色谱 ›› 2025, Vol. 43 ›› Issue (6): 688-695.DOI: 10.3724/SP.J.1123.2025.02005

• 研究论文 • 上一篇    下一篇

基于全二维气相色谱-飞行时间质谱指纹图谱的原油溯源

张伟亚1, 陈品2, 解伟欣3, 高儇博4, 张万峰5, 代威2, 林思源1, 朱书奎2,*()   

  1. 1.深圳海关工业品检测技术中心,广东 深圳 518067
    2.中国地质大学(武汉),地质微生物与环境全国重点实验室,湖北 武汉 430074
    3.惠州港海关综合技术服务中心,广东 惠州 518060
    4.重庆科技大学,复杂油气田勘探开发重庆市重点实验室,重庆 401331
    5.中国科学院广州地球化学研究所,深地过程与战略矿产资源全国重点实验室,广东 广州 510640
  • 收稿日期:2025-02-10 出版日期:2025-06-08 发布日期:2025-05-21
  • 通讯作者: * Tel:(027)67883452,E-mail:shukuizhu@126.com.
  • 基金资助:
    海关总署科研项目(2024HK071)

Tracing the origin of crude oil based on fingerprint profiles obtained by comprehensive two-dimensional gas chromatography-time-of-flight mass spectrometry

ZHANG Weiya1, CHEN Pin2, XIE Weixin3, GAO Xuanbo4, ZHANG Wanfeng5, DAI Wei2, LIN Siyuan1, ZHU Shukui2,*()   

  1. 1. Testing and Technology Center for Industrial Products of Shenzhen Customs,Shenzhen 518067,China
    2. State Key Laboratory of Geomicrobiology and Environmental Changes,China University of Geosciences,Wuhan 430074,China
    3. Comprehensive Technology and Service Center,Huizhou port Customs,Huizhou 518060,China
    4. Chongqing Key Laboratory of Complex Oil and Gas Exploration and Development,Chongqing University of Science and Technology,Chongqing 401331,China
    5. State Key Laboratory of Deep Earth Processes and Resources,Guangzhou Institute of Geochemistry,Chinese Academy of Sciences,Guangzhou 510640,China
  • Received:2025-02-10 Online:2025-06-08 Published:2025-05-21
  • Supported by:
    Research Fund of the General Administration of Customs of China(2024HK071)

摘要:

原油的化学组成极为复杂,而且各组分的相对分子质量、挥发性、含量和极性差异显著。传统的柱层析方法通常操作步骤繁琐,有机溶剂消耗大,样品处理时间长,严重限制了分析效率;常用的气相色谱-质谱(GC-MS)由于分辨率和峰容量较低,难以对复杂原油样品中的成分进行理想分离,影响了化合物的准确定性和定量分析。本研究建立了气流吹扫注射器微萃取(GPMSE)对复杂原油样品进行快速前处理的方法,在避免大量有机溶剂消耗的同时将样品处理时间缩短为10 min。结合全二维气相色谱-飞行时间质谱(GC×GC-TOFMS)技术,对45个原油样品的化学组分进行了详细分析,并构建了原油的指纹图谱。采用多元统计法对各原油样品的GC×GC-TOFMS分析数据进行处理,对不同类型化合物进行冗余分析(redundancy analysis, RDA),利用蒙特卡罗置换检验RDA排序轴的显著性,最终筛选出36个能显著反映原油来源特征的生物标志物。从45个原油样品中选取28个作为建模组构建原油来源分类模型,选取4个单一来源样品和13个混合来源样品作为验证组评估模型的有效性。结果表明该模型的判别准确率达到了97.8%。该方法不仅为原油溯源提供了高效、准确的技术支持,还具有广阔的应用潜力,可扩展至原油掺假鉴定、溢油事故责任追溯及油田开发动态监测等领域。本研究为解决原油贸易欺诈和保障国家能源安全提供了重要的技术手段,同时也为原油品质检测和风险预警提供了科学依据。

关键词: 气流吹扫注射器微萃取法, 全二维气相色谱-飞行时间质谱, 生物标志物, 原油溯源

Abstract:

Crude oils are complex mixtures of thousands of organic compounds that differ significantly in relative molecular mass, volatility, content, and polarity. Traditional methods for analyzing crude oil often involve complicated steps, consume large amounts of organic solvents, and require long sample-preparation times. These limitations lead to inefficient and time-consuming analysis processes. Crude oil is commonly analyzed by gas chromatography-mass spectrometry (GC-MS). However, this technique is incapable of effectively separating complex crude-oil components owing to its low resolution and peak capacity, resulting in overlapping peaks that can lead to inaccurate compound identification and quantification. These challenges highlight the need for advanced analytical techniques. Comprehensive two-dimensional gas chromatography (GC×GC) is a novel separation technique that has been widely used to analyze complex samples, such as food, environmental samples, natural products, and crude oil. GC×GC has several advantages over traditional GC. Firstly, it offers higher resolution and peak capacity, thereby improving separation efficiency. Secondly, its high separation power reduces the need for complex sample pretreatment. Thirdly, the ordered separation and “tile effect” in a GC×GC chromatogram facilitate easier compound identification and quantification in complex mixtures.

In this study, we developed a gas purge microsyringe extraction (GPMSE) method for the rapid pretreatment of crude-oil samples. This method reduces sample processing time to only 10 min while minimizing organic solvent consumption. The chemical compositions of 45 crude oil samples were analyzed using GC×GC-time-of-flight mass spectrometry (GC×GC-TOFMS), which helped to establish detailed chemical fingerprints for each sample. The GC×GC-TOFMS data were processed using multivariate statistical methods, including redundancy analysis (RDA) and Monte Carlo permutation testing, which identified 36 biomarkers that are strongly associated with the origin of the crude oil (p<0.05). A classification model was constructed using a training set of 28 samples. Four single-source and 13 mixed-source samples were used to validate the model. The GPMSE-GC×GC-TOFMS method was demonstrated to be highly efficient and accurate. A discrimination accuracy of 97.8% was achieved during the identification of crude-oil sources. The developed method not only provides a powerful tool for tracing crude oil but also has broad applications potential, including for the detection of adulterated crude oil, tracking oil-spill sources, and monitoring oilfield development. This study offers several significant benefits. For example, it helps to address crude-oil trade fraud and supports national energy security. Additionally, it provides scientific support in relation to crude-oil quality control and risk assessment. The developed method is fast, reliable, and environmentally friendly; hence, it is expected to be a valuable tool for use in the oil industry. The GPMSE-GC×GC-TOFMS method is cost-effective and requires minimal solvent; consequently, it is an attractive option for reducing environmental impacts in laboratory and industrial settings. Furthermore, the high throughput and accuracy of the developed method make it suitable for large-scale analyses. In conclusion, this study demonstrated the effectiveness of combining GPMSE with GC×GC-TOFMS for analyzing crude oil; the ability of the method to identify biomarkers and classify crude-oil sources in a highly accurate manner represents a significant advancement in the field. Future studies are expected to further explore its applications in related areas, such as oil refining and environmental monitoring.

Key words: gas purge microsyringe extraction (GPMSE), comprehensive two-dimensional gas chromatography-time-of-flight mass spectrometry (GC×GC-TOFMS), biomarkers, crude oil origin tracing

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