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Grain-size distribution of volcaniclastic rocks 2: Characterizing grain size and hydraulic sorting

机译:火山碎屑岩的粒度分布2:表征粒度和水力分选

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摘要

Quantification of the grain size distribution of sediments allows interpretation of processes of transport and deposition. Jutzeler et al. (2012) developed a technique to determine grain size distribution of consolidated clastic rocks using functional stereology, allowing direct comparison between unconsolidated sediments and rocks. Here, we develop this technique to characterize hydraulic sorting and infer transport and deposition processes. We compare computed grain size and sorting of volcaniclastic rocks with field-based characteristics of volcaniclastic facies for which transport and depositional mechanisms have been inferred. We studied pumice-rich, subaqueous facies of volcaniclastic rocks from the Oligocene Ohanapecosh Formation (Ancestral Cascades, Washington, USA), Pliocene Dogashima Formation (Izu Peninsula, Honshu, Japan), Miocene Manukau Subgroup (Northland, New Zealand) and the Quaternary Sierra La Primavera caldera (Jalisco State, Mexico). These sequences differ in bed thickness, grading and abundance of matrix. We propose to evaluate grain size and sorting of volcaniclastic deposits by values of their modes, matrix proportion (< 2 mm; F-1) and D16, instead of median diameter (D50) and standard deviation parameters. F-1 and D16 can be uniformly used to characterize and compare sieving and functional stereology data. Volcaniclastic deposits typically consist of mixtures of particles that vary greatly in density and porosity. Hydraulic sorting ratios can be used to test whether inferred density of mixed clast populations of pumice and dense clasts are hydraulically sorted with each other, considering various types of transport under water. Evaluation of this ratio for our samples shows that most studied volcaniclastic facies are deposited by settling from density currents, and that basal dense clast breccia are emplaced by shear rolling. These hydraulic sorting ratios can be applied to any type of clastic rocks, and indifferently on consolidated and unconsolidated samples.
机译:沉积物粒度分布的量化可以解释运输和沉积过程。 Jutzeler等。 (2012年)开发了一种利用功能立体学确定固结碎屑岩粒度分布的技术,从而可以直接比较未固结的沉积物和岩石。在这里,我们开发了此技术来表征水力分选以及推断运输和沉积过程。我们比较了火山碎屑岩的计算粒度和分类,并与已推断出运移和沉积机制的火山碎屑岩相的场基特征进行了比较。我们研究了渐新世的Ohanapecosh组(祖先级联,华盛顿,美国),上新世八Dog岛组(日本本州伊豆半岛),中新世Manukau组(北陆,新西兰)和富四叠纪的火山碎屑岩的水下相。 La Primavera火山口(墨西哥哈利斯科州)。这些顺序在床层厚度,基质的分级和丰度方面有所不同。我们建议通过模态值,基质比例(<2 mm; F-1)和D16(而不是中值直径(D50)和标准偏差参数)的值来评估火山碎屑沉积物的粒度和排序。 F-1和D16可以统一用于表征和比较筛分和功能性立体数据。火山碎屑沉积物通常由密度和孔隙率差异很大的颗粒混合物组成。考虑到在水下的各种运输方式,可以使用水力分拣比率来测试是否以液压方式对推断的浮石和稠密碎石混合种群的密度进行了水力分拣。对我们的样品的该比率的评估表明,大多数研究的火山碎屑相是由密度流沉降沉积的,而基底致密的角砾岩角砾岩则是通过剪切滚压而形成的。这些水力分选比率可以应用于任何类型的碎屑岩,并且对于固结和未固结的样品都可以使用。

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