Modelling of cement raw material compositional indices with direct sequential cosimulation

Almeida, José António de

doi:10.1016/j.enggeo.2010.03.007

Cited by 15 publications

(6 citation statements)

References 11 publications

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“…It is widely used in earth sciences, particularly for facilitating understanding of large data sets in the context of geochemical exploration (e.g. Jimenez‐Espinosa et al ., ; Batista et al ., ; Reis et al ., ; Almeida, ) or related to environmental issues (e.g. Boruvka et al ., ; Tavares et al ., ) or other earth science issues (e.g.…”

Section: Methodsmentioning

confidence: 99%

Geochemical and statistical characterization of the phosphate facies of the Farim‐Saliquinhé phosphate mineralization (Guinea‐Bissau)

et al. 2014

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The Eocene Farim-Saliquinhé phosphate mineralization (FSPM) is a buried sedimentary deposit located in the northern part of Guinea-Bissau, discovered and spatially constrained during the 1980s by the French Geological Survey (BRGM). In the present work some of the data collected at that time are reworked in the framework of the development of a 3D geological and geochemical model of this mineralization. We show the usefulness of two classical multivariate statistical methods -principal component analysis (PCA) and cluster analysis (CA) -applied to eight geochemical variables (P2O5, SiO2, Al2O3, Fe2O3, CaO, MgO, F and CO2) measured in 247 samples from phosphate facies, for differentiation of samples taken from the different phosphate facies recognized in the FSPM, namely the main ore FPA (30 to 35% high grade phosphate), the calcareous low grade phosphate FPB (10 to 20% P2O5) (both Lutetian), and a mineralized Upper Eocene to Lower Oligocene cover (mainly including the FPO level and a silico-aluminous phosphate bed), overlying the FPA, which can also be considered a third set of phosphate facies associated with the FSPM.

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Section: Methodsmentioning

confidence: 99%

Geochemical and statistical characterization of the phosphate facies of the Farim‐Saliquinhé phosphate mineralization (Guinea‐Bissau)

et al. 2014

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“…Also, to estimate yearly average images, simulations plus average of simulations were performed instead of kriging for declustering purposes, thus avoiding the artefacts in the images that would have been obtained by kriging (Almeida and Lopes, 2005). For processing simulated images it is also better to provide a binary image above and below a threshold, which is done at the end of the study (Almeida, 2010).…”

Section: Methodsmentioning

confidence: 99%

Agricultural practices and geostatistical evaluation of nitrate pollution of groundwater in the Júcar River Basin District, Spain

Ferreira

Almeida

Legoinha

et al. 2016

Emir. J. Food Agric

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“…Geometallurgical mapping allows integration of metallurgical responses of a deposit into 3D block models for the purpose of mine planning activities. 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].…”

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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Modelling of cement raw material compositional indices with direct sequential cosimulation

Cited by 15 publications

References 11 publications

Geochemical and statistical characterization of the phosphate facies of the Farim‐Saliquinhé phosphate mineralization (Guinea‐Bissau)

Geochemical and statistical characterization of the phosphate facies of the Farim‐Saliquinhé phosphate mineralization (Guinea‐Bissau)

Agricultural practices and geostatistical evaluation of nitrate pollution of groundwater in the Júcar River Basin District, Spain

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

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