainty in reserve estimation.

Mineral resources and mining are the pillars of development in any country. Mining development must be performed based on the pillars of sustainable development to prevent the damage to water, soil, air, plants, wildlife and social life of local communities by exploiting valuable minerals and economic development. Lack of attention towards the pillars of sustainable development in the long-term can turn into serious damages to environment and social life of local communities. There would probably be needed to spend multiple times more than the added value earned by the mineral production in order to recompense the environmental and social damages caused by unauthorized mining. Therefore, from the late 2001 the beginning of mining activities in the Bauxite mine of the village of Tash has caused challenges for the environment, natural resources and social issues. Some of the most important of which are loss of water reserves in the region, the pollution of ground and surface waters, soil erosion, susceptibility of the region to dust, loss of vegetation and rangelands, the endangerment of wildlife, flooding due to inappropriate tailings depot. This paper addresses to the causes of these pollutions and how to stop further damages of the process.

Tropical laterite-type bauxite deposits often pose a unique challenge for resource modelling and mine planning due to the extreme lateral variability at the base of the bauxite ore unit within the regolith profile. An economically viable drilling grid is often rather sparse for traditional prediction techniques to precisely account for the lateral variability in the lower contact of a bauxite ore unit. However, ground-penetrating radar (GPR) offers an inexpensive and rapid method for delineating laterite profiles by acquiring fine-scale data from the ground. These numerous data (secondary variable) can be merged with sparsely spaced borehole data (primary variable) through various statistical and geostatistical techniques, provided that there is a linear relation between the primary and secondary variables. Four prediction techniques, including standard linear regression, simple kriging with varying local means, co-located cokriging and kriging with an external drift, were used in this study to incorporate exhaustive GPR data in predictive estimation the base of a bauxite ore unit within a lateritic bauxite deposit in Australia. Cross-validation was used to assess the performance of each technique. The most robust estimates are produced using ordinary co-located cokriging in accordance with the cross-validation analysis. Comparison of the estimates against the actual mine floor indicates that the inclusion of ancillary GPR data substantially improves the quality of the estimates representing the bauxite base surface.

The subject of the study is the forecast of the development of the Arctic territories of Russia at the zonal, regional and municipal levels based on the concept of technical and economic (structural) dynamics of N. Kondratiev – S. Glazyev – С. Peres. The object of study is the Arctic zone of the Russian Federation. The purpose of the study is to describe the technical and economic dynamics of the Arctic territories until 2035. This goal determined the solution of three tasks: 1) identifying the features of new resource development of the Russian Arctic based on the mineral resources and fuel and energy potential of the Arctic territories of Russia; 2) justification of the current situation in the regions of the Russian Arctic, such as the dynamics of technological structures and calculated positions on the volume of GRP in 2035; 3) compiling a list of Arctic municipalities (49) with limited delivery times for cargo and their typology based on the speed of technical and economic dynamics. Results of the study: I. The resource potential of the Russian Arctic from the point of view of technological structures can be strengthened through the commissioning of deposits of graphite, antimony, and bauxite, the global demand for which is characterized by favorable conditions in the forecast period; II. The regions of the Russian Arctic are differentiated based on the analysis of greenfield projects carried out during the forecast period into three groups of technological renewal: a) maximum; b) partial; c) minimal. The forecast of the GRP of the Arctic territories based on resource production indicators in 2035 determined their rank: 1) Yamal-Nenets Autonomous Okrug; 2) Murmansk region; 3-4) Nenets Autonomous Okrug and the Arctic of the Krasnoyarsk Territory; 5) Arctic of the Republic of Sakha (Yakutia); 6) Arctic of the Komi Republic; 7) Chukotka Autonomous Okrug; 8) Arctic of the Arkhangelsk region; 9) Arctic of the Republic of Karelia. III. Arctic municipalities with limited delivery times are separated into four groups from the point of view of the prospects for the formation of a new technological structure based on new projects: 1) maximum potential (12); 2) average potential (9); 3) without new mining projects, but with prospects for completing the development of previously started ones and technological modernization of old projects (12); 4) without prospects for the deployment of new projects for the development of non-renewable resources, but with prospects for the development of biological resources (16). Possible application of the results can be documents of strategic planning of the Russian Arctic at the zonal, regional and municipal levels.

Uncertainty quantification of structural and geotechnical parameter by geostatistical simulations applied to a stability analysis case study with limited exploration data

Resource estimation of mineral deposits requires spatial modelling of orebody boundaries based on a set of exploration borehole data. Given lateritic bauxite deposits, the spacing between the boreholes is often determined based on the grade continuity. As a result, the selected drill spacing might not capture the underlying (true) lateral variability apparent in the orebody boundaries. The purpose of this study is to investigate and address the limitations imposed by such problems in lateritic metal deposits through multiple-point statistics (MPS) framework. Rather than relying on a semivariogram model, we obtain the required structural information from the footwall topographies exposed after previous mining operations. The investigation utilising the MPS was carried out using the Direct Sampling (DS) MPS algorithm. Two historical mine areas along with their mined-out surfaces and ground penetrating radar surveys were incorporated as a bivariate training image to perform the MPS simulations. In addition, geostatistical simulations using the Turning Bands method were also performed to make the comparison against the MPS results. The performances were assessed using several statistical indicators including higher-order spatial cumulants. The results have shown that the DS can satisfactorily simulate the orebody boundaries by using prior information from the previously mined-out areas.