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Journal of Emerging Trends in Engineering and Applied Sciences (JETEAS)

ISSN:2141-7016

Article Title: Mineralization Potential Assessment of Stream Sediment Geochemical Data Using R-Mode Factor Analysis in Nigeria
by Awosusi, O.O, Adisa, A.L, and Adekoya, J.A

Abstract:
This research work aims at assessing the mineralization potential of the study area. Stream sediment geochemical data obtained from seventy stream sediment samples from Rivers Iyinsin and Ofosu were subjected to R-mode factor analysis. The two rivers drain an area underlain by migmatite, granite gneiss, coarse porphyritic biotite and biotite hornblende granites, fine-grained biotite granite and pegmatite. The stream sediment were analysed for eighteen trace elements after the samples had been sieved using minus 80 mesh size. The results of R-mode factor analysis produced a six-factor model which accounts for 75.47% of the variability of the data. Factor 1(Ce, Fe, Ni, Zn, V) and Factor 4 (U, Mn),which account for 20.599% and 9.707%, respectively, of the variability of the model, are attributable to the scavenging actions of oxides and hydroxides of Fe and Mn on elements with which they are associated. Factor 2 (Rb, Pb, Ba) interpreted as a lithological factor accounts for 18.75 % of the variation. The sources of these elements are probably the felsic rocks underlying the study area. Factor 3 (As, Cu) and Factor 5 (Au, Ag), which account for 11.457% and 8.5 % of the variation, respectively, probably indicate the occurrence of gold and its associated sulphides, either as disseminations or gold bearing quartz veins in the underlying rocks. While Factor 6 (Co, Ta, Cu) defines the probable occurrence of rare metal pegmatite in the area. In conclusion, there is the possibility of the occurrence of gold mineralization with sulphides in the area. Hydrous Fe and Mn-oxides also pay strong scavenging effect on some of the elements in the sediments. Furthermore, the application of R-mode factor analysis has proved indispensable as it has shed more light on the nature and the type of possible mineralization in the area.
Keywords: stream sediment; correlation coefficient; multivariate statistical technique, scavenging effect; principal component analysis
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ISSN: 2141-7016

Editor in Chief.

Prof. Gui Yun Tian
Professor of Sensor Technologies
School of Electrical, Electronic and Computer Engineering
University of Newcastle
United Kingdom

 

 

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