25th International Meeting on Organic Geochemistry IMOG 2011

P-277
Statistical analysis of diamondoid and biomarker from Brazilian
Basin oil samples
Marcia Springer, Debora Azevedo, Bruno Caldas, Luiz Landau
Federal University of Rio de Janeiro, Rio de Janeiro, Brazil (corresponding
author:marcia_springer@hotmail.com)
Biomarker distributions are widely used in assessing
oil maturity [1]. Many of the isomeric biomarker
maturity parameters reach equilibrium before the
main part of the oil window and, in some cases, show
inversion at high maturity levels. Consequently, these
ratios are not effective as indicators for highly mature
oils. Diamondoids have an unusually high thermal
stability and resistance to biodegradation compared to
other crude oil constituents. Using ratios of
diamondoids and biomarkers in combination provides
a more refined assessment of maturity and
depositional environment [2,3,4].
In the present study, sixteen samples of oils from
Sergipe/Alagoas sedimentary basins of Brazilian
continental margin were selected and studied on
diamondoids and biomarkers. The oil samples were
analyzed by gas chromatography coupled to mass
spectrometry and hierarchical group analysis (Cluster)
aiming to correlate biomarker and diamondoid
parameters. Cluster analysis is an exploratory data
analysis tool for solving classification problems.
Results indicate that the selected crude oils display a
high degree of thermal maturity, when plotting
biomarkers versus diamondoid concentrations (Fig.1)
(e.g. Stigamastane versus 3-+4- Methyldiamantane).
Four groups were well detected: the sample SES45
is highly mature and cracked oil; the samples SES14
and ALS27 are mature and medium cracked oils; the
sample CAP1 is low mature oil; and a fourth group
formed by mature but not cracked oils.
The hierarchical cluster analysis (Fig. 2) allows
recognizing groupings of oil samples according to
obtained in scores plot. Both stigmastane versus
methyldiamantane concentration graphic and
statistical analysis show similar results: the sample oil
CAP1 showed to be the less mature and the oils
ALS27 and SES14 are closer to another group –
sample SES45. The statistical analysis was a
powerful mean to the understanding, analysis and
visualization of the data.
STIGMASTANE STIGMASTANE ( ( ng ng / / mg mg ) )
300.0
250.0
200.0
150.0
100.0
CAP1
4SES12
7D14
SES83
50.0
ALS8
ALS3
4RB19 7CB28
SES14
ALS27
SES45
0.0
6PDM NAB6
20.0 40.0 60.0 80.0 100.0 120.0 140.0
3-+4-METHYLDIAMANTANE 3-+4- 3-+4-METHYLDIAMANTANE 3-+4-
( ng / mg )
Fig.1: Correlation between biomarker (stigmastane)
and diamondoids (methyldiamantanes) concentration
in oils.
Similarity Similarity % %
0
25
50
75
100
SES45 SES45 SES45 SES45
SES14 SES14 SES14 SES14
ALS27 ALS27 ALS27 ALS27
RR1 RR1 RR1 RR1
SES107 SES107 SES107 SES107
6PDM 6PDM 6PDM 6PDM
Fig.2: Dendrogram of hierarchical cluster analysis
calculated using Euclidean distance.
References
[1] Peters, K.E., Moldowan, J. M., 1993. The
Biomarker Guide. Interpreting Molecular Fossils in
Petroleum and Ancient sediments. Pentice-Hall. New
Jersey.
[2] Dahl, J.,et al. (1999). Nature 399, 54-56.
[3] Springer, M.V., Garcia, D.F., Gonçalves, F.T.T.,
Landau, L., Azevedo, D.A. (2010). Organic
Geochemistry, 41(9), 1013-1018.
[4] Azevedo et al. (2008) Fuel 87, 2122-2130.
ALS3 ALS3 ALS3 ALS3
7D14 7D14 7D14 7D14
SES83 SES83 SES83 SES83
7CB28 7CB28 7CB28 7CB28
RB19 RB19 RB19 RB19
NAB6 NAB6 NAB6 NAB6
4SES12 4SES12 4SES12 4SES12
ALS8 ALS8 ALS8 ALS8
CAP1 CAP1 CAP1 CAP1
410