Probabilistic modeling of mineralized zones in Daralu copper deposit (SE Iran) using sequential indicator simulation
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ORIGINAL PAPER
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
Received: 19 November 2014 / Accepted: 23 January 2015 # Saudi Society for Geosciences 2015
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 M. Sojdehee (*) : N. Nezafati : M. V. Abedini Department of Geology, Science and Research Branch, Islamic Azad University, Tehran, Iran e-mail: [email protected] I. Rasa Earth Sciences Faculty, Shahid Beheshti University, Tehran, Iran N. Madani Department of Mining Engineering, University of Chile, Santiago, Chile N. Madani Advanced Mining Technology Center, University of Chile, Santiago, Chile N. Madani CSIRO-Chile International Center of Excellence in Mining and Mineral Processing, Santiago, Chile E. Zeinedini National Iranian Copper Industries Co. (NICICO), Tehran, Iran
leached zones) for evaluation of relevant ore bodies would be advisable. Keywords Geological uncertainty . Mineralized zones . Sequential indicator simulation (SIS) . Daralu porphyry copper
Introduction Geostatistical simulation methods have widely been used to quantify the uncertainty for the attribute of interest. Gaussian approaches are technically developed for modeling continuous variables. Conversely, there are some other techniques for simulating the categorical variables particularly geological domains and their uncertainty. In ore body evaluation, the first step is usually the modeling of geological domains (estimation domain) which can be characterized by mineralization, rock types, and alteration zones. To achieve such an objective, deterministic modeling is a conventional method based on geological interpretation of the deposit. The most common methods of this type are hand contouring and wire framing (Vistelius 1989; Houlding 1994; Mallet 1992, 2002), direct digitization of the geological unit boundaries (Caceres et al. 2011), implicit boundary modeling (Carr et al. 2001), and indicator kriging (Deu
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