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Circum-Arctic petroleum systems identified using decision-tree chemometrics

American Association of Petroleum Geologists Bulletin

By:
, , , , ,
DOI: 10.1306/12290606097

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Abstract

Source- and age-related biomarker and isotopic data were measured for more than 1000 crude oil samples from wells and seeps collected above approximately 55??N latitude. A unique, multitiered chemometric (multivariate statistical) decision tree was created that allowed automated classification of 31 genetically distinct circumArctic oil families based on a training set of 622 oil samples. The method, which we call decision-tree chemometrics, uses principal components analysis and multiple tiers of K-nearest neighbor and SIMCA (soft independent modeling of class analogy) models to classify and assign confidence limits for newly acquired oil samples and source rock extracts. Geochemical data for each oil sample were also used to infer the age, lithology, organic matter input, depositional environment, and identity of its source rock. These results demonstrate the value of large petroleum databases where all samples were analyzed using the same procedures and instrumentation. Copyright ?? 2007. The American Association of Petroleum Geologists. All rights reserved.

Additional Publication Details

Publication type:
Article
Publication Subtype:
Journal Article
Title:
Circum-Arctic petroleum systems identified using decision-tree chemometrics
Series title:
American Association of Petroleum Geologists Bulletin
DOI:
10.1306/12290606097
Volume
91
Issue:
6
Year Published:
2007
Language:
English
Larger Work Type:
Article
Larger Work Subtype:
Journal Article
Larger Work Title:
American Association of Petroleum Geologists Bulletin
First page:
877
Last page:
913
Number of Pages:
37