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Updated: Jun 3, 2026

Chromatographic Fingerprinting by Template Matching for Data Collected by Comprehensive Two-Dimensional Gas Chromatography
Published on: September 2, 2020
Analysis of petroleum compositional similarity using multiway principal components analysis (MPCA) with comprehensive
G Todd Ventura1, Gregory J Hall, Robert K Nelson
1Woods Hole Oceanographic Institution, Department of Marine Chemistry and Geochemistry, Woods Hole, MA, USA. Todd.Ventura@earth.ox.ac.uk
Abstract:
The accurate establishment of oil similarity is a longstanding problem in petroleum geochemistry and a necessary component for resolving the architecture of an oil reservoir. Past limitations have included the excessive reliance on a relatively small number of biomarkers to characterize such complex fluids as crude oils. Here we use multiway principal components analysis (MPCA) on large numbers of specific chemical components resolved with comprehensive two-dimensional gas chromatography-flame ionization detection (GC×GC-FID) to determine the molecular relatedness of eight different maltene fractions of crude oils. MPCA works such that every compound eluting within the same first and second dimension retention time is quantitatively compared with what elutes at that same retention times within the other maltene fractions. Each maltene fraction and corresponding MPCA analysis contains upwards of 3500 quantified components. Reservoir analysis included crude oil sample pairs from around the world that were collected sequentially at depth within a single well, collected from multiple depths in the same well, and from different depths and different wells but thought to be intersected by the same permeable strata. Furthermore, three different regions of each GC×GC-FID chromatograms were analysed to evaluate the effectiveness of MPCA to resolve compositional changes related to the source of the oil generating sediments and its exposure to biological and/or physical weathering processes. Compositional and instrumental artefacts introduced during sampling and processing were also quantitatively evaluated. We demonstrate that MPCA can resolve multi-molecular differences between oil samples as well as provide insight into the overall molecular relatedness between various crude oils.
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