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Statistically learning Archean carbonate diagenesis
Precambrian Research ( IF 3.2 ) Pub Date : 2020-09-01 , DOI: 10.1016/j.precamres.2020.105867
Fulvio Franchi , Ash Abebe

Abstract Geochemical data are often very noisy due to the large natural heterogeneity of the geological materials as well as oversimplification of rock classification. This has serious repercussions on the precision of our knowledge of the deep past as we often rely solely on geochemical proxies to investigate the geological evolution of Archean and Proterozoic environments. Here statistical learning procedures were applied to achieve unbiased classification of Neoarchean stromatolitic dolostone textures on the basis of the distribution of their trace elements and rare earth elements (REE) investigated through laser ablation induced coupled plasma – mass spectrometry (LA-ICP-MS). Multivariate statistical analyses and supervised statistical learning have revealed that different dolomite fabrics, thought as products of aggrading diagenesis and recrystallization, are in fact chemically indistinguishable. The diagenetic processes that cause the re-crystallization of dolomite and the consequent change of textures, is not affecting the distribution of major and trace elements inherited by the depositional environment or during early stages of diagenesis. At the same time the algorithm has revealed that an optically homogeneous microcrystalline dolomite sample may in fact be geochemically inhomogeneous because of processes of ripening and recrystallization occurred at an early stage of marine diagenesis and that have contributed to element mobilization. Statistical learning has succeeded in recognizing chemofacies which not always overlap with dolomite textures and fabrics highlighting the importance of crystallographic and diagenetic studies before any study of carbonates as geochemical proxies.

中文翻译:

统计学习太古代碳酸盐岩成岩作用

摘要 由于地质材料的自然非均质性大以及岩石分类过于简单化,地球化学数据往往非常嘈杂。这对我们对远古时代知识的精确性产生了严重影响,因为我们通常仅依靠地球化学代理来研究太古代和元古代环境的地质演化。在这里,应用统计学习程序,根据通过激光烧蚀诱导耦合等离子体质谱 (LA-ICP-MS) 研究的微量元素和稀土元素 (REE) 的分布,对新太古代叠层石白云岩纹理进行无偏分类。多元统计分析和监督统计学习表明,不同的白云岩织物,被认为是成岩作用和重结晶的产物,实际上在化学上是无法区分的。导致白云岩再结晶和随之而来的结构变化的成岩过程不影响沉积环境或成岩早期阶段继承的主要和微量元素的分布。同时,该算法揭示了光学均质的微晶白云岩样品实际上可能在地球化学上是不均质的,因为在海洋成岩作用的早期阶段发生了成熟和再结晶过程,这有助于元素移动。
更新日期:2020-09-01
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