Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6635760 | Fuel | 2015 | 5 Pages |
Abstract
The purpose of this article is to demonstrate the practicability to classify the sources and types of crude oils from different oil fields in several countries and regions with terahertz time-domain spectroscopy (THz-TDS). THz parameters spectra, such as refractive index and absorption coefficient, were calculated. Multivariate statistical methods, including cluster analysis (CA) and principal component analysis (PCA), were used to build models between THz parameters and crude oils from different countries and regions. The distances of CA between oils and the first principal component (PC1) scores of oils in PCA method reflected the oil-dependent differences, indicating that there existed consistency between CA and PCA. Consequently, the combination of THz technology as well as multivariate statistical methods could be an effective method for rapid identification of crude oils with different properties and geographical locations.
Related Topics
Physical Sciences and Engineering
Chemical Engineering
Chemical Engineering (General)
Authors
Honglei Zhan, Shixiang Wu, Rima Bao, Lina Ge, Kun Zhao,