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Some observations on mineral properties and analytical reproducibility in geochemical samples

机译：地球化学样品中矿物特性和分析重现性的一些观察

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The lack of precision and accuracy in geochemical analysis is not necessarily a result of poor laboratory work. As often as not, the causes are the basic properties of minerals and elements and their behavior in the environment. The effects of uneven mineral distribution in a sample can be calculated. Even a simple, idealized approach, as shown here, serves its purpose. It provides an idea of the effects to be expected on analytical data by sample nonhomogeneity, by the grain size or nugget effect. Also, such information is useful in the design of a sampling program, as shown in Table 2 (these are recalculations of the Table 1 figures). However, such calculations, simple or sophisticated as they may be, remain meaningless if they are not put into a geochemi-cal context, if geochemical exploration is not taken as a trans-disciplinary subject. Data like those in Tables 1 and 2 are useful only in conjunction with a characterization of the geochemical behavior of minerals and elements, as given in the "classification." Details of the natural environment of the sampled area and technical details on sampling, sample preparation and analysis are other essentials in data interpretation. This demonstrates the transdisciplinary character of geochemical exploration, which requires knowledge and appreciation of mineralogy, petrology, geology, chemistry, physics, physicochemistry as well as field and laboratory techniques. Only on such a basis, design of a geochemical program and interpretation of analytical data will lead to meaningful results. Unfortunately, experience shows that this multidisciplinary approach is not standard practice. Misinterpretation or a total reject of a particular set of data are frequent results. How many mineralizations may have been missed because a single-point high Au "anomaly" in a favorable environment could not be confirmed by the laboratory?
机译：地球化学分析缺乏准确性和准确性，不一定是实验室工作不力的结果。原因通常是矿物和元素的基本特性及其在环境中的行为。可以计算出样品中矿物分布不均的影响。如此处所示，即使是简单，理想的方法也可以达到其目的。通过样品的非均质性，晶粒大小或块金效应，可以对分析数据产生预期的影响。另外，如表2所示，此类信息在采样程序的设计中很有用（这些是对表1数据的重新计算）。但是，如果不将地球化学勘探作为跨学科研究对象，那么这些计算（可能是简单的或复杂的）如果不将其用于地球化学范围，则将毫无意义。表1和表2中的数据仅与“分类”中给出的矿物和元素地球化学行为特征结合使用。数据解释的其他要素还包括采样区自然环境的详细信息以及采样，样品制备和分析的技术细节。这证明了地球化学勘探的跨学科特征，这需要对矿物学，岩石学，地质学，化学，物理学，物理化学以及野外和实验室技术的知识和欣赏。只有在这样的基础上，地球化学程序的设计和分析数据的解释才能产生有意义的结果。不幸的是，经验表明，这种多学科方法不是标准做法。经常会误解或完全拒绝特定数据集。由于实验室无法确认在有利环境中的单点高Au“异常”，可能错过了多少矿化作用？

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