2. WA Organic and Isotope Geochemistry Centre, and John de Laeter Centre, the Institute for Geoscience Research, Department of Applied Chemistry, Curtin University of Technology, Perth WA 6845, Australia
Conventional molecular biomarkers (e.g., steranes, terpanes) from mature or high mature condensate usually cannot be accurately identified in conventional gas chromatography mass spectrometry (GC-MS) analysis due to low content and low signal-to-noise ratio (Chen et al., 1996). Moreover, lots of information in the light hydrocarbons of condensate cannot be effectively revealed using conventional GC-MS analysis due to co-elution (Li et al., 2012). Instrumental methods such as GC×GC-TOFMS and GC-IRMS as in structural investigations of organic geomacro-molecules, have provided a wealth of useful information on condensates. The application of GC×GC-TOFMS has been recognized as a powerful method for solving co-elution problems (Aguiar et al., 2010; Ventura et al., 2010), which can help identify novel compounds and geochemical indicators (Ventura et al., 2012; Aguiar et al., 2011).
The gas chromatography-isotopic ratio/mass spectrometry (GC-IRMS) analytical technique permits continuous flow determination of carbon isotopic values of individual components in complex mixtures of geochemical interest (Freeman et al., 1990; Hayes et al., 1990, 1987; Matthews and Hayes, 1978). This method has been successfully applied to investigate the characteristics of specific components in the saturate hydrocarbon fraction to establish oil-oil and oil-source rock correlations (Inaba and Suzuki, 2003; Li et al., 1997). Many researchers have applied this technique to evaluate the presence of unusual polycyclic alkanes in extracts of source rocks and crude oils where hopanoids and steranes were either absent or present in extremely low abundance samples (Zhu et al., 2003; Schaeffer et al., 1994).
The East China Sea Shelf Basin (ECSSB) is China's largest offshore basin with good exploration prospects. Previous biomarker parameter studies show that the condensates in this area are usually derived from terrestrial organic matter and most formed in the oxidation sedimentary environment (Zhu et al., 2012), however, this information is insufficient for the analysis of oil-source correlation as many source formations are present in similar sedimentary environments which make it hard to distinguish the characteristics of each formation. This study aims to examine the natural compositions of condensates and carbon and hydrogen isotopic values of n-alkanes from the ECSCB using GC×GC-TOFMS and GC-IRMS in order to effectively distinguish their depositional environments and source input. This study benifits further oil-oil correlations or oil-source rock correlations in this area.1 BACKGROUND AND ANALYZING METHOD 1.1 Geological Setting
The East China Sea Shelf Basin is China's largest offshore basin with an area of about 2.4×105 km2. This basin can be further subdivided into several depressions that formed at different stages of tectonic development. Among them, Xihu depression and Lishui depression have been two focal points for intensive petroleum exploration in ECSSB (Dai et al., 2014; Cukur et al., 2012; Li et al., 2009; Yang et al., 2004). Developed on Pre-Cambrian and Paleozoic metamorphic basement, the sedimentary sequence, with approximately 10 000 m in maximum thickness, consists of fifteen formations (Fig. 1).
So far, four hydrocarbon-bearing formations have been identified in the Xihu depression, including the Baoshi, Pinghu, Huagang and Longjing formations from bottom to top. Economic oil and gas reservoirs are mostly distributed in the Pinghu and Huagang formations, while gas-bearing intervals identified in Lishui depression are located in the Mingyuefeng Formation.1.2 Sample Collection, Column Chromatography and 5Å Molecular Sieving
Seven typical condensate samples were collected from the Mingyuefeng, Pinghu and Huagang formations. The physical property characteristics of these condensates are shown in Table 1.
Saturated hydrocarbon, aromatic hydrocarbon and non-hydrocarbon (polar/resin/NSO) fractions were chromatographically separated on a column (25 cm×1 cm i.d.) of neutral alumina over silica gel (120 ℃, 8 h). Saturated fractions were eluted with hexane (40 mL), the aromatic hydrocarbon fraction with a mixture of n-hexane and DCM (40 mL, 7 : 3, v : v) and the polar (NSO) fraction with a mixture of DCM and MeOH (40 mL, 1 : 1, v : v).
Then, the total saturated hydrocarbon fraction was separated into normal alkane and branched/cyclicalkane fractions through 5Å molecular sieves before gas chromatography isotope ratio mass spectrometry (GC-IRMS) analysis to reduce problems with coelution of compounds and to enhance the precision of carbon isotopic analysis. Specifically, samples in cyclohexane was added to a 2 mL vial, 3/4 of it filled with activated 5Å molecular sieves. The vial was capped and placed into an oven (80 ℃, overnight). The resulting solution was then cooled and filtered through a small column of silica plugged with cotton wool (pre-rinsed with cyclohexane) and the sieves were rinsed thoroughly with cyclohexane yielding the branched/cyclic fraction (5Å excluded). The n-alkanes were recovered by dissolution of the sieve with HF (2 mL, 50% w/v), followed by neutralization with saturated sodium bicarbonate solution. The aqueous phase was extracted with n-pentane (1 mL×5). This fraction contained n-alkanes suitable for gas chromatography-isotope ratio mass spectrometry (GC-IRMS) analysis.1.3 GC-MS Analysis
GC/MS analyses of hydrocarbons were carried out at Curtin University of Technology using an HP 6890 gas chromatograph interfaced to an Agilent 5975 mass-selective detector. Instrument analytical conditions were described in Grice et al. (2008). Biomarkers were identified by their retention times and comparison to published mass spectral data (Freeman et al., 1990).1.4 GC×GC-TOFMS Analysis
Analyses were performed at Curtin University of Technology using a Pegasus 4D GC×GC-TOFMS instrument LECO (St. Joseph, Michigan, USA) consisting of an Agilent 7890A GC equipped with a liquid nitrogen-cooled pulse-jet modulator. The GC column system consisted of a primary Rxi-5MS (60 m×0.25 mm×0.25 μm) column and a secondary RXi-17MS (1.5 m×0.18 mm×0.18 μm) column. The GC was operated in splitless mode (1 μL of a 5 mg/mL deasphalt and depolar oil injected at 310 ℃) using He as a carrier gas at a constant flow of 1 mL/min. The primary oven temperature program was from 40 ℃ (1 min hold) to 320 ℃ at a rate of 2 ℃/min and the secondary oven temperature held 5 ℃ higher than the primary. The modulator temperature was 15 ℃ higher than the primary oven, and the modulation period was 3 s with a 0.5 s hot-pulse time. The TOF-MS detector signal was sampled at 100 spectra/s with a scan range of 45-550 amu. The transfer line was held at a constant temperature of 315 ℃ and the TOF source temperature was 250 ℃.1.5 Compound Specific Isotope Analysis (CSIA)
Carbon isotope ratios of n-alkanes and aromatics, compound specific deuterium analysis of n-alkanes were measured using a HP 6890 GC coupled to a Micromass Iso Prime isotope ratio mass spectrometer coupled to a HP 6890 GC at Curtin University of Technology. Details of the instrument and analytical conditions are described in Grice et al. (2008). A standard mixture of n-alkanes (n-C12 to n-C32) was used daily to test the performance of the instrument. For the carbon analysis, average values of at least two analyses of each sample and with a standard deviation of less than 0.4‰ were reported and for the deuterium analysis, average values of at least three analyses of each sample and with a standard deviation of less than 4‰ were reported.
Carbon and hydrogen isotopic compositions are reported using the V-PDB (Vienna PeeDee Belemnite) for carbon and standard δ-notation relative to V-SMOW (Vienna Standard Mean Ocean Water) for hydrogen.2 RESULTS AND DISCUSSION 2.1 Basic Geochemical Parameters
The basic geochemical parameters for the selected samples are reported in Table 1. The thin liguid chromatography flame ionization detector (TLC-FID) analysis shows that the saturated hydrocarbon accounted for a significant proportion (ca. 80%-89%) of the samples. Specifically, the samples from the Huagang Formation show higher concentrations of saturate hydrocarbons, followed by the samples from the Pinghu Formation, then the Mingyuefeng Formation. The aromatic hydrocarbon, NSO and asphaltene fractions had similar concentrations for these samples.
The total carbon preference index (CPI) from n-C15 to n-C35 (Bray and Evans, 1961) ranges between 1.08 and 1.50, reaching their thermal evolution equilibrium interval. The maturity indicators (i.e., C29 20S/(20S+20R), C29 ββ/(αα+ββ)) also reach their thermal evolution equilibrium intervals, which are 0.52-0.55 and 0.61-0.71 respectively (Seifert and Moldowan, 1986). The methyl-phenanthrene index (MPI) maturity indicator was homogeneous with a range between 0.7 and 1.0.
The light hydrocarbons are abundant in high mature condensate samples analyzed in this study. In general, the low molecular weight hydrocarbons (n-C11-n-C20, LMWH) are more abundant than the higher molecular weight hydrocarbon (> n-C25, HMWH) (Table 1). The samples show low or absent of gammacerane with its index ranging from 0.05 to 0.12, indicating low salinity and water stratification in depositional environment.
The pristane/phytane ratio has been extensively used in organic geochemistry. Pristane and phytane originate from the oxidation (and subsequent decarboxylation) and reduction of the phytol side chain of chlorophyll, respectively. The generation of pristane and phytane is significantly controlled by the oxic or anoxic conditions during sedimentation with aerobic degradation promoting pristane (Didyk et al., 1978; Powell and McKirdy, 1973). The ternary diagram of pristane/phytane (Pr/Ph), Pr/n-C17, Ph/n-C18 distribution has been widely used to investigate the organic facies of parent source. These biomarkers suggest that all the condensate samples were deposited in limnetic facies (Fig. 2a).
The molecular composition of the sterane series was generally marked by a predominance of C29 sterane over C27 and C28 steranes. C27, C28 and C29 compounds (αααR), implying a strong contribution of higher land plants versus aquatic organisms. However, the sample x-7 is a special case with relatively high concentration of C27, indicate relatively higher aquatic organisms contribution.2.2 Comprehensive GC×GC-TOFMS Characterization 2.2.1 Bulk composition of condensate
A total of eleven groups of compounds were classified (Fig. 3) including n-alkanes, iso-alkanes, cyclic alkanes and aromatic hydrocarbons. Normal alkanes were in the range of n-C3 to n-C31. Mono-, bi- and tri-cyclic aromatics were also present. Compounds (e.g., alkyl cyclohexane, alkyl cyclopentane and diamondoids) that cannot readily be identified using conventional chromatography were resolved by GC×GC-TOFMS.2.2.2 Long chain alkylated cyclic alkanes
As important components of gas condensate (Williams et al., 1988), naphthenic compounds accounted for a large proportion of the condensate samples. Among them, alkyl-cyclohexanes and alkyl-cyclopentanes are two types of biologically characteristic compounds which have been considered as possible indicators of as biosynthetic precursors, maturity, and postdepositional processes (Fowler et al., 1986; Rubinstein and Strausez, 1979). The origins of n-alkylcyclohexanes and methyl-n-alkylcyclohexanes were not able to be determined because both algal and bacterial sources are related to the occurrence of n-alkylcyclohexanes. Thermoacidophilic bacterium Bacillus acidocaldarius which has C17 and C19 n-cyclohexyl acids as dominant fatty acid components (Oshima and Ariga, 1975; de Rosa et al., 1972) was proposed to be responsible for the n-alkyl-cyclohexanes in some sediments. The possibility of n-alkyl-cyclohexanes derived from the cyclisation of straight-chain algal fatty acids has also been proposed (Johns et al., 1966) and demonstrated experimentally by finding both n-alkyl-cyclohexanes and methyl-n-alkyl-cyclohexanes among the products of saturated and unsaturated fatty acids following heating with a clay catalyst (Rubinstein and Strausez, 1979). Also, Spiro (1984) has suggested that alkyl-cyclohexanes may be derived from cracking of the kerogen at high temperatures under the influence of certain minerals (Fowler et al., 1986).
The long side chain substitution cyclohexane and cyclopentane studied previously by GC-MS usually concentrated in the carbon number < C8, with little attention given to > C9 due to their low abundance and vulnerability to the interference of alkane compounds which make tem difficult to be resolved. However, these compounds were much better resolved using GC×GC-TOFMS.
Characterisation by GC×GC-TOFMS analysis of the x-1 condensate (Fig. 3) shows peak markers for the mono alicyclic hydrocarbons are well resolved from the n- and iso-alkanes. The separation of the alkylcyclopentane and alkylcyclohexane series is revealed in Fig. 4 and identification provided in Table 2. Using GC×GC chromatography these two series of compounds can be qualitative and quantitative identified (Ventura et al., 2010).
The relative abundances of each of the alkyl-cyclohexanes are shown in Fig. 5. It can be seen that the relative abundances of alkyl-cyclohexanes decrease dramatically from C1-C5 branched chain alkyl-cyclohexane but much less so for the branched C6-C17 alkyl-cyclohexanes. The ∑(C1+…+C5)-cyclohexane/∑(C6+…+C16)-cyclohexane ratio versus the methyldiamantane index (4-methyldiamantane/(1-+3-+4-methyldiamantane)) (Fig. 6) show positive correlation indicating that the ratio is probably associated with maturity and might be used as an additional maturity parameter. As discussed above, the samples are from similar origin precursors, therefore origin precursors are ruled out as effect factors of the change in ∑(C1+…+C5)-cyclohexane/∑(C6+…+C16) ratio. However, if the ratio is affected by post depositional processes further investigation is required.
The isomerization of cyclohexane to methylcyclopentane has been discussed previously (Triwahyono et al., 2005) and show that the conversion of cyclohexane is drastically reduced when hydrogen is absence. Hence, compared with cyclopentane, cyclohexane is more stable in oxidation conditions. The Pr/Ph ratio is widely used as an oxidation-reduction environment indicator, and high value of Pr/Ph usually corresponds to strong oxidizing environment. The strong positive correlation between Pr/Ph and alkyl-cyclohexane/alkyl-cyclopentane (Fig. 7) is in agreement with the cyclohexane isomerization, suggesting that the alkyl-cyclohexane/alkyl-cyclopentane ratio can be used as an available oxidation-reduction environment indicator.2.2.3 Diamondoid hydrocarbons
The diamondoids are cagelike structures usually abundant in condensates, organic-rich rocks and coals (Wei et al., 2006; Dahl et al., 1999). They comprise adamantanes with one cage, diamantanes with two cages and triamantanes with three cages etc. Because of this highly stablecage structure, they resist thermal decomposition, and thus can be used to assess thermal destruction of oil (Wei et al., 2007). However, the diamondoids are typically present at relatively low concentrations are co-elute when analysed by conventional GC-MS (Li et al., 2012). By contrast, GC×GC-TOFMS improves the resolution and separation efficiency of the compounds (Li et al., 2014, 2012). Using GC×GC-TOFMS, 17 adamantanes and 8 diamantanes were detected in all analysed condensate samples (Fig. 8, Table 3).
Two diamondoid hydrocarbon ratios (MAI-methyl adamantane index (1-MA/(1-MA+2-MA)), and MDI-methyl adamantane index (1-MD/(1-MD+3-MD+4-MD)), were first proposed by Chen et al. (1996) as maturity parameters responsible for high-mature to over-mature crude oils and source rocks (Ro=0.9%-2.0%). The follow-upstudy by Li et al. (2012) suggested that adamantane and diamantane indices can be used for oil correlation and maturity determination of oils that have undergone evaporation (Li et al., 2014).
The maturity level of the oil samples estimated by MDI values (Table 4) ranges from 0.94% to 1.44%, higher than the maturity based on the conversion of MPI. The discrepancy between MPI and MDI maturity indicator might due to different phases of petroleum charging, which is commonly seen in this study area (Ye et al., 2006). Specifically, the methylphenanthrenes might be related to the low maturity petroleum charging in the early period and the methyldiamantanes might be associated with the high maturity petroleum charging in the late period.
The δ13C and δD values of individual n-alkanes (n-C12 to n-C33) are summarized in Figs. 10, 11, respectively. The δ13C values of individual n-alkanes appear to be divided into two categories, whereas the δ13C values of Neogene condensate samples fall within a narrow range from -27‰ to -31‰. It is worth noting that one Paleogene sample x-7 is significantly more positive in δ13C with its value ranging from -26‰ to -27.5‰. As the maturities of these samples are similar, the δ13C value difference between the samples is likely to be the result of the different biosynthetic precursors. Previous studies have shown that n-alkanes from aquatic organisms have relatively positive δ13C n-alkanes from terrestrial plant (Hayes et al., 1987) which is consistent with the above results of C27, C28 and C29 compounds analysis that x-7 have higher aquatic organisms that other samples.
The hydrogen isotopic composition of alkanes in crude oils is controlled by three factors: isotopic compositions of biosynthetic precursors, source water δD values, and postdepositional processes (Wang and Huang, 2003). A large variation was observed in the δD of individual n-alkanes from the samples analyzed. In general, two types of hydrogen distribution were apparent: Group Ⅱ includes sample x-5 and x-7, and the remaining samples belong to Group Ⅰ. The isotopic profile shape of Group Ⅰ appears to be flat in the whole range except for a slight increasing trend in carbon chain length from n-C13 to n-C15. By contrast, the isotopic profile shape of Group Ⅱ show noteworthy unimodal distribution with the most positive δD value at n-C15.
δD composition of n-alkane from mature oils or sediments usually remain constant with slight increasing trend with increasing chain length (Dawson et al., 2007, 2005; Pedentchouk et al., 2006; Radke et al., 2005; Schimmelmann et al., 2004). This differential fractionation effect is speculated to be due to the combined effect of the greater extent of thermal cracking of higher molecular weight n-alkanes compared to lower molecular weight homologues, and the generation of isotopically lighter, lower molecular weight compounds. This differential fractionation proceeds significantly at higher maturity (Ro > 1.0%) (Tang et al., 2005). The depleted δD values with carbon chain length showed in x-5 and x-7 is likely to be attributed to the biosynthetic precursors effect. The n-alkane δD values from C3 angiosperm tree and C3 angiosperm herb plants are reported to have decreasing trend with increasing carbon number (Chikaraishi and Naraoka, 2007). The x-5 and x-7 samples are therefore likely to have more δD depleted biosynthetic precursors.
Previous studies show that the thermally induced hydrogen fractionation of individual n-alkanes in crude oil are less than 10‰ when their Ro are under 1.3% (Tang et al., 2005). The similar maturity of Group Ⅰ samples rule out maturity as a factor for the variation within Group Ⅰ. In addition, the similar sampling location and depth of x-1 and x-2 (Table 1) rule out the source water δD values as an influence factor. Therefore, the variation within the group is more likely to be affected by postdepositional processes, e.g., evaporation and biodegradation are reported to be the main postdepositional processes which affect the δD values in n-alkanes. As there is no sign of biodegradation in these samples, the effect of vaporization was explored.
A vaporization experiment was carried out in a laboratory with temperature (24±1 ℃) and humidity (22%±1%) control. The samples were allowed to evaporate in a fume hood with an air velocity of 81 ft/min without any agitation for 12 h. Sample x-5 was used for the evaporization experiments 81% the starting compounds were left in the vial after evaporite for 12 h. The δD values of the residual n-alkanes became more negative by 4‰-30‰. Therefore, we suggest that the variation of δD values within Group Ⅰ samples might be result from different degrees of evaporation.3 CONCLUSION
Conventional GC-MS analysis of condensate samples from ECSSB was not able to provide sufficient information on depositional environments and source input, and failed to distinguish these condensates. The combination of GC×GC-TOFMS and CSIA analyses provided additional information concerning the maturity, environment and postdepositional processes involved in the production of these condensates and enabled them to be distinguished from each other. These observations indicate that GC×GC-TOFMS and CSIA analyses could be regarded as effective methods to distinguish condensates with relatively low content of biomarkers and shows potential for further oil-oil correlation or oil-source rock correlation.
The long side chain substitution cyclohexane and cyclopentane, and diamandoids, that can be difficult to resolve and identify using the conventional gas chromatography can be more readily identified by GC×GC-TOFMS. A new maturity indicator, C5--cyclohexane/C5+-cyclohexane, and a new oxidation-reduction environment indicator, alkyl-cyclohexane/alkyl-cyclopentane, was proposed, but further verification is required.
Discrepancies were observed for the maturity indicators, MPI and MDI. One explanation for this is that the relatively high molecular weight methylphenanthrene was derived mainly from an early petroleum charging with low maturity, and the methyldiamantane derived mainly from a late petroleum charging with high maturity.
The Paleogene samples have significantly more positive δ13C values of individual n-alkanes than the Neogene samples. δD values of n-alkane could divide samples into two groups; the variation between the two groups is likely to be attributed to different biosynthetic precursors and the variation within the group is more likely to be affected by vaporization.ACKNOWLEDGMENTS
This study was sponsored by the National Science and Technology Major Project of China (Nos. 2016ZX05024-002-003, 2016ZX05027-001-005). The final publication is available at Springer via https://doi.org/10.1007/s12583-018-1001-3.
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