TY - JOUR
T1 - Comparing sequential Gaussian and turning bands algorithms for cosimulating grades in multi-element deposits
AU - Paravarzar, Shahrokh
AU - Emery, Xavier
AU - Madani, Nasser
N1 - Funding Information:
The authors thank the reviewers, Dr. Denis Marcotte and Dr. Joao Felipe Costa, for their recommendations that helped to improve the paper, and to Mr. Esfahanipour R. from the National Iranian Copper Industry Co. (NICICO) for granting access to the Dar-Alu copper deposit exploration data. The last two authors also acknowledge the funding by the Chilean Commission for Scientific and Technological Research, through Project Conicyt/Fondecyt/Regular/No. 1130085.
Publisher Copyright:
© 2015 Académie des sciences.
PY - 2015/1/1
Y1 - 2015/1/1
N2 - Stochastic simulation is increasingly used to map the spatial variability in the grades of elements of interest and to assess the uncertainty in the mineral resources and ore reserves. The practical implementation requires specifying a stochastic model, which describes the spatial distribution of the grades, and an algorithm to construct realizations of these grades, viewed as different possible outcomes or scenarios. In the case of the Gaussian random field model, a variety of algorithms have been proposed in the past decades, but their ability to reproduce the model statistics is often unequal. In this paper, we compare two such algorithms, namely the turning bands and the sequential algorithms. The comparison is hold through a synthetic case study and a real case study in a porphyry copper deposit located in southeastern Iran, in which it is of interest to jointly simulate the copper, molybdenum, silver, lead and zinc grades. Statistical testing and graphical validations are realized to check whether or not the realizations reproduce the features of the true grades, in particular their direct and cross variograms. Sequential simulation based on collocated cokriging turns out to poorly reproduce the cross variograms, while turning bands proves to be accurate in all the analyzed cases.
AB - Stochastic simulation is increasingly used to map the spatial variability in the grades of elements of interest and to assess the uncertainty in the mineral resources and ore reserves. The practical implementation requires specifying a stochastic model, which describes the spatial distribution of the grades, and an algorithm to construct realizations of these grades, viewed as different possible outcomes or scenarios. In the case of the Gaussian random field model, a variety of algorithms have been proposed in the past decades, but their ability to reproduce the model statistics is often unequal. In this paper, we compare two such algorithms, namely the turning bands and the sequential algorithms. The comparison is hold through a synthetic case study and a real case study in a porphyry copper deposit located in southeastern Iran, in which it is of interest to jointly simulate the copper, molybdenum, silver, lead and zinc grades. Statistical testing and graphical validations are realized to check whether or not the realizations reproduce the features of the true grades, in particular their direct and cross variograms. Sequential simulation based on collocated cokriging turns out to poorly reproduce the cross variograms, while turning bands proves to be accurate in all the analyzed cases.
KW - Collocated cokriging
KW - Geological heterogeneity
KW - Multivariate modeling
KW - Sequential simulation
KW - Turning bands
UR - http://www.scopus.com/inward/record.url?scp=84937976682&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84937976682&partnerID=8YFLogxK
U2 - 10.1016/j.crte.2015.05.008
DO - 10.1016/j.crte.2015.05.008
M3 - Article
AN - SCOPUS:84937976682
SN - 1631-0713
VL - 347
SP - 84
EP - 93
JO - Comptes Rendus - Geoscience
JF - Comptes Rendus - Geoscience
IS - 2
ER -