
doi: 10.5382/econgeo.4722
Abstract Analytical methods used by commercial assay laboratories have improved enormously in recent years. Inductively coupled plasma-atomic emission spectroscopy and inductively coupled plasma-mass spectrometry methods now report analyses for half of the periodic table with exceptional detection limits and precision. It is becoming commonplace for mining companies to use such methods routinely for the analysis of drill samples throughout mineral deposits. Improvements in software and computing power now allow rapid interrogation of upward of 100,000 assay samples. Geochemical analyses are quantitative, are independent of observer bias, and can form the basis for robust geologic and mineralogical models of mineral deposits, as well as shed light on scientific questions. In particular, consistently collected, high-quality geochemical analyses can significantly improve and systematize logging of lithological and hydrothermal alteration mineralogic changes within drill core. In addition, abundant, high-quality geochemical data provide insights into magmatic and hydrothermal processes that were previously difficult to recognize and that have obvious applications to mineral exploration and improved genetic models of ore deposits. This paper describes a workflow that mining industry geologists can apply to their multielement analysis data to extract more information about magma compositions and gangue mineralogy.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 47 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 1% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
