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By D T. Ribeiro, J F. C L Costa, J C. Koppe

Drilling and sampling are responsible for most of the costs during mineral exploration, especially in multi-elements and polymetallic deposits, such as iron, manganese and bauxite deposits. On these deposits, often it is necessary to estimate multiple attributes at several granulometric fractions, ie distinct particle sizes. This paper investigates the effect of sampling at a close spacing grid only the head grades for the multiple chemical species in iron ore deposits. The remaining required data at the various grain sizes are sampled at a sparse grid. The derived geological model is checked for precision and accuracy comparing the output obtained against a model obtained using a complete isotopic data set including head grades and chemical analysis at each granulometric fraction analysed at all sampled positions. Among the several tested alternatives, the best procedure for dealing with the posed problem involved utilising the correlation coefficients between the grades at distinct fractions to obtain an isotopic database prior to interpolation. Cokriging was the method used, based on the intrinsic coregionalisation model. Estimates were obtained with the quality needed for the proposal of the study. Results showed that at least 50 per cent of the blocks were estimated with errors less than ten per cent relative to the grades obtained at the reference model, using only 15 per cent of the granulochemical data employed to obtain the reference model. The methodology also preserved the correlations between the attributes in their several granulometric fractions on the estimated model.

Sep 26, 2011

By E Ben-Awuah

Mine planning is the backbone of all mining enterprises and determines the profitability or otherwise of any mining investment. Providing high quality ore and tailings containment at the right time are the main drivers in oil sands mining. Recent environmental and regulatory requirements also makes waste management an integral part of mine planning in the oil sands industry (Directive 074). Due to the limitation of lease area, the pit phase advancement in oil sands mining is carried out simultaneously with the construction of tailings dykes in the mined out areas of the pit. These in-pit dykes are constructed to hold tailings that are produced during the processing of the oil sands ore after an initial external tailings facility. Most of the materials used in constructing these in-pit and ex-pit dykes come from the oil sands mining operation, making it necessary to have a plan for supplying the dyke material. The research problem here is categorised as: determining the order of extraction of ore, dyke material and waste to be removed from a predefined ultimate pit limit over the mine life that maximises the net present value of the operation û a strategic schedule; anddetermining the destination of dyke material that minimises construction cost depending on the construction requirements of the various dykes as per their designs û an operational schedule. There has been developed, implemented and verified a theoretical optimisation framework based on mixed integer goal programming (MIGP) to address the oil sands long-term production scheduling and waste management problem. The research introduced the development of multiple material types and multiple destination optimisation techniques using MIGP in the context of mine planning. This study presents an integration of mixed integer programming and goal programming in solving large-scale mine planning optimisation problems using clustering and pushback techniques.

Sep 26, 2011

The Rio Tinto Iron Ore group currently estimates grade attributes for mineral resources using ordinary kriging (OK). OK produces a smoothed globally unbiased estimate, but does not capture local variability, which can have significant impact on mine planning and scheduling. The dimensions and the multivariate nature of iron ore deposits make point simulations of whole deposits impractical. With a direct block simulation method the size and speed limitations of point simulations can potentially be overcome, resulting in a viable method for capturing local variability and for providing risk measures into the mine plan and schedules. Some iron ore deposits are highly folded (post mineralisation) and require preprocessing using an unfolding algorithm to properly define the continuity parameters and directions of anisotropy before simulation can proceed. Block co-simulation proceeds in unfolded space and since mine planning require a block-model with regular block-sizes; a regular block-model is unfolded first. This paper discusses a block co-simulation approach that can be used to simulate the irregular blocks resulting from the unfolding process. A section of an iron ore deposit is used for testing the block co-simulation algorithm and the simulation results are compared against the Isatis direct block simulation method. Available blasthole data is also used to validate the behaviour of the block co-simulation algorithm.

Sep 26, 2011

By B J. Wilde

Evaluating the resources and reserves in a mineral deposit requires many interdependent subjective decisions. The decision of stationarity is arguably the most important. This decision includes: the choice of domains that subset the entire deposit, modelling the boundaries of each domain, and understanding and considering the nature of the contacts between domains. Reasonable choices are made in consideration of the geological context, the available data, the goals of the study and the available resources for the study. This paper reviews aspects of the decision of stationarity in modern resource assessment with a focus on quantifying uncertainty and using numerical/statistical tools to help the geomodeller. The use of volume/distance functions to quantify uncertainty in domain limits is particularly important and is presented in detail. The use of contact plots provides help with the continuity of grades across domain boundaries. Realisations are not assembled as a branching combinatorial of all possibilities, but as a set of realisations that provide a measure of uncertainty. This paper amounts to a definition of stationarity for modern resource assessment.

Sep 26, 2011

By J F. C L Costa, J C. Koppe, C Diedrich

Currently mineral resources evaluation is firstly expressed in terms of volume. Next the resources are transformed into tonnes by using an average bulk density applied to the whole deposit or, in some other circumstances, various different densities to distinct geological domains. Previous work in uranium, copper and nickel deposits used linear correlation between grades and bulk density to derive the density. Geophysics methods are also another good way to obtain density indirectly.These approaches do not take into account that two samples with the same grade but with different bulk densities can characterise different sample supports, leading to severe bias in grade and tonne estimates. It is important that the systematic measurements of bulk density are included into the estimation process, particularly when density is not correlated with the grades. Additionally, the extra time and costs involved in obtaining the bulk density data have made the mining industry disregard it.This study reports the impact in resource estimates by using a methodology that includes the bulk density variability. It involves the determination of a variability model for the bulk density and another model for the composite that was weighted by density as well as by its length. Next, these variables are estimated by kriging and the final grade estimates are obtained. The tonnages are obtained with the bulk density estimates. The conventional methodology was also applied and both estimates are compared to the reconciliation data from a major copper deposit. The results show a significant difference between the tonnage and grade estimates obtained from these two methodologies.The results show that considering density variability when compositing leads to a more accurate methodology resulting in better grade and tonnage estimates locally and globally.

Sep 26, 2011

The JORC Code contains a mandatory classification system for Mineral Resource and Ore Reserve estimates for public reporting. The classification is a statement of the Competent PersonÆs confidence in the estimate and an attempt to convey that confidence to the various users of the resource estimate. In general the classification process is either largely subjective, relying on the Competent PersonÆs experience, or relies on statistical measures derived from the estimation process, or is derived from an estimated level of confidence in the outcome. However, the statistical measures may not necessarily relate to the overall confidence in the resource or reserve which must take account of the confidence in the geological inputs to the estimation.In addition to the traditional deterministic interpretation and estimations adopted by geologists, semi-quantitative techniques are now available to improve the estimation of confidence while continuing to involve the Competent PersonÆs experience in the process. Methods for quantifying confidence in mineral resource estimates for advanced projects and operating mines have also been developed.Classification is undertaken primarily as a communication tool between the estimators and the other stakeholders in the process. A brief examination of the stakeholdersÆ requirements is included.

Sep 26, 2011

By M R. Asef

Although generation of environmentally harmful hydrogen sulfide is considered to be related to sour gas fields, sweet gas reservoirs and waste fluids, travertine springs and geothermal fields may also produce acid gas (H2S and CO2) under certain conditions. The potential parameters influencing such a possibility need to be fully investigated to evaluate the extent of the consequences and predict hydrogen sulfide generation accordingly. Reports on hydrogen sulfide production at different regions and fields were gathered worldwide for the cases when some of them did not have such a problem previously. In order to inspect different aspects of these case studies, some other regions with no hydrogen sulfide content were selected as control. In all cases water samples were taken carefully for chemical analysis in the laboratory. Besides, mineral compositions were characterised in some cases for better evaluation. In order to give a thorough prospect of hydrogen sulfide production, a geochemical model was prepared. In situ engineering geological conditions, especially pressure and temperature, were assigned in the model to investigate the possibility of H2S generation using PHREEQC software. The results of modelling revealed that although many similarities existed between mineral compositions of the cases, certain formations were particularly prone to hydrogen sulfide generation. For better evaluation, important exchangeable cation ratios such as potassium/sodium, calcium/magnesium and ion proportions like sulfate and chloride were calculated as trends of the formations. As expected, the model could successfully monitor a higher ratio of SO42- and Cl- in potential H2S generator formations. Wide variation in percentage of HCO3- was considered as a secondary observatory parameter for better estimation. In addition, it was noticed that higher anion content created an environment ready to absorb any cations and this makes H2S generation easier. Finally, using correlations between predictors and estimators for low depth and deep samples defined the degree of effectiveness for every sample.

Sep 26, 2011

Production scheduling of open pit mining is a key area as it deals with the management of operating cash flows of mining companies. The efficiency of long-term schedules is usually assessed with economic criteria such as net present value (NPV), discounted cash flow rate of return (DCFROR) and payback period, which are not sufficient on their own for revealing the complex picture of the decision-making process.This paper offers a thorough analysis of the most important contemporary criteria of long-term production scheduling, as way to provide the mining practice with a new approach to the decision-making process. The list of criteria includes technological, economic and probabilistic ones. A detailed case study is provided aiming to illustrate the applicability of the criteria for comparing the scheduling approaches regarding the economic interests of a mineÆs owner and contractor. The results obtained can be used for revealing new trends in the current methodology of open-pit production scheduling optimisations.

Sep 26, 2011

By J Zhou

This paper discusses the implementation of a mixed integer linear programming model for a coal preparation plant. The plant considered consists of primary and secondary heavy media cyclones, hydrocyclones for intermediate fines and froth flotation for the very fine material. The model is designed to optimise the plant settings and product flows to maximise revenues for a given specification for two product outputs. The model can deal with bonus/penalty aspects of the product pricing for products that exceed or fail to meet specification. We report on a model with two separate coal feeds with parallel circuits for the oversize, intermediate and fines streams. The genesis of this model is more than 30 years old but recent improvements in mixed integer programming solvers make a full mixed integer formulation practical. The original model began as an enumeration of cut points with arbitrary rules for product allocation. The product allocation was improved in a linear programming formulation by Gunn (1982) and Sarker (1991 and 1995). Current mixed integer programming capabilities make it possible to replace the enumeration aspects and solve directly as a mixed integer programming problem. The current implementation uses a general purpose modelling language to formulate the model. Open source and commercial mixed integer programming solvers are compared

Sep 26, 2011

By D Misra, R Ganguli, S Bandopadhyay

The objective of this paper is to assess the accuracy and applicability of recent state-of-art methods such as the machine learning algorithms (MLA) for mineral resource estimation. Conventional methods such as geostatistics have been predominantly used in the mining industry for this purpose with varying success. Recent advances in the use of MLA have provided a fresh approach to obtain improved accuracy in the estimation of mineral resources. Two MLA methods: the neural network (NN) and the support vector machine (SVM) have been used to estimate a polymetallic ore deposit in Alaska.The general characteristic of SVM and NN emphasises the fact that they can approximate any multivariate non-linear relation among variables. Although neural network models are able to capture the nonlinear spatial relationships that may be present in the data, they are usually difficult to optimise under sparse data settings. Of the various NN alternatives, despite their effectiveness, the model selection and estimation process is typically difficult as it involves solving complex integration and optimisation of parameters. In support vector modelling (SVM), estimating of parameters involves optimisation of a convex cost function. The working principle of SVM makes it robust against noisy and extreme value data. At the same time, it can capture the spatial distribution of ore grade more effectively with careful modelling and selection of SVM parameters.The outcome of the MLA methods were compared to those of the geostatistical ordinary kriging (OK) application to study their generalisation ability. The comparison was made using the following goodness of fit criteria: mean-squared error; mean absolute error; mean error; and coefficient of determination. The results indicated that the MLA methods may improve the predictability of ore deposits and thereby reduce the inherent risk in mineral resource estimation.

Sep 26, 2011

By C Claassen, R Balusu

Computational fluid dynamics (CFD) models have been developed based upon field data collected from a longwall mine in New South Wales, Australia to study the behaviour of goaf gas flow in both active and sealed goaf areas. A base CFD model was built to represent the goaf situations when the active longwall retreats near the finish-off line. Results from the base model were calibrated and compared against field goaf gas monitoring data. The base model was then used to carry out parametric studies to investigate a number of operational scenarios and their impact on goaf gas behaviour. CFD modelling results indicate that the overall goaf gas flow pattern changes as the operating longwall retreats towards finish-off line. In all cases, oxygen penetration into the active goaf remains high, reaching 15 per cent or higher, even at some 800 m behind the longwall face.The modelling results also indicated that it would be difficult for early detection of an active goaf heating (on the maingate side) based upon CO readings in the return airflow, as the main stream of the gaseous product will be flowing into the sealed deep goafs in adjacent longwall (LW) panels. Monitoring points (such as tube bundles and bag sampling points) should be selected at deep seated seals along the active goaf so that abnormal CO or C2H6 readings can be picked up for early detection and location of potential heating spots; goaf inertisation can be better achieved by injecting inert gas such as nitrogen at deeper points (>200 m) behind the operating longwall; the injection of in-seam drainage methane into the goaf areas will only have a limited impact on goaf inertisation as much of the injected methane will migrate towards deep and higher parts of the goaf due to its buoyancy effect.

Sep 26, 2011

By E Rubio, N Morales

A common practice in the mining industry is to decompose the planning process into different tasks, so the overall process and specific schedules can be constructed easily. Nevertheless, currently there are some adverse effects, such as not capturing the real value of a project by not taking into account the construction of several underground drifts and general infrastructure. Then the common practice is to compute mining sequence and cut-off grade profiles over the life of the mine without constitutively integrating the development schedule as a means to measure the constructability of a given mine design and sequence. Thus, the investigation summarised in this paper shows a novel, integrative way of treating an underground mine sequence and production schedule while considering drift development scheduling. Moreover, it is thought that, because of this original model, the whole underground production scheduling exercise must concentrate on combining the development and the production scheduling to compute a robust and a feasible production schedule.In order to quantify the effect of the conventional way of viewing the planning, the concept of the building information model (BIM) needs to be used, which was postulated by Charles Eastman and has been used extensively since the late 1970s. BIM takes other aspects of a project into account, considering at the same time the spatial relationships, quantities and properties of building components, but especially some kind of model visualisation, which is the advantage to be incorporated. This paper presents the basis for an optimisation model that allows for defining the sequence of the mining development so that the production plan can be achieved. For this, the model considers the space dimensions, time, pattern or strategy, cost or benefit, precedence and resources available. Tests were performed considering a block caving and sublevel open stoping method. Finally these tests showed the main conclusion, that production sequence changes when the building capacity is considered.

Sep 26, 2011

By J Ferreira

To speed up multivariate geostatistical simulation it is common to transform the set of attributes into spatially uncorrelated factors that can be simulated independently. One decorrelation method is the method of minimum/maximum autocorrelation factors (MAF), where a two structure linear model of coregionalisation is assumed. The transformation decorrelates the theoretical model exactly, but the actual data are only approximately decorrelated. The MAF transformation can therefore be seen as a special case of a non-orthogonal approximate diagonaliser of a set of symmetric matrices. A more general approach for approximate joint diagonalisation (AJD) has been developed in the context of blind source separation. For these AJD algorithms no assumptions are made beyond symmetry of the individual matrices and so they can be applied to a family of experimental semivariogram matrices. In their application there are no restrictions on the number of structures in the linear model of coregionalisation (LMC) thus removing one of the conditions placed on the subsequent modelling of the spatial structure of the factors. In this paper the general background for the U-WEDGE AJD method is presented. It is shown that the U-WEDGE method achieves better spatial decorrelation than the MAF method. The factors derived from U-WEDGE are simulated using conditional turning bands simulation and then backtransformed to attribute space.

Sep 26, 2011

By B Tutmez

Determination of stress-strain behaviour of rocks plays a crucial role in understanding the response of rocks during loading. However, it is a tedious, expensive and a time-consuming process to obtain such characteristics both in the laboratory and in situ. On the other hand, non-destructive testing methods such as ultrasonic velocities can produce a reliable and fast solution to indentify state of strain and stress in rocks. The present paper aims to provide insight into the relations amongst ultrasonic wave velocities, amplitudes and deformability properties of porous siltstone under compressive loading. For this purpose, pulse (vP) and shear wave velocities (vS) along with amplitudes (AP - AS), and applied loads with resultant strain were measured simultaneously so that response of siltstone to compression can be evaluated. In addition, initial vP and vS were recorded at the beginning of each test to calculate dynamic elastic properties of the specimens. This provided a comparison between static and dynamic elasticity properties of siltstone. Crack damage associated with the onset of dilation was also investigated. The results showed that there is a non-linear logarithmic relation between velocities and stress-strain level for siltstones.

Sep 26, 2011

By B Olsson, R Norman, M Volz

Australia has seen unprecedented demand for coal exports in the last ten years and this demand is set to expand further still according to many analysts. This rapid increase in demand has placed pressure on multi-user coal chains to guarantee the capability to meet the required demand, in terms of both current operations and capacity expansion.The projects required to deliver these forecast tonnages take place in an increasingly complex commercial and technical environment. These challenges include brownfield and greenfield projects, multiple rail and terminal service providers as well as a myriad of mine operators, all needing to operate in an increasingly integrated manner to get the most out of expensive shared assets.Increasing complexity and integration drives the need for more holistic and sophisticated analysis tools. The capacity of coal chain subsystems, such as mine, rail and port, can no longer be determined effectively in isolation. Understanding the nature of the interactions between these subsystems and the resultant capacity of the integrated system is the key to maximising value. TSG advocates the use of a total integrated system approach to understand the behaviour and performance of complex coal chains.Recently, TSG has worked in conjunction with the Integrated Logistics Company and a number of stakeholders in the Dalrymple Bay Coal Chain to deliver the first independent system master plan. This master plan has provided a quantitative and rational assessment of coal chain capacity in its current state and a prediction of its capacity once a pipeline of committed capacity improvements is in place. It is underpinned by a highly detailed discrete-event simulation model of the complete coal chain as an integrated system, including mine load-outs, rail, terminal and port operations.This paper provides an overview of the study and describes the differences between subsystem and total integrated system model performance.

Sep 26, 2011

By A Galli

Traditionally pit optimisation and scheduling is carried out assuming that the resources, the commodity prices and production costs are all known. Once the pit contour and the mining schedule have been determined, geostatistical simulations can be used to assess the impact of the uncertainty in the resources on the pit design and the schedule, and likewise stochastic simulations can be used to test its robustness to fluctuations in costs and prices. But it would be more interesting to have a dynamic procedure for optimising the pit as the resources become better known and as economic factors such as commodity prices and costs evolve over time. This paper presents a novel approach for doing this. Rather than working with millions of small selective mining units, it was decided to work with large blocks, called macro-blocks. Mining sequences are defined as the quantities to be extracted from each macro-block in each time period. Feasible mining sequences are mining sequences that respect the accessibility constraints, and also the geometric constraints on the amounts that can be extracted from any one block over time, or from all the active blocks at a given time. Having defined feasible mining sequences, their mathematical properties were studied. It was found that natural breakpoints occur in the sequences when one set of blocks have been completely mined out, thereby opening up access to others. It was discovered that families of sequences exist, and that they are convex and closed under certain types of row permutation operations. Convexity is an advantage when optimising. The closure property opens up the possibility of mixing and matching subsequences of rows in the sequences. Another interesting property is that the sequences form branching families, rather like the binomial and trinomial trees used to model prices in finance and in real options.It is easy to generate large numbers of feasible mining sequences randomly. A two-step procedure is used to find the best one (or the best few) using three economic criteria: expected NPV,the probability of a negative NPV, and the percentage of years when the cash flow is negative. The procedure was tested on a synthetic gold mine based on the characteristics of the Essakane mine in Burkina Faso. The results were encouraging.

Sep 26, 2011

By C Niemann-Delius

The problem of long-term open pit mine planning is a large combinatorial problem, which canÆt be solved easily by mathematical programming models because of the large problem size. In this paper a new metaheuristic algorithm, which has been developed based on the ant colony optimisation (ACO) and its efficiency, have been discussed. To apply the ACO process to a mine planning problem, a series of variables is considered for each block as the pheromone trails that represent the desirability of the block for being the deepest point of the mine in that column for the given mining period. During implementation several mine schedules are constructed in each iteration. Then the pheromone values of all blocks are reduced to a certain percentage and additionally the pheromone value of those blocks that are used in defining the constructed schedules are increased according to the quality of the generated solutions. By repeated iterations, the pheromone values of those blocks that define the shape of the optimum solution are increased, whereas those of the others have been significantly evaporated. By using this algorithm a high degree of complexities could be considered in objective function and constraints of optimisation model. In addition it can improve the value of the initial mining schedule up to 34 per cent for some cases in a reasonable computational time.

Sep 26, 2011

In this paper a quantitative deterministic risk modelling approach (Quadrim) is introduced. The mathematical framework and equations for quantifying uncertainty within and aggregating across value chain nodes from error propagation techniques is proposed and discussed. A case study and worked examples, based on a hypothetical mine are then presented. This illustrates how uncertainty from the mining and economic value chains can be handled in a typical net cash flow calculation, and how this can be translated to a risk model. It is then illustrated that current valuation techniques do not just result in an information gap for decision makers. Traditional approaches such as discounted cash flow (DCF) analysis and truck and shovel productivity analysis, which do not take into account uncertainty in input values, can result in potential bias in estimates such as net present value (NPV) or equipment hours

Sep 26, 2011

By J V. Mehrabani, A R. Sayadi

Adequate estimation of equipment costs is a key factor in a feasibility study and in evaluation of design alternatives for mining and mineral processing projects. Inaccurate early cost estimation could lead to the elimination of investment benefits. However, this estimation is complex and time consuming because of data accessibility problems and consequently access to a rapid, up-to-date and accurate tool is desirable for carrying out cost estimations.This paper describes the development of models for estimating capital and operating costs for a jaw crusher, which is used as the primary crusher for a wide variety of mineral beneficiation plants, applying single and multivariate regression analyses, together with the design of experiment approach, based on principal component analysis. Explanatory variables include gape size, length of feed opening and power as numeric (quantitative) variables and toggle type (single or double) and the existence of extra heavy duty construction as categorical (qualitative) variables. The performance of each model has been investigated and comparing the estimated R-squared (R2) of each model, the best was selected and its validity examined. The cost models include the capital and operating costs along with the operating cost components. The results indicate that the suggested best cost model is sufficiently accurate for use in feasibility studies.

Sep 26, 2011

By D Wyborn, P A. Dowd

The characterisation of rock fracture networks is an important component of rock engineering applications involving stability assessment or fluid flow analysis. However, the derivation of a reliable rock fracture model remains a very challenging problem in practice. This paper describes a Bayesian framework, in the form of Markov Chain Monte Carlo (MCMC) simulation, for the construction of such a model. Model conditioning using different data sources is discussed including seismic events recorded during hydraulic fracture stimulation, rock face fracture mapping data and downhole geophysical survey data. The freeware FracSim3D is used for the simulations.

Sep 26, 2011