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Using multiple random walk simulation in short-term grade models

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Using multiple random walk simulation in short-term grade models

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Título Using multiple random walk simulation in short-term grade models
Autor Caixeta, Rafael Moniz
Ribeiro, Diniz Tamantini
Costa, Joao Felipe Coimbra Leite
Abstract Geostatistical simulation comprises a variety of techniques which can help on the decision-making process for uncertainties. They allow the uncertainty assessment of function responses (which depend on the simulated inputs) commonly through a non-linear relationship (net present value, interest tax return, geometallurgical ore recovery…). However, one of their limitations is that running the simulation can take considerable processing time to be executed in large deposits or large grids. Herein is presented an attempt to solve this problem in short-term modeling cases, via the use of Multiple Random Walk Simulation. This algorithm combines kriging with the simulation of independent random walks in order to generate simulated scenarios much faster than via traditional simulation algorithms. A case study is presented to illustrate the application of the method in an iron mine. The Multiple Random Walk Simulation models were properly built, respecting the reproduction of both histogram and variograms. Also, the speed-up was compared with standard methods of geostatistical simulation and there was a considerable speed gain with Multiple Random Walk Simulation (3.39 to 5.65 times faster than the others).
Contido em REM : international engineering journal. Ouro Preto, MG. vol. 70, no. 2 (Apr./June 2017), p. 209-214
Assunto Geoestatística
Mineração
Simulação computacional
[en] Conditional simulation
[en] Geostatistics
[en] Mining
[en] Short-term modeling
Origem Nacional
Tipo Artigo de periódico
URI http://hdl.handle.net/10183/163915
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