Surface sediment hydrocarbons
as indicators of subsurface
hydrocarbons: Field calibration
of existing and new surface
geochemistry methods in
the Marco Polo area,
Gulf of Mexico
Michael A. Abrams and Nicola F. Dahdah
ABSTRACT
Multiple methods are currently used to collect, prepare, extract, and analyze near-surface migrated hydrocarbons from
marine sediments to evaluate subsurface petroleum generation and entrapment. Few have been rigorously tested to evaluate their effectiveness. A Gulf of Mexico field calibration
survey over the Marco Polo field was undertaken as part of an
industry-funded research project to better understand previously published and unpublished seabed geochemical results and determine which gas and liquid hydrocarbon extraction methods best characterize migrated hydrocarbons in
near-surface sediments.
The Marco Polo calibration data set demonstrates the importance of targeted coring and sampling depth. To improve
the detection of seabed migrated thermogenic hydrocarbons,
core samples should be collected along major migration pathways (cross-stratal leakage features) identified by conventional
deep seismic and high-resolution sea floor imaging. Not all
targeted cores hit the designated feature, and thus, collecting
replicates along key migration features is critical. Collecting
sediment samples below the near-surface transition zone known
as the “zone of maximum disturbance” is also important to
Copyright ©2011. The American Association of Petroleum Geologists. All rights reserved.
Manuscript received August 13, 2010; provisional acceptance November 22, 2010; revised manuscript
received January 24, 2011; final acceptance March 21, 2011.
DOI:10.1306/03211110130
AAPG Bulletin, v. 95, no. 11 (November 2011), pp. 1907–1935
1907
AUTHORS
Michael A. Abrams Exploration and
Production Technology Apache Corporation,
Houston, Texas;
[email protected]
Michael A. Abrams is currently the manager of
geochemistry for Apache Corporation. Before
working with Apache, Michael was senior research scientist in the University of Utah’s Energy
and Geoscience Institute and senior research
geochemist in Exxon Production Research Company. Michael’s research interests include surface
geochemistry, petroleum systems evaluation,
and migration pathway analysis. Michael received his Ph.D. from the Imperial College London,
a B.S. degree from George Washington University, and an M.S. degree from the University of
Southern California.
Nicola F. Dahdah Energy and Geoscience
Institute University of Utah Salt Lake City, Utah;
[email protected]
Nick Dahdah currently manages the organic
geochemistry laboratory at EGI and has been
a research scientist with the Institute since 1992,
specializing in oil and source rock characterization. He previously worked as a well site geologist for the Natural Resources Authority in
Jordan. He received a B.S. degree in geology
from Southeast Missouri State University and
an M.A. degree from the University of South
Carolina.
ACKNOWLEDGEMENTS
We thank the Surface Geochemistry Calibration
(SGC) research project industry supporters and
Energy and Geoscience Institute at the University of Utah. Ger van Graas (Statoil), Dennis
Miller (Petrobras), Harry Dembicki (Anadarko),
Neil Frewin (Shell), Andy Bishop (Shell), Brad
Huizinga (ConocoPhillips), Angelo Riva (ENI),
and Peter Eisenach (Wintershall) have all been
extremely helpful during the various phases of
the multiyear industry-funded research project.
We thank Anadarko Petroleum for allowing
the SGC research project to collect samples at
the Marco Polo field and access to key seismic
and geochemical information. We thank Harry
Dembicki who arranged permission for the
Marco Polo location site, chose and monitored
the core locations, and participated in the
cruise. We thank W. L. Gore and Associates
and Taxon Biosciences, which provided staff
and laboratory analysis at no cost. We thank
Fugro and the Seis Surveyor crew as well as
the shipboard research staff Harry Dembicki
(Anadarko), Matt Ashby (Taxon), Shuanglin Li
(Qingdoa Institute of Marine Geology), Rowland
Rincon (Peregrine Ventures), and Chris Reny
(Peregrine Ventures). The figures were drafted by
Jeffrey Massara with Apache Corporation. Reviews by Harry Dembicki, Barry Katz, and an
unnamed reviewer were very helpful.
The AAPG Editor thanks the following for their
work on this paper: Harry Dembicki Jr., Barry J.
Katz, and an anonymous reviewer.
avoid possible alteration effects and interference by recent organic matter.
Geochemical analysis should include a full range of hydrocarbon types: light hydrocarbon gases (C1–C5), gasoline
range (C5–C10+), and high-molecular-weight (HMW) hydrocarbons (C15+). The interstitial sediment gas data should be
plotted on a total hydrocarbon gas (S C1–C5) versus wet gas
fraction (S C2–C5/S C1–C5) chart to identify background,
fractionated, and anomalous populations. Compound-specific
isotopic analysis on selected anomalous samples is critical to
correctly identify migrated subsurface gases from near-surface
generated microbial gases. Microdesorption bound gases did
not provide gas compositions or compound-specific isotope
ratios similar to the Marco Polo reservoir gases, and thus, the
bound gas extraction is not recommended. A gasoline range
analysis provides a new range of hydrocarbons rarely examined
in surface geochemical studies that assist in identifying thermogenic hydrocarbons. Extraction gas chromatography and
total scanning fluorescence (TSF) maximum fluorescence intensity provided information on the presence of thermogenic
HMW hydrocarbons but did not work as well with the lowlevel microseepage samples. The TSF fluorogram signature
was similar for both seep and regional reference (background)
samples and did not help to identify migrated thermogenic
hydrocarbons.
The Marco Polo calibration study provides a framework
to better understand how best to collect (targeted deep cores)
and extract migrated hydrocarbons from near-surface marine
sediments and to evaluate the results.
INTRODUCTION
Multiple methods are currently applied to collect, prepare,
extract, and analyze near-surface migrated hydrocarbons from
marine sediments to evaluate subsurface petroleum generation (Horvitz, 1985; Brooks and Carey, 1986; Abrams et al.,
2001; Abrams, 2005; Logan et al., 2009; and Abrams and
Dahdah, 2010). Many of the sediment hydrocarbon extraction procedures currently used by the industry are based on
sampling and laboratory protocols initially designed for well
cuttings and have not always been rigorously tested to evaluate
their effectiveness with unconsolidated marine sediments. An
extensive series of literature and data reviews, laboratory tests,
and field studies have been conducted as part of an industryfunded Surface Geochemistry Calibration (SGC) research project conducted by the University of Utah’s Energy and Geoscience
1908
Surface Sediment Hydrocarbons as Indicators of Subsurface Hydrocarbons
Figure 1. The Marco Polo field is approximately 175 mi (∼281 km) south of New Orleans, Louisiana, in blocks 563, 607, and 608 Green
Canyon Gulf of Mexico in approximately 4000 ft (∼1219 m) of water.
Institute. The multiphase SGC research project
was organized to better understand previous seabed geochemical results both published and unpublished and determine which sediment hydrocarbon (gas and liquid) extraction methods best
characterize migrated near-surface sediment hydrocarbons (Abrams, 2002).
The SGC Gulf of Mexico Marco Polo field calibration survey was designed to field test specific
analytical procedures examined in the laboratory
studies as well as several emerging and existing
technologies. The Gulf of Mexico Marco Polo field
was chosen because it is an area of known petroleum leakage based on previous seismic and geochemical surveys (Chaouche et al., 2004; Dembicki
and Samuels, 2007), reservoir geochemical data
available (Abrams and Dembicki, 2006), and highquality shallow seismic imaging data acquired
(Dembicki and Samuels, 2007).
The near-surface sediment geochemical methods examined in the Marco Polo field calibration
survey can be subdivided into three categories:
light hydrocarbon gas (C1–C5), gasoline-range hy-
drocarbons (C5–C10+), and high-molecular-weight
(HMW) hydrocarbons (C15+). The light hydrocarbons were examined using two different sediment
gas extraction methods: interstitial (conventional
can headspace and modified headspace method
called “disrupter analysis”) and adsorbed-bound
(microdesorption analysis). The gasoline-range hydrocarbons were examined by two different analytical procedures, disrupter headspace solid-phase
microextraction (HSPME) and Gore Module. The
HMW hydrocarbons were examined using solvent extraction followed by whole-extract gas chromatography (GC) and total scanning fluorescence
(TSF).
The purpose of this article is to provide an
overview of the Marco Polo field SGC survey results for different seepage types and to better understand how the different methods characterize
the seeping hydrocarbons. This article provides
guidance on best practices for seabed geochemical
surveys based on both previously published laboratory experiments and the Marco Polo field calibration survey results.
Abrams and Dahdah
1909
Table 1. Core Description with Target Classification and Depth Information
Core No.
Seep Feature
(based on seismic feature, previous survey)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
Outside Marco Polo minibasin
Outside seep feature
Outside seep feature
Edge potential seepage
Inside area of seepage
Replicate Core 5
Previous survey oil stained
Replicate Core 7
Replicate Core 7
Inside area of seepage
Inside area of seepage
Outside seep feature
Inside area of seepage–edge
Previous survey oil stained with hydrate
Edge potential seepage
Outside seep feature
Outside seep feature
Near seeping fault along mud volcano
On mud volcano
Flank mud volcano
On mud volcano
Flank mud volcano
Flank mud volcano
Flank mud volcano
Outside north edge mud volcano
Outside north edge mud volcano
Outside seep feature
Outside seep feature
Outside seep feature
Outside seep feature
Outside seep feature
Outside seep feature
Outside Marco Polo minibasin
Target Type
A (cm)
B (cm)
C (cm)
Regional reference
Near seep zone
Near seep zone
Near seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Near seep zone
Within seep zone
Within seep zone
Near seep zone
Near seep zone
Near seep zone
Within seep zone
Within seep zone
Near seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Regional reference
3.65
3.90
4.77
3.72
4.96
4.19
4.17
4.23
4.04
2.46
4.29
5.33
3.79
0.31
4.02
4.42
3.40
3.67
3.85
3.42
0.70
1.76
0.50
3.78
5.33
3.66
3.31
3.73
3.63
3.70
2.89
3.14
2.79
156
181
268
163
287
210
208
214
195
37
220
324
170
NA
193
233
131
158
176
133
NA
NA
NA
169
323
157
122
164
154
161
80
105
70
239
264
351
246
370
293
291
297
278
120
303
407
253
NA
276
316
214
241
259
216
0
60
NA
252
406
240
205
197
237
244
163
188
153
322
347
434
329
453
376
374
380
361
203
396
490
336
0
359
399
297
324
342
299
33
143
10
335
489
323
288
280
320
328
246
271
236
FIELD OPERATIONS
Study Area
The Marco Polo field is approximately 175 mi
(281 km) south of New Orleans, Louisiana, in blocks
563, 607, and 608 Green Canyon Gulf of Mexico in
approximately 4000 ft (1219 m) of water (Figure 1).
The Marco Polo field is located in a salt-bounded
minibasin with petroleum production from supra1910
Depth Subsamples
Core
Length (m)
salt Miocene reservoir sands (Chaouche et al., 2004).
Geochemical analysis of reservoir fluids by Anadarko
Petroleum indicates that the medium-gravity oil
originated from a marine type II organic matter type
consistent with generation from the subsalt upper
Jurassic source rocks (see Chaouche et al., 2004,
for details). Areas of fluid movement from the reservoir to near surface had been identified on the
western side of the field area (Green Canyon Block
607) by the presence of mud mounds (volcanoes),
Surface Sediment Hydrocarbons as Indicators of Subsurface Hydrocarbons
Figure 2. The Marco Polo
calibration cruise core locations
on the surface terrain map,
Gulf of Mexico, Green Canyon
Block 607.
pockmarks (seabed craters), shallow acoustic blanking, and bright amplitudes (Dembicki and Samuels,
2007, 2008).
Core Selection and Collection
Thirty-three cores were collected based on 23 targets
and one location far from known seepage (Table 1).
The core locations are displayed on a digital terrain map generated from high-resolution multibeam bathymetry (Dembicki and Samuels, 2007)
(Figure 2). Two types of features were targeted:
within seep zone, sample location within major
seepage zone based on high-resolution acoustic data;
and near seep zone, sample location near feature
with major seepage based on high-resolution acoustic
data. A regional reference (local background reference) location was selected outside the minibasin
for a baseline sample of recent sediment organic
matter. More details on the core locations and targeted seismic features can be found in Dembicki
and Samuels (2007, 2008).
Initial positioning of the vessel was done using
shipboard global positioning system to match the
location of features identified with autonomous
underwater vehicle (AUV) data. The onboard Chirp
subbottom profiler records were then compared
with the AUV subbottom profiler records to confirm the targeted feature.The core samples were
collected aboard the Fugro Seis Survey using a
modified Kullenberg piston coring device (trough
corer trap system) with a 6-m core barrel and a
Abrams and Dahdah
1911
Table 2. Marco Polo Surface Geochemistry Calibration Can Headspace and Disrupter Interstitial Sediment Gas Data
Can Headspace
Core No.
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
01
01
01
02
02
02
03
03
03
04
04
04
05
05
05
06
06
06
07
07
07
08
08
08
09
09
09
10
10
10
11
11
11
12
12
12
13
13
13
14
15
15
15
16
16
1912
Disrupter Headspace
Core
Section
Core Target
Classification
Methane
(ppm)
Sum Wet
Gases (ppm)
Wet Gas
Fraction
Methane
(ppm)
Sum Wet
Gases (ppm)
Wet Gas
Fraction
A
B
C
A
B
C
A
B
C
A
B
C
A
B
C
A
B
C
A
B
C
A
B
C
A
B
C
A
B
C
A
B
C
A
B
C
A
B
C
C
A
B
C
A
B
Regional reference
Regional reference
Regional reference
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Near seep zone
Near seep zone
Near seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
6
7
8
11
19
16
11
22
13
8
59
12
21
10
22
10
10
16
31
42
112
168
206
14,262
32
53
166
43,083
120,570
147,738
191
2736
79,531
407
9206
48,260
74,639
39,127
41,999
5052
106,017
187,246
64,710
7
2387
1
1
2
2
4
2
1
3
2
1
2
2
3
2
1
1
1
2
3
3
5
3
9
61
3
4
4
1177
7978
6384
6
25
121
7
2421
149
224
553
123
89
1309
552
403
1
5
0.14
0.10
0.18
0.14
0.16
0.12
0.11
0.10
0.13
0.12
0.03
0.12
0.11
0.17
0.05
0.11
0.08
0.10
0.08
0.06
0.04
0.02
0.04
0.00
0.07
0.06
0.02
0.03
0.06
0.04
0.03
0.01
0.00
0.02
0.21
0.00
0.00
0.01
0.00
0.02
0.01
0.00
0.01
0.10
0.00
9
16
11
15
30
35
11
22
21
12
19
25
21
17
40
18
21
25
45
111
273
206
831
23,710
92
126
249
71,454
136,500
181,780
268
4364
202,040
179
21,398
105,618
110,879
490,720
87,892
4179
161,053
234,324
211,839
3497
223,696
2
5
4
3
6
4
3
4
4
2
3
3
4
5
2
3
4
3
2
2
6
3
14
66
2
3
4
991
3843
5212
6
27
220
5
59
205
299
4331
172
58
2176
526
1199
22
206
0.17
0.23
0.27
0.18
0.16
0.09
0.22
0.16
0.14
0.12
0.14
0.11
0.17
0.23
0.06
0.15
0.15
0.10
0.05
0.02
0.02
0.02
0.02
0.00
0.02
0.02
0.01
0.01
0.03
0.03
0.02
0.01
0.00
0.03
0.00
0.00
0.00
0.01
0.00
0.01
0.01
0.00
0.01
0.01
0.00
Surface Sediment Hydrocarbons as Indicators of Subsurface Hydrocarbons
Table 2. Continued
Can Headspace
Core No.
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
16
17
17
17
18
18
18
19
19
19
20
20
20
21
21
22
22
23
24
24
24
25
25
25
26
26
26
27
27
27
28
28
28
29
29
29
30
30
30
31
31
31
32
32
32
Disrupter Headspace
Core
Section
Core Target
Classification
Methane
(ppm)
Sum Wet
Gases (ppm)
Wet Gas
Fraction
Methane
(ppm)
Sum Wet
Gases (ppm)
Wet Gas
Fraction
C
A
B
C
A
B
C
A
B
C
A
B
C
B
C
B
C
C
A
B
C
A
B
C
A
B
C
A
B
C
A
B
C
A
B
C
A
B
C
A
B
C
A
B
C
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Near seep zone
Near seep zone
Near seep zone
Within seep zone
Within seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
185
16
20
15
22
26
29
81
310
11,750
180
4125
111,873
102,222
105,464
85,849
68,002
49,834
145
193
1076
294
9800
24,673
10
13
20
19
5
46
112
480
68,185
22
56
91
7
9
13
14
17
21
25
22
37
2
1
3
2
3
5
7
3
8
78
4
31
110
10,581
16,270
463
69
504
7
3
15
3
19
21
1
2
2
2
1
3
2
7
75
2
2
2
1
3
9
8
4
8
3
2
3
0.01
0.04
0.14
0.11
0.12
0.16
0.19
0.03
0.02
0.01
0.02
0.01
0.00
0.09
0.13
0.01
0.00
0.01
0.04
0.01
0.01
0.01
0.00
0.00
0.12
0.15
0.07
0.10
0.22
0.06
0.01
0.01
0.00
0.08
0.03
0.02
0.14
0.25
0.40
0.35
0.18
0.28
0.10
0.07
0.07
234,874
11
15
17
25
31
16
113
427
24,238
384
13,253
206,623
149,638
147,362
153,412
133,143
164,486
222
325
2259
381
45,563
51,987
11
10
16
6
19
22
166
968
87,801
31
88
183
70
17
11
81
12
18
8
25
19
202
2
4
4
5
5
6
3
10
116
8
58
167
7484
11,699
395
156
2163
5
8
46
7
52
48
4
4
6
3
4
4
4
17
78
2
4
4
5
4
4
8
6
9
3
3
5
0.00
0.18
0.20
0.20
0.17
0.14
0.27
0.02
0.02
0.00
0.02
0.00
0.00
0.05
0.07
0.00
0.00
0.01
0.02
0.02
0.02
0.02
0.00
0.00
0.27
0.30
0.28
0.29
0.19
0.16
0.02
0.02
0.00
0.07
0.04
0.02
0.06
0.19
0.25
0.09
0.32
0.33
0.30
0.11
0.21
Abrams and Dahdah
1913
Table 2. Continued
Can Headspace
Core No.
EGI 33
EGI 33
EGI 33
Disrupter Headspace
Core
Section
Core Target
Classification
Methane
(ppm)
Sum Wet
Gases (ppm)
Wet Gas
Fraction
Methane
(ppm)
Sum Wet
Gases (ppm)
Wet Gas
Fraction
A
B
C
Regional reference
Regional reference
Regional reference
14
25
34
2
1
1
0.14
0.04
0.03
19
13
139
6
2
5
0.23
0.14
0.04
6.7-cm internal diameter. The deep-water piston
corer was launched and retrieved using a rotating
A-frame high-speed hydroelectric dual winch. The
33 cores range in length from 0.5 to 5.3 m (1.6–
17.4 ft) with an average recovery of 3.5 m (11.5 ft)
(Table 1). Three core sections were collected from
each sediment core: top (∼0.5–2.0 m [∼1.6–6.6 ft]),
middle (∼2.0–3.0 m [∼6.6–9.8 ft]), and bottom
(∼3.0–5.0 m [∼9.8–16.4 ft]). Each core section
was subdivided in the shipboard laboratory and
processed using the analytical protocols provided
by the participating laboratories or established in
the SGC laboratory studies: a 5-cm subsection
placed in Gore Module sample container with a
sorber; replicate 10-cm sample splits placed in a
disrupter container (500-mL plastic container with
a screw on sealing cap, built-in septum, and internal blades; see Abrams and Dahdah, 2010, for
details) and a metal can for interstitial gas analysis;
3-cm sample placed in a plastic bag for microdesorption analysis; and replicate 10-cm sample
splits were wrapped in aluminum foil for solvent
extraction.
ANALYTICAL PROCEDURES
Sediment Gas Analysis
The conventional can headspace method is a nonmechanical procedure that uses high-speed shaking to release vapor-phase interstitial sediment gases
into the can headspace (Bernard, 1978). A 500-mL
metal can is filled with 170 mL of sediment, 160 mL
of 3.5% NaCl in H2O solution, and the remaining
headspace is flushed with N2 gas. The sample can
Figure 3. The three major groups for
Marco Polo can headspace and disrupter
light hydrocarbon data using the classification scheme from Abrams (2005);
background with total gas concentrations less than 10,000 ppm and low wet
gas fraction (<0.05), fractionated with
total gas concentrations less than 100 ppm
and elevated wet gas fraction (>0.05),
anomalous with total gas concentrations
greater than 10,000 ppm and wet gas
fraction less than 0.1 (<10%).
1914
Surface Sediment Hydrocarbons as Indicators of Subsurface Hydrocarbons
with mud and processed water is stored frozen.
The can is thawed for 24 hr before analysis, heated
to 40°C for 4 hr, and shaken vigorously using a
conventional paint shaker. The headspace gas is
collected by syringe and injected in the gas chromatograph for compositional analysis. See Bernard
(1978) for more details.
The disrupter sediment gas extraction method
was designed as part of the SGC laboratory studies
to capture interstitial gases not easily released by
vigorous shaking (Abrams and Dahdah, 2010). The
disrupter method uses a 165-mL sediment sample
that is placed in a 500-mL disrupter chamber with
165 mL of saturated salt brine solution and remaining volume air headspace. The disrupter chamber
has a fixed internal blade that breaks apart the sediment, releasing interstitial gases without crushing
(Abrams and Dahdah, 2010). The disrupter with
sample is frozen on the vessel, then shipped and
stored frozen until analysis. The disrupter is thawed
to room temperature 24 hr before analysis and
shaken for 5 min using a high-speed unidirectional
paint can shaker. A 0.2-mL disrupter headspace
sample is collected by a syringe through the disrupter cap septum at room temperature and injected into the GC inlet. See Abrams and Dahdah
(2010) for more details.
The bound gases are believed to be attached to
organic and/or mineral surfaces, entrapped in structured water, or entrapped in authigenic carbonate
inclusions and thus require a more rigorous procedure to remove (Horvitz, 1985; Bjoroy and Ferriday,
2002; Whiticar, 2002). The microdesorption bound
sediment gas extraction method (Whiticar, 2002)
uses a 300- to 400-mL bulk sediment sample that
has been stored frozen in a plastic bag. A fixed
weight of wet sediment sample (1–3 g) is placed in
a reaction vessel, sealed, and evacuated. A small
amount of saline water is added, and the sedimentwater slurry is mixed using a vortex ultrasonic mixer.
The interstitial gases are removed by vacuum. Phosphoric acid is added under reduced pressure where
the sorbed gas is released to the vessel headspace.
Potassium hydroxide is added before GC to reduce
carbonate-generated carbon dioxide. The pressure
is increased and sample aliquots of gas are collected
for GC analysis. See Whiticar (2002) for details.
Gasoline-Range (C5–C10+)
Hydrocarbon Analysis
Two methods were used in the Marco Polo field
calibration survey to evaluate sediment gasolinerange hydrocarbons, the Gore Module and disrupter
HSPME. The Gore method evaluates a full range
of hydrocarbons from C2 to C20+ using a specially
engineered hydrophobic adsorbent encased in a
microporous expanded Gore Module polytetrafluoroethylene membrane (Anderson, 2006). The
Gore Module is placed in a special glass container
with a designated volume of sediment and analyzed
via thermal desorption coupled with mass spectrometry (MS). See the W. L. Gore and Associates
Web page for additional details. (www.gore.com)
The HSPME headspace sample is collected
after the disrupter headspace gas analysis. A 1-cm
fused silica fiber coated with 100-mm-thick polydimethylsiloxane is inserted into the headspace for
a 20-min extraction, then manually injected into
the GC inlet for desorption. The SPME fiber is left
in the GC inlet for 5 min. See Abrams et al. (2009)
for details.
High-Molecular-Weight Hydrocarbon Analysis
A dried sediment sample is ground to a uniform size
and an aliquot by weight is extracted using hexane in an automated extraction apparatus (Dionex
ASE 200 Accelerated Solvent Extractor). Extracts
are concentrated to a final volume of 8 mL using
Zymark TurboVap II. The final extracts are submitted for hydrocarbon analysis by GC flame ionization detection (FID) and TSF. See Brooks et al.
(1983) for additional information.
RESULTS AND DISCUSSION
Sediment Gas Analysis
Interstitial Gas Evaluation
The can headspace and disrupter data are summarized in Table 2 and plotted on a total hydrocarbon
gas (S C1–C5) versus wet gas fraction (S C2–C5/S
C1–C5) plot (Figure 3). Both interstitial sediment gas
Abrams and Dahdah
1915
extraction methods provide similar results. Three
major groups exist for both interstitial sediment
gas data sets using the classification scheme from
Abrams (2005): background with total gas concentrations less than 10,000 ppm and low wet gas
fraction (<0.05); fractionated with total gas concentrations less than 100 ppm and elevated wet
gas fraction (>0.05); and anomalous with total gas
concentrations greater than 10,000 ppm and wet
gas fraction less than 0.1 (10%). The cutoffs are
based on an examination of a worldwide surface
geochemistry database (Abrams, 2005).
Examination of the three sediment gas groups
relative to the pre-survey core targets (within seep
zone, near seep zone, and regional reference) reveals interesting observations. The regional reference core samples fall within the background and
fractionated samples. The fractionated group was
defined in Abrams (2005) to represent very low
concentration samples (<100 ppm) with differential volatile loss (methane loss greater than the wet
gases) that results in wet gas enrichment. This is a
common feature noted in most interstitial sediment
gas seabed surveys (Abrams, 2005) and SGC laboratory experiments (Abrams et al., 2009).
The within-seep-zone and near-seep-zone targeted cores fall within all three groups: background,
fractionated, and anomalous. Note the relatively
large number of cores collected from within seep
zone and near seep zone based on AUV acoustic
data that contain very low total interstitial hydrocarbon gas (<10,000 ppm). Several reasons exist
why near-surface sediment cores collected within a
seep feature contain low levels of total interstitial
sediment hydrocarbon gas. First, the core samples
were collected within the transition zone known as
the zone of maximum disturbance (ZMD) (Abrams,
1992). Samples collected within the ZMD may be
altered by microbial processes or pore water flushing (Abrams, 1996) unless the seepage volume and
rate overwhelm the alteration processes (Abrams,
2005). A plot of core sampling depth versus total
disrupter headspace interstitial hydrocarbon gas
indicates that the ZMD is approximately 2.0 m
(6.6 ft) based on the near-seep-zone samples with
elevated total gases (>10,000 ppm) relative to sample depth (Figure 4). Note that the ZMD will vary
1916
Figure 4. The plot of core sampling depth versus total disrupter
headspace interstitial hydrocarbon gas indicates the zone of
maximum disturbance (ZMD) is approximately 2.0 m (6.6 ft).
The within-seep-zone samples have elevated total gas concentrations within and below the ZMD, whereas the near-seepzone samples have elevated total gas concentrations only below
the ZMD.
for each petroleum seepage system (Abrams, 1996,
2005).
The second and more fundamental issue is
collecting cores within the chosen targeted feature. Sampling a relatively small target in 4000 ft
(1219.2 m) of water with a gravity corer is very difficult. Many of the cores collected within the Marco
Polo survey did not sample the targeted feature
based on the geochemistry results. Abrams (1992)
demonstrated the importance of sampling depth
and hitting the target by collecting core samples
from an anchored drill ship using shallow drilling
technology on and off a known hydrocarbon seeping fault. The drill ship survey showed that the
migrated thermogenic signal was quickly lost from
deep sediment cores collected 15 to 25 m (49–92 ft)
away from the migration pathway (leaky fault).
The Marco Polo calibration data set reinforces the
Surface Sediment Hydrocarbons as Indicators of Subsurface Hydrocarbons
Figure 5. The disrupter interstitial sediment gas composition
(wet gas fraction and C1/C2 ratio–methane/ethane) is different
from the Marco Polo Field reservoir gases.
importance of good seismic data to define the seep
feature and a core collection protocol with the
ability to hit the targeted feature at 2+ m below the
water-sediment interface.
The disrupter interstitial sediment gas composition (wet gas fraction and C1/C2 ratio) and Marco
Polo field reservoir gases are different (Figure 5).
Similar observations were made by Abrams and
Dembicki (2006). The differences between reservoir and near-surface sediment gas compositions
are most likely related to near-surface affects (phase
fractionation and microbial alteration) as well as
mixing with shallow microbial gases. Therefore, caution should be used when interpreting near-surface
Figure 6. The methane and ethane d13Cn values for disrupter
extracted interstitial gases are similar to the 12,200 ft (3719 m)
reservoir production gases, except propane (C3) (does not include sample 23C).
sediment gas compositions using interpretation
charts designed for reservoir gases (Abrams, 2005).
Compound-specific carbon isotopic analysis
(methane, ethane, and propane) of selected highconcentration macroseepage (anomalous) can headspace and disrupter extracted interstitial gases provide similar results except for core number 23C
(Table 3). The disrupter d13C1 for sample 23C is
9‰ lighter, indicating in-situ microbial gas generation. The methane and ethane d13Cn values for
the disrupter-extracted interstitial gases are similar to the 12,200-ft reservoir production gases,
except propane (Figure 6). The disrupter and
can headspace-extracted hydrocarbon gases have
propane isotopic values heavier (d13C3, –15.3 to
Table 3. Marco Polo Surface Geochemistry Calibration Interstitial Sediment Gas (Can Headspace and Disrupter) Compound-Specific
Carbon and Methane Hydrogen Isotopic Data
Core No.
10B
10C
21B
21C
23C
Method Laboratory
d13C1 (‰)
d13C2 (‰)
d13C3 (‰)
dDC1 (‰)
Disrupter
Can headspace
Disrupter
Can headspace
Disrupter
Can headspace
Disrupter
Can headspace
Disrupter
Can headspace
−56.8
−55.6
−54.8
−52.6
−56.2
−53.9
−55.1
−54.5
−64.8
−55.7
−35.9
−36.2
−36.4
−36.8
−36.5
−36.5
−36.4
−35.3
−41.1
−38.7
−25.8
−29.2
−29.3
−30.4
−15.3
−16.3
−17.0
−17.0
−18.6
−19.4
−203
−193
−207
−203
−199
−196
−203
−202
−196
−178
Abrams and Dahdah
1917
Table 4. Marco Polo Surface Geochemistry Calibration Microdesorption Sediment Gas Data
Sample ID
EGI 01
EGI 01
EGI 01
EGI 02
EGI 02
EGI 02
EGI 03
EGI 03
EGI 03
EGI 04
EGI 04
EGI 04
EGI 05
EGI 05
EGI 05
EGI 06
EGI 06
EGI 06
EGI 07
EGI 07
EGI 07
EGI 08
EGI 08
EGI 08
EGI 09
EGI 09
EGI 09
EGI 10
EGI 10
EGI 10
EGI 11
EGI 11
EGI 11
EGI 12
EGI 12
EGI 12
EGI 13
EGI 13
EGI 13
EGI 14
EGI 15
EGI 15
EGI 15
EGI 16
EGI 16
EGI 16
EGI 17
1918
Depth
Section
Core Target
Classification
A
B
C
A
B
C
A
B
C
A
B
C
A
B
C
A
B
C
A
B
C
A
B
C
A
B
C
A
B
C
A
B
C
A
B
C
A
B
C
C
A
B
C
A
B
C
A
Regional reference
Regional Reference
Regional Reference
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Near seep zone
Near seep zone
Near seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Carbon Isotopes
C1 (nmol/g)
Total Gas
(nmol/g)
Wet Gas
Fraction
C1
C2
C3
iC4
NC4
236
256
277
267
286
200
232
182
342
187
203
233
221
427
247
201
223
221
243
312
372
227
240
457
258
181
400
227
678
902
362
300
725
223
706
898
847
602
727
109
479
965
609
385
730
872
83
253
278
303
287
309
220
248
196
388
201
218
251
240
475
272
216
240
244
263
345
418
241
257
513
274
194
430
717
772
992
384
314
768
246
807
991
863
634
771
121
545
995
640
409
757
899
89
0.07
0.08
0.09
0.07
0.07
0.09
0.07
0.07
0.12
0.07
0.07
0.07
0.08
0.10
0.09
0.07
0.07
0.09
0.07
0.10
0.11
0.06
0.07
0.11
0.06
0.07
0.07
0.68
0.12
0.09
0.06
0.04
0.06
0.09
0.12
0.09
0.02
0.05
0.06
0.10
0.12
0.03
0.05
0.06
0.04
0.03
0.07
−56.0
−52.3
−48.7
−54.6
−51.1
−48.9
−52.0
−53.7
−45.5
−54.7
−50.2
−51.2
−53.7
−45.9
−49.5
−53.3
−50.1
−49.1
−50.2
−47.8
−49.7
−53.5
−62.0
−49.0
−56.8
−52.8
−53.0
−52.7
−56.2
−55.1
−58.7
−62.7
−57.0
−51.3
−48.3
−58.7
−55.2
−52.9
−48.7
−63.0
−56.4
−56.1
−59.6
−58.3
−62.6
−58.9
−49.2
−32.3
−32.0
−33.2
−32.4
−31.9
−32.7
−32.7
−32.6
−34.3
−32.4
−32.4
−32.8
−32.3
−34.3
−33.9
−33.1
−32.2
−33.9
−32.4
−34.5
−34.5
−32.7
−31.9
−34.8
−32.2
−32.6
−32.6
−29.9
−33.5
−33.8
−32.9
−33.0
−34.8
−32.9
−34.6
−35.2
−33.5
−33.2
−34.6
−31.1
−34.6
−35.3
−34.6
−32.7
−35.3
−36.2
−32.6
−32.5
−30.8
−31.5
−31.1
−30.5
−30.7
−31.4
−31.0
−31.8
−31.6
−30.5
−31.3
−31.0
−31.5
−31.8
−30.6
−31.1
−31.4
−30.5
−32.4
−32.7
−30.4
−29.4
−30.4
−31.0
−30.2
−30.1
−7.7
−23.4
−26.7
−31.8
−26.5
−29.1
−28.5
−28.3
−18.1
−24.2
−34.0
−33.0
−31.0
−33.0
−33.0
−31.0
−31.0
−31.0
−30.0
−30.0
−30.0
−30.0
−31.0
−29.9
−30.0
−30.0
−31.0
−30.0
−29.8
−30.0
−31.0
−29.0
−30.0
−28.0
−30.4
−31.0
−31.0
Surface Sediment Hydrocarbons as Indicators of Subsurface Hydrocarbons
−32.0
−31.3
−31.2
−32.0
−32.0
−33.0
−31.0
−32.2
−31.6
−33.0
−31.5
−32.4
−32.3
−32.2
−32.0
−32.8
−31.5
−32.1
−31.8
−29.1
−31.0
−30.3
−29.8
−28.3
−22.1
−29.8
−30.6
−27.8
−30.0
−30.6
−30.4
−30.2
−29.0
−28.4
−30.7
−30.1
−15.6
−21.7
−27.4
−29.3
−29.5
−29.5
−28.3
−30.7
−31.9
−34.1
−31.6
−32.2
−23.0
−27.7
−29.6
−29.6
−30.1
−29.6
Table 4. Continued
Sample ID
EGI 17
EGI 17
EGI 18
EGI 18
EGI 18
EGI 19
EGI 19
EGI 19
EGI 20
EGI 20
EGI 20
EGI 21
EGI 21
EGI 22
EGI 22
EGI 23
EGI 24
EGI 24
EGI 24
EGI 25
EGI 25
EGI 25
EGI 26
EGI 26
EGI 26
EGI 27
EGI 27
EGI 27
EGI 28
EGI 28
EGI 28
EGI 29
EGI 29
EGI 29
EGI 30
EGI 30
EGI 30
EGI 31
EGI 31
EGI 31
EGI 32
EGI 32
EGI 32
EGI 33
EGI 33
EGI 33
Depth
Section
Core Target
Classification
B
C
A
B
C
A
B
C
A
B
C
B
C
B
C
C
A
B
C
A
B
C
A
B
C
A
B
C
A
B
C
A
B
C
A
B
C
A
B
C
A
B
C
A
B
C
Near seep zone
Near seep zone
Within seep zone
within seep zone
within seep zone
within seep zone
within seep zone
within seep zone
near seep zone
near seep zone
Near seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Regional reference
Regional reference
Regional reference
Carbon Isotopes
C1 (nmol/g)
Total Gas
(nmol/g)
Wet Gas
Fraction
C1
C2
C3
293
259
293
362
302
293
294
381
270
346
822
436
591
862
993
215
138
205
619
215
262
684
280
284
185
83
245
262
174
237
398
243
210
199
287
227
220
70
256
194
61
318
228
66
246
233
312
279
311
391
325
311
316
410
287
373
844
835
1736
937
1020
234
150
227
701
233
285
759
296
305
204
91
262
283
179
252
414
256
223
213
301
244
237
77
270
206
67
338
244
74
263
249
0.06
0.07
0.06
0.07
0.07
0.06
0.07
0.07
0.06
0.07
0.03
0.48
0.66
0.08
0.03
0.08
0.08
0.10
0.12
0.08
0.08
0.10
0.05
0.07
0.09
0.08
0.07
0.07
0.03
0.06
0.04
0.05
0.05
0.06
0.05
0.07
0.07
0.09
0.05
0.06
0.09
0.06
0.07
0.11
0.06
0.07
−55.6
−51.4
−57.5
−48.0
−53.7
−55.4
−53.1
−53.0
−59.8
−50.6
−59.8
−46.5
−54.2
−52.0
−58.0
−55.5
−54.8
−51.2
−44.2
−54.3
−57.7
−52.9
−58.3
−49.3
−49.6
−51.4
−54.6
−51.5
−62.7
−56.2
−64.4
−59.2
−58.2
−57.3
−59.2
−46.6
−53.8
−42.5
−58.4
−55.5
−44.6
−58.5
−53.3
−42.0
−57.9
−52.8
−33.3
−33.0
−32.5
−32.4
−33.4
−32.5
−33.0
−33.8
−32.5
−31.8
−33.0
−33.9
−34.3
−37.0
−35.6
−33.7
−34.0
−33.3
−34.6
−33.1
−33.9
−35.0
−32.6
−32.3
−32.6
−32.9
−32.7
−32.6
−31.9
−33.6
−34.1
−32.3
−33.5
−32.4
−32.3
−32.5
−32.3
−31.9
−33.0
−32.5
−31.7
−33.4
−32.9
−31.0
−32.5
−31.6
−30.9
−31.2
−31.3
−30.6
−32.0
−32.2
−30.9
−31.3
−31.9
−28.7
−28.5
−28.2
−14.8
−26.5
−27.5
−28.9
−30.6
−25.5
−32.1
−30.3
−31.8
−32.0
−32.1
−31.8
−31.4
−29.3
−31.0
−31.0
−28.8
−31.5
−31.0
−30.8
−31.8
−30.3
−30.5
iC4
−33.2
−31.4
−32.5
−31.5
−32.1
−33.6
−31.7
−31.8
−30.3
−30.8
−30.6
−32.4
−32.1
−33.4
−32.2
−32.9
−33.9
NC4
−30.8
−29.9
−30.7
−28.9
−32.1
−30.3
−29.3
−28.7
−30.5
−28.8
−29.7
−26.7
−27.3
−27.7
−26.5
−29.1
−29.3
−30.2
−27.9
−30.7
−30.2
−31.9
−29.6
−32.4
−30.6
−31.2
−30.9
−28.5
−32.1
−30.1
−29.7
−30.0
−33.0
−31.6
−29.7
−30.5
−30.9
−32.9
−29.9
−30.5
−30.5
−30.9
−30.2
Abrams and Dahdah
−33.0
−29.1
−29.4
1919
extracted sediment gases show higher gas wetness
than the reservoir gases (Figure 7).
The bound gases compound-specific isotopic
ratios do not match the reservoir gases (Figure 8).
The sediment-bound methane and ethane isotopes
are as much as 7‰ heavier than the Marco Polo
Field reservoir gases. This is not an uncommon
observation for sediment-bound gases removed
by acid extraction from both washed and closedvessel adsorbed-hydrocarbon analysis (Abrams and
Dahdah, 2010).
Figure 7. The bound gases display different trends from the
interstitial gases. No bimodal distribution and total microdesorption hydrocarbon gas displays significant variability from the
low- and high-concentration samples. Most have wet gas fractions less than 0.12 (<12%) with three notable exceptions: 0.48,
0.66, and 0.68. Most display higher gas wetness than the reservoir gases.
–29.3‰) relative to the reservoir gases (d 13C 3,
–27.8 to –31.1‰) (Table 3; Figure 6). This is most
likely related to near-surface microbial alteration
of propane. The preferential attack of propane
was noted by James and Burns (1984) in reservoir
gases, and microbial fractionation of near-surface
gases is not uncommon for seabed sediment gases
(Abrams, 1989).
Microdesorption (Bound) Gases
The microdesorption bound gas data (Table 4) are
plotted on the same total hydrocarbon gas (S C1–
C4) versus wet gas fraction (S C2–C4/S C1–C4)
evaluation plot using the same core designations
(Figure 7). Note that the microdesorption sediment gases are reported in nanomoles per gram
by weight, whereas the disrupter headspace gas is
reported in parts per million by volume.
The bound gases display a very different trend
than the interstitial gases. No bimodal distribution
is present and total microdesorption hydrocarbon
gas displays significant variability from low- and
high-concentration samples (Figure 7). Most of
the samples have wet gas fractions less than 0.12
(<12%), with three notable exceptions: 0.48, 0.66,
and 0.68 (48–68%). Most of the microdesorption
1920
Gasoline-Range Hydrocarbon Analysis
The gasoline-range petroleum hydrocarbons comprise molecules with 5 to 12 carbon atoms (C5–
C12) arranged in linear, branched, and cyclic aliphatic structures along with monoaromatic hydrocarbons, such as benzene, toluene, and o-, m-, and
p-xylenes. This group of hydrocarbons is normally
derived from thermogenic processes associated
with a mature generating source rock unlike methane and ethane (C1 and C2) that could be derived
from either thermogenic or microbial processes
(Whiticar, 1999). The gasoline-range hydrocarbons
are volatile and migrate within key oil migration
avenues to the sediment surface and should be an
Figure 8. Most Marco Polo sediment-bound gases do not
match the reservoir gas isotopic values. Bound gases are up to
7‰ heavier than the Marco Polo Field reservoir gases.
Surface Sediment Hydrocarbons as Indicators of Subsurface Hydrocarbons
important target for most surface geochemical
surveys (Abrams et al., 2009).
To date, few surface geochemical surveys attempt to evaluate the gasoline-range hydrocarbons
in near-surface marine sediments. Conventional
headspace light hydrocarbon analysis is not an effective method to evaluate the C6 to C12 hydrocarbons because of higher boiling points and low
vapor pressures relative to the hydrocarbons’ gases
(C1–C5) (Abrams and Dahdah, 2010).
Headspace Solid-Phase Microextraction
The HSPME data are reported as the area sum of
a single carbon number (SCN) within the main
boiling point range detected using the SPME fiber.
The unresolved complex mixture (UCM) is included in the area of each SCN (Abrams et al.,
2009) (Table 5). A plot of the disrupter total hydrocarbon interstitial gas (S C1–C5) versus HSPME
SCN (Figure 9) displays moderate correlation between sediment interstitial gas and the concentration of gasoline-range hydrocarbons.
The regional reference HSPME gas chromatograms contain very low overall signal responses
(<10 total GC area) that are dominated by SPME
fiber peaks (Figure 10A) (Abrams et al., 2009). In
contrast, the high-concentration within-seep-zone
HSPME gas chromatograms have an elevated overall signal response increasing with depth, significant
resolvable compounds, depleted light end, and elevated baseline hump or UCM (Figure 10B).
Compound distributions for the within-seepzone chromatograms are very different to an unaltered reservoir oil whole-oil chromatogram. The
HSPME within-seep-zone chromatograms contain
very low n-alkanes (C5, C6, C7, and C8), aromatics
(benzene, toluene, and xylenes), cycloalkanes (cyclopentane and cyclohexane), and cycloalkanes
with one methyl group (methyl-cyclopentane and
methyl-cyclohexane) but elevated isoalkanes and
cycloalkanes with more than one methyl group.
This unique compound distribution is commonly
found in biodegraded oils (George et al., 2002),
indicating that the macroseepage seabed gasolinerange hydrocarbons are rapidly and heavily altered
(Abrams et al., 2009).
Gore Module
The Gore Module examines as much as 150 volatile compounds using cluster analysis and linear discriminate classification for defining petroleum and
background character end members (Anderson,
2006). Three end-member groupings were defined by the Gore statistical evaluation: high aliphatic, medium aliphatic, and background (Table 5;
Figure 11A–C).
The Gore high aliphatic group contains the
higher concentration (based on headspace gas
and HSPME data) within-seep-zone samples, with
two exceptions (Table 5). The key compounds
that characterize this end member group include
2-methylbutane, 3-methylpentane, methylcyclohexane, cyclohexane, 1-octene, cyclopentane,
c1314 dimethylcyclohexane, and ethylcyclohexane (Figure 11A).
The Gore medium aliphatic group contains a
mix of the within-seep-zone and near-seep-zone
samples (Table 5). The key compounds that characterize this end member group include carbon
disulfide, 2,4-dimethylpentane, 2,5-dimethylhexane, pristane, ethane, and cyclooctane (Figure 11B).
The Gore background group contains the
regional reference samples as well as the lowconcentration within-seep-zone and near-seep-zone
samples (Table 5). The key compounds that characterize this end member group include carbon disulfide, propene, ethane, octanal, decanal, propane,
1-butene, butane, and tetradecane (Figure 11C).
A plot of Gore Module total reported hydrocarbons versus total disrupter HSPME SCN indicates that both gasoline-range sediment extraction
methods provide similar results (Figure 12). Both
methods provide strong gasoline-range signals within
the interstitial sediment gas high-concentration
within-seep-zone and near-seep-zone samples and
minimal signal in the regional reference and interstitial sediment gas low-concentration within-seepzone and near-seep-zone targeted cores. The Gore
Module thermal desorption MS analysis provides
greater compound specific information than could
be achieved with the HSPME GC-FID approach.
This could prove to be important to characterize
seep origin (source facies, level of maturity, and/or
seep to oil correlation). In addition, the desorption
Abrams and Dahdah
1921
Table 5. Marco Polo Surface Geochemistry Calibration Headspace Solid-Phase Microextraction and Gore Module Gasoline Plus Data
with Statistical Grouping Classifications
Core No.
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
01
01
01
02
02
02
03
03
03
04
04
04
05
05
05
06
06
06
07
07
07
08
08
08
09
09
09
10
10
10
11
11
11
12
12
12
13
13
13
14
15
15
15
16
16
16
1922
Core
Section
Core Target
Classification
Core Depth
Gore Grouping
Total Gore
Hydrocarbons
Total Disrupter
C1–C5
Total SPME
SCN–UCM
A
B
C
A
B
C
A
B
C
A
B
C
A
B
C
A
B
C
A
B
C
A
B
C
A
B
C
A
B
C
A
B
C
A
B
C
A
B
C
C
A
B
C
A
B
C
Regional reference
Regional reference
Regional reference
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Near seep zone
Near seep zone
Near seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
156
239
322
181
264
347
268
351
434
163
246
329
287
370
453
210
293
376
208
291
374
214
287
380
194
278
361
37
120
203
220
303
396
324
407
490
170
253
336
10
193
276
359
233
316
399
Background
Background
Background
Background
Background
Background
Background
Background
Background
Background
Background
Background
Background
Background
Background
Background
Background
Background
Background
Background
Background
Background
Background
Medium Aliphatic
Background
Background
Background
High aliphatic
High aliphatic
High aliphatic
Medium Aliphatic
Background
Medium aliphatic
Background
Background
Medium aliphatic
High aliphatic
High aliphatic
High aliphatic
Medium aliphatic
High aliphatic
High aliphatic
High aliphatic
Background
Medium aliphatic
Medium aliphatic
142
303
243
131
174
148
131
205
216
146
159
370
214
278
134
173
193
160
129
134
185
124
179
1558
150
154
155
6212
132,986
153,739
443
331
1106
159
202
856
24,625
59,660
47,206
516
34,715
42,592
23,301
150
1390
517
15
21
11
18
36
39
14
26
25
14
22
28
26
22
42
21
25
28
48
113
279
209
845
23,775
94
129
253
72,445
140,343
186,992
274
4391
202,259
184
21,456
105,824
111,178
495,051
88,064
4237
163,229
234,851
213,038
3519
223,903
235,076
158
181
76
493
129
189
70
299
175
119
73
154
82
271
153
86
74
163
252
146
119
83
1467
2334
178
188
171
4588
4859
34,294
116
547
2426
92
116
151
9948
9155
6387
1807
9502
12,214
16,784
510
921
508
Surface Sediment Hydrocarbons as Indicators of Subsurface Hydrocarbons
Table 5. Continued
Core No.
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
17
17
17
18
18
18
19
19
19
20
20
20
21
21
22
22
23
24
24
24
25
25
25
26
26
26
27
27
27
28
28
28
29
29
29
30
30
30
31
31
31
32
32
32
33
33
33
Core
Section
Core Target
Classification
Core Depth
Gore Grouping
Total Gore
Hydrocarbons
Total Disrupter
C1–C5
Total SPME
SCN–UCM
A
B
C
A
B
C
A
B
C
A
B
C
B
C
B
C
C
A
B
C
A
B
C
A
B
C
A
B
C
A
B
C
A
B
C
A
B
C
A
B
C
A
B
C
A
B
C
Near seep zone
Near seep zone
Near seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Near seep zone
Near seep zone
Near seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Regional reference
Regional reference
Regional reference
131
214
297
158
241
324
176
259
342
133
216
299
10
33
60
143
10
169
252
335
323
406
489
157
240
323
122
205
288
164
197
280
154
237
320
161
244
328
80
163
246
105
188
271
70
153
236
Background
Background
Background
Background
Background
Background
Background
Background
Medium aliphatic
Medium aliphatic
Background
High aliphatic
High aliphatic
High aliphatic
High aliphatic
High aliphatic
High aliphatic
Background
Background
Background
Background
Background
Medium aliphatic
Background
Background
Background
Background
Background
Background
Background
Background
Background
Background
Background
Background
Background
Background
Background
Background
Background
Background
Background
Background
Background
Background
Background
Background
133
318
215
244
201
256
145
111
1757
2332
115
882
19,134
226,976
26,428
6983
79,866
147
247
277
124
201
482
269
291
200
206
116
175
102
210
281
130
120
112
184
193
144
255
351
313
151
162
235
195
180
246
13
18
22
29
36
22
116
437
24,355
392
13,312
206,790
157,122
159,061
153,807
133,299
166,649
227
333
2305
389
45,616
52,034
15
15
22
9
9
26
170
985
87,879
34
92
187
75
21
15
88
18
27
12
28
24
15
25
144
97
153
107
124
100
97
145
105
13,076
235
179
1875
14,087
21,952
11,747
6689
16,515
215
177
342
188
126
165
152
263
107
105
105
82
147
235
689
143
64
74
136
86
264
102
142
111
158
97
290
148
102
131
Abrams and Dahdah
1923
Figure 9. The headspace solid-phase microextraction (HSPME)
data reported as sum of single carbon number (SCN) within the
detection range of SPME fiber. The unresolved complex mixture
is included in the area of each SCN. A plot of disrupter total
hydrocarbon interstitial gas (S C1–C5) versus HSPME SCN displays a moderate correlation between sediment interstitial gas
and concentration of gasoline-range hydrocarbons with notable
exceptions.
MS analysis can detect much lower concentrations than other seabed geochemical analysis methods. However, it could not discriminate the lowconcentration within-seep-zone and near-seep-zone
samples any better than the disrupter headspace
gas or HSPME gasoline-range analysis.
The 8, 11, 16, 19, and 25 within-seep-zone and
near-seep-zone core shallow subsamples were classified by Gore in the background group, whereas
the deeper subsamples fall in the medium aliphatic
group. This observation reinforces the importance
of sampling depth and placing the corer directly on
the targeted feature.
High-Molecular-Weight Hydrocarbon Analysis
Extract GC: The sediment extract GC evaluation
includes the chromatogram signature, total UCM,
and total n-alkanes. Table 6 contains extract GC
total UCM and total n-alkanes for the Marco Polo
calibration samples. Samples with UCM values
less than 25 mg/g are considered to be background,
whereas samples with UCM greater than 100 mg/g
1924
are associated with migrated hydrocarbon seepage
(Cole et al., 2001; Abrams, 2005). Six of the 15 cores
collected at the within-seep-zone targets did not
have elevated UCM (>100 mg/g), indicating that
the samples may not have hit the targeted feature
(Table 6). One near-seep-zone sample contains
elevated UCM (Table 6).
Sediments containing migrated thermogenic
HMW hydrocarbons typically have GC-FID chromatograms characterized by a large unresolved complex mixture (UCM) with some discernible C15–
C32 n-alkanes and isoprenoids peaks, depending on
the severity of microbial alteration (Figure 13A)
(Brooks and Carey, 1986). All but one of the withinseep-zone samples have extremely high UCM values (>1000 mg/g) and a sum of total alkanes less than
1. This is a common observation with sediment extract chromatograms and is related to the severe
near-surface bacterial alteration that has destroyed
most of the resolvable normal alkane compounds
very quickly. Sediments containing mainly the recent organic matter (ROM) signature with some
migrated thermogenic signal will contain lower
UCM and overprint of odd n-alkanes greater than
C23 (Figure 13B) (Brooks and Carey, 1986).
Extract TSF: The sediment extract TSF evaluation includes examination of the fluorogram signature and maximum fluorescence intensity (MFI).
Samples with significant seepage require dilution
before TSF analysis. The MFI values are adjusted
by multiplying the measured MFI by the dilution
factor to obtain a corrected MFI (Brooks et al.,
1983).
The extract TSF MFI ranges from 30,140 to
73,260,000 MFI units (Table 6) for the SGC phase III
GOM calibration samples. Most of the samples collected in the within-seep-zone targets contain highextract TSF MFI values (100,000 MFI units) (Cole
et al., 2001; Abrams, 2005). Several near-seep-zone
samples as well as one shallow regional-reference
sample also have extract TSF MFI greater than
100,000 units.
An extract GC total UCM versus TSF MFI plot
demonstrates a relatively strong correlation between
the two HMW screening tools (Figure 14), but examination of the TSF fluorogram signatures indicate a potential problem with the extract TSF
Surface Sediment Hydrocarbons as Indicators of Subsurface Hydrocarbons
method (Figure 15). The fluorogram signatures for
a regional-reference sample with low-interstitial
sediment gas, UCM, and TSF MFI; and within-seepzone sample with highly elevated interstitial sediment gas, UCM, and TSF MFI should have very
different shapes and locations of the maximum excitation wavelength (MFI Max Ex) and maximum
emission wavelength (MFI Max EM), yet they are
similar (Figure 15A, B). This indicates that the
fluorogram shape, MFI Max Ex, and MFI Max EM
may not assist in the identification of thermogenic
seepage in marine sediments.
KEY OBSERVATIONS
to ethane plus gases) results in background lowconcentration sediment gases having elevated wet gas
fractions. The fractionated samples are commonly
confused with migrated thermogenic hydrocarbons
(Abrams, 2005) because of the higher relative wet gas
component. Only the high-concentration samples are
likely to be derived from migrated thermogenic gas.
Compound-specific isotopic measurements are critical to confirm the thermogenic origin, assuming that
isotopically distinctive changes are present.
Many samples collected at within-seep-zone or
near-seep-zone targets identified by conventional
and high-resolution surface seismic data have only
low concentrations (background) of interstitial gas.
We believe that these samples did not hit the intended target or were collected within the ZMD.
Sediment Gases
The can headspace and disrupter extraction methods provide similar interstitial sediment gas data,
indicating that the disrupter plastic container with
screw cap and sealing gasket, built-in septum, and
blades to break up the sediment did not provide
significantly better results than the conventional
can headspace method. Both methods provide
highly variable gas compositions compared with
the Marco Polo reservoir gases. Very few of the
high-concentration within-seep-zone samples have
sediment gas compositions similar to the Marco
Polo reservoir gases. In contrast, the can headspace
and disrupter interstitial sediment gas compoundspecific isotopes are similar to the Marco Polo reservoir gases, except for the propane carbon isotope value. The propane isotopic values are much
heavier most likely because of preferential microbial alteration (James and Burns, 1984; Abrams,
1989, 2005). The bound gas extraction method
did not provide gas compositions or compoundspecific isotopes similar to the Marco Polo reservoir gases. This could be related to the bound gas
removal process, which may fractionate the sediment gas sample (Abrams and Dahdah, 2010).
Proper identification of anomalous versus background interstitial (free) sediment gas is required to
separate background samples that may seem to be
thermogenic because of phase fractionation. Phase
fractionation (preferential loss of methane relative
Gasoline-Range Sediment Hydrocarbons
Both the HSPME and Gore Module extraction
methods provide strong gasoline-range seepage signals for the high-concentration within-seep-zone
and near-seep-zone samples and minimal to no signal in the regional reference and low-concentration
within-seep-zone and near-seep-zone samples. The
Gore Module thermal extraction combined with
MS provides much greater compositional detail
than the HSPME GC-FID method.
The HSPME chromatograms show evidence
for significant near-surface microbial alteration. The
“lack” of an unaltered oil, even in zones of high
flux macroseepage, leads us to believe that the rate of
alteration is rapid. It is our belief that despite microbial alteration, gasoline-range hydrocarbons provide key information for a boiling point range not
examined in most offshore surveys, and this type of
data is very important to help identify subsurface
hydrocarbon generation (Abrams et al., 2009).
High-Molecular-Weight
Sediment Hydrocarbons
The within-seep-zone samples with elevated HMW
hydrocarbons (macroseepage) have extremely high
UCM values and a distinctive GC signature. The
regional reference samples have much lower UCM
Abrams and Dahdah
1925
Figure 10. (A) The headspace solid-phase microextraction (HSPME) data
for regional reference core.
(B) The HSPME data for
the within-seep-zone core.
with a different and distinctive GC signature. When
concentrations of migrated HMW hydrocarbon
are low relative to the in-situ ROM material, the
identification of migrated thermogenic hydrocarbons is difficult. Reworked or transported hydro1926
carbons can be confused with locally migrated
hydrocarbons (Abrams, 2005). Reworking and
transported hydrocarbons have been identified
within the Marco Polo Green Canyon area (Cole
et al., 2001; Dembicki, 2010).
Surface Sediment Hydrocarbons as Indicators of Subsurface Hydrocarbons
Figure 10. Continued.
The Marco Polo extract TSF data indicate that
MFI measurements provide information on the
presence of anomalous hydrocarbons, but TSF
fluorogram shapes do not change with target type
or other geochemical measurements (interstitial
gas, gasoline-range hydrocarbons, or extract UCM).
Edwards and Crawford (1999) demonstrated that
a linear relationship between oil concentration and
total fluorescence intensity can only be obtained
between 0.10 and 10 ppm oil. Within this range,
Abrams and Dahdah
1927
Figure 11. Three end-member
groupings defined by the Gore
Module data for the Marco Polo
calibration data set: (A–C) high
aliphatic, medium aliphatic, and
background.
fluorescence intensity is proportional to concentration, but outside this range, TSF fluorescence
intensity (MFI) and shape can vary because of the
dilution factor (hydrocarbon concentration). Other
factors that affect TSF fluorescence intensity (MFI)
and shape include absorbance (compounds in ex1928
tract that can absorb either excitation or emitted
light), quenching (energy can be transferred nonradiatively to coexisting molecules instead of being
emitted as fluorescence), and secondary alteration
(water washing, biodegradation, evaporative fractionation, and weathering).
Surface Sediment Hydrocarbons as Indicators of Subsurface Hydrocarbons
Figure 11. Continued.
CONCLUSIONS
The Marco Polo SGC and previous SGC laboratory studies provide a strong empirical data set to
evaluate surface geochemical methods used by
industry for marine surface geochemical surveys.
The Marco Polo SGC calibration data set demonstrates the importance of targeted coring and
sampling depth. To improve the detection of seabed migrated thermogenic hydrocarbon seepage,
core samples should be collected along major migration pathways (cross-stratal leakage features)
identified by conventional deep seismic and highresolution sea floor imaging technology. Not all
targeted cores will hit the designated feature, and
thus, collecting replicates along key migration features is recommended. Collecting sediment samples below the ZMD is also important to reduce the
transition zone alteration interference.
Figure 12. A plot of the Gore Module total reported hydrocarbons versus total disrupter headspace solid-phase microextraction
(HSPME) single carbon number (SCN) indicates that both gasolinerange sediment extraction methods provide similar results: strong
gasoline-range signals within the interstitial sediment gas highconcentration within-seep-zone and near-seep-zone samples and
minimal signal in the regional reference and interstitial sediment gas
low-concentration within-seep-zone and near-seep-zone targeted cores.
Abrams and Dahdah
1929
Table 6. Marco Polo Surface Geochemistry Calibration Extract Gas Chromatography and Total Scanning Fluorescence Data
Extract GC
Core ID
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
01
01
01
02
02
02
03
03
03
04
04
04
05
05
05
06
06
06
07
07
07
08
08
08
09
09
09
10
10
10
11
11
11
12
12
12
13
13
13
14
15
15
15
16
16
16
17
1930
Depth (cm)
Core Target
∑ n–Alkanes
UCM (mg/g)
UCM > n-C23 (mg/g)
Extract TSF
MFI
156
239
322
181
264
347
268
351
434
163
246
329
287
370
453
210
293
376
208
291
374
214
287
380
194
278
361
37
120
203
220
303
396
324
407
490
170
253
336
10
193
276
359
233
316
399
131
Regional reference
Regional reference
Regional reference
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Near seep zone
Near seep zone
Near seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
875
486
1841
1414
1209
1618
1037
1562
3044
1110
1233
1255
881
1953
1071
1120
833
2259
1216
996
2034
1260
0
0
1026
1269
1236
0
0
1508
0
0
2302
989
3869
2880
0
0
0
0
0
0
0
1098
935
1793
696
11
6
12
19
9
11
10
18
19
17
32
9
8
12
10
9
8
12
10
8
14
16
6359
3971
16
13
81
664
1070
20
322
941
63
17
26
17
2497
1130
224
3700
3660
3393
5254
20
10
19
16
7
5
8
16
8
9
9
16
13
13
21
7
6
8
8
7
6
9
8
7
11
12
4876
2815
11
9
55
399
598
15
264
469
28
14
22
14
1648
712
126
2456
2344
2265
3400
14
8
12
12
60,920
51,430
56,480
89,960
43,670
34,140
94,720
30,215
68,370
57,310
57,770
49,170
26,205
127,420
54,600
54,440
46,760
107,660
47,810
51,410
119,600
53,760
42,712,000
26,892,000
55,900
50,920
716,400
4,288,000
6,926,000
4,558,000
90,100
2,171,500
563,000
49,420
230,600
201,650
20,516,000
7,032,000
2,382,000
36,080,000
27,768,000
27,560,000
46,752,000
57,700
71,900
121,320
195,600
Surface Sediment Hydrocarbons as Indicators of Subsurface Hydrocarbons
Table 6. Continued
Extract GC
Core ID
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
EGI
17
17
18
18
18
19
19
19
20
20
20
21
21
22
22
23
24
24
24
25
25
25
26
26
26
27
27
27
28
28
28
29
29
29
30
30
30
31
31
31
32
32
32
33
33
33
Depth (cm)
Core Target
∑ n–Alkanes
UCM (mg/g)
UCM > n-C23 (mg/g)
Extract TSF
MFI
214
297
158
241
324
176
259
342
133
216
299
10
33
60
143
10
169
252
335
323
406
489
157
240
323
122
205
288
164
197
280
154
237
320
161
244
328
80
163
246
105
188
271
70
153
236
Near seep zone
Near seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Near seep zone
Near seep zone
Near seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Within seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Near seep zone
Regional reference
Regional reference
Regional reference
1194
988
1314
1293
979
1419
1661
3375
1364
2213
1240
0
0
54,864
0
0
1425
2048
3008
1382
2621
3720
1370
1397
827
958
1553
1133
1096
1140
1016
1243
1245
1157
1385
1446
1016
460
1211
1408
436
1367
1607
424
1467
1101
15
12
18
16
7
22
115
207
19
258
13
3537
7423
6754
2678
1983
11
10
32
15
12
27
24
13
6
19
16
11
14
16
9
19
15
12
24
15
10
8
17
11
9
20
13
18
22
14
10
9
13
14
7
17
100
139
14
228
10
3016
4789
4452
1745
1523
9
8
18
14
10
23
18
11
4
14
13
9
9
14
7
13
13
9
16
11
8
7
11
9
8
14
10
15
16
11
99,680
76,980
78,780
249,300
22,530
98,420
1,147,600
2,335,000
63,100
2,759,500
24,380
35,512,000
73,260,000
67,845,000
22,896,000
18,772,000
78,700
98,360
122,820
76,370
15,965
368,800
72,980
39,515
53,680
118,260
85,520
77,400
66,580
150,510
74,580
117,300
57,530
82,760
84,160
60,170
34,250
58,780
58,970
26,695
30,040
32,670
54,070
269,800
84,220
65,470
Abrams and Dahdah
1931
Figure 13. The Marco
Polo Surface Geochemistry Calibration (SGC) extract gas chromatograms.
(A) Upper: within seep
zone. (B) Lower: regional
reference.
Geochemical analysis should include a full range
of hydrocarbon types; light hydrocarbon gases (C1–
C5), gasoline range (C5–C10+), and HMW hydrocarbons (C15+).
1932
The two interstitial sediment gas extraction
methods, can headspace and disrupter, provide
similar results in both laboratory (Abrams and
Dahdah, 2010) and field calibration studies. The
Surface Sediment Hydrocarbons as Indicators of Subsurface Hydrocarbons
interstitial sediment gas data should be plotted on
a total hydrocarbon gas (S C1–C5) versus wet gas
fraction (S C2–C5/S C1–C5) chart to identify background, fractionated, and anomalous populations
(Abrams, 2005). The Marco Polo survey anomalous interstitial sediment gases have variable gas
compositions compared with the reservoir gases,
thus, caution should be used when plotting seabed
gases on conventional gas interpretation charts.
The methane and ethane stable carbon isotopes
from selected anomalous samples are similar to
the Marco Polo reservoir gases. However, propane
isotope values are much heavier, indicating that
propane is more easily modified by in-situ microbial alteration.
The microdesorption bound gases have gas
compositions and compound-specific isotopes unlike the Marco Polo reservoir gases. The microdesorption sediment gases tend to have more wet gas
fraction and highly variable methane carbon isotopes with heavier ethane carbon isotopes. The
SGC laboratory studies indicate that prewashing to
remove interstitial gases can have a major impact
on bound gas results (Abrams and Dahdah, 2010).
We do not recommend using bound gas extraction methods to evaluate subsurface hydrocarbons
based on the Marco Polo and previous laboratory
calibration studies reported in Abrams and Dahdah
(2010).
Figure 14. The extract gas chromatography (GC) total unresolved complex mixture (UCM) versus total scanning fluorescence
(TSF) maximum fluorescence intensity (MFI) plot demonstrates
relatively strong correlation between two high-molecular-weight
screening tools for Marco Polo extract GC and TSF data.
Figure 15. Fluorogram signatures for regional reference sample with low interstitial sediment gas, unresolved complex mixture
(UCM), and total scanning fluorescence (TSF) maximum fluorescence intensity (MFI); and within-seep-zone sample with highly
elevated interstitial sediment gas, UCM, and TSF MFI should not
have similar shapes and locations of maximum excitation wavelength (MFI Max Ex) and maximum emission wavelength (Max
EM). (A) Regional reference target EGI-1 (322 cm [127 in.]): MFI =
56,480 and DIL 1:10. (B) Within-seep-zone target EGI-22 (60 cm
[24 in.]): MFI = 67,845,000 and DIL 1:4000.
The gasoline-range analysis provides a new
range of hydrocarbons rarely examined in surface
geochemical studies. Both the HSPME and Gore
Module methods used in the Marco Polo calibration
studies provide strong gasoline-range seep signals
having useful information in the macroseepage
(high-flux) and microseepage (low-flux) seep sites.
The Gore Module thermal extraction combined
with MS provides more compositional detail than
the HSPME GC-FID method, which may be helpful to evaluate the seep hydrocarbon source and
maturity.
Extraction GC and TSF analyses provide information on the presence of HMW hydrocarbons
in the Marco Polo calibration survey. The GC
chromatogram signature and total UCM tracked
the migrated thermogenic hydrocarbon macroseepage but did not work as well with the low-level
Abrams and Dahdah
1933
microseepage samples. The TSF MFI data also directionally tracked migrated thermogenic hydrocarbon macroseepage and microseepage samples,
but the fluorogram shape could not distinguish
within-seep-zone and regional reference samples.
We do not recommend extraction TSF to evaluate migrated HMW hydrocarbons in near-surface
marine sediment seep surveys based on the above
results.
Follow-up studies by Dembicki (2010) with
Anadarko examined extract saturate and aromatic
fraction GC-MS to evaluate biomarker signature
variability. Results of Dembicki (2010) demonstrate the importance of biomarker data to assist in
detecting and interpreting low-concentration petroleum seepage (microseepage). Biomarker data
provide a means to characterize the ROM contribution and in turn allow for the identification
of thermogenic hydrocarbons when the seep oil
concentration is low relative to ROM.
The above conclusions are based on the Marco
Polo calibration study as well as previous laboratory calibration studies (Abrams et al., 2009; Logan
et al., 2009; Abrams and Dahdah, 2010). They
provide a framework to better understand how
best to collect and extract migrated hydrocarbons
from shallow-marine sediments and evaluate the
results. However, it is also very important to integrate sediment hydrocarbon results with basin
geology to fully understand how surface geochemistry observations relate to subsurface generation
and potential entrapment (Abrams, 2005). A fully
integrated evaluation provides the best petroleum
systems interpretation model.
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1935