Supplementary Information
A novel molecular index for secondary oil migration distance
Liuping Zhang1, Maowen Li2, Yang Wang3, Qing-Zhu Yin4, Wenzheng Zhang5
1
Key Laboratory of Petroleum Resource, Institute of Geology and Geophysics, Chinese
Academy of Science, 19 Beitucheng W. Road, Chaoyang District, Beijing 100029, China,
2
Sinopec Key Laboratory of Petroleum Accumulation Mechanisms, Sinopec Research
Institute of Petroleum Exploration and Production, 31 Xueyuan Road, Beijing 100083, China,
3
Department of Earth, Ocean and Atmospheric Science, Florida State University, and National
High Magnetic Field Laboratory, Tallahassee, FL 32306-4100, USA,
4
Department of Geology, University of California at Davis, One Shields Avenue, Davis, CA
95616, USA,
5
Changqing Oilfield Company, PetroChina, Xi’an, Shanxi 710021, China.
Correspondence and requests for materials should be addressed to L.Z.
([email protected])
Contents
Model for migration fractionation and source input influences……………..…………….1
Multiple charging and oil volume……………………………………….…………………...7
Supplementary data for the Xifeng Oilfield of the Ordos Basin…………………...…….11
Supplementary data for the Rimbey-Meadowbrook reef trend of the central
Alberta……………………………………………………….………………………………17
Figure S1 Cross plot of Pr/n-C17 vs. Ph/n-C18 ratio of the studied oil samples……………….12
Figure S2 Ternary diagram of 20R- and regular steranes of the studied oil samples.…..12
Figure S3 Variation in the T23/Hop and Ts/(Ts+Tm) ratios of the studied oils in the sand
body of the Xifeng Oilfield.……………………………….. ………………………………...….14
Figure S4 Variation in the aromatic hydrocarbon ratios of the studied oils in the sand
body of the Xifeng Oilfield.……………………………………………………………………...15
Figure S5 Schematic structural cross section showing the distribution of oil, gas and water
in the Leduc reefs of east-central Alberta……………………………………………………….18
Figure S6 Distributions of benzocarbazoles, SMFIs and ratios in the studied oils along
the Rimbey-Meadowbrook reef trend of the central Alberta…………………………………..21
Table S1 Saturate/aromatic hydrocarbon ratio and saturate GC data for the studied oil
samples from the Xifeng Oilfield……………………...……………………………………..23
Table S2 Molecular parameters calculated from the GC-MS analysis of the saturate
fractions for the studied oil samples in the Xifeng Oilfield………………………….……….24
Table S3 Molecular parameters and Ro(equiv.) calculated from the GC/MS analysis of the
aromatic hydrocarbon fractions for the studied oils in the Xifeng Oilfield……………...…...25
Table S4 Concentrations of carbazoles and ACA/ABCA ratio calculated from the GC-MS
analysis of the pyrrolic nitrogen fractions for the studied oil samples from the Xifeng
Oilfield………………………………….…... …………….…... …………….…..... ……….26
Table S5 Calculation results of constants in the model presented in this paper and MII
and MFCI values of the studied oils in the Xifeng Oilfield………………………….……….28
Table S6 Concentrations and ratio from the GC/MS analysis of the benzocarbazoles
for the studied oils in the Rimbey-Meadowbrook reef trend of the central Alberta……….…29
Table S7 Calculation results of constants in the model presented in this paper and MII and
MFCI values of the studied oils in the Rimbey-Meadowbrook reef trend of the central
Alberta…………………………………...………………………………….…...…………....30
References…………………………...………………………………….…...……..……....31
Model for migration fractionation and source input influences
The general advection-reaction-dispersion equation for the concentration variation of a
molecular compound in a liquid (herein petroleum) during migration in porous media can be
written as1,2
(nso C ) 
C

 (nso DL
)  (nso vC)  w
t
x
x
x
(S1)
where C =concentration of a compound (mg/cm3); t =time of liquid migration (year); x =
migration distance (km); v = liquid migration velocity (km/year); D L = dispersion coefficient
(km2/year); n =porosity of the carrier bed (%); so = oil saturation (%); w =concentration
variation arising from sorption, partition between petroleum and water, and chemical
reactions.
Dispersion in Equation (S1) includes molecular diffusion and mechanical dispersion
and can be expressed by DL  De   L v (where De is the effective molecular diffusion
coefficient, and  L the dispersivity)2. Carbazoles are large polar molecules (heavier than
160 Dalton). Their molecular diffusivities are very low in viscous oil in porous media,
especially in those with low porosity and permeability. Moreover, the molecular diffusion of
these large polar molecules is further diminished by strong sorption of these molecules with
their surrounding matrix3. In an interconnected oil reservoir, if molecular diffusion is efficient,
concentration differences of carbazoles would be erased. However, the observed large
concentration differences of these compounds suggest that molecular diffusion must be very
slow (Fig. 3). Therefore, molecular diffusion can be safely neglected4. Mechanical dispersion
arises from differences in microscopic migration velocities on pore scales. Under the
1
condition of slow migration, the effect of mechanical dispersion is smaller than that of
molecular diffusion1. Lateral migration is very slow, especially in cratonic basins such as the
Ordos Basin. Therefore, dispersion effect including molecular diffusion and mechanical
dispersion is neglected in this study.
For a uniform migration pathway, n , so and v are constant. Then, Equation (S1)
reduces to the following equation
C
C
w
 v

t
x ns o
(S2)
As discussed in the introduction of the paper, water soluble compounds are not suitable
for secondary migration studies. Polar organic compounds with very low solubility in water
must be selected. Under this condition, the partition effect between petroleum and water can
be omitted.
Secondary petroleum migration in carrier beds in the up-dip direction results in
decreases in temperature and this holds back, or slows down, the thermal evolution of oils.
Therefore, it is reasonable to assume that thermal evolution of oils ceases once they are
expelled from source rocks. In this scenario, we assume that only sorption occurs during
secondary migration. Then, w can be described as2
w

(n s  s F )
t
(S3)
where ns  1  n (%);  s = the density of solids (g/cm3); F = the amount of sorption
(mg/g).
Substitution of Equations (S3) into (S2) yields the advection-sorption equation:
C
C  ns  s F
 v
 (
)
t
x t nso
(S4)
2
Sorption of carbazoles in migration systems can approach equilibrium on geological
time scales4, as the low velocity of secondary petroleum migration allows sufficient time for
the establishment of at least local equilibrium5. Equilibrium sorption can be described by
either a linear isotherm model or non-linear isotherm models6. The linear isotherm model is
valid for natural systems where concentrations of adsorbable compounds are low enough
(details discussed in the paragraphs after Equation (S25)), and is represented by the following
equation2:
F  so K d C
(S5)
where K d = sorption coefficient (cm3/g).
Substitution of Equation (S5) into (S4) yields
C
C  ns so  s K d
 v
 (
C)
t
x t
nso
(S6)
Equation (S6) shows that the impact of oil saturation so is canceled from the
numerator and denominator in the last term. This illustrates that oil saturation does not need
to be considered for a uniform migration pathway. Assuming that (ns  s K d / n) does not
change with time during secondary petroleum migration, Equation (S6) can be rewritten as
(1 
ns  s
C
C
Kd )
 v
n
t
x
(S7)
Let
Rd  (1 
ns  s
Kd )
n
(S8)
where Rd is the retardation factor (a dimensionless parameter) under the condition of the
linear isotherm sorption2,7. Due to sorption, the migration velocity of an adsorbable
compound in oil ( vc ) becomes slower than the oil migration velocity ( v ). This phenomenon
can be described by the retardation equation7:
3
vc 
v
Rd
(S9)
It was the difference in migration velocity of various adsorbable compounds that
results in the migration fractionation of these compounds. As shown in Equations (S8) and
(S9), the larger the sorption coefficient ( K d ) of a compound, the slower its migration
velocity.
Substitution of Equation (S8) into (S7) yields
Rd
C
C
 v
t
x
(S10)
For the boundary condition, we have
C( x, t ) x0  C0 (t )
(S11)
where C0 (t ) is the initial concentration of a carbazole in oil at the filling point (i.e. start
point of secondary petroleum migration) and incorporates information on source inputs,
specifically the concentration of a carbazole generated from its source rock and any
fractionation during primary migration (expulsion). Concentration variations of carbazoles
from carbonate source rocks are clearly maturity related and are not an effect of primary
migration8-10 . The primary migration fractionation of carbazoles from clastic source rocks
may become significant. However, the primary migration fractionation index (the ratio of the
concentration at generating points to that at filling points) is nearly constant for a certain
compound, because the pathway of primary migration does not vary greatly with time in a
narrow Ro (vitrinite reflectance) range at the expulsion stage in a given region. Therefore,
the initial concentration of a carbazole in oil at the filling point, C0 (t ) , is dominantly
controlled by the maturity of the source. Concentrations of both alkyl- and benzocarbazoles
in source rock extracts vary steadily with maturity over the range of 0.45-1.3% in Ro 8. The
4
oils in the reservoirs close to source rocks can also provide information about the initial
concentrations. These oils still show steady variations over the Ro range of 0.49-0.92% (ref.
11). A quadratic equation can describe most of these variations and a cubic polynomial is
sufficient to describe the most complex ones. Over a narrow Ro (quiv.) range such as
0.7–0.8% (Ro~0.1%) in the Xifeng Oilfield (Table S3), the relationship between C0 (t )
and Ro (or Ro (equiv.)) becomes linear:
C0 (t )  a1 (1  a2 Ro )
(S12)
where Ro (a maturity variable) is a function of time for a given type of source facies, to
represent the values of both vitrinite reflectance and its calculated equivalent; a1 and a2
are constants. The parameter a1 (with a unit of mg/cm3) reflects geochemical processes of
hydrocarbon generation and fractionations in primary migration or migration before a
reference point, whereas a2 is a scaling factor, reflecting the rate of change of initial
concentration with Ro and is therefore dimensionless. If a2 >0, C0 (t ) increases with Ro ;
a2 <0, C0 (t ) decreases with Ro . If Ro changes over a larger range (Ro>>0.1%) a
quadratic of Ro (i.e. a4 Ro 2 , where a4 is a dimensionless constant) should be added in
the parentheses on the right hand side of Equation (S12).
Using the method of separation of variables12, let
C ( x, t )  T (t )  X ( x )
(S13)
Substitution of Equation (S13) into (S10) yields
 ln T (t )
v  ln X ( x)


t
Rd
x
(S14)
In Equation (S14), the left side is a function of time; the right side a function of migration
distance. Equation (S14) is valid only when both sides are equal to a constant12. Setting this
constant to  (with a unit of year-1), we can obtain
5
T (t )  e t  D1
(S15)
X ( x )  e  Rd   x / v  D2
(S16)
where D1 and D2 are dimensionless constants. Substituting Equations (S15) and (S16)
into (S13), we can obtain the solution to Equation (S10):
C ( x, t )  e t  Rd   x / v  H
(S17)
where H  D1  D2 . If   0 , then
C ( x, t )  C0 (t )  e H
(S18)
Yang et al (2005)4 tried to analyze factors influencing the distribution of phenol and
carbazole compounds but did not address source input influences. In their pivotal model
(Equation (33) in Yang et al. (2005)4), the tracer concentration during migration of large polar
compounds is constant and the same as the initial concentration at the filling point, which is
equivalent to Equation (S18) because H is a constant. However, in a natural migration
system, both C ( x, t ) and C0 (t ) are variable. Therefore,   0 .
From Equations (S11) and (S17), we get
C ( x , t )  C 0 ( t ) e a3 x
(S19)
Rd


v
vc
(S20)
where
a3  
The constant a3 (with a unit of km-1) controls the extent of migration fractionation.
Substitution of Equation (S12) into (S19) yields
C( x, t )  a1 (1  a2 Ro )e a3 x
(S21)
As defined in Equation (S12), Ro is a function of time for a given source facies. It is more
convenient to use Ro than time, as Ro data can be easily obtained from measuring the
6
reflectance of vitrinite in sediments (or solid bitumens in older Paleozoic successions that
lack vitrinite). For this reason, the above equation is rewritten as
C ( x, Ro )  a1 (1  a2 Ro )e a3x
(S22)
As sorption equilibrium is achieved during secondary migration5 and the thermal
evolution of the oil either stops or slows down after expulsion (if the basin does not subside
substantially), the present concentrations of a carbazole and Ro (equiv.) values of oils can be
used to represent C ( x, Ro ) and Ro values during secondary migration in Equation (S22).
In addition, concentration values with other units such as µg/g can be directly applied to
Equations (S21) and (S22), without any change of these equations.
Multiple charging and oil volume
The oil volume passing through a carrier bed is increased as a result of multiple charges.
Therefore, multiple charging changes the ratio of migrated oil volume to the carrier bed
volume, which has been interpreted to affect the applicability of carbazole distributions as
migration tracers11. We illustrate in the following that Equation (S22) is applicable to carrier
systems with multiple charging if appropriate compounds are selected, via linearization of the
Langmuir isotherm model.
The Langmuir isotherm model is adopted for sorption of a compound by natural solids
from a liquid7,13. In the derivation of the Langmuir model, the kinetic equation can be written
as13
dC
 k1C ( Fs  F )  s  k 2 F s
dt
(S23)
where k1 and k2 are the rate constants for sorption and desorption, respectively; Fs is the
7
sorption amount at saturation; F is defined in Equation (S3). At equilibrium,
dC
 0 and
dt
Equation (S23) reduces to the Langmuir isotherm model13:
F  Fs
bC
1  bC
(S24)
in which b  k1 / k2 . This isotherm model can also be written as
F  Fs bC (1 
F
)
Fs
(S25)
In the Langmuir model, the amount of sorption, F , increases linearly with increasing
solute concentration C at low surface coverages. In natural systems, Fs can be invariably
an order of magnitude greater than F , and in many cases, many orders of magnitude
greater13, when proper tracers are selected. Under this condition, Equations (S24) and (S25)
reduce to the linear isotherm model:
F  Fs bC  K d C
(S26)
We now examine the effect of multiple charging of petroleum in a carrier system. Fo
is defined as the amount of equilibrium sorption of a compound from the earlier charging
petroleum. At the beginning of the subsequent charging, the kinetic equation can be expressed
by
dC
 k1C ( Fs  Fo )  s  k2 Fo  s .
dt
(S27)
dC
 k1C ( Fs  Fe )  s  k2 Fe  s  0
dt
.
(S28)
At equilibrium
where Fe is the sorption amount at the equilibrium for the subsequent charging. Let
F  Fe  Fo
(S29)
Then
8
Fe  Fs bC (1 
Fo  F
)
Fs
(S30)
From Equation (S27), we can see that if Fo is close to Fs (approaching saturation),
additional sorption of the compound in the subsequent charge of petroleum would be
insignificant and unnoticeable, while desorption during the subsequent charging would
become significant. This phenomenon may also occur under the condition that the
concentration of a compound in the earlier charge is greater than that in the subsequent charge.
Therefore, in order to ensure sorption, adsorbable compounds with progressively increasing
concentrations in multiply charged petroleum system should be selected for secondary
migration study. But this condition is not sufficient. Only if C is always low enough in the
case of multiple charges of petroleum so that Fo , Fe and F are an order or many orders
of magnitude less than Fs , Equation (S30) becomes linear
Fe  Fs bC  K d C
(S31)
This equation is the same as Equation (S26), indicating that under this condition, one can
neglect the influence of the sorption from the former charging on the sorption in the
subsequent charging.
If petroleum is not saturated in porous media (i.e. so  100% ), Equation (S31)
becomes2
Fe  so K d C
(S32)
Equation (S22) is deduced from Equations (S4, S5 and S11) under the assumptions and
conditions mentioned above. As Equation (S32) is the same as (S5), Equation (S22) can also
be deduced from Equations (S4, S32 and S11) under the same assumptions and conditions.
Therefore, Equation (S22) can be applied to carrier systems with multiple charging, when
9
concentrations of the compounds used to study secondary migration are low enough to ensure
that the linear sorption isotherm model is valid. If C is not low enough, Equation (S22) may
not work even if oil charge is limited or oil volume is small.
It is important to select proper compounds for secondary migration study. There are
many adsorbable trace compounds in petroleum. Sorption of a trace organic compound may
be weakened by competitive sorption of other compounds with stronger sorption capabilities.
And if the concentrations of these other compounds with stronger sorption capabilities are
very high, their sorption may approach saturation. In this scenario, the sorption of a trace
organic compound with relatively weaker sorption capacity cannot be observed as if the
saturation of its sorption is approached. Thus, the compounds selected for secondary
migration study must have strong enough sorption capacities. However, if the sorption
capabilities of the selected compounds are too strong, their sorption can only be observed
over a very short distance of the migration pathway. Therefore, both sorption capacities and
concentrations of the compounds that may be used for a secondary migration study should be
compared with those of the other adsorbable compounds.
Properties of carrier systems can also affect sorption of polar organic compounds.
Sorption capabilities of carbazoles on minerals in carbonate reservoirs are very low compared
to those in clastic reservoirs14. Compounds with stronger sorption capacities should be
selected for secondary migration study in carbonate reservoirs in contrast to those in clastic
reservoirs. Therefore, properties of carrier systems, the compositions (including
concentrations) of adsorbable compounds in petroleum and their sorption capacities should all
be considered together in the selection of tracers, to ensure that Equation (S22) or its
10
equivalents are applicable.
In addition, the assumptions and conditions for establishing Equation (S22) or its
equivalent in the above also need to be considered in a secondary migration study. These
include: (1) solubilities of the large polar compounds in water must be very low; (2) thermal
evolution of oils expelled from source rocks ceases or slows down after expulsion (if the
basin does not subside substantially); (3) the primary migration fractionation index is nearly a
constant; (4) the relationship between Ro and the initial concentrations at the filling point or
reference point is linear or can be described by a quadratic equation; and (5) migration
pathways are nearly uniform or can be treated by dividing them into subsections with
constant properties.
Supplementary data for the Xifeng Oilfield of the Ordos Basin
Consistent source facies
Previous studies have demonstrated that the oils in the Xifeng Oilfield were derived
from the source rocks in the Chang 7 member15-19. The consistency in the source facies is
further examined here. Saturated hydrocarbons are the dominant components of the studied
oils, with similar n-alkane distribution patterns, carbon number ranges and pristane/phytane
ratios (Table S1). These features may indicate similar source facies, according to the criteria
established in Han and Calvin (1969)20 and Hwang et al. (2002)21. The trend in the Pr/n-C17
and Ph/n-C18 cross plot of the studied oils (Fig. S1) also illustrates that these oils are most
likely derived from the similar source facies with a mixing type of organic matter22-25. The
difference in Pr/n-C17 and Ph/n-C18 ratios with a trend toward the lower left of Fig. S1 are
11
probably a result of maturity change23,25. The relatively low Pr/Ph ratios of the studied oils
(0.5-1.0) indicate anoxic depositional environments of source rocks (Table S1).
100
Re
du
us
ne
uo
ali
n
s
g
i
rr
nd
II)
Te
II/I ne a
(
e
ri
ur
Ma
xt
i
M
0.1
n
II)
(I/
io
ct
n
0.01
I)
(II
io
0.1
y
at
1
r
rit
id
e
gh
Hi
tu
Ma
Ox
Pr/nC17
10
e
lak
1
10
Ph/nC18
Figure S1. Cross plot of Pr/n-C17 vs. Ph/n-C18 ratio of the studied oil samples (trend lines after
Peters et al. (1999)23 and Hanson et al. (2000)25).
20R-αααsteranes
regular steranes
Figure S2. Ternary diagram of 20R- and regular steranes of the studied oil samples.
Sterane distributions, which reflect variation in algal input to source rocks, are effective
source facies discriminators and are used routinely to group oils21. Homologous distributions
of steranes are often expressed in ternary plots to show similarity in source facies among the
12
oils of interest. The ternary plot of C27–C28–C29 20R-ααα and regular steranes from the Xifeng
Oilfield display very tight distributions (Table S2 and Fig. S2), demonstrating that these oils
were derived from the same source facies.
Gammacerane is thought to originate from phototrophic bacteria, which are generally
abundant in stratified, saline, lake environments26,27. The low gammacerane/hopane ratios of
the studied oils (Table S2) are consistent with freshwater depositional environments and are
consistent with these oils having been derived from the same source facies.
The molecular characteristics discussed above for the studied oils indicate that the
source facies are very consistent and thus there is no need to separate these oils into groups.
They also suggest that the source rocks with the organic matter of type II plus type III
kerogen in the Chang 7 member were deposited in a freshwater deep lacustrine environment,
which is in agreement with the results of Wang et al. (1995)15.
Thermal maturity
The maturity differences are not reflected by the sterane stereoisomer ratios of the
studied oils (i.e., C29 20S/(20R+20S) steranes, C29 αββ/(αββ+ααα) steranes, C29 diasteranes/
C29 regular steranes and C27/C29 steranes), as they have already reached equilibrium values
(Table S2). However, Ts/(Ts+Tm) and C23 tricyclic terpane/C30 hopane ratios of the oils (Fig.
S3) vary with relative distances (i.e. along the sand body of the Xifeng Oilfield), reflecting
changes in the thermal maturity level of the oils28,29. As shown in Fig. S3, large variations
occur at the relative locations from 51 to 62 km, in contrast with those in the 62 to 90 km
range. Aromatic hydrocarbon fractions of the oils also show the same maturity variation
13
trends (Fig. S4), including TA(I)/TA(I + II) triaromatic sterane and (dibenzothiophene +
methyl
dibenzothiophene)/
(phenanthrene+methylphenanthrene)
values
as
well
as
dibenzothiophene/ phenanthrene ratios.
0.20
0.7
Ts/(Ts+Tm)
T23/Hop
0.15
0.10
0.6
0.5
0.05
0.00
0.4
45
55
65
75
85
95
Relative distance (km)
45
55
65
75
85
95
Relative distance (km)
Figure S3. Variation in the T23/Hop and Ts/(Ts+Tm) ratios of the studied oils in the sand body of
the Xifeng Oilfield. T23/Hop: C23 tricyclic terpane/C30 hopane ratio; Ts: C27 18 trisnorneohopane;
Tm: C27 17 trisnorhopane.
To further constrain the thermal maturity range of the studied oils, we use
methylphenanthrene index (MPI-1)30-33 and dimethyldibenzothiophene (DMDBT) index34 to
estimate the maturity levels of the studied oils. In Fig. S4 and Table S3, R(MPI-1) values show a
remarkable decreasing trend at the locations from 51 to 62 km but a less pronounced change
with some scatter from 62 to 90 km. However, 4-MDBT/1-MDBT, 4,6-DMDBT/1,4-DMDBT
and TA(I)/TA(I + II) ratios at the locations from 62 to 90 km show clear variation trends (Fig.
S4), compared with R(MPI-1). Therefore, the relationship between 4,6-DMDBT/1,4-DMDBT
ratios and maturities, Ro (equiv.)= 0.14(4,6-DMDBT/1,4-DMDBT)+0.5734, was employed to
estimate the maturities of the studied oils. The calculated Ro (equiv.) values are in a narrow
range of 0.69 to 0.77% (Table S3), similar to R(MPI-1), but display a clear trend throughout the
Xifeng Oilfield (Fig. 2).
14
0.12
0.11
6.0
TDBT/TPH
TA(I)/TA(I+II)
8.0
4.0
2.0
0.07
65
85
105
Relative miragtion distance (km)
2.5
2.0 45
4,6-DMDBT/1,4-DMDBT
3.0 45
(2-+4-MDBT)/1-MDBT
0.09
0.08
0.0
2.0
1.5
1.0
0.5
65
85
105
Relative miragtion distance (km)
No.13
1.8
1.6
1.4
1.2
1.0
0.8
0.6
6.0 45
65
85
105
0.80 45
Relative miragtion distance (km)
5.0
65
85
105
Relative miragtion distance (km)
R(MPI-1) (%)
4-MDBT/1-MDBT
0.10
4.0
3.0
0.75
0.70
2.0
1.0
0.65
45
65
85
105
Relative distance (km)
45
65
85
105
Relative distance (km)
Figure S4. Variation in the aromatic hydrocarbon ratios of the studied oils in the sand body of the
Xifeng Oilfield. TA(I)/TA(I + II): C21+22/C21+22+26+27+28-triaromatic steranes; TDBT/TPH:
(dibenzothiophene+methyl
dibenzothiophene/(phenanthrene+methyl
phenanthrene);
MDBT:
methyl dibenzothiophene; DMDBT: dimethyl dibenzothiophene; R(MPI-1)= 0.60(MPI-1)+0.37;
MPI-1= 1.5(2-MP+3-MP)/(P+1-MP+9-MP)30; MP: methyl phenanthrene, P: phenanthrene.
The 4,6-DMDBT/1,4-DMDBT ratio of Sample No. 13 is extremely high but the other
maturity parameters do not show any abnormality at this location (Figs. S3 and S4). Thus, the
4,6-DMDBT/1,4-DMDBT ratio of this sample is considered an outlier and was not used to
calculate the Ro (equiv.) value. Instead, the Ro (equiv.) value of this sample was estimated
15
by using the regression equation shown in the upper part of Fig. 2 and the relative distance x
of this sample in Table S1. This regression equation was computed from the calculated
Ro (equiv.) values and relative distances of all samples (except Sample No. 13) at the relative
locations from 51 to 62 km.
The source rocks in the Chang 7 member have thermal maturities (represented by the
measured Ro values) of 0.75-0.96%19. The maturities calculated from both MPI-1 and 4,6DMDBT/1,4-DMDBT (Table S3) are slightly lower than the present kerogen vitrinite
reflectance of the source rocks. After oil was expelled from source rocks to shallow locations,
maturation of source rocks continued but maturation of the expelled oils would have stopped
or slowed down if the basin did not subside substantially. Therefore, the differences in
maturities between the oils and the source rocks support our assumption about thermal
evolution of oils and the migration from the source rocks to the reservoirs of the Xifeng
Oilfield.
Biodegradation level
Several authors have compiled a ‘quasi-stepwise’ sequence to describe the general order
of susceptibility of various biomarker compound classes to biodegradation, mostly following
the sequence: n-alkanes (most susceptible) > acyclic isoprenoids > steranes > hopanes >
diasteranes > aromatic steroids (least susceptible)27,35-37. The aliphatic hydrocarbons in the
Xifeng Oilfield are characterized by the presence of a full range of n-alkanes throughout the
reservoir (Table S1). The extent of biodegradation in the Xifeng Oilfield should be at level 0
on the biodegradation scale of Peters and Moldowan (1993)27 and the ultimate Manco
(Modular Analysis and Numerical Classification of Oils)38 numbers are 0.
16
At the molecular level, (Pr+Ph)/n-C17+18 and C30αβ hopane/(Pr+Ph) have been used to
quantitatively indicate the degree of biodegradation in petroleum. When the highly sensitive
biodegradation ratio (Pr+Ph)/n-C17+18 exceeds 2, it is indicative of significant biodegradation
of carbazoles; while the C30 αβ hopane/(Pr+Ph) ratio, when > 5, indicates that alkylcarbazoles
may have been affected by biodegradation39. As the (Pr+Ph)/n-C17+18 and C30αβ
hopane/(Pr+Ph) ratios of the studied oils are less than 0.6 and 0.2, respectively (Tables S1 and
S2), the biodegradation effect on carbazoles is considered to be negligible.
Supplementary data for the Rimbey-Meadowbrook reef trend of the central
Alberta
The petroleum reservoirs along the Rimbey-Meadowbrook reef trend belong to the Late
Devonian Woodbend Group (Fig. S5). It consists of, in ascending order, a thick sequence of
shallow water platform carbonates (Cooking Lake Formation), numerous platform margin
reef buildups (Leduc Formation), and basin-filling shales and limestones (Duvernay and
Ireton Formations). The Cooking Lake and Leduc Formations along the central core of the
reef trend are extensively dolomitized, and thus the Leduc biohermal buildups are connected
to the underlying Cooking Lake aquifer to a varying extent40,41. The Duvernay Formation, one
of the most important sources of conventional oil within the Alberta portion of the Western
Canada Sedimentary Basin, is thought to be the source for all of the oils in Leduc and Nisku
reservoirs along the Rimbey-Meadowbrook reef trend42,43. The stratigraphic association also
illustrates that the crude oils along this reef trend are derived from Duvernay source rocks, as
no other prolific sources are present in the area which could contribute significantly to Leduc
17
reservoirs (Fig. 2 in Li et al., 1998)44. The Duvernay Formation comprises two principal
interbedded lithofacies: (1) nodular to nodular-banded lime mudstones that exhibit varying
degrees of bioturbation and indicate relatively oxygenated conditions in the water column and
sediments, and (2) laminated lime mudstones that contain fine carbonate material and organic
rich layers (up to 20% total organic carbon) deposited in deep water, euxinic conditions28,45.
Figure S5 Schematic structural cross section showing the distribution of oil, gas and water in the
Leduc reefs of east-central Alberta44.
Oil and gas along the Rimbey-Meadowbrook reef trend are found in both Leduc and
Nisku reservoirs. The preproduction distribution of oil and gas along the reef trend shows two
general patterns (Fig. S5): (1) gas is in general present in the more down-dip reservoirs
(Homeglen-Rimbey to Bonnie Glen) while oil is present in up-dip reservoirs (Acheson, Big
Lake and St. Albert); (2) most of the down-dip reservoirs are filled to their spill points (from
Homeglen-Rimbey to Bonnie Glen). It was these two general patterns that formed the key
18
evidence for the Gussow Theory of differential entrapment involving long distance
migration46-48 , which explains why gas is preferentially trapped close to the hydrocarbon
source kitchen while oil is preferentially trapped along the basin margins. This theory is
considered important in petroleum geology, but is still being debated as there are
discrepancies between the hydrocarbon distributions observed in this reef trend and those
predicted by the differential entrapment model44. Several researchers have proposed concepts
such as "leaky pipeline"49 and "leaky caprock"50 to explain why certain reservoirs do not
contain an expected gas cap or are not filled to their spill points. However, their evidence is
not sufficient to support the Gussow Theory because definitive migration fractionations
related to secondary petroleum migration of long distance along the reef trend have not been
demonstrated for most oils.
The oil samples were collected along the reef trend and analyzed using the same
methods as in the Xifeng Oilfield. The oils along the trend clearly fall into two subfamilies as
shown in the C23 tricyclic terpane/hopane-Ts/(Ts + Tm) plot (Fig. 6 in Li et al., 1998)44. In this
study, we focused on the second subfamily as it contains most of the oils in the trend and
there are no clear relationships of either the concentrations or the ratios of carbazoles with
relative migration distances. To ensure the consistency of source facies, we re-examined the
geochemical data and found that four samples (Nos. 868, 1824, 869 and 867 in Table 4 in Li
et al. (1998)44) of this subfamily had extremely high C23 tricyclic terpane/hopane ratios. These
four samples are thus excluded from the second subfamily. The remaining samples of this
subfamily are listed in Table S6 with their equivalent vitrinite reflectance values calculated
from MPI-130.
19
There are two possibilities regarding the secondary migration of the oils in the
build-up44: the first one is that the petroleum in this trend came from the adjacent source rocks
in the Duvernay Formation; the second is that the petroleum accumulated as the result of long
distance migration from the source kitchen in the Duvernay Formation located to the south
west of the Rimbey-Meadowbrook reef trend. The Ro (equiv.) values of the studied oils in
Table S6 and the data in Stoakes and Creaney (1984)49 illustrate that the studied oils came
from the mature Duvernay source zone. But the source rocks close to these reservoirs or at the
depths equivalent to the petroleum reservoirs are immature for hydrocarbon generation8,44.
Therefore, the clear difference in maturity between the oils in this buildup and the adjacent
source rocks suggests that they were not sourced locally.
To investigate the second possibility concerning the secondary migration of the studied
oils, we calculated the relative migration distance. The deepest reservoir at the southwest end
of the reef trend, Rimbey, was used as the reference point (Fig. S5). The relative distances of
petroleum migration in the reef trend were determined using the map distance of each trap to
the reference point and are shown in Table S6.
Sorption capabilities of carbazoles in carbonate reservoirs are very low compared to
clastic reservoirs14. Benzocarbazole data of these oils (shown in Table S6) were re-examined
in this paper as benzocarbazoles are much more easily adsorbed than alkylcarbazoles51. The
concentrations of benzocarbazoles appear to decrease with increasing relative distance of
secondary migration (Fig. S6) but their correlation coefficients are very low. The
benzo[a]carbazole/benzo[c]carbazole ratio is expected to decrease with increasing migration
distance for net migration fractionation because of preferential removal of the more
20
rod-shaped benzo[a]carbazole relative to the sub-spherical benzo[c]carbazole due to selective
sorption of benzocarbazoles from the oil onto minerals in the carrier bed 52. However, the
correlation coefficient of this ratio with relative distance is very low. The maturity values of
these oils also decrease with relative distance (Table S6). Therefore, it is difficult to directly
determine whether the concentration variation of benzocarbazoles along the reef trend arises
from migration fractionation or from maturity variation, solely based on distributions of
benzocarbazole concentrations and/or their ratio.
10
Y = 32.2e
R2 = 0.46
-0.0068X
10
Y = 18.2e
2
R = 0.40
Y = 1.78e
R2 = 0.15
100
150
200
250
Relative distance (km)
10
Y = 102.6e
R2 = 0.88
-0.0083X
1
0
50
100
150
200
Relative distance (km)
250
-0.0017X
0.1
100 0
50
100
150
200
250
10 0
Relative distance (km)
50
100
150
200
250
Relative distance (km)
[a]/[c]BCA SMFI
50
1
-0.0051X
1
100 0
SMFI of Benzo[c]carbazole(%)
SMFI of Benzo[a]carbazole(%)
1
10
[a]/[c]BCA
100
Benzo[c]carbazole(μg/g)
Benzo[a]carbazole(μg/g)
100
10
Y = 98.8e -0.0048X
R2 = 0.63
1
1
Y = 1.04e -0.0035x
R2 = 0.46
0.1
0
50
100
150
200
Relative distance (km)
250
0
50
100
150
200
250
Relative distance (km)
Figure S6. Distributions of benzocarbazoles, SMFIs and ratios in the studied oils along the
Rimbey-Meadowbrook reef trend of the central Alberta. [a]/[c]BCA: benzo[a]carbazole/
benzo[c]carbazole; SMFI：secondary migration fractionation index; [a]/[c]BCA SMFI: ratio of
SMFI of benzo[a]carbazole to SMFI of benzo[c]carbazole. Y-axis scales are kept the same to
illustrate the improvement of fit (R2 values). All the regression lines were obtained by only using
the actually data points without forcing through the reference point. Therefore, they are derived
only from the data.
Because of the large variations in maturity (0.68-0.87%Ro in Table S6), a quadratic
( a4 Ro 2 ) were added into the parentheses in Equations (S12) and (1), and Equations (2-4) are
adjusted accordingly. The non-linear regression analyses were conducted for the constants in
our model and then maturity influence index were calculated. Maturity influence index can
21
reach 85.8% (Table S7), showing a strong influence of maturity. Thus, the SMFIs of
benzocarbazoles were calculated for these oils and the results are listed in Table S6. Fig. S6
shows that both SMFIs and their ratio are significantly correlated with the relative distance.
These demonstrate that most of the oils in the trend migrated long distances from the source
kitchen along the Rimbey-Meadowbrook reef trend in the up-dip direction. This is in good
agreement with the results of oil-source correlation study including maturities8,44. The slope
coefficients in Fig. S6 are lower than those in Fig. 4, which could be explained by the fact
that carbazoles have lower sorption capabilities in carbonate reservoirs than in clastic
reservoirs.
The Rimbey-Meadowbrook reef trend is a classical example used by Gussow (1954)47
to develop his theory of differential petroleum entrapment involving long distance migration
in the up-dip direction. The SMFI and maturity data of the reef trend constitute the basic
evidence for the Gussow Theory and thus indicate that this theory is generally applicable,
because the oils in the up-dip direction in general have longer implied migration distances as
demonstrated in Fig. S6. The "leaky pipeline"49 and "leaky caprock"50 concepts explain
specific discrepancies between the hydrocarbon distributions observed in this reef trend and
those predicted by the differential entrapment theory. These various lines of evidence support
that the Gussow principle is reasonable and can be used to guide the exploration of petroleum
accumulation fairways.
22
Supplementary Tables
Table S1 Saturate/aromatic hydrocarbon ratio and saturate GC data for the studied oil samples from the Xifeng Oilfield*.
Sample
No.
Well
Depth
RD(km)
1
2
3
X130
D68-54
D58-70
1303.36
1268.02
1325.93
89.85
4
5
6
7
X44-039
X161
X110
X33-26
1278.10
1352.32
1365.11
1387.71
8
9
10
11
X34-023
X28-09
X167
X28-8
1397.27
1409.62
1395.71
1392.21
12
13
14
15
16
17
18
19
X27-17
X27-23
X26-28
X21-25
X30-34
X33-39
X27-35
X29-43
1397.69
1401.56
1406.91
1433.08
1289.22
1407.41
1427.83
1437.54
87.48
84.02
82.59
82.19
78.76
74.54
73.82
67.28
63.79
61.93
59.28
57.26
55.31
54.97
54.58
53.92
53.59
51.48
Sat
Crange
Arom
Cmax
nC 21nC 22
1.71
2.29
1.58
11-34
11-31
11-32
20
20
20
1.45
1.44
1.49
2.31
2.64
1.93
1.41
11-31
11-32
11-32
11-34
19
20
20
19
2.30
1.82
2.65
2.31
11-31
11-33
11-31
11-32
1.63
1.22
1.27
2.60
1.82
1.55
1.96
2.51
11-31
11-33
11-32
11-31
11-31
11-32
11-31
11-32
nC 21 22
nC 28 29
Ph/nC18
Pr  Ph
nC1718
OEP
CPI
Pr/Ph
Pr/nC17
2.18
2.19
2.29
1.02
1.01
1.00
1.09
1.14
1.14
0.901
0.901
0.938
0.452
0.446
0.431
0.504
0.471
0.441
0.478
0.459
0.436
1.41
1.40
1.38
1.44
2.19
2.10
2.16
2.02
1.00
1.02
1.00
0.99
1.12
1.11
1.11
1.13
0.942
0.927
0.915
0.956
0.448
0.439
0.449
0.427
0.451
0.463
0.491
0.436
0.450
0.451
0.470
0.432
19
20
19
20
1.42
1.48
1.45
1.43
2.11
2.15
2.13
2.11
1.01
1.03
1.01
1.03
1.12
1.14
1.10
1.11
0.930
0.724
0.910
0.912
0.419
0.472
0.394
0.391
0.447
0.633
0.431
0.423
0.433
0.554
0.412
0.407
20
20
18
20
19
19
18
20
1.49
1.58
1.61
1.59
1.54
1.43
1.74
1.63
2.28
2.29
2.34
2.36
2.37
1.96
2.50
2.34
1.03
1.01
1.01
1.01
1.00
1.00
1.01
1.01
1.12
1.10
1.10
1.12
1.11
1.10
1.11
1.09
0.915
0.917
0.938
0.923
0.942
0.936
0.957
0.934
0.361
0.348
0.335
0.344
0.343
0.334
0.336
0.324
0.392
0.365
0.344
0.368
0.365
0.361
0.339
0.334
0.376
0.357
0.340
0.356
0.354
0.348
0.337
0.329
*GC: gas chromatography; Depths are in meters below sea level. RD: Relative migration distance; Sat/Arom: ratio of saturates/aromatic hydrocarbons; Crange: distribution
range of n-alkanes; Cmax: the n-alkane with the max peak area; nC21-/nC22+ = ≤C21 n-alkanes /≥C22 n-alkanes; nC21+22/nC28+29 = (nC21+ nC22)/( nC28+ nC29); OEP =
[Ci+6Ci+2+Ci+6)/ (4Ci+1+4Ci+3)](-1)i+1, i= 24-34，i+2= Cmax; CPI = {(C25+C27+C29+C31+C33) [1/(C24+C26+C28+C30+C32)+1/(C26+C28+C30+C32+C34)]}/2; Pr: Pristane; Ph:
Phytane.
23
Table S2
Molecular parameters calculated from the GC-MS analysis of the saturate fractions for the studied oil samples in the Xifeng Oilfield*.
% 20R-ααα Steranes
% Steranes
Sample
No.
Well
1
2
3
20S
20R


Dia
Reg
Hop
St
T23
Hop
Ts
Ts  Tm
Gam
Hop
C30H
Pr  Ph
C27
C28
C29
C27
C28
C29
X130
D68-54
D58-70
30.96
30.19
33.87
29.87
29.84
28.85
39.17
39.97
37.28
41.44
43.00
42.23
27.01
25.69
26.55
31.55
31.31
31.22
0.478
0.465
0.452
0.588
0.620
0.605
0.111
0.101
0.096
7.62
7.59
7.08
0.074
0.063
0.071
0.505
0.511
0.512
0.054
0.066
0.060
0.091
0.110
0.098
4
5
6
7
8
9
10
11
X44-039
X161
X110
X33-26
X34-023
X28-09
X167
X28-8
30.47
30.97
29.70
31.05
30.67
31.09
31.81
30.70
29.21
29.22
29.76
29.57
30.44
29.39
29.58
29.20
40.33
39.82
40.54
39.38
38.89
39.52
38.62
40.10
41.83
41.42
40.32
41.11
41.41
43.34
41.36
41.44
25.92
25.61
27.15
26.45
26.67
26.51
26.71
26.01
32.25
32.97
32.53
32.44
31.91
30.16
31.92
32.55
0.466
0.447
0.474
0.443
0.447
0.481
0.458
0.454
0.608
0.613
0.604
0.596
0.589
0.605
0.607
0.602
0.099
0.110
0.094
0.157
0.125
0.108
0.098
0.105
7.64
7.89
7.26
6.49
7.12
5.61
6.88
6.92
0.067
0.064
0.067
0.082
0.075
0.073
0.076
0.078
0.519
0.487
0.499
0.505
0.513
0.448
0.511
0.516
0.067
0.063
0.062
0.061
0.061
0.056
0.068
0.067
0.108
0.116
0.102
0.086
0.096
0.090
0.094
0.086
12
13
14
15
X27-17
X27-23
X26-28
X21-25
30.86
33.15
30.37
30.57
29.27
28.41
30.00
29.56
39.88
38.44
39.63
39.87
41.73
40.33
40.83
40.07
25.91
25.89
25.51
25.15
32.35
33.79
33.66
34.78
0.450
0.449
0.448
0.445
0.591
0.580
0.586
0.585
0.111
0.129
0.130
0.140
5.27
4.39
5.09
5.12
0.107
0.122
0.126
0.111
0.538
0.577
0.597
0.567
0.071
0.068
0.074
0.078
0.058
0.041
0.039
0.046
16
17
18
19
X30-34
X33-39
X27-35
X29-43
32.62
34.21
30.12
31.24
29.36
28.62
30.60
29.98
38.02
37.17
39.28
38.78
42.16
43.03
40.69
42.17
25.74
25.73
26.36
25.90
32.10
31.24
32.95
31.92
0.435
0.464
0.450
0.431
0.589
0.590
0.591
0.610
0.153
0.132
0.127
0.142
4.69
4.67
4.69
4.78
0.146
0.137
0.142
0.135
0.620
0.627
0.615
0.627
0.071
0.071
0.079
0.076
0.038
0.037
0.037
0.033
*GC gas chromatography; MS: mass spectrometry; 20S/20R: C29 20S/(20R+20S) steranes; αββ/ααα: C29 αββ/(αββ+ααα) steranes; Dia/Reg: C29 diasteranes/C29 regular steranes;
Reg/Hop: regular steranes/hopanes; Hop/St: hopanes(C27-35)/Steranes (C27-29); Ts/(Ts+Tm): C27 18 trisnorneohopane/(C27 18 trisnorneohopane + C27 17 trisnorhopane); T23/Hop:
C23 tricyclic terpane/C30 hopane ratio; Gam/Hop: gammacerane / αβ-C30 hopane; C30αβH: C30αβHopane.
24
Table S3 Molecular parameters and Ro(equiv.) calculated from the GC-MS analysis of the aromatic hydrocarbon fractions for the studied oils in the Xifeng
Oilfield*.
Sample
No.
Well
MPI-1
MPI-2
R(MPI-1)
TDBT
TPH
2 - 4 - MDBT
1 - MDBT
4 - MDBT
1 - MDBT
2,4 - DMDBT
1,4 - DMDBT
4,6 - DMDBT
1,4 - DMDBT
TA(I)
TA(I  II)
(equiv.)
1
2
3
X130
D68-54
D58-70
0.528
0.547
0.557
0.530
0.594
0.588
0.687
0.698
0.704
0.078
0.085
0.092
1.154
1.573
1.503
2.37
2.68
2.61
0.649
0.801
0.698
0.842
0.902
0.854
0.582
0.638
0.745
0.688
0.696
0.690
4
5
6
7
X44-039
X161
X110
X33-26
0.539
0.535
0.568
0.533
0.564
0.556
0.602
0.546
0.693
0.691
0.711
0.690
0.079
0.097
0.093
0.089
1.035
1.494
1.609
1.350
2.76
2.38
2.57
2.70
0.707
0.702
0.719
0.753
0.836
0.902
0.907
0.952
0.764
0.775
0.794
0.920
0.687
0.696
0.697
0.703
8
9
10
11
X34-023
X28-09
X167
X28-8
0.520
0.543
0.571
0.589
0.522
0.561
0.596
0.614
0.682
0.696
0.713
0.724
0.089
0.096
0.086
0.099
1.326
1.517
1.587
1.619
2.65
2.54
3.05
2.83
0.651
0.733
0.684
0.749
0.879
0.938
0.880
1.003
0.923
0.741
1.007
1.301
0.693
0.701
0.693
0.710
12
13
14
15
16
17
18
19
X27-17
X27-23
X26-28
X21-25
X30-34
X33-39
X27-35
X29-43
0.596
0.635
0.611
0.605
0.628
0.622
0.619
0.640
0.626
0.675
0.623
0.630
0.655
0.645
0.649
0.659
0.727
0.751
0.737
0.733
0.747
0.743
0.741
0.754
0.098
0.103
0.102
0.095
0.105
0.103
0.099
0.108
2.091
2.297
2.353
2.268
2.296
2.129
2.362
2.539
3.49
4.01
4.36
4.48
4.14
3.86
4.32
4.84
0.784
1.283
0.931
0.932
0.965
0.885
0.916
1.009
1.130
1.730
1.321
1.349
1.283
1.292
1.336
1.439
1.747
3.095
9.695
4.644
2.950
3.252
6.275
6.183
0.728
0.812
0.755
0.759
0.750
0.751
0.757
0.771
*GC:
gas
chromatography;
MS:
mass
spectrometry;
MPI-1=1.5(2-MP+3-MP)/(P+1-MP+9-MP);
P:
phenanthrene;
MP:
methyl
Ro
phenanthrene;
MPI-2=3(2-MP)/(P+1-MP+9-MP); R(MPI-1)=0.6(MPI-1)+0.37; TDBT/TPH: (dibenzothiophene+methyldibenzothiophene)/(phenanthrene+methylphenanthrene); MDBT:
methyl
dibenzothiophene;
DMDBT:
dimethyl
dibenzothiophene;
TA(I)/TA(I
34
0.14(4,6-DMDBT/1,4-DMDBT)+0.57 ; Ro (equiv.): vitrinite reflectance equivalent.
25
+
II):
C21+22/C21+22+26+27+28-triaromatic
steranes;
Ro(equiv.)=
Table S4 Concentrations of carbazoles and ACA/ABCA ratio calculated from the GC/MS analysis of the pyrrolic nitrogen fractions for the studied oil samples from
the Xifeng Oilfield*.
No.
Wells
CA
1-MCA
4-MCA
1,2-DMCA
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
X130
D68-54
D58-70
X44-039
X161
X110
X33-26
X34-023
X28-09
X167
X28-8
X27-17
X27-23
X30-34
X33-39
X26-28
X21-25
X27-35
X29-43
n.d.
0.31
0.15
0.21
0.20
n.d.
0.66
0.35
0.86
0.42
0.65
0.41
0.33
0.60
0.55
0.65
0.53
0.70
1.35
1.84
1.75
1.37
1.77
1.35
1.25
4.28
2.62
3.08
3.22
3.74
3.50
3.99
4.64
4.18
4.87
4.67
4.82
6.35
0.52
0.85
0.65
0.82
0.70
0.57
1.47
1.09
1.31
1.54
1.89
2.01
2.15
2.42
2.23
2.47
2.29
2.41
2.92
0.29
0.66
0.51
0.69
0.48
0.44
1.56
0.90
1.07
1.23
1.66
1.44
1.63
1.66
1.48
1.93
1.51
1.64
2.07
1,3-DMCA
2.37
3.49
3.08
3.42
3.10
2.84
7.02
4.85
3.96
5.94
6.44
7.05
8.06
8.22
7.19
8.30
7.71
8.09
9.26
1,4-DMCA
2.52
3.57
3.32
3.64
3.11
3.30
6.39
4.69
3.36
5.83
6.21
7.15
8.87
8.93
7.76
8.04
8.18
8.85
9.53
1,5-DMCA
2.40
4.08
3.26
4.09
3.26
3.30
8.02
5.24
4.56
7.06
7.41
8.22
9.98
9.27
9.21
10.03
10.00
10.38
11.40
1,6-DMCA
1,7-DMCA
1,8-DMCA
1.60
2.70
2.23
2.74
2.22
2.01
5.77
3.69
4.04
4.70
5.35
5.14
6.40
6.32
5.67
7.18
6.09
6.32
7.48
1.37
3.00
2.39
2.95
2.28
1.94
6.53
3.90
4.78
4.84
6.15
5.72
6.93
7.21
6.39
7.92
6.85
7.59
8.17
3.58
5.06
4.47
5.02
4.33
4.36
10.02
6.62
4.83
8.16
8.09
10.05
12.26
11.93
10.14
11.20
11.31
12.52
13.31
*ACA/ABCA: alkyl carbazoles/(alkyl- +benzocarbazoles) ratio; GC gas chromatography; MS: mass spectrometry; the unit of concentrations: μg/g; CA, MCA, DMCA,
TMCA: carbazole, methyl-, dimethyl- and trimethyl-carbazoles, respectively; n.d.: no data/below detection limits.
26
Table S4 (continued).
No.
Wells
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
X130
D68-54
D58-70
X44-039
X161
X110
X33-26
X34-023
X28-09
X167
X28-8
X27-17
X27-23
X30-34
X33-39
X26-28
X21-25
X27-35
X29-43
2,3-DMCA
0.13
0.14
0.15
0.16
0.13
0.21
0.30
0.24
0.53
0.48
0.70
0.44
0.44
0.63
0.70
0.95
0.52
0.48
0.76
2,4-DMCA
2,5-DMCA
2,6-DMCA
2,7-DMCA
3,4-DMCA
TMCA-A
TMCA-B
TMCA-C
ACA/BCA
0.71
1.29
0.88
1.12
0.99
0.84
2.55
1.52
1.43
2.05
2.54
2.49
3.09
2.74
2.69
3.46
2.73
2.96
3.61
0.69
1.40
1.08
1.36
1.04
0.89
2.89
1.75
1.97
2.24
3.01
2.85
3.36
3.17
2.90
3.96
3.05
3.21
4.06
0.17
0.50
0.37
0.61
0.38
0.24
1.12
0.73
1.71
1.08
1.62
0.99
1.16
1.38
1.32
2.00
1.23
1.29
1.96
0.68
1.46
1.06
1.44
1.15
1.00
2.92
1.73
3.72
2.69
3.12
2.67
3.43
3.43
3.27
4.18
3.19
3.55
4.44
0.15
0.49
0.21
0.22
0.21
0.39
0.86
0.33
0.22
0.80
0.59
0.50
1.30
1.15
1.15
1.34
0.53
0.66
1.38
11.92
17.64
16.52
18.83
15.87
15.93
29.72
20.93
14.23
25.62
24.99
30.45
38.27
35.93
31.38
32.65
33.31
39.07
38.92
8.06
14.23
13.21
14.66
12.38
11.59
24.58
16.42
14.82
21.21
23.17
24.63
31.34
28.52
25.33
29.86
27.45
29.59
33.42
1.24
2.82
2.69
3.43
2.76
2.56
5.15
3.66
5.31
4.84
5.80
5.39
7.01
6.21
5.68
7.62
5.85
6.09
7.59
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
0.991
1.000
0.999
1.000
0.999
1.000
0.999
0.999
1.000
1.000
1.000
27
Table S5 Calculation results of constants in the model presented in this paper and MII and MFCI values of the studied oils in the Xifeng Oilfield*.
Alkylcarbonzoles
ln C  ln[ a1 (1  a2 Ro )]  a3 x
RD from 51 to 62 km
RD from 62 to 90km
a1
a2
a3
MIImin
MIImax
MIImean
MFCImean
MIImin
MIImax
MIImean
MFCImean
1-MCA
4-MCA
1,2-DMCA
1,3-DMCA
1,4-DMCA
1,5-DMCA
1,6-DMCA
1,7-DMCA
1,8-DMCA
2,3-DMCA
2,4-DMCA
2,5-DMCA
2,6-DMCA
2,7-DMCA
3,4-DMCA
TMCA-A
TMCA-B
TMCA-C
0.70
1.19
91.66
7.15
1.00
16.57
86.60
143.41
1.14
70.13
0.47
50.60
304.78
196.16
0.51
3.06
3.05
245.08
49.93
20.72
-1.00
6.00
51.17
3.49
-0.62
-0.72
59.99
-1.07
52.85
-0.57
-1.15
-1.02
20.02
50.02
50.02
-1.02
-0.032
-0.039
-0.047
-0.029
-0.029
-0.033
-0.036
-0.040
-0.028
-0.056
-0.034
-0.039
-0.060
-0.046
-0.040
-0.023
-0.026
-0.040
19.52
16.18
32.50
18.32
21.25
14.86
15.99
18.64
21.68
34.11
18.55
13.28
41.94
34.43
15.65
25.32
23.09
37.27
20.42
16.93
36.45
19.04
22.21
15.40
16.67
19.69
22.66
39.50
19.42
13.79
51.12
38.81
16.38
26.40
24.10
41.66
19.95
16.54
34.48
18.66
21.71
15.12
16.34
19.17
22.15
36.78
18.96
13.54
46.41
36.62
16.00
25.84
23.57
39.46
80.05
83.46
65.52
81.34
78.29
84.88
83.66
80.83
77.85
63.22
81.04
86.46
53.59
63.38
84.00
74.16
76.43
60.54
2.11
1.68
3.31
1.93
2.34
1.50
1.47
1.74
2.40
3.42
1.98
1.19
4.37
3.57
1.62
2.92
2.60
4.03
2.18
1.73
3.57
1.98
2.42
1.53
1.51
1.80
2.48
3.76
2.05
1.22
4.99
3.86
1.67
3.02
2.68
4.35
2.15
1.71
3.41
1.96
2.39
1.52
1.48
1.76
2.45
3.55
2.02
1.20
4.60
3.68
1.65
2.98
2.65
4.15
97.85
98.29
96.59
98.04
97.61
98.48
98.52
98.24
97.55
96.45
97.98
98.80
95.40
96.32
98.35
97.02
97.35
95.85
EDMCA sum
430.44
-0.82
-0.044
22.23
23.88
23.06
76.94
2.11
2.21
2.15
97.85
PEDMCA sum
52.22
4.70
-0.032
16.36
16.99
16.66
83.34
1.68
1.72
1.71
98.29
*RD: relative migration distance; MII: maturity influence index (%) calculated from Equation (3); MFCI: migration fractionation contribution calculated from 100-MII (%).
The units of a1 and a3 are μg/g and km-1 respectively; a 2 is a dimensionless constant.
28
Table S6 Concentrations and ratio from the GC/MS analysis of the benzocarbazoles for the studied oils in the
Rimbey-Meadowbrook reef trend of the central Alberta*.
Lab No.
RD
Ro(equiv.)
[a]
[c]
[a]/[c]
SMFI of [a]
SMFI of [c]
1832
866
872
863
871
2095
2209
2210
944
860
2097
859
24
70
102
116
118
150
150
150
194
224
224
235
0.87
0.85
0.80
0.85
0.81
0.70
0.83
0.68
0.80
0.76
0.76
0.79
24.53
28.27
21.90
18.74
21.11
5.55
10.45
3.69
12.96
7.96
7.10
8.31
18.17
15.53
12.30
8.96
11.79
4.05
9.25
4.11
14.24
7.04
6.40
4.59
1.35
1.82
1.78
2.09
1.79
1.37
1.13
0.9
0.91
1.13
1.11
1.81
75.33
66.32
39.99
43.96
39.22
23.87
21.03
46.01
23.67
15.58
13.90
15.12
93.92
75.24
58.03
43.43
55.12
37.43
43.37
59.42
67.18
37.29
33.88
22.02
*GC gas chromatography; MS: mass spectrometry; Lab numbers, RD (relative distance) and Ro (equiv.) data are taken from
Tables 1 and 2 in Li et al. (1998)44; Ro (equiv.): vitrinite reflectance equivalent. [a] and [c]: benzo[a] and [c]carbazoles;
SMFI: secondary migration fractionation index (%).
29
Table S7 Calculation results of constants in the model presented in this paper and MII* and MFCI* values of the
studied oils in the Rimbey-Meadowbrook reef trend of the central Alberta
ln C  ln[ a1 (1  a2 Ro  a4 Ro 2 )]  a3 x
BCA[a]
BCA[c]
a1
a2
a4
a3
-1767
-478
-2.57
-2.55
1.61
1.56
-0.0076
-0.0048
MIImin
MIImax
MIImean
MFCImean
1.81
5.03
85.76
76.24
30.74
27.86
69.26
72.14
*MII: maturity influence index (%); MFCI: migration fractionation contribution index (%). The units of
μg/g and km-1 respectively; a 2 and a4 are dimensionless constants.
.
30
a1 and a3 are
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