Next Article in Journal
Evaporative Fractionation as the Important Formation Mechanism of Light Oil Reservoirs in the Dongying Depression, NE China
Previous Article in Journal
Unmanned Aerial Vehicle (UAV)-Assisted Damage Detection of Wind Turbine Blades: A Review
Previous Article in Special Issue
Carbon Dioxide Oil Repulsion in the Sandstone Reservoirs of Lunnan Oilfield, Tarim Basin
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Classification Method of Heavy Oil Based on Chemical Composition and Bulk Properties

State Key Laboratory of Heavy Oil Processing, Petroleum Molecular Engineering Center (PMEC), China University of Petroleum, Beijing 102249, China
*
Authors to whom correspondence should be addressed.
Energies 2024, 17(15), 3733; https://doi.org/10.3390/en17153733
Submission received: 11 June 2024 / Revised: 15 July 2024 / Accepted: 24 July 2024 / Published: 29 July 2024

Abstract

:
Heavy oil resources in the world are extremely abundant, and viscosity is currently the main reference index for heavy oil classification. However, the diversification of practical issues in heavy oil exploitation, and the refinement of processing and utilization urgently require the support of heavy oil classification with more reference indexes. In this study, the macroscopic properties of typical heavy oils in China were analyzed, and the semi-quantitative analysis of the molecular composition of different heavy oils was completed based on high-resolution mass spectrometry. The results show that heavy oils with similar viscosities can exhibit huge differences in macroscopic properties and chemical composition. According to the evaluation of the chemical composition and macroscopic properties of typical Chinese heavy oils, 12 types of compounds belonging to saturates, aromatics, resins, and asphaltenes (SARA) were identified, establishing a connection between the macroscopic fractions and molecular compositions of heavy oils. By summarizing the comparative results, a new classification criterion for heavy oils was established, focusing on the main parameters of H/C ratio and total acid number (TAN), with sulfur content as a supplementary indicator. H/C is the embodiment of the degree of molecular condensation in the macroscopic properties, reflecting the structural characteristics of the main molecules of the heavy oil. Chinese heavy oil is generally characterized by high TAN, which corresponds to the composition of petroleum acids, and it is also an important reference index for the exploitation and processing of heavy oils. Most Chinese heavy oils have a very low sulfur content, but the presence of sulfur compounds in high-sulfur heavy oils can lead to significant differences in the distribution of compound types among the SARA. This new classification method for heavy oil combines the characteristics of chemical composition of heavy oils, which is expected to provide valuable support for the extraction and processing of heavy oil.

1. Introduction

World heavy oil resources have proven reserves of 9911 × 108 t, with a global annual production scale of around 5000 × 104 t [1,2]. China ranks as the world’s fourth-largest heavy oil resource country, with proven reserves of 4000 × 106 t, and with having discovered over 70 heavy oil fields in 12 basins [3,4,5]. The exploration and processing of heavy oil resources have always been a challenge in the utilization of petroleum resources, with high viscosity being a significant characteristic distinguishing heavy oil from conventional crude oil [6,7,8]. In order to facilitate heavy oil exploitation and processing, as early as 1977, the United Nations Institute for Training and Research (UNITAR) introduced a heavy oil classification standard with viscosity as the first index and density and API gravity as the second index [9]. However, with the increasing diversity of heavy oil types, there are significant differences in the development methods and recovery rates of different heavy oil reservoirs. Yu et al. [10] added reservoir lithology as an auxiliary index in addition to the viscosity index and conducted a more refined classification of heavy oil. Yashchenko and Polishchuk [11] proposed a comprehensive classification method for the physicochemical properties of heavy oil on the basis of analysis and generalization of the published indicators such as density, viscosity, sulfur, resins and asphaltenes content. Subsequently, they introduced a quality index to further refine the classification of heavy oil, and established the physicochemical property characteristics of heavy oils belonging to different quality classes [12]. Bagheri et al. [13] characterized different crude oils using attenuated total reflectance mid-infrared spectroscopy. The obtained spectra were classified using chemometric techniques and a geology-based classification method for crude oils was proposed. Mohammadi et al. [14] combined infrared spectroscopy with chemometric methods to regress and classify crude oils based on API gravity values. These classification methods for heavy oil provide reference for the selection of exploration technologies and processing methods for different heavy oils.
With the increased effort in heavy oil exploration and development, more and more practical problems are exposed in the oil recovery process. Heavy oils with similar viscosities may not yield similar recovery efficiency when using the same development methods [15,16,17]. This indicates that it is difficult to accurately reflect the differences among heavy oils by classification criteria based solely on viscosity. Additionally, with the development of refinement and intelligence in oil processing, there are increasing demands for understanding the chemical composition of heavy oils [18,19]. In conclusion, both the exploration and processing of heavy oil have put forward finer requirements for its classification indexes, especially the indexes reflecting the molecular composition of heavy oil.
Gas chromatography (GC) combined with different detectors is a common method for characterizing the molecular composition of petroleum samples [20,21]. Flame ionization detector (FID) can be used for the analysis of hydrocarbons in crude oil [22]. Gas chromatography-mass spectrometer (GC-MS) can be used for the analysis and identification of biomarkers of saturated and aromatic hydrocarbons in crude oil [23]. Nitrogen chemiluminescence detectors (NCDs) and sulfur chemiluminescence detectors (SCDs) and other selective detectors are able to achieve selective analysis of nitrogen-containing compounds and sulfur-containing compounds in crude oils to a certain extent [24,25]. However, heavy oil generally lacks characteristic hydrocarbons that can be captured by GC techniques, resulting in an increase in the proportion of heteroatomic compounds [18]. It is difficult to gain the chemical composition characteristics of heavy oil through GC techniques. The successful application of high-resolution mass spectrometry (HRMS) in petroleum molecular composition provides a possible way to understand the complex chemical composition of heavy oil [26,27]. Much effort has been devoted to the study of the molecular characterization of petroleum on the basis of various soft ionization techniques combined with HRMS [28]. Qian et al. [29,30] combined electrospray ionization (ESI) with HRMS to selectively ionize and identify nitrogen compounds and acidic oxygen compounds in petroleum. Purcell et al. [31] successfully coupled an atmospheric pressure photoionization (APPI) with HRMS. It realized effective ionization of non-polar compounds in petroleum such as hydrocarbons and sulfur compounds, which are unobservable by ESI. Jin et al. [32] compared atmospheric pressure chemical ionization (APCI) MS with field ionization (FI) MS for the determination of hydrocarbon distribution in lubricant base oils. The paraffinic content of the base oils measured by the two methods was almost the same, and the reproducibility of the APCI-MS was significantly better than that of the FI-MS. Li et al. [33] systematically characterized the molecules of different compounds in fluid catalytic cracking decant oil using various ionization techniques such as ESI, APPI and chemical derivatization with HRMS. The molecular compositions obtained by different ionization techniques were combined and normalized using elemental composition to obtain quantitative results for each detected molecule. However, the ionization efficiency of different soft ionization techniques for different compounds in petroleum varies significantly, and more detailed characterization of the molecular composition of petroleum is becoming increasingly important [34].
Li et al. [35] established a systematic molecular composition analysis method and quantitative scheme on the basis of HRMS with the same ionization source (ESI) to achieve semi-quantitative analysis of molecular composition for petroleum fractions. Wu et al. [36] applied the semi-quantitative analysis method for petroleum fractions to heavy oil and revealed the differences in molecular composition between heavy oil and conventional crude oil. Understanding heavy oil at the molecular level helps to more accurately confirm compositional differences between different heavy oils.
This study will conduct semi-quantitative analysis of molecular composition of typical heavy oils from different regions in China. Through the semi-quantitative analysis results, the molecular composition characteristics of different heavy oils will be obtained, and a classification method that effectively reflects the properties and compositional differences of heavy oil will be established. This new classification method is expected to provide effective support for the evaluation of heavy oil resources and the selection of heavy oil extraction technologies.

2. Experimental Section

2.1. Materials

Eighteen heavy oils were collected from Junggar Basin (6), Tarim oilfield (2), Chagan depression (2), Liaohe oilfield (2), Shengli oilfield (4), and Henan oilfield (2) in China. Analytical grade n-hexane, n-heptane, dichloromethane, toluene, methanol, and ethanol were purchased from Beijing Chemical Reagent Company (Beijing, China), and used after re-distillation and purification. Chromatographically pure carbon disulfide, carbon tetrachloride, acetonitrile, water, sodium periodate, silver tetrafluoroborate, and methyl iodide were purchased from J&K Scientific (Beijing) Ltd. (Beijing, China), and used directly. Chlorosulfonic acid was purchased from TCI (Shanghai) Ltd., (Shanghai, China).

2.2. Properties Analysis

The total acid number (TAN) and viscosity of the heavy oils were analyzed according to the Chinese national standard GB/T 18609 [37] and Chinese industry standards SY/T 0520 [38], respectively. Saturates, aromatics, resins, and asphaltenes (SARA) analysis was conducted according to the Chinese petrochemical industry standard NB/SH/T 0509 [39], which utilizes n-heptane thermal reflux to precipitate asphaltenes. The basic nitrogen content was determined according to the Chinese petrochemical industry standard NB/SH/T 0162 [40]. Elemental analysis of organic carbon and hydrogen were carried out according to the American Society for Testing and Materials (ASTM) standard D5291 [41]; the content of oxygen was analyzed according to ASTM D5622 [42]; the content of sulfur and nitrogen were analyzed through trace element analysis, respectively, following ASTM D5453 [43] and ASTM D5762 [44].

2.3. GC-FID Analysis

GC-FID analysis was performed on an Agilent 7890A gas chromatograph equipped with an HP-5 capillary column (60 m × 0.25 mm × 0.25 µm). The temperature program of the chromatographic oven was set as follows: initial temperature of 40 °C held for 10 min, then ramped up at 4 °C/min to 70 °C, followed by a ramp up at 8 °C/min to 300 °C, held for 40 min. The temperatures of the injector and detector were both set at 300 °C. Split mode was used with a split ratio of 20:1. The carrier gas was nitrogen, with a flow rate of 1 mL/min.

2.4. Semi-Quantitative Analysis of Molecular Composition Using HRMS

HRMS analysis was performed on an Orbitrap Fusion mass spectrometer (Orbitrap MS) manufactured by Thermo Fisher Scientific (Waltham, MA, USA). The Orbitrap MS is equipped with an electrospray ionization source (ESI) that can operate in both positive and negative ion modes. During analysis, the sample being tested was directly injected into the ESI source at a flow rate of 5 μL/min using a micro-injection pump. The sheath gas flow rate was set at 5.0 Arb, the auxiliary gas flow rate was 2.0 Arb, and the ion transfer tube and evaporation temperatures were set at 300 °C and 20 °C, respectively. The mass scanning range was set from 150 to 1000 Da, with an automatic gain control (AGC) value of 5.0 × 105, an accumulation time of 100 ms, and a spectrum scanning time of 2 min. Data acquisition and exporting were performed using Qual Browser Thermo Xcalibur 3.0.63, and data processing and analysis were completed using software developed in the laboratory [45]. The molecular formulae of different compounds obtained after data processing can be expressed as CcHhNnOoSs (c, h, n, o, and s represent the number of elements C, H, N, O, and S in the molecular formula, respectively). The definition of equivalent double bond (DBE) is the sum of the number of cycloalkane rings and the number of double bonds in the molecule, which can be calculated according to Equation (1) [46]. DBE is a reflection of the condensation degree of each molecule. The larger the DBE value, the more condensed the molecule is
D B E = c h 2 + n 2 + 1
Semi-quantitative analysis of the molecular composition of heavy oil has been reported previously [36], and only a brief introduction will be provided here. All molecules in heavy oil can be classified into the following categories: saturated hydrocarbons, aromatic hydrocarbons, sulfur compounds, acidic oxygen compounds, neutral nitrogen compounds, and basic nitrogen compounds. The saturated fraction in SARA was derivatized by RICO and analyzed by −ESI Orbitrap MS to obtain the saturated hydrocarbon composition. The aromatic hydrocarbon composition of heavy oil is analyzed using −ESI Orbitrap MS after sulfonation treatment. The sulfur compound composition of heavy oil is analyzed using +ESI Orbitrap MS after methylation treatment. The composition of neutral nitrogen compounds and acidic oxygen compounds in heavy oil can be obtained directly by −ESI Orbitrap MS. The basic nitrogen compound composition of heavy oil can be obtained through direct analysis using +ESI Orbitrap MS. The above steps lead to the results of the complete molecular composition of the heavy oil. Quantitative analysis of heavy oil molecules is realized by assigning the contents of elements C, H, S, N and O. The specific assignment methods have been described in a previous work and will not be repeated here [36].

3. Results and Discussion

3.1. Bulk Properties

Table 1 lists the result of viscosity, TAN, SARA and element content analyses of typical heavy oils. The viscosities of these heavy oil samples at 50 °C are all above 1500 mPa·s. Generally, there are significant differences in viscosity among heavy oils from different regions, and even within the same region, there can be significant variations in viscosity. Apart from the Tahe heavy oil, most of the heavy oils in China have TAN values exceeding 3 mgKOH/g, classified as high-acid crude oil [47], with the TAN value of Junggar-P601 reaching as high as 11.77 mgKOH/g. In terms of the distribution of the SARA, there are also considerable differences among heavy oils from different regions or even within the same region. The content of saturates in Junggar-P601 is close to 60 wt%, while the content of asphaltenes is only 0.19 wt%. For the Shengli heavy oils, the difference in the content of asphaltenes between J8 and C373 is also significant. The content of asphaltenes in Tahe heavy oil even exceed 20 wt%. The H/C ratio of Chinese heavy oil generally falls between 1.50 and 1.75, exhibiting a wide distribution range. There are significant variations in the content of heteroatoms S, N, and O among different heavy oils. Most Chinese heavy oils have low sulfur content, but some high-sulfur heavy oils, such as Shengli-C373, can have sulfur content of nearly 5.0 wt%. The nitrogen content is usually below 0.8 wt%. The oxygen content is generally above 0.5 wt%, with Junggar-P601 showing oxygen content as high as 1.91 wt%. The high oxygen content in heavy oil may be related to its high TAN value [48].

3.2. Molecular Composition

GC-FID can be used for the trace analysis of organic matter within the carbon number range of C2 to C40, and it is widely applied in the screening and comparison of petroleum samples [49,50]. Figure 1 shows the GC-FID chromatograms of typical heavy oils in China. Except for the Tarim heavy oil which contains n-alkanes in the chromatogram, the other heavy oils have formed unresolved complex mixture (UCM) humps that are difficult to distinguish by GC [51]. Only some characteristic naphthenic hydrocarbons on the UCM hump can be identified. Junggar-P601 and Henan-L3511 are rich in naphthenic hydrocarbons with low cycle numbers and long side chains, as well as significant amounts of β-carotene. Shengli-J8 and Shengli-C373 are rich in naphthenic hydrocarbons with high cycle numbers and short side chains, and the hopane biomarkers are significant. GC-FID can reflect the compositional characteristics of some hydrocarbons among heavy oils. For heavy oils with significant property differences such as Shengli-J8 and Shengli-C373, their GC-FID chromatograms are similar. This indicates the need for more detailed molecular information to reveal the chemical composition differences between them.
The semi-quantitative results of the molecular composition of each heavy oil include information about nearly ten thousand molecules. Here, each molecule in the heavy oil was classified according to the SARA composition, thus obtaining the distribution of different types of compounds in SARA, as shown in Figure 2. For heavy oils with low sulfur content, naphthenic hydrocarbons are the main compounds in their saturate fractions. For heavy oils with high sulfur content, cyclic thioethers are the main compounds in their saturate fractions. Low-condensed aromatic hydrocarbons are dominant in all the heavy oils, with a significant abundance of thiophenes in the aromatic fraction of high-sulfur heavy oils. Compounds with multiple heteroatoms and high condensation are mainly distributed in the resins and asphaltenes. Monocarboxylic acids are significantly abundant in heavy oils with high TAN values. Junggar-P601, with the highest TAN value, has the highest proportion of polycarboxylic acids. The resins and asphaltenes of Tahe heavy oil are mainly composed of highly condensed aromatic hydrocarbons and nitrogen compounds, with over 10 wt% of unidentified compounds.
A comprehensive understanding of the chemical composition of heavy oil has been achieved by semi-quantitative analysis. The characteristic molecules of each heavy oil can be obtained by the abundance distribution of different compound types (Figure 2). Figure 3 illustrates characteristic molecules of typical Chinese heavy oils.
Junggar-P601 has a high content of saturates approaching 60 wt% and a low asphaltenes content of less than 0.5 wt%. The heteroatom content of Junggar-P601 is relatively low, with sulfur content around 0.2 wt%, and an H/C ratio generally greater than 1.7. Additionally, heavy oils in this region have very high TAN values, usually exceeding 10 mg KOH/g. Figure 3a shows the characteristic molecules of Junggar-P601. Saturated hydrocarbons are the main components of heavy oils in this region, and semi-quantitative analysis indicate that these saturated hydrocarbons are predominantly naphthenic hydrocarbons with 1–5 rings, and their abundance is evenly distributed from C15 to C50. In addition, the abundance distribution of C40 carotenes is also significant, with basically no alkanes present. The heavy oil in this area has a high TAN value, indicating a rich content of petroleum acids. Similar to the distribution of saturated hydrocarbons, the petroleum acids are mainly naphthenic acids with 1–3 rings, and their abundance distribution is relatively uniform from C15 to C50. The main characteristics of the molecular composition of the heavy oil in this area are the abundant long alkyl side chains, cycloalkane rings, and carboxylic acid groups.
The saturated hydrocarbons in Henan-L3511 contain both long alkyl side chain-substituted naphthenic hydrocarbons and abundant short alkyl side chain-substituted steranes and hopanes. The petroleum acids of Henan-L3511 are mainly composed of alkanoic acids, and there are also abundant sterol and hopanoid carboxylic acids. Additionally, Henan-L3511 has a high content of resins, in which there are significantly highly condensed carbazoles. Both the bulk properties and molecular composition indicate that the chemical composition of Henan-L3511 falls between Junggar-P601 and Shengli-J8. The main characteristics of the molecular composition of Henan-L3511 combines the long alkyl side chains of Junggar-P601, and the rich steranes and hopanes with short alkyl side chains of Shengli-J8.
Unlike Junggar-P601, Shengli-J8 heavy oil has a saturated hydrocarbon content of less than 30 wt%, with resins exceeding 40 wt% and asphaltene content over 3 wt%. Shengli-J8 has a low sulfur content and acid value above 3 mgKOH/g. The characteristic molecules of Shengli-J8 are depicted in Figure 3c. The molecular composition of Shengli-J8 differs significantly from Junggar-P601, in addition to the difference in SARA content. The saturated hydrocarbons of Shengli-J8 are mainly composed of steranes and hopanes with 4–5 naphthenic rings, with carbon numbers concentrated in the range of C27–C35. Similar to the composition of saturated hydrocarbons, the heavy oil in this region is also rich in steranic acids and hopanic acids. The presence of alkylphenols and highly condensed nitrogen compounds is another characteristic of its acidic oxygen compounds.
The SARA distribution of Shengli-C373 is similar to that of Shengli-J8, being low in saturates (less than 30 wt%) but high in asphaltenes, exceeding 6 wt%. High sulfur content (over 3 wt%) is a significant characteristic that distinguishes it from Shengli-J8. Figure 3d shows the characteristic molecules of Shengli-C373. The high abundance of steranes and hopanes is the main feature of the molecular composition of Shengli heavy oils. The abundant sulfur elements in Shengli-C373 are also bound to the carbon skeleton of these steranes and hopanes, forming abundant sulfur-containing steranes and sulfur-containing hopanes. The heavy oil in this region has a high asphaltenes content, with sulfur and other heteroatomic compounds mainly concentrated in the asphaltenes.
The significant characteristic of Tahe heavy oil is its exceptionally high asphaltene content, which can be over 40 wt% (Table S1). Furthermore, Tahe heavy oil is characterized by low TAN value and low content of heteroatoms. Figure 3e depicts the characteristic molecules of Tahe heavy oil. The hydrocarbons and nitrogen compounds in Tahe heavy oil both have a high degree of condensation, and its asphaltenes contain a large number of unidentified compounds. The heavy oil from this region exhibits a significant distribution of alkanes in its saturated hydrocarbons. Both hydrocarbons and heteroatomic compounds exhibit highly condensed aromatic ring structures.

3.3. Classification Method of Heavy Oil

Figure 4 illustrates the basis of the correlation analysis from the macro-components to the compound types and then to the molecular composition of heavy oil. The analysis results regarding bulk properties and molecular composition indicate that there are significant differences in the condensation degree of compounds in different heavy oils. Junggar-P601 has a high proportion of saturated hydrocarbons and petroleum acids. Its saturated hydrocarbons mainly consist of 2–3 cycloalkane rings with long alkyl side chains, and the petroleum acids are primarily composed of naphthenic acids with 1–3 rings. Junggar-P601 shows low levels of condensation with H/C ratio exceeding 1.70. In contrast to Junggar-P601, Shengli-J8 is rich in carbon skeletons with 4–5 cycloalkane rings with short alkyl side chains. These carbon skeletons are significantly distributed in the saturated hydrocarbons, acidic oxygen compounds, and sulfur compounds of Shengli-J8. Therefore, Shengli-J8 has a higher condensation degree compared to Junggar-P601, with an H/C ratio of around 1.60. Henan-L3511 combines the compositional characteristics of both Junggar-P601 and Shengli-J8, rich in carbon skeletons with both fewer cycloalkane ring numbers with long alkyl chain substitution, and more cycloalkane ring numbers with short alkyl chain substitution. The condensation level of Henan heavy oil falls between Junggar-P601 and Shengli-J8, with H/C ratio generally above 1.65. The composition characteristics indicate that Tahe heavy oil has the highest condensation degree, with an H/C ratio generally below 1.55. In addition to significant differences in condensation levels among different heavy oils, most heavy oils in China have relatively high TAN values due to the biodegradation. The presence of petroleum acids directly impacts the exploration and processing of heavy oils, making it necessary to take TAN values in a new index for heavy oil classification. For some high-sulfur heavy oils (sulfur content greater than 3 wt%), the compound type distribution of their saturates and aromatics are significantly different from those of low sulfur ones. Thus, it is possible to establish a correspondence between the molecular composition and the H/C value, the TAN value, and the sulfur content of heavy oil. The H/C value represents the condensation degree of the heavy oil, and the higher the H/C value, the richer the skeletons of alkyl chain and cycloalkane are in the heavy oil. The TAN value and the sulfur content indicate the abundance of the key compound types in the heavy oil, namely, the petroleum acids and sulfur compounds, respectively.
Thus, by combining the bulk properties and molecular composition analysis results of typical heavy oils, and taking into account the special impact of sulfur content on the composition characteristics of heavy oil, a new classification method for heavy oil has been established (Table 2). The H/C ratio is a key parameter reflecting the overall condensation degree of heavy oil and serves as the primary classification index, dividing heavy oils into low condensation, medium condensation, and high condensation degrees based on thresholds of 1.65 and 1.55. TAN value is an indicator reflecting the characteristic components, naphthenic acids, in heavy oil. It directly influences the selection of heavy oil exploration technologies and progressing processes, serving as the preferred secondary index. The sulfur content of Chinese heavy oil is generally low, but there are occasional instances of high-sulfur heavy oil. Moreover, the presence of sulfur compounds in high-sulfur heavy oil shows significant differences in the composition of the saturates fraction and aromatics fraction of the heavy oil. Therefore, sulfur content is used as a supplementary index for the classification of heavy oil.

4. Conclusions

In this study, heavy oil samples from Junggar Basin, Tarim oilfield, Chagan depression, Liaohe oilfield, Shengli oilfield, and Henan oilfield in China were collected. Bulk properties like viscosity, TAN value, SARA, and element analyses were conducted based on standard methods. Additionally, semi-quantitative analysis of the molecular composition of typical heavy oils was carried out using HRMS. By combining bulk properties and molecular composition analysis results, the composition characteristics of typical Chinese heavy oils were revealed: Junggar-P601 has a high proportion of saturated hydrocarbons, very high TAN value, and a characteristic carbon skeleton with fewer cycloalkane ring numbers with long alkyl side chains. Henan-L3511 contains both long alkyl side chain-substituted naphthenic hydrocarbons and abundant short alkyl side chain-substituted steranes and hopanes. Shengli-J8 has a low content of saturated hydrocarbons, high TAN value, and a characteristic carbon skeleton of more cycloalkane ring numbers with short alkyl side chains. Tahe heavy oil has a very high asphaltene content, low TAN value, and shows a highly condensed level of molecular composition. Finally, a new classification method for heavy oils has been established, combining the understanding of the composition characteristics of typical Chinese heavy oils and the actual processes of heavy oil exploration and processing. The new classification method uses the H/C ratio as the first index, and TAN value and sulfur content as the second indexes. Heavy oils with H/C ≥ 1.65 are classified as low condensation degree heavy oils. Heavy oils with an H/C ratio ranging from 1.55 to 1.65 are classified as medium condensation degree heavy oil. Heavy oils with an H/C ratio < 1.55 are classified as high condensation degree heavy oil.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/en17153733/s1, Table S1: Bulk properties of the 18 Chinese heavy oils; Figure S1: GC-FID chromatograms of the 18 Chinese heavy oils.

Author Contributions

Conceptualization, S.Z.; Methodology, J.W., S.L. and Q.S.; Software, S.L. and Y.Z.; Validation, S.L. and S.Z.; Formal analysis, Y.Z.; Investigation, W.Z.; Writing—original draft, W.Z.; Writing—review & editing, J.W.; Supervision, J.W. and Q.S.; Project administration, S.Z. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the National Key R&D Program of China, grant number 2018YFA0702400, and Science Foundation of China University of Petroleum, Beijing, grant number 2462023QNXZ017.

Data Availability Statement

The original contributions presented in the study are included in the article, further inquiries can be directed to the corresponding author.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Liu, Z.; Wang, H.; Blackbourn, G.; Ma, F.; He, Z.; Wen, Z.; Wang, Z.; Yang, Z.; Luan, T.; Wu, Z. Heavy Oils and Oil Sands: Global Distribution and Resource Assessment. Acta Geol. Sin. Engl. Ed. 2019, 93, 199–212. [Google Scholar] [CrossRef]
  2. Wu, Z.; Chen, H.; Cai, X.; Gou, Q.; Jiang, L.; Chen, K.; Chen, Z.; Jiang, S. Current Status and Future Trends of In Situ Catalytic Upgrading of Extra Heavy Oil. Energies 2023, 16, 4610. [Google Scholar] [CrossRef]
  3. Xue, L.; Liu, P.; Zhang, Y. Development and Research Status of Heavy Oil Enhanced Oil Recovery. Geofluids 2022, 2022, 5015045. [Google Scholar] [CrossRef]
  4. Liu, H.; Dong, X. Current status and future trends of hybrid thermal EOR processes in heavy oil reservoirs. Pet. Sci. Bull. 2022, 7, 174–184. [Google Scholar] [CrossRef]
  5. Sun, H.; Liu, H.; Wang, H.; Shu, Q.; Wu, G.; Yang, Y. Development technology and direction of thermal recovery of heavy oil in China. Acta Pet. Sin. 2022, 43, 1664–1674. [Google Scholar]
  6. Briggs, P.J.; Baron, P.; Fulleylove, R.; Wright, M.S. Development of heavy-oil reservoirs. J. Pet. Technol. 1988, 40, 206–214. [Google Scholar] [CrossRef]
  7. Zhao, Q.; Guo, L.; Huang, Z.; Chen, L.; Jin, H.; Wang, Y. Experimental investigation on enhanced oil recovery of extra heavy oil by supercritical water flooding. Energy Fuels 2018, 32, 1685–1692. [Google Scholar] [CrossRef]
  8. Ke, H.; Yuan, M.; Xia, S. A review of nanomaterials as viscosity reducer for heavy oil. J. Dispers. Sci. Technol. 2020, 43, 1271–1282. [Google Scholar] [CrossRef]
  9. Ma, F.; Zhang, G.; Wang, H.; Liu, Z.; Jiang, L.; Xie, F.; Fei, L.; Liang, J. Potential, distribution and exploration trend of global heavy oil and oil sand resources. J. Jilin Univ. Earth Sci. Ed. 2015, 45, 1042–1051. [Google Scholar]
  10. Yu, K.; Ma, H.; Hetaer, M.U.; Li, Q. Subdivision and Geological Significance of Shallow Heavy-oil Reservoirs in Junggar Basin. J. Oil Gas Technol. 2011, 33, 32–35. [Google Scholar]
  11. Yashchenko, I.G.; Polishchuk, Y.M. Classification of Poorly Recoverable Oils and Analyis of Their Quality Characteristics. Chem. Technol. Fuels Oils 2016, 52, 434–444. [Google Scholar] [CrossRef]
  12. Yashchenko, I.G.; Polishchuk, Y.M. Classification Approach to Assay of Crude Oils with Different Physicochemical Properties and Quality Parameters. Pet. Chem. 2019, 59, 1161–1168. [Google Scholar] [CrossRef]
  13. Bagheri Garmarudi, A.; Khanmohammadi, M.; Ghafoori Fard, H.; de la Guardia, M. Origin based classification of crude oils by infrared spectrometry and chemometrics. Fuel 2019, 236, 1093–1099. [Google Scholar] [CrossRef]
  14. Mohammadi, M.; Khanmohammadi Khorrami, M.; Vatani, A.; Ghasemzadeh, H.; Vatanparast, H.; Bahramian, A.; Fallah, A. Rapid determination and classification of crude oils by ATR-FTIR spectroscopy and chemometric methods. Spectrochim. Acta Part A Mol. Biomol. Spectrosc. 2020, 232, 118157. [Google Scholar] [CrossRef]
  15. Li, T.; Xu, J.; Zou, R.; Feng, H.; Li, L.; Wang, J.; Cohen Stuart, M.A.; Guo, X. Resin from Liaohe heavy oil: Molecular structure, aggregation behavior, and effect on oil viscosity. Energy Fuels 2017, 32, 306–313. [Google Scholar] [CrossRef]
  16. Wang, Y.; Han, X.; Li, J.; Liu, R.; Wang, Q.; Huang, C.; Wang, X.; Zhang, L.; Lin, R. Review on Oil Displacement Technologies of Enhanced Oil Recovery: State-of-the-Art and Outlook. Energy Fuels 2023, 37, 2539–2568. [Google Scholar] [CrossRef]
  17. Guo, K.; Li, H.; Yu, Z. In-situ heavy and extra-heavy oil recovery: A review. Fuel 2016, 185, 886–902. [Google Scholar] [CrossRef]
  18. Zhang, S.; Huo, J.; Sun, X.; Yang, F.; Wang, P.; Wu, J.; Zhang, Y.; Shi, Q. Molecular composition reveals unique rheological property of Karamay heavy crude oil. Energy Fuels 2020, 35, 473–478. [Google Scholar] [CrossRef]
  19. Zhu, H.; Wang, Q.; Yan, Y.; Xu, Y.; Liu, S.; Zhang, S.; Xu, J.; Yang, C. Effect of Naphthenic Acid and Metal Ions on Emulsification of Heavy Oil. Energy Fuels 2022, 36, 2561–2571. [Google Scholar] [CrossRef]
  20. Ragunathan, N.; Krock, K.A.; Klawun, C.; Sasaki, T.A.; Wilkins, C.L. Gas chromatography with spectroscopic detectors. J. Chromatogr. A 1999, 856, 349–397. [Google Scholar] [CrossRef]
  21. Barman, B.N.; Cebolla, V.L.; Membrado, L. Chromatographic Techniques for Petroleum and Related Products. Crit. Rev. Anal. Chem. 2000, 30, 75–120. [Google Scholar] [CrossRef]
  22. Saari, E.; Perämäki, P.; Jalonen, J. Evaluating the impact of GC operating settings on GC–FID performance for total petroleum hydrocarbon (TPH) determination. Microchem. J. 2010, 94, 73–78. [Google Scholar] [CrossRef]
  23. Wang, Z.; Fingas, M.; Li, K. Fractionation of a Light Crude Oil and Identification and Quantitation of Aliphatic, Aromatic, and Biomarker Compounds by GC-FID and GC-MS, Part II. J. Chromatogr. Sci. 1994, 32, 367–382. [Google Scholar] [CrossRef]
  24. Cheng, X.; Hou, D. Characterization of Severely Biodegraded Crude Oils Using Negative-Ion ESI Orbitrap MS, GC-NCD and GC-SCD: Insights into Heteroatomic Compounds Biodegradation. Energies 2021, 14, 300. [Google Scholar] [CrossRef]
  25. Yan, X. Unique selective detectors for gas chromatography: Nitrogen and sulfur chemiluminescence detectors. J. Sep. Sci. 2006, 29, 1931–1945. [Google Scholar] [CrossRef]
  26. Marshall, A.G.; Rodgers, R.P. Petroleomics: Chemistry of the underworld. Proc. Natl. Acad. Sci. USA 2008, 105, 18090–18095. [Google Scholar] [CrossRef]
  27. Shi, Q.; Zhang, Y.; Xu, C.; Zhao, S.; Chung, K. Progress and prospect on petroleum analysis by Fourier transform ion cyclotron resonance mass spectrometry. Sci. Sin. Chim. 2014, 44, 694. [Google Scholar] [CrossRef]
  28. Borisov, R.S.; Kulikova, L.N.; Zaikin, V.G. Mass Spectrometry in Petroleum Chemistry (Petroleomics) (Review). Pet. Chem. 2019, 59, 1055–1076. [Google Scholar] [CrossRef]
  29. Qian, K.; Robbins, W.K. Resolution and identification of elemental compositions for more than 3000 crude acids in heavy petroleum by negative-ion microelectrospray high-field Fourier transform ion cyclotron resonance mass spectrometry. Energy Fuels 2001, 15, 1505–1511. [Google Scholar] [CrossRef]
  30. Qian, K.; Rodgers, R.P.; Hendrickson, C.L.; Emmett, M.R.; Marshall, A.G. Reading chemical fine print: Resolution and identification of 3000 nitrogen-containing aromatic compounds from a single electrospray ionization Fourier transform ion cyclotron resonance mass spectrum of heavy petroleum crude oil. Energy Fuels 2001, 15, 492–498. [Google Scholar] [CrossRef]
  31. Purcell, J.M.; Hendrickson, C.L.; Rodgers, R.P.; Marshall, A.G. Atmospheric Pressure Photoionization Fourier Transform Ion Cyclotron Resonance Mass Spectrometry for Complex Mixture Analysis. Anal. Chem. 2006, 78, 5906–5912. [Google Scholar] [CrossRef]
  32. Jin, C.; Viidanoja, J.; Li, M.; Zhang, Y.; Ikonen, E.; Root, A.; Romanczyk, M.; Manheim, J.; Dziekonski, E.; Kenttämaa, H.I. Comparison of Atmospheric Pressure Chemical Ionization and Field Ionization Mass Spectrometry for the Analysis of Large Saturated Hydrocarbons. Anal. Chem. 2016, 88, 10592–10598. [Google Scholar] [CrossRef]
  33. Li, H.; Zhang, Y.; Xu, C.; Zhao, S.; Chung, K.H.; Shi, Q. Quantitative Molecular Composition of Heavy Petroleum Fractions: A Case Study of Fluid Catalytic Cracking Decant Oil. Energy Fuels 2020, 34, 5307–5316. [Google Scholar] [CrossRef]
  34. Bojkovic, A.; Vermeire, F.H.; Kuzmanović, M.; Dao Thi, H.; Van Geem, K.M. Analytics Driving Kinetics: Advanced Mass Spectrometric Characterization of Petroleum Products. Energy Fuels 2022, 36, 6–59. [Google Scholar] [CrossRef]
  35. Li, S.; Wu, J.; Wang, Y.; Li, Y.; Zhang, W.; Zhang, Y.; He, K.; Cai, C.; Bian, G.; Wang, H.; et al. Semi-quantitative analysis of molecular composition for petroleum fractions using electrospray ionization high-resolution mass spectrometry. Fuel 2023, 335, 127049. [Google Scholar] [CrossRef]
  36. Wu, J.-X.; Li, S.-F.; Li, Q.-F.; Yan, F.; Zhou, Q.-L.; Ma, S.; Zhang, Y.-H.; Zhao, S.-Q.; Shi, Q. Characterization of chemical composition of high viscosity heavy oils: Macroscopic properties, and semi-quantitative analysis of molecular composition using high-resolution mass spectrometry. Pet. Sci. 2024; in press. [Google Scholar] [CrossRef]
  37. GB/T 18609; Determination of Acid Number of Crude Oil by Potentiometric Titration. China National Standardization Management Committee: Beijing, China, 2011.
  38. SY/T 0520; Viscosity Determination of Crude Petroleum. Equilibrium Method by Rotational Viscometer. National Development and Reform Commission: Beijing, China, 2008.
  39. NB/SH/T 0509; Test Method for Separation of Asphalt into for Fractions. National Energy Administration: Beijing, China, 2010.
  40. NB/SH/T 0162; Determination of Basic Nitrogen in Petroleum Distillates-Color Indicator Titration Method. National Energy Administration: Beijing, China, 2021.
  41. ASTM D5291; Standard Test Methods for Instrumental Determination of Carbon, Hydrogen, and Nitrogen in Petroleum Products and Lubricants. American Society for Testing and Materials: West Conshohocken, PA, USA, 2016.
  42. ASTM D5622; Standard Test Methods for Determination of Total Oxygen in Gasoline and Methanol Fuels by Reductive Pyrolysis. American Society for Testing and Materials: West Conshohocken, PA, USA, 2017.
  43. ASTM D5453; Standard Test Method for Determination of Total Sulfur in Light Hydrocarbons, Motor Fuels and Oils by Ultraviolet Fluorescence. American Society for Testing and Materials: West Conshohocken, PA, USA, 2004.
  44. ASTM D5762; Standard Test Method for Nitrogen in Petroleum and Petroleum Products by Boat-Inlet Chemiluminescence. American Society for Testing and Materials: West Conshohocken, PA, USA, 2012.
  45. Shi, Q.; Pan, N.; Long, H.; Cui, D.; Guo, X.; Long, Y.; Chung, K.H.; Zhao, S.; Xu, C.; Hsu, C.S. Characterization of middle-temperature gasification coal tar. part 3: Molecular composition of acidic compounds. Energy Fuels 2013, 27, 108–117. [Google Scholar] [CrossRef]
  46. Marshall, A.G.; Rodgers, R.P. Petroleomics: The next grand challenge for chemical analysis. Cheminform 2004, 35, 53–59. [Google Scholar] [CrossRef]
  47. Peters, K.E.; Moldowan, J.M. The Biomarker Guide: Interpreting Molecular Fossils in Petroleum and Ancient Sediments; Prentice Hall: Saddle River, NJ, USA, 1993. [Google Scholar]
  48. Dou, L.; Hou, D.; Cheng, D.; Li, M.; Pan, X. Origin and distribution of high-acidity oils. Shiyou Xuebao/Acta Pet. Sin. 2007, 28, 8–13. [Google Scholar]
  49. Harrison, G.; Lamont, N.A. Simulated time-based studies to evaluate changes in crude oil composition through evaporation and biodegradation. In Proceedings of Oil and Hydrocarbon Spills III: Modelling, Analysis and Control; MIT Press: Cambridge, MA, USA, 2002; pp. 201–210. [Google Scholar]
  50. Sun, P.Y.; Gao, Z.H.; Zhou, Q.; Zhao, Y.H.; Wang, X.P.; Cao, X.L.; Li, G.M. Evaluation of the Oil Spill Accident in Bohai Sea, China. Environ. Forensics 2009, 10, 308–316. [Google Scholar] [CrossRef]
  51. Gough, M.A.; Rowland, S.J. Characterization of unresolved complex mixtures of hydrocarbons in petroleum. Nature 1990, 344, 648–650. [Google Scholar] [CrossRef]
Figure 1. GC-FID chromatograms of typical Chinese heavy oils.
Figure 1. GC-FID chromatograms of typical Chinese heavy oils.
Energies 17 03733 g001
Figure 2. Histogram of the distribution of the contents of different compound types in the SARA fractions of typical Chinese heavy oils based on semi-quantitative analysis of molecular composition.
Figure 2. Histogram of the distribution of the contents of different compound types in the SARA fractions of typical Chinese heavy oils based on semi-quantitative analysis of molecular composition.
Energies 17 03733 g002
Figure 3. Characteristic molecules of typical Chinese heavy oils: (a) Junggar-P601; (b) Henan-L3511; (c) Shengli-J8; (d) Shengli-C373; (e) Tahe-1.
Figure 3. Characteristic molecules of typical Chinese heavy oils: (a) Junggar-P601; (b) Henan-L3511; (c) Shengli-J8; (d) Shengli-C373; (e) Tahe-1.
Energies 17 03733 g003
Figure 4. Schematic classification of Chinese heavy oils based on the correlation analysis from the macro-components to the compound types, and then to the molecular composition.
Figure 4. Schematic classification of Chinese heavy oils based on the correlation analysis from the macro-components to the compound types, and then to the molecular composition.
Energies 17 03733 g004
Table 1. Bulk properties of typical Chinese heavy oils.
Table 1. Bulk properties of typical Chinese heavy oils.
Junggar-P601Henan-L3511Shengli-J8Shengli-C373Tahe-1
Viscosity, 50 °C mPa·s30331665186468836732
TAN, mgKOH/g11.774.913.873.110.15
Saturates, wt%58.2045.7944.8625.2830.97
Aromatics, wt%19.7322.9124.8539.6825.91
Resins, wt%20.3131.1928.1729.0011.47
Asphaltenes, wt%0.19<0.051.327.6923.19
H/C1.721.681.651.571.54
S, wt%0.220.270.314.980.64
N, wt%0.250.640.750.730.45
O, wt%1.911.310.570.980.63
Table 2. Recommended new classification indicators for Chinese heavy oils.
Table 2. Recommended new classification indicators for Chinese heavy oils.
First IndexSecond IndexTypical Heavy Oil
H/CTAN Value, mgKOH/gSulfur Content, wt%
Low condensation≥1.65≥6.0<1.0Junggar-P601, Junggar-H8317
<6.0<1.0Henan-L3511, Shengli-JX17
Medium condensation1.55~1.651.0~6.0≥3.0Shengli-C373, Shengli-GD2
1.0~6.0<3.0Shengli-J8, Junggar-F3167
High condensation<1.55<1.0<1.0Tahe-1, Tahe-2, Liaohe-H70
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Zhang, W.; Wu, J.; Li, S.; Zhang, Y.; Zhao, S.; Shi, Q. Classification Method of Heavy Oil Based on Chemical Composition and Bulk Properties. Energies 2024, 17, 3733. https://doi.org/10.3390/en17153733

AMA Style

Zhang W, Wu J, Li S, Zhang Y, Zhao S, Shi Q. Classification Method of Heavy Oil Based on Chemical Composition and Bulk Properties. Energies. 2024; 17(15):3733. https://doi.org/10.3390/en17153733

Chicago/Turabian Style

Zhang, Weilai, Jianxun Wu, Shuofan Li, Yahe Zhang, Suoqi Zhao, and Quan Shi. 2024. "Classification Method of Heavy Oil Based on Chemical Composition and Bulk Properties" Energies 17, no. 15: 3733. https://doi.org/10.3390/en17153733

APA Style

Zhang, W., Wu, J., Li, S., Zhang, Y., Zhao, S., & Shi, Q. (2024). Classification Method of Heavy Oil Based on Chemical Composition and Bulk Properties. Energies, 17(15), 3733. https://doi.org/10.3390/en17153733

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop