Oil Characterization

Oils can be characterized using a variety of analytical techniques. Sulfur content, API gravity, pour point, wax content, and viscosity are all used to give an evaluation of the overall properties of an oil. A more-detailed description of gross composition can be obtained by the so-called SARA analysis, in which the oil is divided chromatographically into the saturate, aromatic, resin (or NSO), and asphaltene fractions.

The saturate fraction can then be analyzed in much more detail using gas chromatography (GC) and gas chromatography combined with mass spectrometry (GC-MS), which separate the saturate fraction into individual molecular components.

Image 18

Gas chromatogram of a whole oil. Separation of the saturate fraction was not necessary in this case because the oil was highly paraffinic, with low aromatic, asphaltene, and resin contents.

Top: m/z 217 trace showing steranes in an oil. Middle: m/z 218 trace that also shows steranes in the same oil. Bottom: m/z 191 trace showing triterpanes in the same oil.

Top: m/z 217 trace showing steranes in an oil. Middle: m/z 218 trace that also shows steranes in the same oil. Bottom: m/z 191 trace showing triterpanes in the same oil.

GC-MS analysis can also be performed on the aromatic fraction, if desired.

Carbon-isotope ratios can be measured on the whole oil, on any of the SARA fractions, and even on individual compounds. This latter analysis is not common, and is usually limited to the n-alkanes and isoprenoids.

The data from these analyses that characterize an oil can then be used in a number of ways: to help define the organofacies from which the oil was generated; to help estimate which layer is likely to be the source rock; to estimate maturity of the oil; to correlate this oil with other oils, permitting us to divide a group of oils into different oil families, subfamilies, and mixtures, and to correlate oils with their suspected or proposed source rocks. We recommend Biomarkers for Geologists (Waples and Machihara, 1991) and The Biomarker Guide (Peters et al., 2005) as valuable references for interpreting these data.