Institutional Repository
Technical University of Crete
Technical University of Crete
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| URI: | http://purl.tuc.gr/dl/dias/824497C2-65DC-442A-A000-7B95F96C77D5 | ||
| Year | 2015 | ||
| Type of Item | Diploma Work | ||
| License |
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| Bibliographic Citation | Anna Koukounya, "Identifying oil families using Malcom (SLB) software package", Diploma Work, School of Mineral Resources Engineering, Technical University of Crete, Chania, Greece, 2015 https://doi.org/10.26233/heallink.tuc.42493 | ||
| Appears in Collections |
Petroleum system definition and analysis use compositional links between petroleum and source kerogen. Petroleum families are commonly classified using qualitative or semi-quantitative methods based on compound presence or relative abundance, while petroleum-source rock correlation links a petroleum family to a stratigraphic unit, facies and/or locality containing the source kerogen. In this study, we apply multivariate statistical analysis to explore the oil family classification in Williston Basin using the Malcom (SLB) software package.In this study twenty oil samples, that belong to five previously defined compositional families (oil families A, B, C, D and E) obtained from the Williston Basin are analyzed. The objective is to utilize biomarkers distribution and apply classification methods using the Malcom Interactive Fluid Characterization Software to identify the oil families. Principal Component Analysis (PCA), Ascending Hierarchical Classification (AHC) and Sammon mapping were employed to explore compositional data from saturated hydrocarbon fractions and hopane biomarkers of the oil samples from Williston Basin petroleum province. The results indicate that an efficient classification of the oil families may be obtained when the AHC was used, with Ward’s aggregation method. In addition PCA also revealed a good classification scheme of the oil families, especially when the n-alkanes are used. Finally the Malcom (SLB) software package was found to be a useful tool in geochemical data treatment.
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