In multi-unit deposits, the risk of facing uncertainties in estimating geological domains is generally high. The uncertainties increase when there is no exact boundary among geological domains, which is called “soft boundaries”. The geostatistical method of Partial Grade (PG) is an estimation technique developed for multi-unit deposits in the presence of “soft boundaries” when the spatial variability of the grades varies between different geological formations. A partial grade is the product of the indicators of the geological domains with the ore grade, so the partial grade cokriging of different geological formations can be performed in the case of multi-unit deposits. However, the partial grade cokriging is relevant only in the presence of a “border effect”, evidencing the evolution rate of average grade when moving from one geological domain to another. Additional geostatistical tools with respect to standard geostatistics, such as variogram ratio and preferential relationship schemes allows to identify the grade relation among different geological domains. In this work, we present an application of partial grade cokriging to an iron multi-unit deposit with soft boundaries located in Iran. Up to the knowledge of authors, although the PG method has been applied to several case studies in literature, this application is the first case study where the border effect is present. The three main geological domains are defined: Poor mineralization: (low grade of iron, 20 < Fe% < 45), Rich mineralization: (high grade of iron, Fe%≥ 45) and Metasomatite mineralization (strongly altered rock, Fe% < 45). The partial grade cokriging results have shown to reduce uncertainties in grade estimation of geological domains with respect to the classical geostatistical estimation methods (Ordinary Kriging and Co-Kriging). Results were validated with the blast hole data used as reference.

Partial Grade method to improve estimation of multi-unit deposits with soft boundaries: application to an iron mine deposit

Sara Kasmaeeyazdi;Giuseppe Raspa;Stefano Bonduà;Francesco Tinti;Roberto Bruno
2018

Abstract

In multi-unit deposits, the risk of facing uncertainties in estimating geological domains is generally high. The uncertainties increase when there is no exact boundary among geological domains, which is called “soft boundaries”. The geostatistical method of Partial Grade (PG) is an estimation technique developed for multi-unit deposits in the presence of “soft boundaries” when the spatial variability of the grades varies between different geological formations. A partial grade is the product of the indicators of the geological domains with the ore grade, so the partial grade cokriging of different geological formations can be performed in the case of multi-unit deposits. However, the partial grade cokriging is relevant only in the presence of a “border effect”, evidencing the evolution rate of average grade when moving from one geological domain to another. Additional geostatistical tools with respect to standard geostatistics, such as variogram ratio and preferential relationship schemes allows to identify the grade relation among different geological domains. In this work, we present an application of partial grade cokriging to an iron multi-unit deposit with soft boundaries located in Iran. Up to the knowledge of authors, although the PG method has been applied to several case studies in literature, this application is the first case study where the border effect is present. The three main geological domains are defined: Poor mineralization: (low grade of iron, 20 < Fe% < 45), Rich mineralization: (high grade of iron, Fe%≥ 45) and Metasomatite mineralization (strongly altered rock, Fe% < 45). The partial grade cokriging results have shown to reduce uncertainties in grade estimation of geological domains with respect to the classical geostatistical estimation methods (Ordinary Kriging and Co-Kriging). Results were validated with the blast hole data used as reference.
IAMG 2018 the 19th Annual Conference of the International Association for Mathematical Geosciences
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Sara Kasmaeeyazdi, Giuseppe Raspa, Chantal de Fouquet, Stefano Bonduà, Francesco Tinti, Roberto Bruno
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11585/643624
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