Experimental simulation of oil migration — Distribution effects on organic compound groups and on metal/metal ratios

• Published in: Chemical geology Vol. 116; no. 3; pp. 281 - 299
• Main Authors: Greibrokk, T., Lundanes, E., Norli, H.R., Dyrstad, K., Olsen, S.D.
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 05.10.1994
• ISSN: 0009-2541; 1872-6836
• DOI: 10.1016/0009-2541(94)90019-1

A laboratory experiment was set up to determine the distribution effects in a heavy oil migrating through a 104-m-long column packed with water-wet 20–60-μm particles of glacimarine silt. The oil was pumped through the column at 100°C, with a backpressure of 400 bar, collected in small fractions at the outlet, and the distribution of saturates, aromatics and polars in each fraction was determined. After preparative class fractionation, the fractions were analyzed by gas chromatography, -mass spectrometry (GC-MS), -atomic emission detection (GC-AED) and with inductively coupled plasma-mass spectrometry (ICP-MS). In the oil front, the amount of volatile hydrocarbons, mainly below C 10–12, were lowered compared to the later eluting fractions, due to water-washing. The amounts of sulfur-containing compounds in a polar fraction were affected by migration, but the composition of hydrocarbons was in general little influenced by the migration. The concentrations of several metals in the migrated oil were reduced compared to the levels in the not-migrated oil. In contrast, some elements, particularly Cu and Mn, were extracted from the column into the migrating oil. Class fractionation was essential to obtaining a view into different migration effects for several metals. In the asphaltenes class, the migration had little effect on the Ni/V, Co/V and Mo ( Mo + Cr) ratios which are used in oil-oil and oil-source rock correlations. In other classes several metals were distributed unevenly in the migration fractions, most likely due to different migration effects. Ni and V were the metals least affected by the migration process. Correlation factor calculation and factor analysis were performed to improve the quality of the analytical data and to control the consistency of the main conclusions.