PREDICTING THE DEPOSITIONAL ENVIRONMENTS AND TRANSPORTATION MECHANISMS OF SEDIMENTS USING GRANULOMETRIC PARAMETERS, BIVARIATE AND MULTIVARIATE ANALYSES

Abstract

Grain size distribution and classes present in sedimentary rocks are responsive to the physical changes of the transporting media and the basin of deposition. Analyzing grain size data is germane in reconstructing the sedimentary processes including identifying the palaeoenvironment of deposition. Twenty-three (23) samples, mainly sandstones, collected within latitude 6 055’-6 059’N and Longitude 005 044’-005 053’E in the Anambra Basin, were subjected to granulometric analysis, where grain size parameters (mean grain size, sorting, skewness, and kurtosis) sensitive to environmental conditions were calculated. These parameters were integrated with bivariate and multivariate analyses. Graphics mean (M_z) in the study area range from 1.1 to 2.27 ɸ with an average value of 1.7 ɸ, suggesting that grains are predominantly fine to medium; sorting range from 0.71 to 1.36 ɸ with an average value of 1.02 ɸ, suggesting sediments are moderately sorted; skewness range from -0.57 to 0.51 ɸ with an average value of 1.28 ɸ suggesting coarsely skewed to fine skewed with a predominating near symmetrical skewness and kurtosis range from 0.57 to 1.51ɸ, with an average of 1.28 ɸ suggesting a very platykurtic to leptokurtic character. Bivariate scatter plots of the grains size parameters predicted the environment of deposition as a shallow marine. Multivariate analysis calculated from established functions suggested environments that range from the beach (backshore) to shallow marine (subtidal). The integration of the granulometric parameters, bivariate and multivariate plots predict an environment that is dominated by high energy indicating that the sediments of the study area were deposited in a shallow marine environment. In addition, the Visher and Passega’s C-M diagrams characterized the transport mechanism of the sediments as predominantly by saltation although traction and suspension modes also play some roles.

Keywords: transportation mechanism, granulometric parameters, bivariate analysis, multivariate analysis

http://doi.org/10.35180/gse-2019-0002