The first method, a combination of chromatographic column-aided extract separation from actual crude oil samples and hydrocarbon source rock samples with GC-MS, is a qualitative and quantitative analysis method for diamondoids, which has been developed earliest and widely applied (Wingert, 1992; Chen et al., 1996; Grice et al., 2000; Li et al., 2000; Schulz et al., 2001; Zhang et al., 2005).

Crude oil or hydrocarbon source rock samples are usually accompanied by the interference of complex matrix components. Despite high selectivity of GC-MS, the signal of target analytical compounds will still be obscured by the interference of complex matrix components in the analysis results of samples, especially in case of the low concentration of target analytical compounds. Before the actual crude oil samples and hydrocarbon source rock extracts are analyzed via GC-MS, therefore, the interference of the complex matrix is usually eliminated by separating their group components through chromatographic column separation technology, while the target analytical compounds are concentrated and enriched using solvent volatilization (Wingert, 1992; Chen et al., 1996; Grice et al., 2000; Li et al., 2000; Schulz et al., 2001; Zhang et al., 2005). During instrumental analysis, the selective ion monitoring (SIM) mode in GC-MS can enhance the detection signal of diamondoids and improve the sensitivity of target compound analysis. Therein, ions with m/z of 136, 135, 149, 163, 177, and 191 are commonly applied to detect diamantane compounds, those with m/z of 188, 187, 201, 215, and 229 to diamantane compounds, and those with m/z of 240 and 239 to triamantane compounds.

During the separation of group components, condensate gas and gasoline can be directly injected under natural conditions, aiming to avoid the possible volatilization loss of diamondoids. The spectrogram results reveal that in the nonpolar chromatographic column, adamantane peaks earlier than n-C11 (Stout and Douglas, 2004). However, the injection system and chromatographic column of GC-MS will be polluted by complex matrix components and non-paraffinic components with high molecular weights in crude oil samples and hydrocarbon source rock extracts, leading to the reduction of column efficiency. Therefore, this detection and analysis means for diamondoids, i.e., direct injection, does not apply to crude oil and hydrocarbon source rock samples.

During chromatographic column separation and sample concentration, moreover, evaporation may result in the loss of diamondoids, or cause the deviation of quantitative results, thus affecting the analytical research based on the concentration of diamondoids. Hence, developing the quantitative detection and analysis method integrating the nondestructive pretreatment method with the high-selectivity and high-sensitivity detection method is essential for describing and exploring low-concentration diamondoids in crude oil and hydrocarbon source rock samples.

GC-MS-MS, a highly sensitive and selective instrumental analysis method, eliminates the interference of matrix ions mainly through the selected-reaction monitoring (SRM) mode, without needing any complicated sample pretreatment or purification and separation technology before injection (Frenich et al., 2005; Hernandez et al., 2005). Under the SRM mode of GC-MS-MS, the parent ion of the set target compound is selected when passing through the first quadrupole and then collides with argon molecules in the second quadrupole. Afterward, the resulting fragment ions pass through the third quadrupole, followed by the selection, detection, and analysis of daughter ions corresponding to the target compound in the fragment ions. Thanks to this selection and detection process of GC-MS-MS, the limit of quantification (LOQ) and limit of detection (LOD) of the instrument are reduced, leading to the analysis and detection results of target compounds as low as several ppb (Hernandez et al., 2005; Qu et al., 2010).

For diamondoid detection and analysis, methyl diamantane (MD) compounds in crude oil were quantitatively detected and analyzed at the earliest by monitoring the m/z202+-187+ conversion process (Dahl et al., 1999).

Afterward, Liang et al. (2012b) optimized GC-MS-MS parameters like parent and daughter ions, collision energy, and scanning time using standard diamondoid samples, and then established a complete GC-MS-MS quantitative analysis method for diamondoids. Under the optimal operating parameters of the instrument, good linear relationships were manifested in the standard curves of 10 standard diamondoid samples, and the correlation coefficient (R2) characterizing linear correlations was always higher than 0.9980. In this process, all target diamondoids presented good repeatability, with a relative standard deviation of 1.3%–5.1% (n = 5). The LODs and LOQs of all target diamondoids in oil samples obtained by this method were 0.02–0.11 and 0.08–0.37 μg/g, respectively. The above data manifested the good applicability of this method to quantitative detection and analysis of diamondoids, especially for samples with a low concentration of diamondoids.

Under the SRM mode and optimal operating parameters, GC-MS-MS displays the maximum sensitivity and selectivity for the quantitative analysis of diamondoids in crude oil samples. Besides, this technology can eliminate the interference of co-eluted compounds in crude oil samples and hydrocarbon source rock extracts by monitoring the transformation process of paired parent ions and daughter ions, with high selectivity. In the meanwhile, its high sensitivity can compensate for the low concentration of diamondoids in samples due to the absence of concentration and enrichment pretreatment. Therefore, GC-MS-MS can serve as an effective means for the reliable quantitative analysis of diamondoids in actual samples, only needing simple sample dilution.

As a new technology developing on the basis of the traditional 2D technology in the 1990s, comprehensive 2D GC×GC characterized by good sensitivity, high resolution, large peak capacity (the product of the peak capacities of two chromatographic columns), fast analysis speed, qualitative analysis with rules to follow, family separation, and tile effect (Frysinger and Gaines, 1999; Lu et al., 2005; Ruan et al., 2002) can be used to separate complex mixtures. Specifically, this technology connects two relatively independent chromatographic columns differing in the separation mechanism and stationary phase (e.g., nonpolar column and chiral column or polar column) in series to form a 2D GC column system by using a modulator with the functions of trapping, focusing, and transmission.

TOFMS, a common MS technique, realizes separation and determination based on different time taken by moving ions with different mass-to-charge ratios and the same kinetic energy in a steady electric field to reach the receiver. This technique is characterized by a wide detectable mass range, fast response speed, and high sensitivity (Zhao and Shen, 2006). If combined with GC×GC, TOFMS is applicable to qualitative and quantitative analysis of compounds in complex systems (Lu et al., 2004b).

GC×GC and GC×GC-TOFMS have been applied to such fields as tobacco, food, wine making, petroleum geology, refined oil products, and environmental monitoring (Schoenmakers et al., 2000; Frysinger and Gaines, 2001; Hua et al., 2002; Frysinger et al., 2003; Lu et al., 2004a; Lu et al., 2007; Ventura et al., 2008). On this basis, Wang et al. (2010) established an analytical detection method for diamondoids in actual crude oil samples by optimizing parameters like column system selection, temperature program, modulation period, hot-air blowing time, and the flow rate of the carrier gas.

However, the pretreatment method can not only remove the interference of other compounds on diamondoids, but also improve the concentration of diamondoids. Therefore, scholars are also constantly improving the pretreatment process of this method to reduce the loss of adamantanes in the pretreatment process (Wang et al., 2019). In addition, scholars have been developing quantitative analysis of diamondoids with higher carbon number (such as triamantane, tetramantane) and more complex structure (such as ethanodiamondoids) (Wang et al., 2019; Ma et al., 2022).

The concentration of diamondoids in crude oil and source rock extracts has been investigated in oil and gas geochemistry. For instance, the relative abundance of diamondoids in light oil and condensate gas can serve as an important “fingerprint” tool to identify the sources of oil spill events (Stout and Douglas, 2004).

According to the theory of Dahl et al. (1999), moreover, once formed, diamondoids will be neither destroyed nor produced again. It is believed, therefore, that the increase in the concentration of diamondoids in oil results from the thermal degradation of most other non-diamondoids in oil (Dahl et al., 1999). Given this, Dahl et al. (1999) proposed that the cracking degree of crude oil can be evaluated by an effective index, the concentration of 3-+4-MD (Figure 5) (Dahl et al., 1999), which has been applied in some studies (Wei Z. B. et al., 2007; Springer et al., 2010). Here, we need to pay attention to the selection of baseline concentration for different regions (Springer et al., 2010).

However, Wei et al. (2006b) explored the thermal maturity-dependent changes in the concentration of diamondoids in a set of coal and sedimentary rock samples with a maturity range of Ro=0.20%–6.40%. The quantitative results of diamondoids in coal and source rock extracts manifested that the concentration of diamondoids began to decrease after Ro>4.0% (Wei et al., 2006b). It was also found that some diamondoids can also be thermally cracked to aromatic hydrocarbons under high temperatures (Oya et al., 1981; Schoell and Carlson, 1999; Wei et al., 2006b). As the research deepens, scholars have found that the diamondoids continuously enriched in the cracking process of crude oil may be ascribed to two aspects: the cracking of relatively unstable hydrocarbons in crude oil (Dahl et al., 1999), and the sustained production of diamondoids (Wei et al., 2006c; Fang et al., 2012). Dahl et al. (1999) evaluated the cracking degree of crude oil based on the cracking of relatively unstable hydrocarbons in crude oil, in which the total amount of diamondoids is assumed to be constant. Therefore, this parameter is still applicable at the stage of constant content (EasyRo<2.0%) (Fang et al., 2013), while it needs to be carefully judged at the stage of changing content.

Among diamondoids, the homologous compounds differing in thermal stability are formed due to the different substitutions on each substituent. For homologous diamondoids formed by the same alkyl substitution, for example, the compounds substituted at “bridge” carbon positions (positions 1, 3, 5, and 7 of adamantane in Figure 1) display higher thermal stability than those substituted at the corresponding “quaternary” carbon positions (positions 2, 4, 6, and 8 of adamantane in Figure 1). In other words, for adamantane compounds with the same methyl substitution, 1- methyl adamantane (MA) formed by methyl substitution at the “bridge” carbon position shows higher thermal stability than 2-MA (Wingert, 1992) (Figure 1). For diamantane compounds with the same methyl substitution, 4-MD formed by methyl substitution at the “bridge” carbon position presents better thermal stability than the other two homologous isomers (1-MD and 3-MD) (Wingert, 1992; Chen et al., 1996).

Based on the aforesaid thermal stability relationships, Chen et al. (1996) also established the ratio parameters of diamondoids, namely, MA index [MAI=1-MA/(1-MA + 2-MA)] and MD index [MDI=4-MD/(1-MD + 3-MD + 4-MD)]. In the meanwhile, they pointed out that these ratios increased with the increase in the thermal maturity of crude oil and hydrocarbon source rocks. Then, such indexes were used to evaluate the maturity of condensate oil samples with a high evolutionary degree in Tarim Basin, and the corresponding Ro was 1.6%–1.7%. The Ro of condensate oil in Ying-Qiong Basin was obtained in a similar fashion as 1.6%–2.0%.

Following this rule, many adamantane maturity parameters have been established in the existing studies and applied in practice. For instance, MAI and MDI have been adopted to evaluate crude oil and hydrocarbon source rocks (Chen et al., 1996; Schulz et al., 2001; Wei et al., 2006b, Wei et al., 2007 Z.). In addition, dimethyl adamantane index-1 (DMAI-1), DMAI-2, ethyl adamantane index (EAI), trimethyl adamantane index-1 (TMAI-1), TMAI-2, dimethyl diamantane index-1 (DMDI-1), and DMDI-2 have been applied in simulation experiments and actual geological samples (Schulz et al., 2001; Zhang et al., 2005; Wei Z. et al., 2007). According to the simulation results of crude oil cracking, the relative changes in TMAI-1 and DMA/MD (DMA stands for DMA compounds, including the sum of adamantane compounds formed by dimethyl substitution at different positions. MD denotes MD compounds, including the sum of diamantane compounds formed by methyl substitution at different positions), and DMAI-1 and DMA/MD are also applicable parameters for crude oil maturity (Figure 6) (Fang et al., 2013).

Taking advantages of diamondoids in maturity evaluation, Duan et al. (2007) investigated the distribution characteristics of diamantane parameters of crude oil in Tahe Oilfield, Tarim Basin, analyzed and discussed the charging period and migration direction of oil and gas in this oilfield, and explored the migration direction of crude oil. Bao et al. (2015) analyzed the distribution characteristics of alkyl adamantane and alkyl diamantane compounds in condensate oil in Zhujiadun, Yancheng Depression, Subei Basin, and that in upper Cretaceous mature hydrocarbon source rocks in Taizhou Formation, as well as their parameters. On this basis, the source of condensate oil was explored, and the comparison with the measured Ro showed that adamantane compounds are practical, to some extent, in the maturity evaluation of crude oil and hydrocarbon source rocks.

Problems exist despite the extensive practical application of adamantane parameters in maturity evaluation. As suggested by the existing studies, MAI and MDI are only applicable in a narrow range of Ro. Li et al. (2000) analyzed the adamantane parameters obtained from the extracts of the hydrocarbon source rocks in lower Ordovician Majiagou Formation in the central gas field of Ordos Basin, China, and thought that MDI changes within 44%–65%, without obvious changes in the area of Ro>2.0%, so it is only applicable in a Ro range of 0.9%–2.0%. However, Schulz et al. (2001) and Wei Z. B. et al. (2007) conducted thermal cracking experiments on actual samples under water-bearing conditions, and held that MAI and MDI are only applicable to the maturity evaluation of samples with Ro>1.3%.

On the other hand, Li et al. (2000) also pointed out no obvious correlation between MDI and sample depth or Ro, which contradicts with the previous conclusion drawn by Chen et al. (1996). As discovered through laboratory simulation of MDI-Ro correlation thermal maturation of hydrocarbon source rocks in different horizons of Ying-Qiong Basin, samples from different horizons are correlated with maturity differently, which also highlights the reliability problem and limitations of adamantane parameters in practical application (Li et al., 2000; Wei Z. et al., 2007).

At present, the research on the genetic types of organic matter in diamondoids is still insufficient. Schulz et al. (2001) proposed for the first time that dimethyl diamantane compounds (4,9-dimethyl diamantane, 4,8-dimethyl diamantine, and 3,4-dimethyl diamantane) show different distribution characteristics in different types of hydrocarbon source rocks (Figure 7). To be specific, marine siliceous clastic rocks of type II kerogen are rich in 4,9-dimethyl diamantane and carbonate rocks are rich in 4,8-dimethyl diamantine, while type III carbon mudstone and coal contain abundant 3,4-dimethyl diamantane. Accordingly, it was pointed out that different types of organic matter can be distinguished using a triangle diagram characterizing the relative content of dimethyl diamantane compounds.

With this triangle diagram, which was considered an effective identification method, Chen et al. (2008) identified the genetic types of organic matter of condensate oil in Jiyang Depression, and concluded that the condensate oil in Jiyang Depression originates from the mixture of coal bed and lake facies.

The existing studies have shown that the difference in some maturity parameters may result from different sources or causes of organic matter during hydrocarbon generation (Li et al., 2015; Jiang et al., 2018). For instance, DMAI-1 and DMAI-2 may be different due to the primary cracking of kerogen at different stages and the secondary cracking of its resulting asphalt (Li et al., 2015). Among the gold tube thermal cracking products of type I and type II kerogen, two bivariant parameters (DMA/MD and TMAI-1, and DMA/MD and DMAI-1) of diamondoids also display different evolutionary characteristics. Even the loss of volatile components of crude oil in the low-mature stage will generate an influence on the maturity parameters of adamantane in the later stage (Fang et al., 2016).

Some scholars have suggested that the application of diamondoids can be extended by deeply exploring their evolutionary characteristics during the thermal evolution of different types of hydrocarbon source rocks (Ma, 2016). As aforementioned, the influence of organic matter types on the composition characteristics of diamondoids has been analytically investigated through gold tube cracking simulation experiments on different types of kerogens (Jiang et al., 2018). However, the difference in composition characteristics is attributed to the combined effects of the primary cracking of kerogen and the secondary cracking of asphalt, which goes against the situation under actual geological conditions. Efforts have been made to distinguish the two effects, but what has been obtained is the staged cumulative generation result of diamondoids in kerogen and its resulting asphalt in three stages: EasyRo0.8%–1.0%, 1.0%–1.3%, and >1.3% (Li et al., 2015).

Biodegradation, a significant transformation process of crude oil in underground oil and gas-bearing basins (Connan, 1984; Peters and Moldwan, 1993; Head et al., 2003), will influence the physical and chemical molecular characteristics of crude oil (Winters and Williams, 1969; Hunt, 1979; Connan, 1984; Peters and Moldowan, 1993) and further affect oil exploitation and refining costs. Moreover, biodegradation can generate important economic impacts on oil (Connan, 1984; Wilhelms et al., 2001; Larter et al., 2006) and strategic impacts on oil exploration (Larter et al., 2012).

A few studies regarding the biodegradation process and degree of crude oil by diamondoids have been reported. Generally, hydrocarbons present consistent overall variation trends and different individual rates in the process of biodegradation (Larter et al., 2006). Accordingly, the evaluation indexes of biodegradation degree have been established in past studies based on the differences in relative abundance and sequentially sensitive structures among different series of compounds (Volkman et al., 1984; Peters and Moldowan, 1993). Following the same principle, Grice et al. (2000) quantitatively detected diamondoids in actual crude oil samples with different degrees of biodegradation, and the results manifested that MA/A (MA stands for MA compounds, including the sum of MA at each substitution position, and A denotes adamantane) will change regularly with the variation of the biodegradation degree, which can serve as an evaluation index of the biodegradation degree and can also be used to identify the mixture of severely biodegradable oil and non-biodegradable oil. Besides, MA/A will not be significantly influenced by the difference in maturity. Wei Z. B. et al. (2007) already applied this parameter in related studies.

Wang et al. (2006), Yang et al. (2013), Grice et al. (2000), Wei Z. B. et al. (2007), and Chai et al. (2022) quantitatively detected diamondoids in crude oil biodegradation products during indoor and outdoor simulations and those in actual crude oil biodegradation products. Results revealed that diamondoids will be affected by biodegradation in actual oil reservoirs, with their content presenting an overall declining trend (Grice et al., 2000; Wang et al., 2006; Wei Z. B. et al., 2007; Yang et al., 2013; Chai et al., 2022). Therein, the decreasing trend of the content of adamantane resembles that of total diamondoids, which is decided by the dominant position of adamantane compounds in diamondoids. The content of diamantane compounds, however, shows a less obvious decreasing trend than that of adamantane compounds, reflecting the better anti-biodegradation ability of diamantane compounds than adamantane compounds. In the meanwhile, triamantane compounds are subjected to minor content changes (Wang et al., 2006; Wei Z. B. et al., 2007). Even if the biodegradation degree reaches the eighth grade defined by Peters and Moldowan (1993), crude oil will still contain diamondoids with a certain concentration (Wei Z. B. et al., 2007), which also effectively guarantees the application of diamondoids in biodegradable oils, especially in highly biodegradable oils.

The application of other parameters in biodegradable oils has also been studied by scholars. Dahl et al. (1999) proposed an effective index, namely, the concentration of 3-+4-MD, to evaluate the cracking degree of crude oil and mixed oil. This method is considered immune to biodegradation (Wei Z. B. et al., 2007). Grice et al. (2000) calculated the MAI and MDI in actual crude oil samples biodegraded to different degrees, and found that the MAI is consistent well, reflecting their similar maturity. However, the MDI varies a lot, which may be associated with the mineral content in source rocks (Grice et al., 2000). In addition, Xu (2007) tested the stability of MAI and MDI in biodegradation, both of which indicated a good anti-biodegradation ability. And the research results of Chai et al. (2022) indicate that no significant biodegradation impact on MAI, EAI, MDI, DMDI-1 and DMDI-2.