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Improving the estimates of recoverable reserves

机译：改善可采储量的估计

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Reconciliation of long-term, block-model reserves and mine production frequently shows significant discrepancies. This reconciliation can be done comparing the long-term, block-model reserves against a grade control model (a model based on blastholes or production data). In this article, this is called an F1 factor for tonnages, grade and ounces. This reconciliation should also be done by comparing the grade control model to the mill feed (or loaded to heaps) tonnages, grades and ounces (F{sub}2 factor).The long-term model usually contains blocks with dimensions larger than the size of the selective mining unit (SMU) of the operation. The smoothing effect of an estimator, such as kriging, will generally result in a grade-tonnage curve that does not match the grade-tonnage curve of the SMUs to be recovered. This problem is partly to blame for the reconciliation discrepancies found. In addition, in-pit perfect selection is impossible. Therefore, the grade-tonnage predictions based on blast-holes also needto be assessed - considering unplanned dilution and the errors of estimation of the grade control model.This article focuses on using conditional simulations to assess the uncertainty of the predicted grade-tonnage curve in terms of minable reserves and in the framework of long-term mine planning. Quantifying the uncertainty in no uncertain terms is done in conjunction with a popular pit optimizer. It yields several possible minable reserves and several possibleminable tonnages and grades, per pit shell or scheduled phase.
机译：长期，区块模型储量与矿山产量之间的核对经常显示出重大差异。可以通过将长期的区块模型储量与品位控制模型（基于爆破孔或生产数据的模型）进行比较来完成此对帐。在本文中，这称为吨位，品位和盎司的F1因子。还应通过将坡度控制模型与工厂进料（或装载到堆肥）的吨位，坡度和盎司（F {sub} 2因子）进行比较来进行对账。长期模型通常包含尺寸大于尺寸的块操作的选择性采矿单元（SMU）的名称。估计器的平滑效果（例如克里金法）通常会导致阶跃-吨位曲线与要恢复的SMU的阶跃-吨位曲线不匹配。发现的和解差异部分归咎于此问题。另外，坑内完美选择是不可能的。因此，基于爆破孔的品位吨位预测也需要进行评估-考虑到计划外稀释和品位控制模型估计的误差。本文着重使用条件模拟来评估预测的品位吨位曲线的不确定性可开采储量和长期矿山规划框架内。结合流行的凹坑优化器，可以毫无不确定性地量化不确定性。每个基坑壳体或计划的阶段，它都会产生几种可能的可采储量以及几种可能的吨位和品位。

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