首页> 外文期刊>Journal of Mining Scinece >RISK QUANTIFICATION IN GRADE-TONNAGE CURVES AND RESOURCE CATEGORIZATION IN A LATERITIC NICKEL DEPOSIT USING GEOLOGICALLY CONSTRAINED JOINT CONDITIONAL SIMULATION
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RISK QUANTIFICATION IN GRADE-TONNAGE CURVES AND RESOURCE CATEGORIZATION IN A LATERITIC NICKEL DEPOSIT USING GEOLOGICALLY CONSTRAINED JOINT CONDITIONAL SIMULATION

机译:基于地质约束联合条件模拟的红壤镍矿床吨压曲线风险量化与资源分类

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摘要

The risk quantification in grade-tonnage curves is critical for capital investment in mining projects. Geostatistical simulations for orebodies can be used to obtain grade-tonnage curves, and determine uncertainty and risk assessments. Applying these in multi-element deposits can be a difficult practice, as the related attributes using the traditional co-simulation approaches require intensive computational work and may be impractical for use in the mineral industry. This paper presents the risk assessment for integrating grade-tonnage curves and resources categorization for lateritic nickel deposits in the central region of Brazil, by joint simulation of multiple correlated variables of interest: Ni, MgO and SiO_2. The joint simulation of these variables is based on Minimum/Maximum Autocorrelation Factors (MAF). Based on this approach, the resources are categorized honoring Ni joint simulated results by applying the 15 % rule, where it is considered there will be a statistical error < 15 %, with 90 % of a confidence interval per production period.
机译:品位/吨位曲线中的风险量化对于采矿项目的资本投资至关重要。矿体的地统计学模拟可用于获得品位吨位曲线,并确定不确定性和风险评估。将它们应用于多元素矿床可能是一个困难的实践,因为使用传统的协同模拟方法的相关属性需要大量的计算工作,并且在矿物工业中使用可能不切实际。本文通过对多个感兴趣的相关变量:Ni,MgO和SiO_2进行联合模拟,对巴西中部地区红土镍矿床的品位-吨位曲线和资源分类进行整合,进行了风险评估。这些变量的联合模拟基于最小/最大自相关因子(MAF)。基于此方法,通过应用15%规则将资源归类为采用Ni联合模拟结果,其中认为统计误差<15%,每个生产周期的置信区间为90%。

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