Predicting Physicochemical Properties of Upper Jurassic Circum-Arctic Crude Oil

Peters, Kenneth E.¹, L. Scott Ramos², John E. Zumberge³, Zenon C. Valin¹, Donald L. Gautier⁴ (1) U.S. Geological Survey, Menlo Park, CA (2) Infometrix, Inc, Bothell, WA (3) GeoMark Research, Inc, Houston, TX (4) U. S. Geological Survey, Menlo Park, CA

Biomarkers (molecular fossils) and stable carbon isotope ratios were measured for >550 crude oil samples expelled from Upper Jurassic source rock collected from wells and seeps north of ~55^oN latitude. A unique, multi-tiered chemometric (multivariate statistical) decision tree was used to classify genetically distinct Upper Jurassic oil families from West Siberia, the North Sea, and offshore Labrador. The method, which we call decision-tree chemometrics, utilizes PCA (principal components analysis), multiple tiers of KNN (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 type of organic matter input, lithology, and depositional environment of each organofacies of the source rock. Partial least squares analysis (PLS) of the measured geochemical data was used to predict various physicochemical properties of the samples, such as API gravity, sulfur, and metal content. Present-day and paleogeographic maps predict the distribution of physicochemical properties of oil expelled from different organofacies of the Upper Jurassic source rock. For example, families of oil samples in West Siberia show concentric distributions that mimic the measured physicochemical properties and are controlled by oxic-anoxic and terrigenous-marine conditions during deposition of the Bazhenov Formation source rock.