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Exploratory analysis of Campos basin crude oils via geochemical parameters by comprehensive two-dimensional gas chromatography/time-of-flight mass spectrometry Lívia Carvalho Santos, Georgiana da Cruz, Bárbara Marini Fernandez Ávila, Vinícius Barreto Pereira, and Débora A. Azevedo Energy Fuels, Just Accepted Manuscript • DOI: 10.1021/acs.energyfuels.8b01299 • Publication Date (Web): 10 Sep 2018 Downloaded from http://pubs.acs.org on September 11, 2018

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Exploratory analysis of Campos basin crude oils

via

geochemical

comprehensive

parameters

by

two-dimensional

chromatography/time-of-flight

gas mass

spectrometry Lívia C. Santos†, Georgiana F. da Cruz*†, Bárbara M. F. Ávila‡, Vinícius B. Pereira‡, Débora A. Azevedo‡.

†

Universidade Estadual do Norte Fluminense Darcy Ribeiro, Laboratório de Engenharia

e Exploração de Petróleo, LENEP, Macaé RJ, Brazil. ‡

Universidade Federal do Rio de Janeiro, Instituto de Química, LAGOA-LADETEC,

Rio de Janeiro RJ, Brazil. (*corresponding author: [email protected])

KEYWORDS:

Petroleum

biomarkers,

GC×GC–TOFMS,

time-of-flight

mass

spectrometry, petroleum geochemical parameters, chemometric treatment, unusual biomarkers.

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ABSTRACT. Comprehensive two-dimensional gas chromatography coupled to timeof-flight

mass

spectrometry

(GC×GC–TOFMS)

was

used

for

geochemical

characterization of 18 oil samples from Campos Basin, Brazil. Conventional analyses were also performed on these oils (API gravity and GC-FID) and in the maltenic fraction (saturated, aromatic, and polar analysis) after asphaltene precipitation, aiming the oil screening for a rapid assessment of general characteristics. The results from principal component analysis with the biomarker parameters of source, maturity, and biodegradation obtained by GC×GC–TOFMS separated the oils into two groups, mainly explained by gammacerane content. The higher sensitivity and resolution of GC×GC– TOFMS allowed the identification of unusual compounds in oils from this basin, such as methylhopanes (whose calculated ratios allowed classifying the oils in this work as being of marine, lacustrine, or “mixed” source, the same interpretation obtained by statistical analysis), moretanes (with results that reinforce the hypothesis of same thermal evolution for the studied samples), and also the short-chain steranes (C21 and C22), detected in very low concentration for all samples. This study is the first to show the presence of these compounds in Campos basin crude oils.


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INTRODUCTION One of the major applications of organic geochemistry when using chromatography and mass spectrometry techniques is to determine the distribution of various biomarker classes in oils and source rocks, and the identification of individual compounds. This allows correlating crude oils to their source and indicates oil maturity and biodegradation level, among others1–7. For this purpose, conventional gas chromatography–mass spectrometry (GC/MS) is one of the most commonly used chromatographic techniques2,8. GC/TOFMS (gas chromatography coupled to time-offlight mass spectrometry) and GC/Q–TOFMS (gas chromatography coupled to quadrupole-time-of-flight mass spectrometry) systems can be used to solve complex analytical problems such as identification of compounds not present in any known database9,10, in environmental analysis, or in the differentiation of genetically related oils with very similar characteristics11. While traditional one-dimensional gas chromatography continues to be extremely popular and despite the enhanced detectability and selectivity when performing GC–MS analysis, by single ion monitoring and using multiple reaction monitoring on GC–MS/MS systems10,12, two-dimensional gas chromatography has emerged from niche techniques into more commonly used methods in industry, national laboratories, and academic research sectors13, mainly due the possibility of solving coelution problems in complex matrices such as crude oil, which makes the identification of some biomarkers a difficult task14,15. GC×GC is a powerful separation technique, based on orthogonal separation mechanisms using two columns containing different stationary phases. This one coupled to time-of-flight mass spectrometry (GC×GC–TOFMS) is an option for overcoming the limitations of one-dimensional GC. Further, a mass spectrometer as a GC×GC detection system can very well enhance the


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identification capability, but only time-of-flight (TOFMS) is able to scan at high scan rates, providing an important tool for identification and quantification16,17. Applications of GC×GC–TOFMS in organic geochemistry have been recently reported15,18–20, some related to Brazilian oils: GC×GC–TOFMS

promoted the

separation of hopanes and methylhopanes in petroleum analysis that were poorly separated using a GC–MS system6, permitted the investigation of new compound families (demethylated tri- and tetracyclic terpanes) for studies that are characteristic of diverse petroleum systems14, and the characterization of unusual tetracyclic compounds21, allowed a better detection of β-carotane and several other biomarker series that were useful to distinguish different source facies in Lacustrine Brazilian oils, such as the separation of monoaromatic steroids from triaromatic steroids in marine and lacustrine crude oils11,22. The great improvement in peak capacity, resolutions and sensitivity from GC×GC–TOFMS reveals the possibility to discover several new compounds, and considerably increases the amount of information obtained from the studied samples. Traditional data evaluation methods, such as visual inspection of chromatograms or interpretation of ternary composition diagrams allow analyzing data quality and identifying important differences among samples. However, they are poorly suited to the extraction of meaningful information from large data sets, not providing an efficient and reliable analysis of chemical analytical data2. In research involving a large number of samples, where for example it is necessary that multiple biomarker parameters be used, multivariate statistical methods can enhance the interpretation of data23. The chemometric analysis can be used to identify and remove noise from data, show affinities among samples or variables, and make an accurate prediction about an unknown sample2. A full data-analysis procedure often starts with exploratory data


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analysis, in which one tries to summarize and to visualize the data as well as possible24. Analytical chemical data are typically first analyzed using principal component analysis (PCA) to inspect the main sources of variation in the data, to grasp relationships between variables as well as to observe a possible grouping of samples in the data set24,25. Thus, this work intends to characterize Brazilian oils from Campos basin (the most important region of offshore petroleum production in Brazil), with different °API values, using biomarker parameters obtained by GC×GC–TOFMS associated with multivariate statistical analysis, besides investigating the presence of unusual compounds with the potential of geochemical applicability. With regard to the petrochemical industry, the results are useful to help establish petroleum systems, thereby to improve exploration success, and to define reservoir compartments, thereby enhancing production22.

MATERIAL AND METHODS Samples and geological settings. A set of 18 crude oil samples from Campos basin, Brazil, were analyzed. The Campos Basin is located along the southeast Brazilian margin (Figure 1) between latitudes 21° and 23°S and covers an area of about 100,000 km2 (up to the 3400 m isobath). The continental slope is 40 km wide and extends from the shelf-break, at the 110 m isobath, to 2000 m where it merges with the São Paulo Plateau. The oil fields discovered occur in water depths ranging from 80 m to more than 2600 m26,27. The Lagoa Feia Group, deposited in the rift and sag pre salt phases, includes lacustrine organic-rich shales, which constitute the source rocks of the basin, and carbonate rocks, which correspond to the main reservoir rocks of the rift section28.


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The Campos basin is one of the most prolific oil basins in Brazil, holding about 90% of total Brazilian oil reserves (before the pre-salt reservoir discovery), and produces mostly from turbiditic sandstones of the Carapebus formation (Cretaceous Tertiary), comprising 80% of the total production. Other important reservoirs are calcarenites of the Macaé formation (Albian), bioclastic lacustrine limestones of the Lagoa Feia formation (Barremian) and fractured basalts of the Cabiúnas formation (Neocomian)29,30.

Sample preparation. Except for the API gravity and GC-FID (flame ionization detection) analysis, the other analyses were peformed with the maltenic fraction from the crude oils. For this, the asphaltenes were removed by n-hexane precipitation followed by filtration according to Martins et al.31. Asphaltene deposits were collected by filtration and washed with hexane (60 mL) for removal of impurities such as resins and possible adsorbed compounds. The maltenic fraction was used in the determination of saturated, aromatic,c and polar content and chromatography analysis. The composition (%) of saturated, aromatic, and polar compounds was determined as follows: the maltene samples (about 0.1 g) were submitted to liquid chromatography using activated silica gel column. Saturated, aromatic and polar compound fractions from the maltenic fraction were eluted using 40 mL of n-hexane, nhexane:dichloromethane

(8:2

v/v),

and

dichloromethane:methanol

(9:1

v/v),

respectively19. The saturated compounds diluted in n-hexane (0.02 mg µL–1) were submitted to GC×GC–TOFMS , using n-tetracosane-D50 (0.01 mg mL–1) (Cambridge Isotopes Laboratories, Andover, MA, USA) as an internal standard. All solvents used for sample processing and analyses (hexane, dichloromethane, and methanol) were chromatographic grade from Sigma-Aldrich (Brazil).


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API gravity. The °API values of crude oils were obtained using an Anton Paar Density Meter DMA 35, according to the ASTM D 5002-99 method. Two replicates were made for each oil sample. For each test, approximately 2 mL of sample were fed to the equipment. Gas Chromatography. The whole oil analyses (0.02 mg µL–1) for all samples were performed using a GC-FID instrument (6890 N, Agilent Technologies, USA) equipped with an HP-5 (5% phenyl–95% methylsiloxane) capillary column (30 m, 0.32 mm i.d., 0.25 µm film thickness), using synthetic air, H2, and N2. The GC oven was programmed from 40 °C to 310 °C (19 min isothermal) at 6 °C min-1. The injector temperature was set at 290 °C and the FID at 320 °C. High-purity He was used as carrier gas with a constant flow rate (2.2 mL min–1). In all samples was added α-androstane (to reach the concentration of 0.02 mg mL–1) as an internal standard.

GC×GC–TOFMS and data processing. The GC×GC system was a Pegasus 4D instrument (Leco, St. Joseph, MI, USA), which is an Agilent Technologies 7890 gas chromatograph (Palo Alto, CA, USA) equipped with a secondary oven and non moving quad-jet dual stage modulator. Data acquisition and processing were carried out using ChromaTOF® software version 4.4 (Leco Corp., St. Joseph, MI). A DB-5ms (5%phenyl–95%-methylsiloxane) column (30 m, 0.25 mm i.d., 0.25 µm film thickness) was used as the first dimension column (1D) and a BPX-50 (50%-phenyl–50%methylsiloxane; Austin, Texas, USA) column (1.5 m, 0.1 mm i.d., 0.1 µm film thickness) as the second dimension (2D). The second column was connected to the TOFMS (Leco, St. Joseph, MI, USA) via an empty deactivated column (0.5 m × 0.25 mm i.d.). The columns and the empty deactivated column were connected


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by SGE unions using SilTite metal ferrules (Austin, Texas, USA) for 0.10–0.25 mm i.d. GC columns. The injection mode was splitless, at a temperature of 280 °C. GC conditions for 1D followed published experimental settings12,32. The primary oven temperature program was: 70 °C (1 min) to 170 °C at 20 °C min−1, and then to 325 °C at 2 °C min−1. The secondary oven temperature program had a temperature 10 °C higher than the primary one. The carrier gas was He at 1.5 mL min−1, in constant flow mode. The modulation period was 8 s with a 2 s hot pulse duration and a 35 °C modulator temperature offset vs the primary oven temperature. The MS transfer line was held at 280 °C. The TOFMS was operated in the electron ionization mode with a range of m/z 50–700. The ion source temperature was 230 °C, the detector was operated at 1500 V, the applied electron energy was 70 eV and the acquisition rate was 100 spectra s−1. The saturated fractions were analyzed in total ion current chromatogram and extracted ion chromatogram (EIC) modes using m/z 66 (internal standard tetracosaneD50), m/z 57 (paraffins), m/z 191 (tri-, tetra-, and pentacyclic terpanes), m/z 177 (demethylated terpanes), m/z 205 (methylhopanes and C31 homohopanes), (m/z 217 and 218 (ααα and αββ steranes, respectively), and m/z 259 (diasteranes and tetracyclic polyprenoids). Assignment was performed by examination and comparison with literature mass spectra, retention time, and elution order2,6,12,14,19,32,33.

Chemometric analysis. Biomarker ratios (source, maturity, and biodegradation) data were explored by PCA on autoscaled columns data. Chemometric analyses were performed using the software Statistica 7.0 (version 7.0.61.0).


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RESULTS AND DISCUSSION Bulk characteristics. All samples were initially evaluated by saturated, aromatic and polar (SAP) compounds analyses, API gravity, and GC-FID to screen the oils for a rapid assessment of general characteristics. SAP fractionation separates the crude oil into three main classes based on polarity and solubility: (i) saturated (n-alkanes, branched alkanes and cycloalkanes), (ii) mono and polyaromatic, and (iii) polar compounds. The content of SAP obtained by precipitation of asphaltenes and by liquid chromatography of maltene is given in Table 1, as the API results. The oils investigated (16.7–26 °API) showed saturated compounds levels between 28.2 and 47.6%, aromatic compounds levels between 17.7 and 35%, polar compounds levels between 15.2 and 25.3% and asphaltene levels between 6.5 and 23.8%. Although these oils originated in the same source rock, the results show significant differences in the contents of the fractions, in agreement with reported studies in the literature for this basin34,35. During thermal maturation, the heavy components in oil (polar compounds, asphaltenes), and saturated and aromatic compounds undergo increased cracking, resulting in increased API gravity. However, this increase in the API is also affected by other factors, including water washing, biodegradation, and others1. The occurrence of biodegradation and meteoric water circulation can transform light oils (high content of saturated hydrocarbons) in heavy oils (high content of asphaltenes and resins), leading to a decrease in the saturated hydrocarbon content and API gravity and a progressive increase of sulfur content, acidity (formation of carboxylic acids and phenols), viscosity, and the asphaltenes content36. The C01 sample, for example, has a low API degree (16.7) and high content of asphaltene (23.8%), while, as expected, the oils with


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higher API values presented the biggest content of saturated compounds, as C06 sample (API degree 26.0 and saturated content equal to 47.6%) (Table 1). Gas chromatography fingerprints obtained by GC-FID analyses allow comparison of crude oils based on loss of n-alkanes (relative to pristane and phytane) and presence of a “baseline shift” of the unresolved complex mixture (UCM)1. Figure 2 illustrates whole oil chromatograms of five petroleum samples organized in ascending order of API degree (left to right). An expected trend is observed: the content of n-alkanes is more pronounced in oils with higher API degree. This is verified observing the signal of the internal standard (IS) α-androstane compared with the signal of n-alkanes, which is clear when the oils C01 (API degree 16.7) and C18 (API degree 24.1) are compared. The n-alkanes concentrations for these two samples corroborate with the result found: 0.25 mg µL-1 and 0.52 mg µL-1, respectively. However, the calculated ratios pristane/n-C17 and phytane/n-C18 did not show a trend with another parameters such as API and % of asphaltene in this work, since the C01 sample (API 16.7 and 22% of asphaltene), for example, presented Pr/n-C17=0.74 and Ph/n-C18=0.56, but the C18 oil (API 24.1 and 16% of asphaltene) showed Pr/n-C17=1.94 and Ph/n-C18=0.71, both level 3 (according to Peters and Moldowan scale – PM 3)37. In general, these ratios are higher in moderately biodegraded samples (PM 3) than in nonbiodegraded or lightly biodegraded oils (PM 2). In contrast, these ratios tend toward zero in highly biodegraded oil (PM > 6), due to the absence of nC17, Pr, nC18 and Ph38,39. Consequently, increasing values of Pr/n-C17 and Ph/n-C18 indicate increasing biodegradation. Besides, these ratios are also affected by source and maturity and therefore should be used with caution. Biomarker parameters and chemometric analysis. The calculated geochemical parameters obtained by GC×GC–TOFMS of saturated hydrocarbon fractions are shown


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in Table 2. Compound assignment was performed by comparison with mass spectra, retention time, and elution order. The detailed procedure adopted for structural characterization can be found in the literature6,11,14. To get a maturity degree evaluation from the oil samples, a graphic was constructed as shown in Figure 3. The isomerization at C14 and C17 in the C29 20S and 20R regular steranes causes an increase in αββ/(ααα + αββ) with increasing maturity, as with isomerization at C20 in the C29 5α,14α,17α(H)-steranes2. Based on this, no clear basin maturity differentiation could be obtained by analyzing only these conventional parameters because most samples are below the average equilibrium2,40, as observed in Figure 3. The same behavior was observed in the evaluation of oils from five sedimentary basins of the Brazilian continental margin when using these same parameters of steranes12. Although the oils C10 and C16 (Figure 3) present the lowest values of the steranes ratios, it is not possible to affirm that they have lower thermal maturity among the studied samples because the values for the ratio H32 S/(S + R) (Table 2) were within the equilibrium range (0.57–0.62)2,41. It is important to highlight, however, due to the greater sensitivity of the technique (GC×GC–TOFMS) comparing with GC–MS (in which equilibrium limits/ranges were determined), it may be necessary to change the limit values, once the higher resolution of the technique may alter the values of the diagnostic ratios of biomarkers. Another parameter used to infer the maturity is the C24 tetracyclic terpane/hopane ratio (Te24/H30), which increases in more mature source rocks and oils because of the greater stability of the tetracyclic terpanes2. However, the values found for this ratio were low and similar for all oils (0.08-0.19), which made it impossible for the samples to be compared with each other in relation to this parameter.


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According to Soares et al., analysis of oils from Colombia showed similar values of the maturity ratios discussed above (H32 S/(S+R) and steranes isomers, and also Ts/(Ts + Tm), presented in Table 2)41. However, the Te24/H30 ratio values found are approximately 10 times higher than those obtained in this work (despite the similarity between the maturity parameters). This can be explained by the fact that C24 tetracyclic terpane is dependent on the depositional environment, being found mainly in carbonate and evaporite environments42,43. A consequence of these inconclusive data was observed in the results from the PCA, used to determine differences in the oils’ thermal maturity (Figure 4). As could be seen in loadings plot (Figure 4b), the maturation parameters were well distributed (with a similar contribution to PC1 and PC2), as the samples in the scores plot (Figure 4a). Because the degrees of thermal maturity were similar, it was not possible to group or distinguish the samples in terms of this parameter. It is interesting to observe that C10 and C16 are the less related samples with the C29 ββ/(αα + ββ) and C29 ααα S(S+R) variables, as expected by previous graphic analysis (Figure 3). Despite the limited information obtained from the above-discussed parameters, based on the TNH/(TNH + Hopanes) ratio {25,28,30-trisnorhopanes/[25,28,30trisnorhopanes + (C29 + C30 hopanes)]} and API gravity, it can be observed that lighter oils have a higher thermal maturity, consistent with the higher amount of cracking reactions. TNH is associated with the original free bitumen in the rock and the TNH/hopanes ratio decreases to zero in the late oil window2. The calculated values of Hop/St ratio suggest that oils were accumulated in reservoirs deposited in nonmarine facies, with contribution of amorphous and organic matter in the source rock and presence of β-carotane3.


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In addition, the Ts/Tm ratio (below 1 for all oils), suggests a lacustrine saline, carbonate, or marine evaporite depositional environment for all oils, and this is consistent with the H35/H34 and H31R/H30 ratio values2,3. The abundance of gammacerane and presence of β-carotane are indicative of an anoxic and saline depositional environment for the source rocks44. TPP (C30 tetracyclic polyprenoids) were identified in all samples. The abundance of TPP in petroleum from lacustrine source rocks reflects the predominance of fresh-water algal precursors45. Gammacerane indicates a stratified water column, typically due to hypersalinity during source rock deposition46. The samples showed Gam/H30 values that ranged from 0.10 to 0.30, which suggests a depositional environment with normal marine salinity47. It can be noticed, by the results in Table 2, that the oils C07, C08, and C18, which presented higher concentration of gammacerane, were also those with higher β-carotane content (>700 ppm). The high concentrations found for the carotenoid may suggest a highly marine depositional environment48,49. A significant difference in the concentration of β-carotane was observed in two different horizons of the Campos Basin source rock50, which justifies the variation of the concentration of this compound in oils from the same sedimentary basin. Figure 5 shows the results from the PCA of the source parameters. The PCA model explains 55.54% of the variance (sum of the principal components 1 and 2, which are 36.62% and 18.92%, respectively) and separate the oils into two groups: marine (C01, C07, C08, and C18, in blue) and saline lacustrine (C02 to C06 and C09 to C17, in green), represented in Figure 5a. As the scores plot (Figure 5a) is a raw data linear combination, with weighting given by the loadings plot (Figure 5b), the superimposing of the scores and the loadings


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allows us to conclude that the C08 sample has the higher salinity among the other oils, which is consistent with its gammacerane content, 1702 ng mg–1 (Table 2). In the lacustrine samples group, C15 oil provides a distinctive PC1 (Figure 5a), probably due to the higher Hop/St ratio value among all studied samples. According to the loadings plot (Figure 5b), this ratio is an important parameter that contributes to PC1. Two distinct environments of organic matter deposition presented for the Campos Basin oils are justified when evaluating their stratigraphic evolution, which presents four tectonostratigraphic sequences associated with rift, proto-oceanic and oceanic development phases50. To get a relation between TPP and gammacerane concentrations, a graphic was constructed as shown in Figure 6. Because TPP are most prominently observed in samples derived from low salinity and are generally present in low levels in samples derived from saline (i.e., marine and saline lacustrine, environments)5 and the presence of high concentrations of gammacerane results from a hypersalinity environment, it was expected that TPP concentration was inversely proportional to gammacerane concentration (although these two parameters are related to the marine samples group, as demonstrated in Figure 5). However, as presented in Figure 6, the graphic between gammacerane and TPP concentrations showed good correlation (R2 greater than 0.9), with TPP and gammacerane increasing together. In the results obtained in this work, despite what is common in marine-derived samples, moderate increase of TPP was found in ostensibly marine source rocks and oils from certain basins of western and northern South America, probably due to transport from the nonmarine to the marine environment because of an influx of fresh water into the near-shore marine environment5.


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The GC×GC–TOFMS data for the biodegradation parameters of the 18 crude oil samples were also statistically analyzed. Figure 7 shows the results from the PCA. The PCA model explains 58.47% of the variance (sum of the principal components 1 and 2, which are 34.67% and 23.80%, respectively). The samples analyzed showed low values for 25NH/H30 (25NH at m/z 177), ranged from not detected to 0.12. The small quantities of 25-norhopanes suggest that samples have not undergone intensive biodegradation51. This result agrees with the group of oils (in a black circle) presented in Figure 7a. The samples in this group did not have significant representation in relation to the factors. The oils C04 and C08 (pink circle in Figure 7a) have the higher value of 25,30BNH/H30b ratio, a parameter with a significant contribution to PC1 (Figure 7b). For the C15 sample (green circle in Figure 7a) it was not possible to detect the 25,30BNH, which justifies this sample’s position in the scores plot. Among the samples, C07 (blue circle in Figure 7a) yielded a distinctive PC2, probably because of the two TNH/H30 ratios, that considerably contribute to PC2, because this oil presents the higher 25,28,30TNH/H30 ratio value. According Soares et al (2013)41 the presence of 25,30BNH, 25,28BNH and 25,28,30TNH detected in higher abundance by GC×GC–TOFMS means that oil samples can be classified as severely biodegraded (PM rank > 6). However, the analyzed samples in this work showed low values for these ratios, not being able to classify them in this level of biodegradation. Thus, the higher values of 25,30BNH/H30 ratio for C04 and C08 samples and the higher value of 25,28,30TNH/H30 ratio for C07 sample only suggest that these oils have different biodegradation levels than other samples, as shown in the PCA.


Energy & Fuels 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 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 26 of 51

Unusual biomarkers. Besides the compounds and respective ratios discussed previously, some unusual saturated biomarkers have also been identified by GC × GC – TOFMS. Methylhopanes were detected by monitoring the m/z 205 EIC (addition of a methyl group to the ring A/B fragment of the hopane series increases the fragment from m/z 191 to 205)2. Methylhopanoids are organic compounds synthesized by certain bacteria, that when preserved in sediments act as molecular fossils or biomarkers for organic matter inputs from specific bacterial sources52. In Figure 8 it can be seen (with very low intensity) the presence of 3β-methyl17α(H),21β(H)-30-hopane (3βMH31) and 2αMH32 and 2αMH33 (R and S isomers) homohopanes. These last two were the only compounds detected from the 2αmethylhopanes series, that extends from C28 through C36 with carbon number distributions comparable with those of the hopanes6,47,52. The

2α-methylhopanes

appear

to

be

specific

for

oxygen-producing

cyanobacteria2. Because of the small abundance of these compounds in the analyzed oils, the 2α-methylhopane index (2α-methylhopane/(2α-methylhopane + hopanes)) did not prove enlightening, with values between 0.005 and 0.060. From the 3β-methylhopane series, only 3βMH31 was detected. The same behavior was observed in Ceará basin oils6. Although widely variable, the methylhopane composition in oils presents similar values to their source rock samples, being a useful correlation marker. In more mature geological samples, for example, only the 2α-methyl isomers were found53,54. Concerning the biological source and geochemical significance, 3β-methylhopanes are characteristic of a few lacustrine environments around the world55,56. Marine samples generally have higher proportions of 2α-methylhopanes52. Lacustrine oils and source rocks exhibit a diverse methylhopane composition, but some,


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Energy & Fuels

which represent a distinct source facies, are enriched in 3β-methylhopanes6,52. The 3βMH31 over total 2-methylhopanes ratio for the studied oils shows an enrichment in 2methylhopanes, with values between not detected and 2.50. This result, as the 2methylhopanes/hopane(C29–C33) ratio and

the

3-methylhopanes/hopane(C29–C33)

classify the oils in this work as being of marine, lacustrine, or “mixed” source, in accordance with the results obtained for a suite of oils from offshore West Africa52 and consistent with the two groups of oils obtained by statistical analysis with the source parameters (Figure 5a). Regarding βα hopanes (or moretanes), the M31(S + R) homomoretanes (17β(H),21α(H)-30-homohopanes (22S + 22R)), eluted after the regular hopanes (Figure 8) and were not resolved even in 2D analytical conditions. The abundances of moretanes decrease to their corresponding hopanes with thermal maturity2. For Campos basin samples, the ratio values of 17β(H),21α(H)-30homohopanes (22S + 22R) over 17α(H),21β(H)-30-homohopane (22S +22 R) ranged from not detected (C09 oil) to 0.12 (C04 oil). These results are consistent with the previous correlation between steranes in Figure 3, reinforcing the hypothesis that all samples have a similar level of thermal evolution. Besides the common steranes cited previously, the recently reported new series of short-chain steranes57 was observed with a diagnostic ion at m/z 232 (Figure 9). The C22

13β,17α(H)-3β-methyldiapregnane

(3βMDia21βα),

C22

3β-methylpregnane

(3βMSt21ααα), and C22 3β-methyldiginane (3βMSt21αββ) were detected in all samples and identified by comparison with mass spectra, retention time, and elution order. This study is the first to show the presence of these compounds in Campos basin crude oils, being detected in very low concentration for all samples. The difference in the


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Page 28 of 51

distribution of short-chain steranes may be used to distinguish oils with very similar characteristics, even those that originated from the same sedimentary basin. The diagnostic ions for short-chain steranes (Figure 9B and 9C) are due to 5α(H) configuration (m/z 163) and 14α(H) or 14β(H) configuration (m/z 231 or 232, respectively)57. The short side chain 5α(H),14β(H),17β(H), 5α(H),14β(H),17α(H), and 5α(H),14α(H),17α(H) pregnanes and homopregnanes were the most abundant compounds present in samples of a Messinian evaporitic basin, a hypersaline environment58. The abundance of uncommon steranes in hypersaline samples was also cited in Haven et al 59. Recently, it was suggested that the abundance and occurrence of 3β-alkylsteranes would be related with high microalgal input (marine algae, mainly) in crude oils from Sergipe-Alagoas basin, that presents high contributions of C27 steranes and dinosteranes, besides the marine and saline depositional environment57. In this work, the oil samples present characteristics of a marine and a lacustrine depositional environmental, with normal marine salinity, as previously discussed and demonstrated by Gam/H30 and Ts/Tm ratios (Table 2). The absence of hypersaline conditions associated with the high values for Hop/St ratio explain the very low abundance of these short-chain alkylsteranes in the Campos basin oils: a calculated ratio of total 3-methylhopanes over total hopanes (C29–C33) has presented values from 0.048 to 0.14.

CONCLUSIONS The use of comprehensive two-dimensional gas chromatography coupled to time-of-flight

mass

spectrometry

(GC×GC–TOFMS)

afforded

a

meticulous

characterization of Brazilian oils, using saturated biomarker parameters related to the


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Energy & Fuels

source, maturity, and biodegradation. The higher sensitivity and resolution of GC×GC– TOFMS allowed the identification of unusual compounds, even in low concentration, such as methylhopanes and short-chain steranes. These short-chain steranes were detected for the first time in Campos basin crude oils, which would not be possible to analyze by conventional techniques. The investigated oils presented no clear maturity differentiation, with most of them below the average equilibrium. The analogous conclusion was obtained with chemometric analysis by principal components. Regarding origin, the multivariate data analysis separates the set of Campos oils into two groups: marine and saline lacustrine, as discussed from the depositional environmental biomarkers, and in accordance with previous works in organic geochemistry. Based on saturated biomarker biodegradation parameters, it could be concluded that samples have not undergone intensive biodegradation. Statistical analysis was a powerful tool for data understanding and visualization, mostly because of the number of studied samples. However, it was not always possible to find a direct relationship between the groupings obtained by PCA and the interpretations derived from the biomarker ratios. This reinforces the importance of a joint and exhaustive analysis of results obtained from different techniques, given the complexity of the oil samples and the many factors that affect their quality and composition. A deep analysis of the geochemical results and interpretation of the information obtained are essential to the petroleum industry because the understanding of petroleum systems is directly related to the exploration success and, consequently, to increasing production.


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Page 30 of 51

TABLES

Table 1. Percentage (%) of Saturated, Aromatic, Polar Compounds and Asphaltenes for the crude oils Oil

API,

Saturated

Aromatic

Polar

Recovery

Asphaltenes

sample

gravity

(%)

(%)

(%)

(%)*

(%)

C01

16.7

38.6

17.8

16.8

73.2

23.8

C02

23.8

40.5

30.6

18.9

90.0

13.7

C03

24.4

44.7

26.7

18.6

90.0

11.9

C04

20.7

40.1

28.2

20.0

88.3

14.6

C05

19.7

35.8

33.2

17.1

86.1

16.7

C06

26.0

47.6

18.9

22.1

88.6

10.5

C07

19.9

37.8

18.2

15.2

71.2

18.3

C08

19.2

30.1

35.0

24.6

89.7

15.7

C09

24.1

42.0

29.2

17.5

88.6

12.2

C10

19.3

38.9

27.7

25.3

91.9

12.7

C11

20.3

34.7

17.7

21.8

74.2

14.5

C12

21.1

28.2

28.3

19.7

76.3

6.5

C13

25.6

44.3

19.8

12.1

76.2

16.1

C14

25.9

44.9

27.5

14.2

86.6

16.0

C15

23.8

44.6

19.2

16.0

79.9

20.5

C16

23.0

43.7

25.2

16.0

84.9

12.0

C17

21.7

39.5

28.3

19.9

87.7

12.8

C18

24.1

47.5

18.5

19.8

85.8

16.1

*Recovery refers to percentage of Saturated, Aromatic and Polar compounds.


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Table 2. Geochemical data showing selected source, maturity and biodegradation parameters of samples by GC×GC–TOFMS . Biomarker parameters SOURCE Hop/Sta H30/C27 αααb St/Hopc Tr23/H30d (Tr28+Tr29)/Hope TeT24/H30f H29/H30g H31R/H30h Gam/H30i Gammacerane (ng/mg)j H35/H34k β-carotane/H30l β-carotane (ng/mg)m TPP/Dia27n TPP (ng/mg)o Ts/Tmp MATURITY Tricyclic/Hopaneq H32 S/(S+R)r C29 ααα S/(S + R)s C29 ββ/(αα + ββ)t Ts/(Ts+Tm)u C29Ts/H29v TNH/(TNH + Hopanes)w BIODEGRADATION 25NH/H30x 25NH/H30y 25,28BNH/H30z 25,28BNH/H30aa 25,30BNH/H30ab 25,30BNH/H30ac 25,28,30TNH/H30ad 25,28,30TNH/H30ae

C01

C02

C03

C04

C05

C06

C07

C08

C09

C10

C11

C12

C13

C14

C15

C16

C17

C18

7.46 9.10 0.13 0.69 0.16 0.14 1.32 0.25 0.24 328.7 0.19 0.11 151.4 0.78 119.1 0.34

5.75 7.53 0.17 0.27 0.16 0.15 0.83 0.22 0.12 314.6 0.78 0.12 309.7 0.42 136.5 0.44

6.63 15.49 0.15 0.47 0.12 0.11 0.86 0.20 0.13 150.7 0.86 0.08 90.2 0.42 47.7 0.20

3.55 3.84 0.28 0.35 0.18 0.09 0.61 0.21 0.10 141.5 0.67 0.21 284.8 0.03 4.8 0.35

5.72 7.45 0.17 0.47 0.11 0.10 0.82 0.25 0.14 215.7 0.74 0.14 218.8 0.31 49.9 0.51

7.53 9.10 0.13 0.24 0.11 0.11 0.74 0.26 0.13 150.7 0.70 0.12 131.7 0.00 0.3 0.47

3.98 3.17 0.25 0.09 0.21 0.19 1.25 0.36 0.30 787.9 0.70 0.27 710.9 0.42 291.8 0.47

5.22 4.45 0.19 0.43 0.15 0.18 1.03 0.22 0.20 1702 0.81 0.12 984.8 0.94 638.0 0.32

5.67 5.51 0.18 0.59 0.13 0.11 0.73 0.23 0.20 399.3 0.84 0.13 274.7 0.33 84.6 0.45

7.11 8.19 0.14 0.70 0.21 0.10 0.73 0.20 0.12 201.6 0.75 0.12 200.8 0.20 37.2 0.52

4.91 5.46 0.20 0.46 0.17 0.08 0.51 0.21 0.26 491.2 0.64 0.17 314.9 0.50 108.1 0.34

6.67 7.37 0.15 0.52 0.14 0.10 0.92 0.20 0.11 355.7 0.69 0.13 409.9 0.35 105.0 0.39

6.06 8.43 0.17 0.55 0.11 0.14 0.81 0.23 0.16 328.6 0.63 0.10 210.0 0.60 95.7 0.64

7.05 14.94 0.14 0.47 0.10 0.10 0.80 0.23 0.11 132.5 0.72 0.11 130.9 0.42 46.5 0.39

9.76 18.90 0.10 0.42 0.08 0.08 0.33 0.18 0.13 170.0 0.72 0.12 167.5 2.30 46.1 0.71

5.65 6.68 0.18 0.75 0.15 0.12 0.30 0.28 0.15 159.9 0.84 0.18 200.2 0.28 29.4 0.23

4.84 6.77 0.21 0.53 0.15 0.08 0.58 0.19 0.13 191.5 0.75 0.15 228.0 0.58 74.4 0.42

6.77 6.54 0.15 0.66 0.14 0.13 0.91 0.16 0.20 633.8 0.40 0.30 945.9 2.61 307.9 0.12

0.78 0.60 0.67 0.25 0.25 0.13 n.d.

1.12 0.59 0.53 0.41 0.31 0.07 0.09

0.60 0.59 0.58 0.52 0.17 0.06 0.08

0.67 0.58 0.72 0.48 0.26 0.38 0.11

0.63 0.58 0.46 0.33 0.34 0.22 0.08

0.62 0.57 0.48 0.28 0.32 0.21 0.10

0.61 0.58 0.51 0.33 0.32 0.22 0.17

0.88 0.58 0.37 0.50 0.25 0.14 0.14

0.92 0.59 0.35 0.46 0.31 0.18 0.06

0.82 0.60 0.26 0.14 0.34 0.42 0.13

0.78 0.59 0.74 0.45 0.25 0.38 0.09

0.60 0.59 0.48 0.75 0.28 0.08 0.09

0.89 0.59 0.46 0.41 0.39 0.20 0.12

0.84 0.30 0.42 0.43 0.28 0.07 0.09

0.49 0.60 0.74 0.09 0.42 0.14 n.d.

1.04 0.58 0.17 0.27 0.19 0.21 0.13

0.58 0.57 0.31 0.60 0.30 0.38 0.09

1.21 0.68 0.43 0.49 0.10 0.09 0.06

0.15 0.10 0.06 0.06 0.03 0.10 n.d. n.d.

0.12 0.08 0.01 0.02 0.02 0.13 0.01 0.19

0.07 0.05 0.06 0.05 0.02 0.01 0.01 0.17

0.29 0.00 0.14 0.03 0.05 0.24 0.01 0.20

0.10 0.07 0.12 0.03 0.02 0.01 0.01 0.17

0.10 0.05 0.02 0.02 0.03 0.01 0.02 0.19

n.d. n.d. 0.23 0.05 0.03 0.01 0.03 0.45

0.21 0.12 0.11 0.02 0.04 0.28 0.03 0.34

0.14 0.08 0.04 0.04 0.02 0.11 0.01 0.11

0.11 0.08 0.03 0.03 0.04 0.12 0.02 0.25

0.19 0.10 0.10 0.02 0.03 0.19 0.01 0.14

0.04 0.02 0.06 0.06 0.02 0.00 0.01 0.19

0.08 0.05 0.15 0.04 0.02 0.01 0.02 0.24

0.06 0.04 0.09 0.02 0.02 0.00 0.01 0.17

0.01 0.02 n.d. n.d. n.d. n.d. n.d. n.d.

0.18 0.11 0.13 0.03 0.02 0.01 0.01 0.20

0.07 0.05 0.06 0.05 0.02 0.10 0.01 0.16

0.04 0.02 0.14 0.03 0.02 0.00 0.01 0.13

21


Energy & Fuels 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 34 35 36 37 38 39 40 41 42 43 44 45 46 47

H35 hopane indexaf Steranes ratioag

2.49 0.48

6.45 0.53

8.55 0.39

7.00 0.64

6.36 0.46

6.68 0.58

7.03 0.54

7.94 0.59

Page 32 of 51

8.64 0.57

8.38 0.55

6.84 0.54

5.90 0.55

5.90 0.41

7.90 0.41

8.22 0.45

8.62 0.50

8.12 0.55

3.44 0.58

nd: not detected; aCalculated from peak areas of ΣH29-H35 hopanes in the m/z 191 chromatogram over peak areas of ΣC27-C29 steranes in the m/z 217 chromatogram. Hop/St: (H29-H35)/[C27,C28,C29 ααα (20S + 20R) and αββ (20S + 20R)] (m/z 191 and 217). bCalculated from peak area of C30 17α(H),21β(H)- 30-hopane in the m/z 191 chromatogram over peak areas of C27 5α(H),14α(H),17α(H)-cholestanes (20S + 20R) in the m/z 217 chromatogram. H30/C27 ααα: (H30)/C27 ααα (20S + 20R). cCalculated from peak areas of ΣC27-C29 steranes in the m/z 217 chromatogram over peak areas of ΣH29-H35 hopanes in the m/z 191 chromatogram: [C27,C28,C29 ααα (20S + 20R) and αββ (20S + 20R)]/(H29-H35). dCalculated from peak area of C23 tricyclic terpane (Tr23) over peak area of C30 17α(H),21β(H)-30-hopane (H30) in the m/z 191 chromatogram. eCalculated from peak areas of ΣTr28-Tr29 tricyclic terpanes over peak areas of ΣH29-H35 hopanes in the m/z 191 chromatogram. fCalculated from peak area of C24 tetracyclic terpane (TeT24) over peak area of C30 17α(H),21β(H)-30-hopane (H30) in the m/z 191 chromatogram. gCalculated from peak area of 17α(H),21β(H)-29-hopane (H29) over peak area of C30 17α(H),21β(H)-30-hopane (H30) in the m/z 191 chromatogram. hCalculated from peak area of 17α(H),21β(H)-30-homohopane (22R) (H31R) over peak area of C30 17α(H),21β(H)-30-hopane (H30) in the m/z 191 chromatogram. iCalculated from peak area of gammacerane (Gam) over peak area of C30 17α(H),21β(H)-30-hopane (H30) in the m/z 191 chromatogram. jRelative concentration to internal standard deuterated n-tetracosane (ng/mg). k

Calculated from peak area of 17α(H),21β(H)-pentakishomohopane (22S + 22R) (H35) over peak areas of 17α(H),21β(H)-tetrakishomohopane (22S + 22R)

(H34) in the m/z 191 chromatogram. H35/H34: [H35 (22S + 22R)/H34 (22S + 22R)] (m/z 191). lCalculated from peak area of β-carotane in the chromatogram m/z 125 over peak area of C30 17α(H),21β(H)-30-hopane (H30) in the m/z 191 chromatogram. mRelative concentration to internal standard deuterated n-tetracosane (ng/mg). nCalculated from peak area of C30 tetracyclic poliprenoid in the m/z 259 chromatogram over peak area of Dia27 [C27 13β(H),17α(H)-diacholestanes (S + R)] in the m/z 217. oRelative concentration to internal standard deuterated n-tetracosane (ng/mg). pCalculated from peak 22


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Energy & Fuels

area of 18α(H),21β(H)-22,29,30-tris-nor-neohopane (Ts) over peak area of 17α(H),21β(H)-22,29,30-tris-nor-hopane (Tm) in the m/z 191 chromatogram. q

Calculated from peak area of tricyclics terpanes [ΣTr19-Tr30 (22S + 22R)] in the m/z 217 chromatogram over peak area of H28-H34 hopanes [ΣH28-H34

(22S + 22R)] in the m/z 191 chromatogram. rCalculated from peak areas of H32 17α(H),21β(H)-bishomohopane (22S + 22R) in the m/z 191 chromatogram. s

Calculated from peak areas of C29 5α(H),14α(H),17α(H)-24-ethyl-cholestane (20S + 20R) in the m/z 217 chromatogram. tCalculated from peak areas of

C29 5α(H),14α(H),17α(H)-24-ethyl-cholestane (20S + 20R) and C29 5α(H),14α(H),17α(H)-24-ethyl-cholestane (20S + 20R) in the m/z 217 chromatogram. u

Calculated from peak areas of 18α(H),21β(H)-22,29,30-tris-nor-neohopane (Ts) and 17α(H),21β(H)-22,29,30-tris-nor-hopane (Tm) in the m/z 191

chromatogram. vCalculated from peak area of 18α(H),21β(H)-30-nor-neohopane (C29Ts) over peak area of 17 α(H),21β(H)-30-nor-hopane (H29) in the m/z 191 chromatogram. wCalculated from peak areas of 25,28,30-tris-nor-hopane (25,28,30-TNH) in the m/z 177 chromatogram and peak areas of C29 17α(H),21β(H)-29-hopane (H29) and C30 17α(H),21β(H)-30-hopane (H30) in the m/z 191 chromatogram. xCalculated from peak area of 25-nor-hopane (25NH) in the chromatogram m/z 191 over peak area of C30 17α(H),21β(H)-30-hopane (H30) in the m/z 191 chromatogram. yCalculated from peak area of 25nor-hopane (25-NH) in the chromatogram m/z 177 over peak area of C30 17α(H),21β(H)-30-hopane (H30) in the m/z 191 chromatogram. zCalculated from peak area of 25,28-bis-nor-hopane (25,28-BNH) in the m/z 191 chromatogram over peak area of C30 17α(H),21β(H)-30-hopane (H30) in the m/z 191 chromatogram. aaCalculated from peak area of 25,28-bis-nor-hopane (25,28-BNH) in the m/z 177 chromatogram over peak area of C30 17α(H),21β(H)-30hopane (H30) in the m/z 191 chromatogram. abCalculated from peak area of 25,30-bis-nor-hopane (25,30-BNH) in the m/z 191 chromatogram over peak area of C30 17α(H),21β(H)-30-hopane (H30) in the m/z 191 chromatogram. acCalculated from peak area of 25,30-bis-nor-hopane (25,30-BNH) in the m/z 177 chromatogram over peak area of C30 17α(H),21β(H)-30-hopane (H30) in the m/z 191 chromatogram.

ad

Calculated from peak area of 25,28,30-tris-nor-

hopane (25,28,30-TNH) in the m/z 191 chromatogram over peak area of C30 17α(H),21β(H)-30-hopane (H30) in the m/z 191 chromatogram. aeCalculated from peak area of 25,28,30-tris-nor-hopane (25,28,30-TNH) in the m/z 177 chromatogram over peak area of C30 17α(H),21β(H)-30-hopane (H30) in the m/z 23


Energy & Fuels 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 34 35 36 37 38 39 40 41 42 43 44 45 46 47

Page 34 of 51

191 chromatogram. afCalculated from peak areas of H30-H35 hopanes in the m/z 191 chromatogram; H35 hopane index: (100 x H35 hopane/ ΣH30-H35 hopanes). agCalculated from peak areas of ΣC27-C29 steranes in the m/z 217 chromatogram; Steranes ratio: [C27 ααα (20S + 20R) and αββ (20S + 20R)]/ C27,C28,C29 ααα (20S + 20R) and αββ (20S + 20R)].

24


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Energy & Fuels

FIGURES

Figure 1. Map showing the Campos Basin location, between Espírito Santo and Santos sedimentary basins, Brazil.


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 34 35 36 37 38 39 40 41 42 43 44 45 46 47

Abundance (%)

Energy & Fuels

API = 16.7

C01

Page 36 of 51

API = 19.9

C07

C04

API = 20.7 Ph

Ph

Ph

Pr

Pr

Pr

IS

IS

IS

API = 23.8

C02

C18

Pr

API = 24.1

Ph

Ph

IS

Pr IS

Time (min) Figure 2. GC-FID whole oil chromatograms from 5 Brazilian oils from Campos Basin: C01, C02, C04, C07 and C18 samples. IS refers to the Internal Standard, α-androstane.

26


Page 37 of 51

0.8 C11

C29 20S/(20S + 20R)

C04

C01

0.6

C03

C05

average equilibrium: 0.52-0.55

0.5

C02

C07

C06 0.4

C13 C18

C14

C08 C09

0.3

C17

C10 0.2

average equilibrium: 0.67-0.71

C15 0.7

C12

C16

0.1 0

0.2

0.4 C29 αββ/(αββ + ααα)

0.6

0.8

Figure 3. Graphic of conventional thermal maturity parameters based on apparent isomerization of asymmetric centers in the C29 steranes for Brazilian oils.

(a)

(b)

PCA Scores plot

PCA Loadings plot

5 1,0 4 3

C29Ts/H29

C10

0,5

Tricyclic/Hopane

H32 S/(S+R)

1

C18

C09 C02 C08

0

C13 C17 C05 C06 C11C07 C01 C04

Factor 2 : 19,80%

C16

2 Factor 2: 19,80%

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 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Energy & Fuels

C15

Ts/(T s+T m) 0,0

-1

C29 ßß/(aa + ßß)

C03 C12 C14

C29 aaa S/(S + R)

-0,5

-2 -3 -1,0 -4 -5

-4

-3

-2

-1

0

1

2

3

4

5

-1,0

-0,5

0,0

0,5

Factor 1 : 31,32%

Factor 1: 31,32%

Figure 4. PCA scores (a) and loadings (b) plot based on saturated hydrocarbon compound maturation parameters.


1,0

Energy & Fuels

(a)

(b)

PCA Scores plot

PCA Loadings plot

6 1,0 5

TPP/Dia27

C18 4

Hop/St

3

TPP (ng/mg) ß-carotano (ng/mg) 0,5Gamacerano (ng/mg)

C15 C08 C01

1

C12 C13 0 -1

C14 C03

C06 C02 C09C05C10 C11 C17 C16

C07

H30/C27 aaa Tr23/H30

H29/H30 TeT24/H30 Gam/H30

Factor 2 : 18,92%

2

ß-carotano/H30 0,0

Ts/Tm (Tr28+Tr29)/Hop H31R/H30 H35/H34

-2

-0,5

St/Hop

C04

-3 -4

-1,0 -5 -10

-8

-6

-4

-2

0

2

4

6

8

-1,0

-0,5

Factor 1: 36,62%

0,0

0,5

Factor 1 : 36,62%

Figure 5. PCA scores (a) and loadings (b) plot based on saturated hydrocarbon compound source parameters.

2000

1600 [Gam] ng/mg

Factor 2: 18,92%

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 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 38 of 51

1200 y = 2.396x + 84.996 R² = 0.9549 800

Campos Basin Linear (Campos Basin)

400

0 0.00

200.00 400.00 600.00 [TPP] ng/mg

800.00

Figure 6. Graphic of TPP versus gammacerane concentrations (ng mg–1) for oils from Campos basin, showing correlation based on the coefficient of determination (R2) higher than 0.9.


1,0

Page 39 of 51

(a)

(b)

PCA Scores plot

PCA Loadings plot

7 1,0 6 5

b a 25,28,30TNH/H30 25,28BNH/H30 25,28,30TNH/H30 a

C07

4

0,5

3 2

C13 C12 C18 C14 C03 C05 C17C06 C16

1 0

Factor 2 : 23,80%

Factor 2: 23,80%

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 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Energy & Fuels

C10

C15

H35 hopane index

0,0

25,30BNH/H30 Steranes ratio

C08 C04

C02 C09

-1

25,28BNH/H30 b

25,30BNH/H30 b 25NH/H30 b 25NH/H30 a

-0,5

C11

C01 -2 -3

-1,0 -4 -7

-6

-5

-4

-3

-2

-1

0

1

2

3

4

5

6

Factor 1: 34,67%

-1,0

-0,5

0,0

0,5

Factor 1 : 34,67%

Figure 7. PCA scores (a) and loadings (b) plot based on saturated hydrocarbon compound biodegradation parameters. Indices a and b in the parameters indicate m/z 191 and 177 (to the numerator), respectively.


1,0

Energy & Fuels 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 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 40 of 51

Figure 8. GC×GC–TOFMS EIC m/z 191 and 205 from saturated hydrocarbon fraction from C11 oil showing H31S: 17α(H),21β(H)-30-homohopane (22S), H31R: 17α(H),21β(H)-30-homohopane

(22R),

3βMH31:

3β-methyl-17α(H),21β(H)-30-

hopane, Gam: gammacerane, M31(S+R): 17β(H),21α (H)-30-homohopanes (22S+22R), H32S:

17α(H),21β(H)-30-bishomohopane

(22S),

H32R:

17α(H),21β(H)-3030


Page 41 of 51 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 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Energy & Fuels

bishomohopane (22R), 2αMH32S: 2α-methyl-17α(H),21β(H)-30-bishomohopane (22S), 2αMH32R: 2α-methyl-17α(H),21β(H)-30-bishomohopane (22R), 2αMH33S: 2αmethyl-17α(H),21β(H)-30-trishomohopane

(22S),

2αMH33R:

2α-methyl-

17α(H),21β(H)-30-trishomohopane (22R).


Energy & Fuels 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 34 35 36 37 38 39 40 41 42 43 44 45 46 47

Page 42 of 51

Figure 9. (A) GC×GC–TOFMS EIC m/z 232 for short methyl steranes: 3βMDia21βα (C22 13β,17α(H)-3β-methyldiapregnane), 3βMSt21ααα (C22 3β-methylpregnane) and 3βMSt21αββ (C22 3β-methyldiginane); mass spectra of: (B) C22 3β-methylpregnane; (C) C22 3β-methyldiginane.

32


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Energy & Fuels

AUTHOR INFORMATION Corresponding Author *E-mail: [email protected]

Author Contributions The manuscript was written through contributions of all authors. All authors have given approval to the final version of the manuscript.

ACKNOWLEDGEMENTS The authors thank Capes, CNPq and FAPERJ (Brazilian research councils) and PRH20-ANP (Brazilian Petroleum Agency) for scholarships and financial support.

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