Improving processing by adaption to conditional geostatistical simulation of block compositions

Tolosana‐Delgado, Raimon; Mueller, Ute; Boogaart, K. Gerald van den; Ward, Clint; Gutzmer, Jens

doi:10.17159/2411-9717/2015/v115n1a2

Cited by 14 publications

(7 citation statements)

References 43 publications

(42 reference statements)

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“…The orebody is discretized into a grid of blocks, which are characterized by grade, tonnage and other mineral properties, the value of the block which is the difference between the ore value and its extraction and processing costs and a geometric model i.e., the location of the blocks, determining the sequence of mining and haulage costs. For optimally estimating the grades of the blocks geostatistical methods like kriging are applied or more advanced methods like conditional geostatistical simulation of block compositions [15,16].…”

Section: The Optimal Rate Of Miningmentioning

confidence: 99%

What Is the Optimal and Sustainable Lifetime of a Mine?

Wellmer

Scholz

2018

Sustainability

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Abstract:The first stage of the circular economy, mining, is examined from the perspective of sustainability. The authors discuss how to maximize the use of phosphate rock, a primary commodity. To attract investment capital in a market economy system, a mine has to operate profitably, i.e., its lifetime must be optimized under economic conditions, for example, according to Taylor's Rule. From a sustainability perspective, however, the lifetime should extend as long as possible and the grades mined be as low as possible. The authors examine methods for optimizing a mine's lifetime under economic conditions according to practical experience and learning effects to optimize exploration and exploitation. With the condition of sustainability, a recently developed concept of cut-off grade for a layered phosphate deposit is examined and considerations for prolonging a mine's lifetime are discussed. As there are big losses from the current and potential future value chains above and below the current cut-off grade, we argue that the losses and use efficiency of phosphorus are key parts of a circular economy.

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Section: The Optimal Rate Of Miningmentioning

confidence: 99%

What Is the Optimal and Sustainable Lifetime of a Mine?

Wellmer

Scholz

2018

Sustainability

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“…The processing cost per tonne is considered to be a constant value. Present value (PV), future value (FV) and net present value (NPV) of the material (concentrate or metal) produced by the process are calculated as shown by Equation (9). The results from the economic model can be used for comparison between different scenarios, or for estimating the impact of managerial decisions.…”

Section: Economicsmentioning

confidence: 99%

“…However, in this work we use only one realisation, since studying uncertainties is beyond the scope of the study. Although the problem of upscaling was neglected in the study, its importance has been widely discussed in literature [7][8][9][10]. One possible solution proposed by Coward et al [8] is to use primary-response framework to reduce the bias of non-linear scaling up.…”

Section: Introductionmentioning

confidence: 99%

Simulation of a Mining Value Chain with a Synthetic Ore Body Model: Iron Ore Example

et al. 2018

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Reconciliation of geological, mining and mineral processing information is a costly and time demanding procedure with high uncertainty due to incomplete information, especially during the early stages of a project, i.e., pre-feasibility, feasibility studies. Lack of information at those project stages can be overcome by applying synthetic data for investigating different scenarios. Generation of the synthetic data requires some minimum sparse knowledge already available from other parts of the mining value chain, i.e., geology, mining, mineral processing. The aim of the paper is to describe how to establish and construct a synthetic testing environment, or “synthetic ore body model” for data integration by using a synthetic deposit, mine production, constrained by a mine plan, and a simulated beneficiation process. The approach uses quantitative mineralogical data and liberation information for process simulation. The results of geological and process data integration are compared with the real case data of an apatite iron ore. The discussed approach allows for studying the implications in downstream processes caused by changes in upstream parts of the mining value chain. It also opens the possibility of optimising sampling campaigns by investigating different synthetic drilling scenarios including changes to the spacing between synthetic drill holes, composite length, drill hole orientation and assayed parameters. A synthetic deposit model can be a suitable tool for testing different scenarios for implementation of geometallurgical programs and also an educational tool for universities and companies.

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“…Introducing these parameters into resource modeling complements traditional geology and grade-based attributes, enabling a more comprehensive approach to the economic maximization of mineral production through better mine planning and reduced associated risk and uncertainty [1][2][3]. Most of the time, geostatistical algorithms are applicable for producing high-resolution maps of geometallurgical variables [4][5][6]. However, in some circumstances such as oxide copper deposits, the complexity of these underlying variables requires consideration of enhanced geostatistical techniques.…”

Section: Introductionmentioning

confidence: 99%

A Hybrid Approach for Joint Simulation of Geometallurgical Variables with Inequality Constraint

2019

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Geometallurgical variables have a significant impact on downstream activities of mining projects. Reliable 3D spatial modelling of these variables plays an important role in mine planning and mineral processing, in which it can improve the overall viability of the mining projects. This interdisciplinary paradigm involves geology, geostatistics, mineral processing and metallurgy that creates a need for enhanced techniques of modelling. In some circumstances, the geometallurgical responses demonstrate a decent intrinsic correlation that motivates one to use co-estimation or co-simulation approaches rather than independent estimation or simulation. The latter approach allows us to reproduce that dependency characteristic in the final model. In this paper, two problems have been addressed, one is concerning the inequality constraint that might exist among geometallurgical variables, and the second is dealing with difficulty in variogram analysis. To alleviate the first problem, the variables can be converted to new variables free of inequality constraint. The second problem can also be solved by taking into account the minimum/maximum autocorrelation factors (MAF) transformation technique which allows defining a hybrid approach of joint simulation rather than conventional method of co-simulation. A case study was carried out for the total and acid soluble copper grades obtained from an oxide copper deposit. Firstly, these two geometallurgical variables are transferred to the new variables without inequality constraint and then MAF analysis is used for joint simulation and modelling. After back transformation of the results, they are compared with traditional approaches of co-simulation, for which they showed that the MAF methodology is able to reproduce the spatial correlation between the variables without loss of generality while the inequality constraint is honored. The results are then post processed to support probabilistic domaining of geometallurgical zones.

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Improving processing by adaption to conditional geostatistical simulation of block compositions

Cited by 14 publications

References 43 publications

What Is the Optimal and Sustainable Lifetime of a Mine?

What Is the Optimal and Sustainable Lifetime of a Mine?

Simulation of a Mining Value Chain with a Synthetic Ore Body Model: Iron Ore Example

A Hybrid Approach for Joint Simulation of Geometallurgical Variables with Inequality Constraint

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