Prata Paloma S, Alexandrino Guilherme L, Mogollón Noroska Gabriela S, Augusto Fabio
Institute of Chemistry, State University of Campinas, 13084-971, Campinas, São Paulo, Brazil.
092, Guaranda, Bolivar, Ecuador.
J Chromatogr A. 2016 Nov 11;1472:99-106. doi: 10.1016/j.chroma.2016.10.044. Epub 2016 Oct 18.
The geochemical characterization of petroleum is an essential task to develop new strategies and technologies when analyzing the commercial potential of crude oils for exploitation. Due to the chemical complexity of these samples, the use of modern analytical techniques along with multivariate exploratory data analysis approaches is an interesting strategy to extract relevant geochemical characteristics about the oils. In this work, important geochemical information obtained from crude oils from different production basins were obtained analyzing the maltene fraction of the oils by comprehensive two-dimensional gas chromatography coupled to quadrupole mass spectrometry (GC×GC-QMS), and performing multiway principal component analysis (MPCA) of the chromatographic data. The results showed that four MPC explained 93.57% of the data variance, expressing mainly the differences on the profiles of the saturated hydrocarbon fraction of the oils (C-C and C-Cn-alkanes and the pristane/phytane ratio). The MPC1 grouped the samples severely biodegraded oils, while the type of the depositional paleoenvironments of the oils and its oxidation conditions (as well as their thermal maturity) could be inferred analysing others relevant MPC. Additionally, considerations about the source of the oil samples was also possible based on the overall distribution of relevant biomarkers such as the phenanthrene derivatives, tri-, tetra- and pentacyclic terpanes.
在分析原油开采的商业潜力时,石油的地球化学特征是制定新战略和技术的一项重要任务。由于这些样品的化学复杂性,采用现代分析技术并结合多变量探索性数据分析方法是提取有关石油相关地球化学特征的一种有效策略。在这项工作中,通过全二维气相色谱-四极杆质谱联用仪(GC×GC-QMS)分析原油的可溶沥青质馏分,并对色谱数据进行多向主成分分析(MPCA),从而获得了来自不同生产盆地原油的重要地球化学信息。结果表明,四个主成分解释了93.57%的数据方差,主要体现了原油饱和烃馏分(C-C和C-Cn-烷烃以及姥鲛烷/植烷比值)谱图上的差异。主成分1将严重生物降解油的样品归为一组,而通过分析其他相关主成分可以推断出油的沉积古环境类型及其氧化条件(以及它们的热成熟度)。此外,基于菲衍生物、三、四和五环萜烷等相关生物标志物的总体分布,也可以对油样的来源进行考量。