Probabilistic modeling of mineralized zones in Daralu copper deposit (SE Iran) using sequential indicator simulation

Mona Sojdehee, Iraj Rasa, Nima Nezafati, Mansour Vosoughi Abedini, Nasser Madani, Ehsan Zeinedini

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

Deterministic modeling of the geological domains is often restricted to the uncertainty assessment. Using stochastic modeling can be considered as an effective solution in order to overcome this restriction. It can also be effectively used for evaluation of ore bodies. Sequential indicator simulation as a stochastic modeling method is a widely used technique to characterize the categorical variables such as facies, rock types, alterations, and mineralized zones. Inverting the categorical variables to indicators proposes the global and local variability of the variable under study by descriptive and spatial statistics. In this study, this approach has been applied to a set of experimental data acquired from Daralu ore deposit located in southern part of the Urumieh–Dokhtar magmatic arc, south of Kerman province, SE Iran. Kerman province hosts several porphyry copper deposits in which calculation of probabilistic description of four normally presented mineralized zones (hypogene, supergene, oxide, and leached zones) for evaluation of relevant ore bodies would be advisable.

Original languageEnglish
Pages (from-to)8449-8459
Number of pages11
JournalArabian Journal of Geosciences
Volume8
Issue number10
DOIs
Publication statusPublished - Oct 30 2015
Externally publishedYes

Fingerprint

ore body
copper
modeling
simulation
porphyry
ore deposit
oxide
rock
indicator
province
evaluation
calculation
statistics
method

Keywords

  • Daralu porphyry copper
  • Geological uncertainty
  • Mineralized zones
  • Sequential indicator simulation (SIS)

ASJC Scopus subject areas

  • Environmental Science(all)
  • Earth and Planetary Sciences(all)

Cite this

Probabilistic modeling of mineralized zones in Daralu copper deposit (SE Iran) using sequential indicator simulation. / Sojdehee, Mona; Rasa, Iraj; Nezafati, Nima; Abedini, Mansour Vosoughi; Madani, Nasser; Zeinedini, Ehsan.

In: Arabian Journal of Geosciences, Vol. 8, No. 10, 30.10.2015, p. 8449-8459.

Research output: Contribution to journalArticle

Sojdehee, Mona ; Rasa, Iraj ; Nezafati, Nima ; Abedini, Mansour Vosoughi ; Madani, Nasser ; Zeinedini, Ehsan. / Probabilistic modeling of mineralized zones in Daralu copper deposit (SE Iran) using sequential indicator simulation. In: Arabian Journal of Geosciences. 2015 ; Vol. 8, No. 10. pp. 8449-8459.
@article{2c32e08fc0d7425cbdf6784edd58fc89,
title = "Probabilistic modeling of mineralized zones in Daralu copper deposit (SE Iran) using sequential indicator simulation",
abstract = "Deterministic modeling of the geological domains is often restricted to the uncertainty assessment. Using stochastic modeling can be considered as an effective solution in order to overcome this restriction. It can also be effectively used for evaluation of ore bodies. Sequential indicator simulation as a stochastic modeling method is a widely used technique to characterize the categorical variables such as facies, rock types, alterations, and mineralized zones. Inverting the categorical variables to indicators proposes the global and local variability of the variable under study by descriptive and spatial statistics. In this study, this approach has been applied to a set of experimental data acquired from Daralu ore deposit located in southern part of the Urumieh–Dokhtar magmatic arc, south of Kerman province, SE Iran. Kerman province hosts several porphyry copper deposits in which calculation of probabilistic description of four normally presented mineralized zones (hypogene, supergene, oxide, and leached zones) for evaluation of relevant ore bodies would be advisable.",
keywords = "Daralu porphyry copper, Geological uncertainty, Mineralized zones, Sequential indicator simulation (SIS)",
author = "Mona Sojdehee and Iraj Rasa and Nima Nezafati and Abedini, {Mansour Vosoughi} and Nasser Madani and Ehsan Zeinedini",
year = "2015",
month = "10",
day = "30",
doi = "10.1007/s12517-015-1828-1",
language = "English",
volume = "8",
pages = "8449--8459",
journal = "Arabian Journal of Geosciences",
issn = "1866-7511",
publisher = "Springer Verlag",
number = "10",

}

TY - JOUR

T1 - Probabilistic modeling of mineralized zones in Daralu copper deposit (SE Iran) using sequential indicator simulation

AU - Sojdehee, Mona

AU - Rasa, Iraj

AU - Nezafati, Nima

AU - Abedini, Mansour Vosoughi

AU - Madani, Nasser

AU - Zeinedini, Ehsan

PY - 2015/10/30

Y1 - 2015/10/30

N2 - Deterministic modeling of the geological domains is often restricted to the uncertainty assessment. Using stochastic modeling can be considered as an effective solution in order to overcome this restriction. It can also be effectively used for evaluation of ore bodies. Sequential indicator simulation as a stochastic modeling method is a widely used technique to characterize the categorical variables such as facies, rock types, alterations, and mineralized zones. Inverting the categorical variables to indicators proposes the global and local variability of the variable under study by descriptive and spatial statistics. In this study, this approach has been applied to a set of experimental data acquired from Daralu ore deposit located in southern part of the Urumieh–Dokhtar magmatic arc, south of Kerman province, SE Iran. Kerman province hosts several porphyry copper deposits in which calculation of probabilistic description of four normally presented mineralized zones (hypogene, supergene, oxide, and leached zones) for evaluation of relevant ore bodies would be advisable.

AB - Deterministic modeling of the geological domains is often restricted to the uncertainty assessment. Using stochastic modeling can be considered as an effective solution in order to overcome this restriction. It can also be effectively used for evaluation of ore bodies. Sequential indicator simulation as a stochastic modeling method is a widely used technique to characterize the categorical variables such as facies, rock types, alterations, and mineralized zones. Inverting the categorical variables to indicators proposes the global and local variability of the variable under study by descriptive and spatial statistics. In this study, this approach has been applied to a set of experimental data acquired from Daralu ore deposit located in southern part of the Urumieh–Dokhtar magmatic arc, south of Kerman province, SE Iran. Kerman province hosts several porphyry copper deposits in which calculation of probabilistic description of four normally presented mineralized zones (hypogene, supergene, oxide, and leached zones) for evaluation of relevant ore bodies would be advisable.

KW - Daralu porphyry copper

KW - Geological uncertainty

KW - Mineralized zones

KW - Sequential indicator simulation (SIS)

UR - http://www.scopus.com/inward/record.url?scp=84942552714&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84942552714&partnerID=8YFLogxK

U2 - 10.1007/s12517-015-1828-1

DO - 10.1007/s12517-015-1828-1

M3 - Article

AN - SCOPUS:84942552714

VL - 8

SP - 8449

EP - 8459

JO - Arabian Journal of Geosciences

JF - Arabian Journal of Geosciences

SN - 1866-7511

IS - 10

ER -