Mineral Resource Classification Research Articles

Impact of Competent Persons' judgements in Mineral Resources classification

Uncertainty with regard to estimated grades and tonnages of a mineral deposit demands risk assessment in order to build investor confidence and attract the interest of other stakeholders in the success of a project. Uncertainties associated with Mineral Resource estimates can lead to unreliable production schedules and unpredictable cash flows. However, the techniques used in the mining industry to determine these uncertainties are inconsistent, because the important decisions taken in the process are solely dependent on the responsible Competent Person (CP), without limitations. This leads to disparities between different CPs' results, using data-sets from the same drill-holes. The various standard codes for public disclosure provide guidelines and recommendations for the classification of Mineral Resources and Reserves but do not provide details on, for example, the amount of geological and geostatistical information needed to qualify for each category of Resources and Reserves. The parameters used to generate the classification categories are subjectively assumed by the responsible CP. In this paper we investigate the impacts of different CPs' judgements on resource classification, using the same data-sets. The results underpin the need for the mining industry to develop a uniform Mineral Resources and Reserves classification framework that can minimize or avoid significant discrepancies that lead to potential misleading public disclosures.

Optimising the placement of additional drill holes to enhanced mineral resource classification: a case study on a porphyry copper deposit

ABSTRACT In this study, we compared outcomes of optimising the placement of five additional drill holes using three geostatistical cost functions (AKV, WAKV, and CV) and the Particle Swarm Optimisation algorithm (PSO). WAKV identified locations with higher average copper grades compared to AKV. Conversely, CV suggested sites with high kriging variance and copper grade variation. Initial holes, alongside those determined by each cost function, were used to classify mineral resources. Findings underscored the effectiveness of optimising drill hole placement based on cost functions in reducing uncertainty and improving mineral resource classification.

Classification of rare earths mineral resources using the Jequié/BA complex rock weathering chemical index

The most common economic mineral deposits of Rare Earths are associated to magmatic calc-alkaline to alkaline rocks and their products. This work presents data from drilling carried out in rocks of the Jequié/BA Complex, mineralized in rare earths, which were subjected to an intense weathering process, similar to what occurred in the Ion Adsorption Clays deposits in southern China. The interpretation of the survey data allowed the classification of rare earths mineral resources with similar, sometimes higher, levels than those of Chinese deposits, contained in the lateritic regolithic profile studied. The chemical index of rock alteration (CIA) was adopted as a classification tool, horizontally separating the mineralized weather profile into six zones. The data indicate that there was supergenic enrichment REO in the lower portions of the profile and sometimes in the upper zones. The average levels ranged between 0.09% and 0.22% REO, with maximum values of 1.6%. A model section representing the deposit of rare earths minerals of supergenic origin in rocks of the Jequié/BA Complex was developed.

Mineral Resource Classification Using Geostatistical and Fractal Simulation in the Masjed Daghi Cu–Mo Porphyry Deposit, NW Iran

Mineral resource classification is an important step in mineral exploration and mining engineering. In this study, copper and molybdenum resources were classified using a combination of the Turning Bands Simulation (TBSIM) and the Concentration–Volume (C–V) fractal model based on the Conditional Coefficient of Variation (CCV) for Cu realizations in the Masjed Daghi porphyry deposit, NW Iran. In this research, 100 scenarios for the local variability of copper were correspondingly simulated using the TBSIM and the CCVs were calculated for each realization. Furthermore, various populations for these CCVs were distinguished using C–V fractal modeling. The C–V log–log plots indicate a multifractal nature that shows a ring structure for the “Measured”, “Indicated”, and “Inferred” classes in this deposit. Then, the results obtained using this hybrid method were compared with the CCV–Tonnage graphs. Finally, the results obtained using the geostatistical and fractal simulation showed that the marginal parts of this deposit constitute inferred resources and need more information from exploration boreholes.

ЕКОЛОГІЧНІ ТА СОЦІАЛЬНІ РИЗИКИ В МІЖНАРОДНИХ ТА ВІТЧИЗНЯНИХ СИСТЕМАХ ОЦІНКИ МІНЕРАЛЬНИХ РЕСУРСІВ

It was defined that the ecological and social risks became key in the implementation of mining projects from the stage of geological study through development till mining operation. The main components of these risks are fixed over the past years, which are related to the problems of water resources management, the processes of decarbonization of production, the reduction of the negative impact on climate change, the environmental friendliness of production and the emissions volumes that are directly or indirectly related to mining enterprises, etc. A comparison of domestic and international standards for the assessment of mineral reserves and resources was carried out according to the basic features of classification with the determination of social and environmental assessment factors. The features of the Classification of Mineral Reserves and Resources of the State Subsoil Fund, the UN Framework Classification, the PRMS Petroleum Resources Management System, the International Reporting Standards of the CRIRSCO Mineral Resources Committee are analyzed and compared in order to find features that allow determining the social and environmental risks of mining projects. The presence of these direct features in the classification systems indicates the orientation of the assessment standards to the comprehensive assessment of projects as such meeting the goals of sustainable development. The social and ecological viability of subsurface and natural resource projects is used as a direct feature only in the UN Framework Classification, while its inclusion took place in 2009 in the part of social factors, and in 2019 – in the part of environmental factors. This classification is considered as a tool for the effective management of national resources, necessary for the realization of the goals of sustainable development, which enables all stakeholders to find a common understanding of the development of resources and territories, to compare projects in different types of resources and subsoil use. In other international standards, as well as in the domestic classification of the State Fund of Subsoil, socio-ecological criteria are taken into account indirectly, which is one of the key areas of development of these mineral resource assessment systems. Such development can take place in two directions: the inclusion of social and ecological criteria directly as basic features, while this is possible both in the form of complex parameters and individual classes/subclasses; use and improvement of existing methods of resource and reserves valuation, taking into account the environmental and social risks of the implementation of subsoil use projects.

Classification of Laterite Nickel Resources Using the Average Distance Approach

The resource classification system helps protect producers and consumers from ambiguous reporting of mineral resources. Classification systems have been introduced in many countries, but they are often general, so they are not easy to apply in the field. Geostatistical approaches are often inaccurate on data with high nugget values. The system requires sophisticated knowledge and takes time to understand, while field practitioners are eager to immediately get mineral resource classification results. This study aims to introduce the average distance from the borehole as a mineral resource classification parameter. In this study, modeling and grade estimation uses a block model with nearest-neighbor polygon and inverse distance weighing techniques as grade estimation techniques. The highest weight in the NNP estimation technique is the closest sample, while the IDW weight depends on the distance; therefore the NNP and IDW techniques use distance considerations only. Based on the histogram of the average distance, the populations in the graph show the classification as inferred resources, indicated resources, and measured resources. The application of the average distance technique for the classification of laterite nickel resources uses the block model.

On the Use of Machine Learning for Mineral Resource Classification

On the Use of Machine Learning for Mineral Resource Classification

Conditional Simulation for Mineral Resource Classification and Mining Dilution Assessment from the Early 1990s to Now

Andre Journel joined Stanford University in 1978, and his program grew quickly to include a dozen students from the USA, Canada, Europe, and South Africa. He was instrumental in organizing the Second International Geostatistical Conference (Tahoe ’83), during which 13 papers were presented that can be linked to his group. Out of these 13 papers, 9 were mining-related, with 7 on recoverable reserves, 2 on uncertainty, 2 on conditional simulation, and 3 on nonparametric geostatistics. A significant research effort at the time was therefore directed at change of support, global and local recoveries, and uncertainty, but future trends could also be identified, such as nonparametric geostatistics and conditional simulation. This paper is a practical review of conditional simulation as a tool to improve mineral resource estimation in the areas of uncertainty, classification, and mining selectivity or dilution, based on the authors’ experience. Some practical considerations for conditional simulation are briefly discussed. Four case studies from the early 1990s to the late 2010s are presented to illustrate some solutions and challenges encountered when dealing with real-world commercial projects.

Research on Reserve Classification of Solid Mineral Resources in China and Western Countries

Combined with the development and application of mining markets at home and abroad, the following understandings are obtained through comparative analysis of GB/T 17766-1999 Classification for resources/reserves of solid fuels and mineral commodities, GB/T 17766-2020 Classification for resources/reserves of solid fuels and mineral commodities and JORC Code. 1) GB/T 17766-2020 is more concise and efficient, focusing on the objective evaluation of economic value; 2) Since the form and connotation of GB/T 17766-2020 is similar to JORC Code and other Western norms, the implementation of GB/T 17766-2020 will be conducive to international integration; 3) A variety of factors caused the low recognition of domestic reports and small market influence. However, according to GB/T 17766-2020, we can gradually improve the recognition and influence by means of strengthening process management and responsibility to natural persons.

Modeling and Resource Classification Lateritic Nickel Deposits on a Heterogeneous Block in The Haul-Sagu Area using Estimation and Simulation Geostatistical Method

Deposits modeling is a very important thing in the exploration field, especially in estimating reserves. This research was conducted to model the geometry of lateritic nickel ore deposition on heterogeneous blocks using the geostatistical estimation method Ordinary kriging (OK) and simulation methods namely, Sequential Gaussian Simulation (SGS) then the distribution of laterite zonation was carried out to calculate the resource and mineral resource classification based on estimation data and simulation. The estimation results using the OK method have an average value of Ni higher than the average Ni grade from the SGS simulation results. Analysis of the calculation of total tonnage of resources from the estimated OK data shows the total amount of measured tonnage of 5,875 tons is far lower than the amount of resource tonnage from the SGS simulation data which displays the total amount of tonnage measured 189,766 tons. However the average grade of Ni from measured OK Resources is 1.49% higher, compared to the average Ni grades from measured resources of SGS 1.33%. with a difference of 0.16% Ni grades. The opposite occurs when the average Fe grade of the measured OK resource is lower 24.15% compared to the average Fe grade of the Measured resource of SGS 32.81% with a very large difference in Fe grade of 8.66%.

Quantifying the criteria for classification of mineral resources and reserves through the estimation of block model uncertainty using geostatistical methods: a case study of Khoshoumi Uranium deposit in Yazd, Iran

ABSTRACT Investments and progress of mineral projects depend on the quantity (tonnage) and quality (grade) of mineral resources and reserves. This study examines the impact of various criteria used in the classification of mineral deposits or parameters defining these criteria. The data used in this study include the uranium assay analysis from 127 exploratory boreholes, which were then subjected to a three-directional variography after statistical studies to identify regional anisotropy. A grade block model was built using the optimal parameters of variograms and with the help of kriging estimator. Then, by using different methods of estimating the block model uncertainty including kriging estimation variance, block error estimation, kriging efficiency and slope of regression, classification of mineral reserves was carried out in accordance with the JORC standard code. Based on different cut-off grades, the tonnage and average grade were calculated and plotted. An innovative quantitative method based on the distribution function of the mentioned parameters and the fractal pattern of separation of populations was used for the classification of mineral reserves. The existence of the least difference between the use of standard and fractal patterns in the slope of regression method indicated less error and was a proof of more reliable results.

Mineral Resources Management on the basis of the United Nations FrameworClassificaion (National Classification of Mineral Reserves and Resources of Ukraine)

Characteristic of United Nations Framework Classification for fossil energy and mineral reserves and resources (UNFC-2009) as an universal system of mineral reserves/resources deposits evaluation in market conditions, is given. The UNFC-2009 ensures reporting on reserves / resources evaluation for all types of raw ma-terials, takes into account the influence of ecological and social factors and allows to maintain national termi-nology while ensuring its consistency with the international standards. The comparison with the Classification of Ukraine has allowed to establish that National classification is based on the same approaches to categorization of reserves/resources as the UNFC-2009 and all categories of mineral reserves and resources, which are used by Classification of Ukraine, find their analogues in the UNFC-2009 that not only allows to take into account the needs of the state, but also provides comparability of the statistical reporting on reserves/resources at an international level. The directions for development of the Ukraine Classification on the path to its further harmo-nization with the UNFC-2009 and other classification systems (CRIRSCO, SPE PRMS) are determined. The issues of development, promotion and support for the implementation of a global system that can be used as a tool for sustainable management of natural resources are highlighted. Priority is given to the development and deployment of the United Nations Resource Management System (UNRMS) based on the United Nations Framework for Classification of Resources (UNFC), including principles, specifications, guidelines, protocols (procedures and checklists) and best practices designed to promote the sustainable management of energy, raw materials and other resources.

Critical Review of Mineral Resource Classification Techniques in the Gold Mining Industry

Critical Review of Mineral Resource Classification Techniques in the Gold Mining Industry

A product classification approach to optimize circularity of critical resources – the case of NdFeB magnets

The circular economy concept and critical resources have recently received significant momentum across the board. However, only little work is done so far to assess the role of circular economy strategies in reducing a system's vulnerability to the increasing supply risk experienced by a number of critical resources. This study is aimed at exploring different resource circularity options (e.g., reuse, refurbishment, remanufacturing, and recycling) for critical resources, such as neodymium (Nd) and dysprosium (Dy) that are two key rare earth elements (REEs) found in the neodymium-iron-boron (NdFeB) magnets, along their value chain. A product classification approach is presented to better understand the circularity potential of critical resources, which in this study is demonstrated by the case study of NdFeB magnets. The proposed approach allows for grouping products considering their most feasible resource circularity pathway. As a next step, the product classification approach leads to developing a theoretical framework for anthropogenic resource classification, inspired from the natural mineral resource classification system of the United States Geological Survey. The key advantage of anthropogenic resource classification is identification and grouping of products with respect to varying degree of economic and technical feasibility of resource recovery from them, under current and future framework conditions.

Categorization of Mineral Resources Based on Different Geostatistical Simulation Algorithms: A Case Study from an Iron Ore Deposit

Mineral resource classification plays an important role in the downstream activities of a mining project. Spatial modeling of the grade variability in a deposit directly impacts the evaluation of recovery functions, such as the tonnage, metal quantity and mean grade above cutoffs. The use of geostatistical simulations for this purpose is becoming popular among practitioners because they produce statistical parameters of the sample dataset in cases of global distribution (e.g., histograms) and local distribution (e.g., variograms). Conditional simulations can also be assessed to quantify the uncertainty within the blocks. In this sense, mineral resource classification based on obtained realizations leads to the likely computation of reliable recovery functions, showing the worst and best scenarios. However, applying the proper geostatistical (co)-simulation algorithms is critical in the case of modeling variables with strong cross-correlation structures. In this context, enhanced approaches such as projection pursuit multivariate transforms (PPMTs) are highly desirable. In this paper, the mineral resources in an iron ore deposit are computed and categorized employing the PPMT method, and then, the outputs are compared with conventional (co)-simulation methods for the reproduction of statistical parameters and for the calculation of tonnage at different levels of cutoff grades. The results show that the PPMT outperforms conventional (co)-simulation approaches not only in terms of local and global cross-correlation reproductions between two underlying grades (Fe and Al2O3) in this iron deposit but also in terms of mineral resource categories according to the Joint Ore Reserves Committee standard.

Mineral Resources classification of a nickel laterite deposit: Comparison between conditional simulations and specific areas

Mineral Resources classification of a nickel laterite deposit: Comparison between conditional simulations and specific areas

Discovered and undiscovered mineral resources: Evolving accounts and future prospects of minerals in Finland

Minerals are natural resources requiring accurate investigation and planning of extraction prior the actual mining stage. National and regional mineral resource inventories would benefit from adding more detail beyond tonnage, grade and location, when evaluating both current and potential future mineral wealth. In this paper, we consider the effect of information, time and project cycle on the mineral resource inventories for Finland. The research is forward-looking, and thus, we include the identified (but not mined) portions of discovered mineral resources and also the estimated undiscovered mineral resources (terminology based on the United States Geological Survey mineral resource classification). In addition, we consider how other types of land use limit mineral exploration. The studied metals were Cu, Ni, Zn, Cr, Fe, Au, Ag, Pt and Pd. The identified mineral resources of all of these metals increased from 2008 to 2015, driven by exploration and development at already known mineral deposits and mine sites. The results show that continuation of mine production is relatively well supported by currently profitable resources (i.e. ore reserves) in active mines and via development projects in the pipeline. In addition, a significant amounts of resources are still inferred to be discoverable for Pt, Pd, Cr, Au and Cu. A quarter of the mineral potential areas are reserved for land uses that restrict but not necessarily prevent mineral exploration. A share of identified resources occur in deposits that are not feasible for mining or interesting enough for exploration and development today. Our study demonstrates that identified resources become usable within different time periods. Knowledge of mineral resources and their usability is constantly changing, and even though mineral deposits are non-renewable, known mineral resources can be increased by exploration and mine planning processes.

Development of a best-practice mineral resource classification system for the De Beers group of companies

Development of a best-practice mineral resource classification system for the De Beers group of companies

Wykazywanie zasobów wêgla kamiennego w Polsce zgodnie z JORC Code / Reporting of Hard Coal Reserves and Resources in Poland on the Basis of the JORC Code

Streszczenie Wykazywanie zasobów złóż kopalin oraz podawanie tych informacji do wiedzy publicznej stanowi istotne zagadnienie w odniesieniu do zasadności prowadzenia działalności gospodarczej w branży geologiczno-górniczej. Od szeregu lat w przestrzeni międzynarodowej funkcjonuje system raportowania i klasyfikacji zasobów kopalin stałych bazujący na australijskim kodeksie JORC. Dokument ten, honorowany przez giełdy, przedstawia minimum standardów i wytyczne niezbędne do rzetelnego i wiarygodnego wykazywania zasobów złóż; kodeks JORC stosuje dwie podstawo­we kategorie zasobów: resources i resenres, z których pierwsza odnosi się do zapasów (zasobów bilansowych) kopaliny, a druga do zasobów wydobywalnych - czyli wielkości możliwych do wy­dobycia przy uwzględnieniu aktualnie dostępnych środków technicznych i obecnych kryteriów ekonomicznych. Układ klasyfikacji jest hierarchiczny - zasoby resen/es stanowią podzbiór zapasów. Wraz z napływem informacji geologicznej wśród tych ostatnich wyróżnia się zasoby domniemane (inferred), oznaczone (indicated) oraz zmierzone (measured), natomiast w obrębie pierwszych - zasoby prawdopodobne (probable) i pewne (proved). Zasoby bilansowe zmierzone oraz wy doby walne pewne stanowią najlepiej rozpoznane partie złóż. W związku z sukcesem JORC wiele krajów wprowadziło bazujące na nim własne, narodowe kodeksy wykazywania zasobów. Kodeksy te sku­pione są w obrębie CRIRSCO - Komitecie Międzynarodowych Standardów Wykazywania Zasobów Kopalin [stałych]. Polska klasyfikacja zasobów ma hierarchiczny charakter - z łącznych zasobów geologicznych wyodrębnia się zasoby bilansowe obejmujące zasoby przemysłowe i nieprzemysłowe. W zależności od zakresu wiedzy geologicznej zasoby wykazuje się w pięciu kategoriach rozpoznania: D, C2, Cj, B i A. Po odjęciu strat i uwzględnieniu zubożenia otrzymuje się zasoby eksploatacyjne. Jak do­tychczas, pomimo doświadczeń rosyjskich w tym zakresie, w Polsce nie wypracowano standardu harmonizującego system polski i międzynarodowy. Treść niniejszego artykułu przedstawia pro­pozycję takiego dostosowania.

Combination of geostatistical simulation and fractal modeling for mineral resource classification

The separation, identification and assessment of high-grade ore zones from low-grade ones are extremely important in mining of metalliferous deposits. A technique that provides reliable results for those purposes is thus paramount to mining engineers and geologists. In this paper, the simulated size–number (SS–N) fractal model, which is an extension of the number–size (N–S) fractal model, was utilized for classification of parts of the Zaghia iron deposit, located near Bafq City in Central Iran, based on borehole data. We applied this model to the output of the turning bands simulation method using the data, and the results were compared with those of the application of the concentration–volume (C–V) fractal model to the output of kriging of the data. The technique using the SS–N model combined with turning bands simulation presents more reliable results compared to technique using the C–V model combined with kriging since the former does not present smoothing effects. The grade variability was classified in each mineralized zones defined by the SS–N and C–V models, based on which tonnage cut-off models were generated. The tonnage cut-off obtained using the technique of combining turning bands simulation and SS–N modeling is more reliable than that obtained using the technique of combining kriging and C–V modeling.