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首页> 外文期刊>Geochemistry: exploration, environment, analysis >Strategies for reducing sampling errors in exploration and resource definition drilling programmes for gold deposits
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Strategies for reducing sampling errors in exploration and resource definition drilling programmes for gold deposits

机译:减少金矿勘探和资源界定钻探计划中抽样误差的策略

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摘要

Sampling error is the degree to which the concentration of an element differs from the true element concentration of the material from which the sample was collected. Gold mineralization commonly exhibits sampling errors as large as 50–100%. As a result, collection and preparation of drill samples from Au mineralization can provide significant challenges for the geoscientist, largely because of the coarse particulate nature of Au. To avoid this, geoscientists have opted to collect and prepare larger drill samples to reduce the magnitude of this ‘nugget effect’. Unfortunately, the ‘nugget effect’ can cause sampling error at any stage of sample treatment when sub-sampling takes place. Knowledge of the magnitude of error at each sub-sampling step is necessary to identify strategies to reduce overall error. This is because reduction of only the largest component of measurement error will reduce total measurement error in the most numerically efficient and effective manner. With knowledge of the various components of sampling, preparation and analysis costs, the sample treatment strategy that will most cost-effectively reduce sampling error can be identified. Regrettably, the typical absolute and relative errors that occur during sample collection and preparation of sub-samples with finer particle sizes are not generally known for many Au deposits. Results from three Au drilling projects document the magnitude of sampling, preparation and analytical errors experienced, and range from 22 to 46%, 7 to 20%, and 1 to 13%, respectively. These results are derived from large, laboratory-blind, duplicate quality control/quality assessment (QA/QC) programmes involving sample treatment protocols that would be considered to be appropriate for coarse Au-bearing samples. These QA/QC programmes measured the sampling errors, and ensured that they were minimized on these projects. In general, results indicate that a very large component of total measurement error is introduced during the collection of the initial sample, and that subordinate amounts of error are introduced during preparation and analysis. As a result, undertaking extraordinary efforts to reduce preparation or analytical errors does not result in a significant total measurement error reduction. In contrast, the collection of larger initial samples can result in the substantial reduction of total measurement error.
机译:采样误差是指元素浓度与从中收集样品的材料的真实元素浓度不同的程度。金矿化通常表现出高达50–100%的采样误差。结果,从金矿化中收集和制备钻探样品可能给地球学家带来重大挑战,这主要是因为金的颗粒性质较粗。为避免这种情况,地球科学家选择收集并准备更大的钻探样本以减小这种“金块效应”的程度。不幸的是,在进行子采样时,“金块效应”会在样品处理的任何阶段引起采样误差。必须知道每个子采样步骤的误差幅度,才能确定减少总体误差的策略。这是因为仅减少最大的测量误差将以最有效和最有效的方式减少总的测量误差。通过了解采样,准备和分析成本的各个组成部分,可以确定最经济有效地减少采样误差的样品处理策略。遗憾的是,对于许多金矿床,通常不知道在样品收集和制备具有更细粒度的子样品过程中发生的典型绝对和相对误差。三个金钻探项目的结果记录了所经历的取样,制备和分析误差的幅度,范围分别为22%至46%,7%至20%和1至13%。这些结果来自大型的实验室盲目重复质量控制/质量评估(QA / QC)程序,其中涉及样品处理方案,这些方案被认为适用于含粗金的样品。这些QA / QC程序测量了抽样误差,并确保在这些项目中将其最小化。通常,结果表明,在收集初始样品的过程中引入了很大的总测量误差,而在制备和分析过程中引入了从属误差。结果,为减少制备或分析误差而付出的巨大努力并不会导致总测量误差的显着降低。相反,较大的初始样本的收集可以大大降低总测量误差。

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