Improving hydrocarbon classification analysis for lubricant base oils

通过精炼过程对原油及其产品进行分析在石化工业中一直是至关重要的。特别值得一提的是，质谱学仍然是石化分析的主要技术。森科尔润滑油事业部生产各种润滑油产品，其中原油是主要原材料。事实上，对性能更高的汽车和工业用油的需求正在增长，开发和生产此类材料的竞争非常激烈。化石油是许多化合物的极其复杂的混合物，其组成因其地质年代和地理来源的不同而有很大差异。精炼过程从对原材料的分析开始。对基础油进行质谱分析，得到的质谱图用于放置基础油。 在美国石油协会(API)指定的五个类别中的一个。这些基团在油的化学成分上有所不同。根据对基础油的分析结果，选择了精制方法。选择不适当的精炼方法可能会产生代价高昂的后果：所得产品可能不符合规格，和/或用于精炼的催化剂的寿命可能会大大缩短。公司特有的问题是，目前使用的质谱学方法并不总是能就所需的精炼方法做出正确的预测。新的仪器和新的进样系统产生与基础油不同的剖面，这使得使用现有的分类技术很难或不可能从一个平台转换到另一个平台。我们建议将理论、计算和 渥太华大学该小组的仪器知识和专业知识通过发展结构-性质关系来解决这一问题，从而能够以可靠的、独立于平台的方式对基础油烃进行分类。我们将重点加强从质谱学数据中获得的信息，这反过来将导致与精炼过程相关的更好的预测值。

The analysis of crude oil and products derived therefrom via the refining process is and has always been of crucial importance in the petrochemical industry. In particular, mass spectrometry remains the prominent technique for the analysis of petrochemicals. Suncor's lubricants division manufactures a wide range of lubricant products, for which crude oil is the main raw material. Indeed, the need for higher performing automotive and industrial oils is growing and the race to develop and produce such material is highly competitive. Fossil oils are extremely complex mixtures of many compounds, varying greatly in composition depending on their geological age and geographical origin. The refining process begins with the analysis of the raw material. Base oils are analyzed by mass spectrometry and the resulting mass spectra used to place the oils in one of five classes as specified by the Americal Petroleum Institute (API). These groups differ in the chemical composition of the oils. On the basis of the analytical result for the base oil, a refining method is chosen. Choosing an inappropriate refining method can have expensive consequences: the resulting product may not meet specifications, and/or the lifetime of the catalysts used for refining can be greatly reduced. The company-specific problem is that the mass spectrometric methods currently in use do not always produce correct predictions in terms of the needed refining method. New instruments and new sample inlet systems produce different profiles from their base oils, which makes using existing classification techniques difficult or impossible to translate from one platform to the next. We propose to apply the theoretical, computational and instrumentation knowledge and expertise present in the group at the University of Ottawa to solve this by developing structure-property relationships to enable the classification of the base oil hydrocarbons in a reliable, platform-independent manner. We will focus on enhancing the information obtained from the mass spectrometric data, which in turn will lead to improved predictive value related to the refining process.