SciELO - Scientific Electronic Library Online

 
vol.115 número1Fatigue risk management: Charting a path to a safer workplace índice de autoresíndice de materiabúsqueda de artículos
Home Pagelista alfabética de revistas  

Servicios Personalizados

Articulo

Indicadores

Links relacionados

  • En proceso de indezaciónCitado por Google
  • En proceso de indezaciónSimilares en Google

Compartir


Journal of the Southern African Institute of Mining and Metallurgy

versión On-line ISSN 2411-9717
versión impresa ISSN 2225-6253

Resumen

VAN DER GRIJP, Y.  y  MINNITT, R.C.A.. Application of Direct Sampling multi-point statistic and sequential gaussian simulation algorithms for modelling uncertainty in gold deposits. J. S. Afr. Inst. Min. Metall. [online]. 2015, vol.115, n.1, pp.73-85. ISSN 2411-9717.

The applicability of a stochastic approach to the simulation of gold distribution to assess the uncertainty of the associated mineralization is examined. A practical workflow for similar problems is proposed. Two different techniques are explored in this research: a Direct Sampling multi-point simulation algorithm is used for generating realizations of lithologies hosting the gold mineralization, and sequential Gaussian simulation is applied to generate multiple realizations of gold distributions within the host lithologies. A range of parameters in the Direct Sampling algorithm is investigated to arrive at good reproducibility of the patterns found in the training image. These findings are aimed at assisting in the choice of appropriate parameters when undertaking the simulation step. The resulting realizations are analysed in order to assess the combined uncertainty associated with the lithology and gold mineralization.

Palabras clave : Direct Sampling; multi-point statistics; MPS simulation; training image; uncertainty in gold deposits.

        · texto en Inglés     · Inglés ( pdf )

 

Creative Commons License Todo el contenido de esta revista, excepto dónde está identificado, está bajo una Licencia Creative Commons