Article
Version 1
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Interpretation of Sedimentary Processes Using Heavy Mineral Unconstrained Data
Version 1
: Received: 12 October 2018 / Approved: 15 October 2018 / Online: 15 October 2018 (05:34:41 CEST)
How to cite: Cascalho, J. Interpretation of Sedimentary Processes Using Heavy Mineral Unconstrained Data. Preprints 2018, 2018100280. https://doi.org/10.20944/preprints201810.0280.v1 Cascalho, J. Interpretation of Sedimentary Processes Using Heavy Mineral Unconstrained Data. Preprints 2018, 2018100280. https://doi.org/10.20944/preprints201810.0280.v1
Abstract
This work describes and interprets the presence of heavy minerals in the western Portuguese continental margin using a set of 78 bottom samples collected from 3 distinct areas of this margin: Porto, Aveiro and Nazaré canyon head areas. The main transparent heavy mineral suite (minerals with frequencies >10%), is composed by amphiboles (hornblende), mica (biotite), andalusite, tourmaline and garnet. A secondary suite (minerals with frequencies between 1 and 10%), is composed by pyroxene (enstatite, diopside and augite), staurolite, zircon and apatite. With very low frequency representing less than 1% we found rutile, olivine, kyanite, monazite, epidote, sphene, anatase, sillimanite and brookite. The main primary sources (igneous and metamorphic rocks) explain the presence of these minerals. However, the application of the principal component analysis, with a previous application of the centered log ratio transformation of the heavy mineral data, also stresses for the importance of the grain sorting as a process in controlling the heavy mineral occurrence. The importance of this process is mostly sustained by the distribution pattern of mica and of the most flattened amphibole grains in a way that these particles tend to have a hydraulic affinity to finer grained sediments.
Keywords
sand particles; geological sources; grain sorting
Subject
Environmental and Earth Sciences, Geophysics and Geology
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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