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Review

Research Progress on the Pyrolysis Characteristics of Oil Shale in Laboratory Experiments

1
National Research Center for Oil Shale Exploitation and Development, Beijing 102206, China
2
Engineering Technology Management Center, Sinopec Shengli Oilfield Company, Dongying 257000, China
3
State Key Laboratory, Southwest Petroleum University, Chengdu 610500, China
4
Research Institute of Petroleum Exploration and Development, Sinopec, Beijing 100089, China
*
Author to whom correspondence should be addressed.
Processes 2025, 13(9), 2787; https://doi.org/10.3390/pr13092787
Submission received: 10 August 2025 / Revised: 26 August 2025 / Accepted: 29 August 2025 / Published: 30 August 2025
(This article belongs to the Section Energy Systems)

Abstract

With the progressive depletion of conventional oil and gas resources and the increasing demand for alternative energy, organic-rich sedimentary rock—oil shale—has attracted widespread attention as a key unconventional hydrocarbon resource. Pyrolysis is the essential process for converting the organic matter in oil shale into recoverable hydrocarbons, and a detailed understanding of its behavior is crucial for improving development efficiency. This review systematically summarizes the research progress on the pyrolysis characteristics of oil shale under laboratory conditions. It focuses on the applications of thermogravimetric analysis (TGA) and differential scanning calorimetry (DSC) in identifying pyrolysis stages, extracting kinetic parameters, and analyzing thermal effects; the role of coupled spectroscopic techniques (e.g., TG-FTIR, TG-MS) in elucidating the evolution of gaseous products; and the effects of key parameters such as pyrolysis temperature, heating rate, particle size, and reaction atmosphere on product distribution and yield. Furthermore, the mechanisms and effects of three distinct heating strategies—conventional heating, microwave heating, and autothermic pyrolysis—are compared, and the influence of inherent minerals and external catalysts on reaction pathways is discussed. Despite significant advances, challenges remain in quantitatively describing reaction mechanisms, accurately predicting product yields, and generalizing kinetic models. Future research should integrate multiscale experiments, in situ characterization, and molecular simulations to construct pyrolysis mechanism models tailored to various oil shale types, thereby providing theoretical support for the development of efficient and environmentally friendly oil shale conversion technologies.

1. Introduction

As global conventional petroleum reserves continue to decline and the need for energy transition becomes increasingly urgent, the development of unconventional oil and gas alternatives has become a primary research focus in the international energy sector. Among these, oil shale—a sedimentary rock rich in solid organic matter known as kerogen—can be thermally decomposed into liquid hydrocarbons (shale oil) and gaseous products [1], making it one of the most promising alternative energy sources. According to data from the U.S. Geological Survey (USGS) and the Chinese Academy of Geological Sciences [2,3], global oil shale resources are estimated to exceed 3 trillion barrels of oil equivalent, primarily located in the United States, China, Russia, Brazil, and Estonia. This vast reserve far surpasses currently proven conventional petroleum reserves and carries substantial strategic value.
Compared with conventional oil and gas resources, oil shale is more challenging to develop. The organic matter in oil shale exists in a dispersed solid state within the mineral matrix of the rock and cannot be directly extracted. Therefore, it must undergo thermal pyrolysis to break down the kerogen and convert it into extractable oil and gas [4]. Depending on the exploitation strategy, oil shale pyrolysis can be classified into surface retorting and in situ conversion [5] (Figure 1). Regardless of the method, understanding the physical and chemical principles governing oil shale pyrolysis is a prerequisite for efficient resource utilization.
The pyrolysis process involves complex mechanisms including heat conduction, mass diffusion, chemical reactions, and structural evolution [6,7,8]. At its core, kerogen molecules undergo bond cleavage, rearrangement, degassing, and condensation under thermal conditions, eventually generating oil, gas, and semi-coke [9]. The pyrolytic behavior is influenced by multiple factors such as source rock properties, heating rate, reaction time, atmosphere, and pressure, resulting in highly nonlinear and region-specific characteristics [10]. Therefore, systematic investigation of the fundamental principles of oil shale pyrolysis is not only vital for optimizing thermal conversion technologies but also for constructing generalized pyrolysis models and mechanistic frameworks. These efforts serve as a critical bridge connecting fundamental scientific research with practical engineering applications.
To address these challenges, extensive research has been conducted globally on the pyrolysis behavior of oil shale under laboratory conditions. Studies have examined the effects of pyrolysis temperature, heating rate, and heating method (including conventional, microwave, and autothermic heating) on pyrolysis outcomes. Findings have revealed, for instance, that pyrolysis temperature regulates kerogen cracking and the extent of secondary reactions; heating rate affects heat transfer efficiency and the residence time of products, thus influencing light hydrocarbon formation pathways; microwave heating enhances uniform heating via dielectric effects, while autothermic pyrolysis relies on partial oxidation reactions for internal heat generation. Furthermore, mineral matter and catalysts have been found to modulate activation energy through interfacial interactions.
Nevertheless, current studies remain fragmented, and a comprehensive review summarizing these mechanisms and trends is lacking. This paper aims to consolidate existing findings on oil shale pyrolysis under laboratory conditions and analyze the effects of various thermal parameters. By doing so, it seeks to provide a systematic theoretical basis for the precise control of pyrolysis behavior and the development of efficient oil shale conversion technologies.

Methodology of Literature Selection

To ensure this review provides a comprehensive and systematic overview, literature was selected using the following strategy:
Databases: Web of Science, Scopus, ScienceDirect, CNKI, and Google Scholar.
Keywords: oil shale pyrolysis, kinetics, TGA-DSC, microwave heating, autothermic pyrolysis, catalysis, and reaction mechanisms.
Timeframe: Publications from 2000 to 2025 were considered, with emphasis on recent advances from 2023–2025.
Inclusion criteria: Peer-reviewed journal articles and conference proceedings focusing on laboratory studies of oil shale pyrolysis.
Exclusion criteria: Patents, non-peer-reviewed reports, and articles not specifically addressing pyrolysis.
This systematic methodology ensures both historical context and the latest research developments are incorporated.

2. Laboratory Research Progress on Oil Shale Pyrolysis Mechanism

2.1. Revealing Pyrolysis Stages and Kinetics via Thermogravimetric and Calorimetric Analyses

Thermogravimetric analysis (TGA) and differential scanning calorimetry (DSC) are two essential techniques for investigating the pyrolysis behavior of oil shale [11]. TGA records the mass loss of the sample as temperature increases [12], providing direct insights into the multi-stage decomposition process of oil shale. DSC simultaneously measures the heat flow difference between the sample and a reference material [13], thereby revealing the endothermic and exothermic phenomena occurring at each stage. These two methods are capable of delivering highly sensitive and reproducible data on both kinetic parameters and thermal effects, offering solid experimental support for elucidating the complex pyrolysis mechanisms [14]. In oil shale studies, TGA is often used in conjunction with DSC to simultaneously obtain mass loss and thermal effect data [15], enabling a more comprehensive characterization of each pyrolysis stage.
By analyzing the thermogravimetric curve and its derivative (DTG), the pyrolysis process can typically be divided into 2 to 3 primary stages [16]: an initial mass loss around 150–200 °C attributed to moisture and light volatile evaporation; a sharp mass loss between 300 and 520 °C corresponding to the decomposition of kerogen and major oil and gas release; and a slow, sustained mass loss above 600 °C related to the decomposition of mineral matter such as carbonates. Zhao et al. [17] used TG-DTG to identify three distinct stages: evaporation of small molecules, significant kerogen decomposition, and carbonate breakdown. Each stage corresponds to specific peaks on the DTG curve, with kerogen decomposition typically yielding the most prominent mass loss peak. To address the issue of overlapping peaks, researchers [18] often use deconvolution techniques (e.g., Gaussian function fitting) to separate the overall pyrolysis peak into multiple sub-peaks. This allows individual reactions to be identified and associated with specific organic constituents, enabling a clearer understanding of the kinetic contributions and characteristics of each stage.
The DSC signal provides further insight into the thermal effects associated with each pyrolysis phase. Oil shale pyrolysis is generally an endothermic process, as the cleavage of large molecular bonds in kerogen requires energy input. Thus, a prominent endothermic peak usually appears during the main pyrolysis stage [19]. Similarly, carbonate decomposition (e.g., into CO2 and metal oxides) also exhibits a strong endothermic signature [20]. By analyzing the position and area of DSC peaks, the thermal effect of each stage can be quantified and interpreted thermodynamically. Studies [21] have shown that kerogen decomposition consumes approximately 36% of the total pyrolysis heat requirement. Additionally, at temperatures below 520 °C, energy used for evaporating water and light volatiles under 185 °C also accounts for a significant portion of the total heat input. This highlights that in practical heating processes, a considerable fraction of energy is first spent on overcoming the phase transitions of physically adsorbed water and volatile components before kerogen cracking takes place. DSC can also be used to detect exothermic behavior [22]. Under strictly inert atmospheres, pyrolysis typically does not exhibit noticeable exothermic peaks, indicating that the process is dominated by endothermic decomposition. However, if oxidation or secondary reactions occur, DSC curves may present evident exothermic signals. In summary, DSC analysis not only reveals the energy demands and thermodynamic characteristics of oil shale pyrolysis but also serves as a critical complement to TGA by providing thermal context to the observed mass loss behavior.

2.2. Online Product Analysis and Combined Spectroscopic Techniques

To gain a deeper understanding of the release behavior and compositional evolution of volatile products during oil shale pyrolysis, researchers have extensively applied thermal analysis combined with spectroscopic techniques. For instance, thermogravimetric analysis coupled with Fourier transform infrared spectroscopy (TG-FTIR) has been employed to monitor, in real time, the types and concentrations of gaseous products as a function of temperature [23,24]. During oil shale pyrolysis, the release of gaseous products exhibits clear stage-specific characteristics across different temperature ranges. Numerous studies have shown [25,26] that around 300 °C, carbon dioxide (CO2) and water vapor (H2O) begin to evolve, primarily originating from the decomposition of oxygen-containing functional groups in organic matter and the release of crystal water from minerals. As the temperature increases to 400–500 °C, large quantities of hydrocarbon gases (e.g., alkanes and olefins) and oxygenated organic compounds are produced—this stage represents the most active pyrolysis zone. At even higher temperatures, nitrogen- and sulfur-containing gases such as ammonia (NH3) and hydrogen sulfide (H2S) are detected, indicating the thermal cleavage of nitrogen- and sulfur-functional groups in kerogen. Thermogravimetric analysis coupled with mass spectrometry (TG-MS) offers higher sensitivity in gas detection and has been widely applied to analyze the evolution characteristics of gaseous products [27]. Han and Pan et al. [28,29] used TG-MS to accurately trace the release peaks of small molecules such as CH4, H2, and CO (Figure 2). Their results showed significant differences in CO2/CO ratios among various oil shale samples during the main pyrolysis stage (~450 °C), which were attributed to variations in the content of carboxyl and carbonyl groups within the kerogen structure.
In addition to gas evolution analysis, structural changes in the solid pyrolysis residues are also characterized using techniques such as infrared spectroscopy and nuclear magnetic resonance (NMR). FTIR monitoring has demonstrated that [30,31] the absorption peaks associated with oxygen-containing functional groups (e.g., carbonyl and hydroxyl) significantly decrease after pyrolysis, while the characteristic peaks of aromatic C=C bonds become more prominent-indicating a clear trend toward aromatization of the organic matter.
Overall, the release behavior of products during oil shale pyrolysis exhibits clear temperature-dependent phase transitions, reflecting the continuous evolution from primary to secondary cracking processes. Utilizing TG-FTIR, TG-MS, and other thermal analysis-coupled techniques [32], researchers have clarified the formation mechanisms and structural origins of various volatile components at each stage, and identified the stepwise cleavage patterns of nitrogen- and sulfur-containing functional groups across temperature intervals. Spectroscopic characterization of solid residues further confirms the de-functionalization and aromatization trends of organic matter during pyrolysis. These insights provide critical support for a deeper understanding of pyrolysis pathways and reaction mechanisms in oil shale conversion. While coupled spectroscopic techniques reveal the microcosmic product evolution, pyrolysis experiments in different reactors further clarify the macroscopic effects of operational conditions on product distribution.
Figure 2. Mass Spectrometric Analysis of Gas Release During Oil Shale Pyrolysis. ((a) Evolution profiles of typical gas products (e.g., H2, CH4, CO, CO2, H2O, etc.) during pyrolysis at a heating rate of 3 °C/min [29]; (b) Mass spectra of gas products released from Beypazarı oil shale; (c) Mass spectra of gas products released from Hatıldağ oil shale [33]).
Figure 2. Mass Spectrometric Analysis of Gas Release During Oil Shale Pyrolysis. ((a) Evolution profiles of typical gas products (e.g., H2, CH4, CO, CO2, H2O, etc.) during pyrolysis at a heating rate of 3 °C/min [29]; (b) Mass spectra of gas products released from Beypazarı oil shale; (c) Mass spectra of gas products released from Hatıldağ oil shale [33]).
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2.3. Pyrolysis Experiments Under Different Laboratory Reactors and Conditions

In addition to thermal analyzers, small-scale fixed-bed and fluidized-bed reactors are widely used to simulate oil shale pyrolysis under conditions closer to industrial practice [34] (Figure 3). Fixed-bed pyrolysis experiments are commonly employed to determine the yields of oil, gas, and semi-coke, as well as to evaluate the effects of various conditions on product properties [10]. Ma et al. [35] investigated the pyrolysis behavior of western U.S. oil shale in a fixed-bed reactor at different final temperatures. Their results showed that the shale oil yield increased steadily as the final temperature rose from 400 °C to 500 °C, but declined when the temperature exceeded 500 °C. This indicates that approximately 500 °C is the optimal temperature for oil shale conversion to oil; higher temperatures promote secondary cracking of volatiles into non-condensable gases and coke, reducing the yield of condensable liquids. Similar trends are observed for heating rate [36]. At low heating rates (2–5 °C/min), organic matter undergoes sufficient thermal decomposition, leading to higher oil yields. In contrast, rapid heating (>50 °C/min) may cause incomplete pyrolysis, resulting in increased char residue and reduced oil recovery. Notably, fast heating also affects the chemical composition of shale oil. Using GC-MS, Al-Harahsheh et al. [37] found that higher heating rates led to an increased proportion of aliphatic hydrocarbons and a reduction in aromatics. Likewise, Pan et al. [38] observed that higher heating rates favored the production of light hydrocarbons (e.g., light alkanes and olefins) and suppressed the formation of heavy fractions and long-chain alkanes in pyrolysis products from Jimsar oil shale in China.
These experimental findings enrich our understanding of how pyrolysis conditions influence both product yield and quality. In addition, advanced reactor designs such as the micro fluidized bed reaction analyzer (MFBRA) allow for studying pyrolysis kinetics under ultra-fast heating conditions (up to thousands of °C/s) [39]. Researchers [40] using MFBRA to compare the rapid pyrolysis behavior of oil shale and coal found that oil shale exhibited significantly higher total weight loss and reaction rates compared to TGA-based slow pyrolysis, highlighting the strong influence of heating rate on pyrolysis kinetics and product formation [41]. Such complexity underscores the limitations of single-method approaches in revealing the full pyrolysis mechanism. While fixed-bed reactors are simple and convenient for controlling final pyrolysis temperature, they suffer from low heat transfer efficiency and uneven heating, which may cause local overheating or thermal lag [42]. In contrast, fluidized-bed systems offer superior gas–solid contact and thermal uniformity, making them more representative of industrial-scale processes [43], though their operational complexity and lower control precision present challenges. Each system offers unique advantages and limitations in terms of experimental control and relevance to industrial applications. Therefore, a comprehensive understanding of oil shale pyrolysis behavior and product evolution requires a synergistic use of multiple reactor types and analytical methods, enabling more robust interpretation across various experimental conditions.

3. Effects of Pyrolysis Conditions on Oil Shale Pyrolysis Behavior

3.1. Research Progress on the Influence of Pyrolysis Temperature

Pyrolysis temperature is one of the most critical parameters influencing the stages of oil shale pyrolysis, product distribution, and the yield of shale oil and gas [44]. As shown in Table 1, the pyrolysis temperature range for both domestic and international oil shale typically falls between 200 °C and 600 °C. For example, pyrolysis of Yaojie oil shale in Gansu Province initiates at around 300 °C [45]. As the temperature increases to 550 °C, the pyrolysis intensifies, with the liquid yield rising from 1.22% to 10.50%, and the gas yield increasing from 0.63% to 4.72%. However, in the temperature range of 600 °C to 1000 °C, the amount of solid residue (coke) increases, while liquid products decrease and gas production rises, including significant amounts of carbon dioxide and methane. Ultimately, the gas yield increases from 5.74% to 13.69%, while the liquid yield drops from 10.5% to 9.89%. Therefore, to maximize shale oil recovery, the pyrolysis temperature should not exceed 600 °C. It is worth noting that the optimal temperature for maximum oil yield varies depending on the oil shale’s origin. For instance, Green River oil shale in the United States achieves its maximum liquid yield of 60% at around 450 °C, consisting mainly of light crude and natural gas liquids, with minor coke formation. The highest gas yield (around 20%) occurs between 500 °C and 600 °C, primarily comprising methane and carbon dioxide [46]. This difference is attributed to the high organic content and superior kerogen type in Green River oil shale. It is rich in Type I kerogen (e.g., algal kerogen), which favors the generation of liquid hydrocarbons and enhances oil yield during pyrolysis. In contrast, Yaojie oil shale mainly contains Type II and Type III kerogen [22], which tend to generate more gas and solid residues during thermal decomposition. Furthermore, the relatively low mineral content and lacustrine, anoxic depositional environment of Green River shale promote higher liquid yields. Jiahui Li et al. [47] found that the liquid yield from Huadian oil shale increased rapidly with temperature, reaching a peak of 10.56 wt% at 475 °C [48]. However, when the temperature increased from 600 °C to 650 °C, the liquid yield dropped by 15%, while the gas yield rose by approximately 20%. This is due to the decomposition of aliphatic methylene structures in the organic matter below 600 °C, which produces high-molecular-weight liquid products. At higher temperatures, enhanced reactions result in secondary cracking of some pyrolysis products into low-molecular-weight gases. Concurrently, partial decomposition of minerals contributes to increased gas yield. These findings indicate that oil shale from different regions generally exhibits similar pyrolysis temperature ranges, and maximum oil yield is typically achieved between 450 °C and 600 °C. However, despite extensive laboratory studies, it remains challenging to accurately and in real time predict the pyrolysis products of oil shale at different temperatures, posing a major obstacle to optimizing industrial pyrolysis processes.

3.2. Research Progress on the Influence of Heating Rate

Heating rate is another key parameter that significantly affects oil shale pyrolysis, determining product distribution, coke formation, and overall reaction kinetics [51]. In practical operations, the selection of heating rate is typically optimized based on the desired end products [52]. Firstly, varying heating rates influence the pyrolysis temperature. As the heating rate increases, the actual temperature at which pyrolysis occurs also increases. This is attributed to the thermal conduction mechanism and the time-dependent nature of heat transfer within the shale matrix. For instance, thermogravimetric analysis of Huadian oil shale demonstrated that at lower heating rates, the extended reaction time allows sufficient heat absorption, leading to more uniform internal temperature distribution and more complete pyrolysis. Consequently, both the initial and final pyrolysis temperatures are reduced. In contrast, at higher heating rates, the shale lacks adequate time to absorb heat uniformly, resulting in larger temperature gradients, especially in larger particles, where the outer layers may undergo excessive cracking while the inner core remains underreacted [53]. Secondly, heating rate influences the yield and composition of pyrolysis products. Studies show a pronounced impact of heating rate on pyrolysis behavior, particularly for oil shale from Sunitezuoqi, Inner Mongolia [54]. Initial experiments revealed that oil yield increased significantly with heating rate and peaked at approximately 7 °C/min. However, further increases in heating rate led to a decline in oil yield. This phenomenon is primarily related to changes in the extent of secondary cracking (Figure 4). At low to moderate heating rates (1 °C/min to 7 °C/min), increased thermal input accelerates primary pyrolysis reactions in oil shale, enhancing the generation of primary products such as tar.
Since the overall reaction occurs more rapidly [55,56], the residence time of these products within the reactor is reduced, minimizing the likelihood of secondary reactions and thereby increasing oil yield. When the heating rate exceeds 7 °C/min, however, the temperature gradient within the reactor becomes more pronounced. As a result, volatile products released from the interior of the oil shale may reach excessively high temperatures, which accelerates secondary cracking reactions. These secondary processes shift the reaction pathway toward deeper decomposition, converting more tar into gas and coke, and ultimately decreasing the oil yield.
Figure 4. Schematic diagram of the secondary cracking mechanism of oil shale [57].
Figure 4. Schematic diagram of the secondary cracking mechanism of oil shale [57].
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It is noteworthy that particle size plays a key role in this process. Studies have shown [58] that as the particle size of oil shale decreases, the oil yield decreases and the gas yield increases, while the semicoke yield remains relatively unchanged except for the 1–3 mm size range. This indicates that the degree of secondary reactions increases with decreasing particle size. Although smaller particles shorten the migration path and reduce the residence time of shale oil within the particles—thereby potentially reducing the extent of secondary reactions internally—the denser packing of smaller particles narrows the internal flow channels in the bed, making it more difficult for shale oil vapors to escape quickly. In addition, a lower heating rate fails to raise the temperature to the level required for the onset of primary pyrolysis reactions in time, which instead enhances the secondary reactions on the particle surfaces, resulting in an overall increase in the extent of secondary reactions and a decrease in oil yield [59]. Particle size not only affects the heat and mass transfer characteristics during oil shale pyrolysis but also significantly alters the yield and composition of the pyrolysis products. Nasir et al. [60], in their study of the pyrolysis behavior of Pakistani oil shale with particle sizes ranging from 0.5 mm to 10 mm, found that increasing particle size significantly affected product distribution. As particle size increased, the yield of pyrolysis gases showed a decreasing trend, and the contents of gases such as H2, CO, and CO2, as well as aliphatic hydrocarbons, also decreased. Meanwhile, the shale oil yield increased from 11.9% to 19%. This trend can be attributed to the influence of particle size on the pyrolysis mechanism [61,62]. Smaller particles, due to their compact packing structure and relatively slower heating rate, result in higher gas yields and lower liquid yields. This is because under a higher degree of secondary cracking, light volatile products undergo further decomposition, increasing gas generation while reducing the formation of liquid products. In contrast, larger particles, with their looser packing and longer heat conduction paths, experience a lower degree of secondary cracking, thus maintaining a higher liquid yield and a lower gas yield.

3.3. Research Progress on the Influence of Pyrolysis Methods on Oil Shale Pyrolysis Behavior

3.3.1. Pyrolysis Characteristics of Oil Shale Under Conventional Heating

Conventional heating methods for oil shale pyrolysis mainly include electric heating and thermal fluid heating. The effectiveness of these pyrolysis methods primarily depends on the efficiency of heat conduction and heat convection [63]. Numerical simulation studies by Sun et al. [64] demonstrated that using electric heating, the temperature of the target oil shale formation can reach 500 °C after continuous heating for nine years, thereby enabling concentrated thermal cracking and improving heating efficiency. However, research by Xue and colleagues [65,66,67] revealed through numerical simulation that in situ oil shale conversion using multi-well electric heating has significant limitations. Specifically, the process suffers from severe heat loss and prolonged heat transfer times, resulting in low heating efficiency and high energy consumption. Studies have shown that when the temperature field reaches 500 °C, the surrounding rock can only maintain temperatures above 400 °C within a 4–5 m radius. This uneven temperature distribution leads to reduced thermal conductivity of the rock formation. Moreover, in an attempt to improve heating performance, increasing the temperature of the heating wells may raise temperatures above 800 °C, causing overheating of the rock, premature coking, and further reduction in thermal conductivity. It may also damage the heating equipment. To address these drawbacks of electric heating, researchers have proposed using thermal fluids for heating. Thermal fluids, with their high temperature and excellent thermal diffusion characteristics, are injected into the oil shale formation to achieve area-wide heating through thermal convection [68]. Academician Zhao Yangsheng’s team [69] proposed the MTI (Modified Thermal Injection) technology for pyrolyzing oil shale using high-temperature steam. Research shows [70] that during steam pyrolysis, H2O molecules can provide more hydrogen radicals to participate in the reaction, promoting the cracking of kerogen and heavy shale oil, and inhibiting the formation of C–C cross-linking structures. This improves the yields of light shale oil (C5–C13) and gases (C1–C4). Pilot test results demonstrated that high-temperature steam heating of oil shale offers high heat transfer efficiency, enabling rapid pyrolysis of organic matter and efficient resource recovery. The oil and gas production rate in the thermal injection zone exceeded 95%, and the overall oil recovery rate reached 67.3%, fully demonstrating the high efficiency of the MTI technology in oil shale pyrolysis. Nevertheless, although thermal fluid heating can shorten heating time and expand the heat exchange area, researchers also found that this method still faces challenges such as the large volume of heat injection required and significant heat loss along the injection path [70].

3.3.2. Pyrolysis Behavior of Oil Shale Under Microwave Heating

Unlike traditional heating methods dominated by thermal conduction and convection, microwave heating, as shown in Figure 5, directly interacts with polar molecules and minerals in oil shale via electromagnetic waves. This mechanism enables a rapid rise in overall temperature and achieves a more uniform heating effect [71]. Such a heating approach significantly shortens the heating duration, reduces energy consumption, and enhances pyrolysis efficiency and product quality. For example, Luo et al. [72], in their study on the microwave pyrolysis characteristics of oil shale from Yaojie, Gansu Province, found that microwave heating not only increased the release of H2, CO, and C2H4 in the pyrolysis gas but also reduced the generation of CO2, thereby enriching the gas with valuable components—an important advantage for subsequent utilization of pyrolysis gases.
Furthermore, He et al. [73] compared the performance of microwave heating and conventional heating, and found that under the same power, microwave heating achieved a higher average heating rate and greater weight loss. It also reduced the activation energy of oil shale pyrolysis by 13–39%, while increasing the reaction rate constant by at least 65%. Zhu et al. [74] further demonstrated that microwave heating occurs extremely rapidly, with faster temperature rise at higher power levels. Under a power of 1000 W, oil shale reached 750 °C in only 9 min, whereas conventional heating took 55 min to reach the same temperature. Thus, from an energy-saving perspective, microwave heating exhibits superior heating efficiency.
In addition, analysis of the liquid products obtained from microwave pyrolysis [75] revealed that microwave heating could yield more shale oil—up to 2.7 g, compared to only 1.33 g via conventional heating. The shale oil produced by microwave heating also contained higher proportions of saturated and aromatic hydrocarbons, lower amounts of asphaltenes and resins, and exhibited desulfurization and denitrogenation capabilities, resulting in lower sulfur and nitrogen contents in the liquid products.
These findings indicate that microwave heating, with its unique volumetric heating mechanism and ability to handle large-sized materials, can effectively reduce processing time and improve product quality, showing broader application prospects than conventional heating methods.
Figure 5. Schematic diagram of heating section in sample under microwave heating and conventional heating [76,77,78] ((a) Microwave Heating; (b) Conventional Heating).
Figure 5. Schematic diagram of heating section in sample under microwave heating and conventional heating [76,77,78] ((a) Microwave Heating; (b) Conventional Heating).
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However, despite its many advantages in oil shale pyrolysis, microwave heating still faces certain challenges. For instance, although increasing the power accelerates heating, it may also cause local overheating, leading to secondary cracking of oil and gas and thus a reduction in oil yield [79]. Therefore, in-depth research on the reaction mechanisms, temperature field distribution, and parameter optimization during microwave pyrolysis is crucial for further improving thermal processing efficiency and optimizing product yield. As research continues, in addition to microwave heating technology, auto-thermal (self-heating) pyrolysis methods have also been attracting increasing attention in recent years for their application in oil shale pyrolysis.

3.3.3. Pyrolysis Behavior of Oil Shale Under Auto-Thermal Heating

Auto-thermal heating has gradually demonstrated its unique advantages and regularities in oil shale pyrolysis. As shown in Figure 6, unlike traditional external energy supply methods, auto-thermal heating relies on partial oxidation reactions between organic matter and minerals within the oil shale. The heat generated from these reactions directly drives the pyrolysis process [80]. This approach effectively reduces external energy consumption, lowers the energy demands of the pyrolysis process, and enhances its overall sustainability.
However, auto-thermal heating still faces certain challenges, such as how to precisely control oxygen supply to achieve optimal pyrolysis performance and how to address potential issues of localized under-oxidation or over-oxidation [82]. Solving these issues is crucial for optimizing the auto-thermal heating technique and improving the efficiency of oil shale pyrolysis. Future research should delve deeper into the microscopic reaction mechanisms and macroscopic operational parameters of oil shale pyrolysis under auto-thermal heating to develop more efficient and sustainable technologies.
The in situ auto-thermal pyrolysis method not only ensures efficient recovery of pyrolysis oil and gas products but also offers extremely high energy efficiency and excellent economic feasibility. Experiments conducted by Yang et al. [83] on the Huadian deposit in the Songliao Basin, Jilin Province, showed that under an injected gas flow rate of 5 L/min with 16% oxygen content, the effective recovery rate of shale oil reached 67.1%, close to the 69.1% recovery rate achieved through high-temperature nitrogen injection for in situ conversion. More importantly, the energy efficiency of this method reached 3.46, which is 6.78 times that of the latter method’s energy efficiency of 0.51.
Studies have shown [84] that the key to auto-thermal heating lies in accurately controlling the oxygen supply to ensure that partial oxidation reactions produce sufficient heat while avoiding excessive oxidation that would lead to the loss of organic matter. Furthermore, research indicates [85] that under appropriate oxygen supply conditions, as the in situ conversion progresses, the shale oil undergoes a transformation from medium and heavy components toward lighter fractions. Higher localized pyrolysis temperatures promote the secondary cracking of heavy components, resulting in more pronounced light-oil characteristics—significantly outperforming the yields under conventional heating.
Another advantage of the auto-thermal method lies in utilizing the exothermic oxidation of residual carbon as the core mechanism for sustaining the pyrolysis process. Relevant studies have shown [86] that during auto-thermal pyrolysis, the oxidation of residual carbon releases substantial heat, which provides a continuous and stable energy supply for kerogen thermal decomposition. Thermodynamic analyses indicate that this exothermic effect can maintain the system within the optimal pyrolysis temperature range of 450–550 °C, significantly enhancing pyrolysis efficiency (oil-phase recovery rate > 90%). Meanwhile, the sustained heat supply promotes the selective breaking of weak bonds in kerogen (such as C–S and C–O bonds), increasing the proportion of light components (C5–C13) in the pyrolysis products by 15–20% compared to traditional retorting methods, and substantially improving oil quality. This self-sustaining energy mechanism gives the auto-thermal method clear advantages in both product yield and quality.
All in all, conventional heating, microwave heating, and auto-thermal heating each have distinct characteristics in oil shale pyrolysis. A comparison of their key features can be found in Table 2. A systematic summary of their energy efficiency, limitations, and core mechanisms provides a clearer reference for the selection and optimization of heating methods in subsequent studies.

3.4. Research Progress on the Effects of Minerals and Catalysts on Oil Shale Pyrolysis Behavior

Both inherent minerals in oil shale and externally added catalysts can influence the pyrolysis reaction pathways. Regarding inherent minerals, carbonates and clays coexist with organic matter and may act as catalysts or inhibitors during pyrolysis. For example, Ballice et al. [87] found that carbonate minerals in rocks exhibit a certain catalytic effect on the decomposition of organic matter, whereas silicate minerals (such as quartz and clays) tend to inhibit pyrolysis, with the overall inhibitory effect outweighing the catalytic effect. Chang et al. [88] further confirmed that inherent carbonates promote shale oil production, while silicates suppress oil formation and facilitate the cracking and aromatization of long-chain hydrocarbons. In addition, the effects of different minerals vary significantly with the type of kerogen. Experiments by Hetényi et al. [89] showed that for Type I kerogen, montmorillonite clay exhibits strong catalytic activity, enhancing the release of soluble organic matter; however, for Type III kerogen, montmorillonite slightly inhibits pyrolysis.
Beyond the role of inherent minerals, the addition of external catalysts has become a research focus over the past decade. Metal oxides and zeolite catalysts have been shown to alter the pyrolysis reaction pathway and reduce the activation energy of certain reactions. One study [90] involved pyrolysis experiments with the addition of Fe2O3 and CaCO3, revealing that Fe2O3 helps increase shale oil yield while reducing gas-phase products, whereas CaCO3 promotes secondary cracking of tar, thereby increasing gas yields. Classical studies have also shown [91] that hydrogen-type zeolites such as ZSM-5 enhance the cracking of kerogen into small hydrocarbon molecules, resulting in increased gas production and reduced oil yield. At the same time, they help reduce nitrogen- and sulfur-containing impurities in the oil phase, as these heteroatoms tend to form gaseous NH3 and H2S, which can be removed. Overall, minerals and catalysts influence pyrolysis behavior by altering the generation and removal rates of reaction intermediates. Effectively utilizing the advantages of external catalysts—such as lowering reaction temperatures and selectively increasing the yield of light oil fractions—while addressing the potential issue of reduced oil yield, has become one of the key directions in recent oil shale pyrolysis research.

4. Mechanism Understanding: Current Insights and Challenges

Although numerous studies in recent years have employed TGA-DSC and coupled techniques to investigate the pyrolysis of oil shale, the current understanding of its mechanisms remains incomplete [87]. In particular, three aspects—the heterogeneity of kerogen, the role of mineral matter, and the quantitative effects of secondary reactions which require further clarification, and limitations in kinetic analysis further constrain the depth of mechanistic interpretation.
First, the heterogeneity of kerogen plays a decisive role in determining the diversity of pyrolysis behaviors and kinetic characteristics. Different kerogen types exhibit significant differences in structure and composition, leading to distinct pyrolysis pathways and kinetic parameters (e.g., activation energy Ea, pre-exponential factor A): Type I kerogen (e.g., from the Green River Formation, USA) is hydrogen-rich, tends to produce a high yield of shale oil, and is characterized by relatively low activation energies (205–280 kJ/mol) [46,92]; Type II kerogen, common in Fushun (China) and the Green River Formation (USA), produces both oil and gas, with intermediate kinetic parameters (e.g., activation energies of 225–295 kJ/mol for Fushun oil shale) [47,49]; whereas Type III kerogen (e.g., from Yaojie, China) is oxygen-rich, mainly generating gas and char, with high activation energies (280–350 kJ/mol) and low liquid yields [45,88,93]. Such heterogeneity often results in significant differences in pyrolysis characteristics and kinetic parameters even under similar experimental conditions, thereby complicating kinetic modeling (e.g., difficulties in unifying model assumptions across kerogen types) and limiting the universality of mechanistic interpretations.
Second, the role of mineral matter extends far beyond the traditional view of simple catalytic or inhibitory effects, and further interacts with the kinetic process of pyrolysis. Recent studies demonstrate that minerals can influence pyrolysis through multiple mechanisms that couple with kinetics: quartz and carbonates, owing to their differences in thermal conductivity, can alter the local temperature distribution, leading to variations in apparent activation energy (e.g., uneven heating may cause a 30 kJ/mol deviation in Ea within a single oil shale particle) [88]; clay minerals (e.g., montmorillonite in Fushun oil shale) can adsorb free radicals or intermediates via ion exchange, modifying reaction pathways and increasing apparent activation energy by 15–25 kJ/mol compared to mineral-free kerogen [88,94]; mineral expansion or phase transformation at high temperatures may alter pore structures, affecting the diffusion and residence time of volatile products, which in turn influences the extent of secondary reactions and the corresponding kinetic parameters (e.g., prolonged residence time may increase the contribution of high-energy secondary cracking reactions) [94]. Hence, minerals impact not only the chemical composition of products but also fundamentally influence the kinetics and mechanisms of pyrolysis through coupled physical–chemical processes.
Third, the quantitative effects of secondary reactions are critical in shaping product distributions, and their kinetic characteristics remain insufficiently addressed in current models. Primary products such as oil vapors and asphaltenes often undergo secondary cracking at elevated temperatures, reducing liquid yields while promoting the generation of gases and char [95]. Experimental results have shown that reaction temperature exerts a profound influence on the yields of oil and gas, as well as on the kinetics of secondary reactions: under optimized primary reaction conditions, when the temperature of the secondary reaction reactor increased from 600 °C to 650 °C, the yield of pyrolyzed shale oil decreased by 15% (mass) and the gas yield increased by 20% (mass), which is attributed to the accelerated secondary cracking of heavy hydrocarbons (with a corresponding decrease in activation energy for secondary reactions) [48]. Compared with a nitrogen atmosphere, adding steam as the reaction atmosphere in the second stage could enhance the liquid oil yield by 5%, as steam provides hydrogen radicals to inhibit the formation of high-energy carbon–carbon cross-linking reactions, thereby reducing the apparent activation energy of secondary reactions [48]. Furthermore, recent studies have highlighted the importance of pressure and in situ conditions in regulating secondary reaction kinetics: for instance, Liu et al. [96] demonstrated that supercritical water can reduce the activation energy of kerogen pyrolysis and enhance oil quality while suppressing char formation; similarly, Zhang et al. [97] reported that in semi-closed, high-pressure systems (500 °C, 8 MPa), oil yields decreased significantly while gas production increased, indicating that pressure modulates the kinetic balance between primary and secondary reactions (e.g., high pressure may promote the condensation of intermediates, increasing the activation energy of cracking reactions) [97]. Moreover, pore-scale modeling has recently been employed to investigate heat and mass transfer during CO2-enhanced pyrolysis, providing deeper insights into the coupling of mass transfer and reaction kinetics in in situ processes [98].
Current kinetic analysis also faces inherent limitations: there is a lack of systematic comparison of kinetic parameters across different oil shale types, making it difficult to distinguish the contributions of kerogen intrinsic properties versus external factors (e.g., minerals, atmosphere) to kinetic parameters; the reliability boundaries of different kinetic models (e.g., Coats-Redfern, Flynn-Wall-Ozawa) are insufficiently discussed, with some studies over-reliant on single models that assume a single reaction mechanism, leading to deviations in activation energy (e.g., the Coats-Redfern model may underestimate Ea by 40 kJ/mol for Type III kerogen compared to the Distributed Activation Energy Model) [18,38,87]; and complex multi-step reactions (primary + secondary reactions) are often simplified in models, failing to accurately quantify the kinetic characteristics of intermediate product conversion [99].
In summary, the complexity of oil shale pyrolysis mechanisms arises not only from the intrinsic heterogeneity of kerogen but also from mineral–organic interactions and secondary reaction pathways, with kinetic analysis limitations further hindering mechanistic clarity. Future research should integrate advanced in situ characterization (e.g., in situ TG-FTIR-MS to track intermediate kinetics) and multi-scale simulation approaches (e.g., coupling ReaxFF molecular dynamics with macroscopic kinetic models) to quantitatively and visually capture these processes, thereby improving kinetic models (e.g., developing dynamic activation energy models that account for kerogen heterogeneity and mineral effects) and supporting the industrial application of oil shale pyrolysis.

5. Future Research Directions and Outlook

The pyrolysis process of oil shale involves a complex network of chemical reactions, and current understanding of its mechanisms still faces many uncertainties and diversities. During pyrolysis, the kerogen in oil shale is a highly complex and heterogeneous organic polymer with a constantly varying composition and structure. The breaking and recombination of different chemical bonds result in pyrolysis being not a single reaction, but a combination of numerous parallel reactions contributing to oil and gas production [100]. Literature reviews highlight the extreme complexity of oil shale pyrolysis mechanisms, with existing kinetic models often simplifying the average effects of various reactions into overall kinetic parameters [99]—a limitation that becomes more prominent when addressing cross-type oil shale differences, as kinetic parameters (e.g., activation energy Ea, pre-exponential factor A) can vary by 50–70 kJ/mol between Type I and Type III kerogen [45,46,93].Additionally, the structural and elemental composition of kerogen varies significantly across different oil shale deposits, leading to diverse pyrolysis pathways and product distributions, thereby increasing the uncertainty in mechanism studies [100]. The presence of minerals further complicates the pyrolysis process, as inorganic minerals may catalyze or inhibit certain reactions during kerogen decomposition. For instance, clay minerals can increase apparent Ea by 15–25 kJ/mol via radical adsorption, while carbonates may reduce Ea by altering local heat transfer, creating a “kinetic modulation effect” that is yet to be fully quantified [88,94].
Due to the complex structure of kerogen and the difficulty of directly observing reaction pathways, current understanding of pyrolysis mechanisms mainly relies on modeling methods and indirect experimental characterizations, which have inherent limitations. In recent years, researchers [101] have used reactive molecular dynamics simulations to model the initial steps of kerogen pyrolysis, and the results are consistent with experimental analysis of pyrolysis products, to some extent verifying the reliability of the models. However, there is still a lack of understanding regarding more fundamental mechanisms, such as the changes in electronic distribution within kerogen molecules, and current mechanism models fall short of fully revealing the details of bond cleavage and rearrangement, especially for intermediate species (e.g., asphaltenes, heavy hydrocarbons) whose kinetic characteristics (e.g., secondary cracking Ea are often omitted or simplified [48,95].
Overall, the complexity of kerogen structure and the limitations of existing mechanism models remain core scientific challenges in oil shale pyrolysis research, with kinetic analysis gaps further exacerbating these challenges. Future studies need to integrate advanced characterization techniques and simulation methods to explore microscopic reaction pathways in depth, while specifically addressing kinetic-related limitations:
Construct a cross-type oil shale kinetic parameter database: Systematically collect Ea, A, and reaction order data for Type I–III kerogen from different deposits (e.g., Green River, Fushun, Yaojie), and use machine learning to decouple the contributions of kerogen intrinsic properties (H/C ratio, bond distribution) and external factors (mineral content, atmosphere) to kinetic parameters, establishing a “kerogen property-kinetic parameter” prediction model [45,46,87].
Develop multi-mechanism coupled kinetic models: Move beyond single-reaction-assumption models (e.g., Coats-Redfern) and integrate distributed activation energy models (DAEM) with reaction pathway networks to separately quantify the kinetic parameters of primary reactions (kerogen→ asphaltenes, Ea: 205–280 kJ/mol for Type I) and secondary reactions (asphaltenes→ light oil/gas, Ea: 240–320 kJ/mol), while introducing dynamic Ea (varying with conversion and temperature) to capture the coupling effects of mineral heat transfer and radical adsorption [18,38,99].
Standardize the validation process for kinetic models: Use multi-technique cross-validation (e.g., combining TG-FTIR for product evolution with DSC for heat flow analysis) to verify the physical meaning of kinetic parameters. For example, comparing Ea derived from Flynn-Wall-Ozawa (FWO) and Friedman methods to ensure deviations are within 10%, and correlating model-predicted product yields with experimental data (e.g., shale oil yield at 475 °C) to avoid over-fitting [87,102].
Techniques such as in situ spectroscopy (e.g., in situ TG-FTIR-MS) and quantum chemical calculations can help elucidate the key bond cleavage events and the evolution of intermediates, thereby providing the basis for constructing high-precision reaction models. Existing research has shown that combining multi-scale molecular simulations with Mayer bond order and electrostatic potential analyses reveals that weak bonds such as hydroxyl, ether, and amide bonds in kerogen tend to cleave preferentially during the early stages of pyrolysis (Ea: ~50–75 kcal/mol) [102]. Furthermore, HOMO/LUMO orbital distributions and Hirshfeld charge characteristics have been used to identify critical regions for intermediate formation and transformation (Figure 7a,b) [102]. Meanwhile, ReaxFF molecular dynamics simulations have demonstrated strong capabilities in capturing dynamic processes in the pyrolysis of lacustrine shale and heavy oil. These simulations have successfully modeled processes such as aromatic ring opening, aliphatic chain cracking, and free radical formation at different stages of evolution (Figure 7c,d), and have revealed how temperature, pressure, and reaction atmosphere regulate intermediate selectivity and product distribution [103,104]. Notably, coupling ReaxFF simulations with macroscopic kinetic models can bridge the gap between molecular bond cleavage (microscale) and reactor-scale product distribution (macroscale), enabling more accurate prediction of kinetic parameters under industrial conditions (e.g., high pressure, steam atmosphere) [96,97].
In addition to these directions, future research also needs to give more attention to three aspects highlighted in recent mechanistic studies: (1) refining kerogen heterogeneity and differentiating pyrolysis behaviors of Type I–III kerogen; (2) quantifying the physical–chemical coupling of mineral–organic interactions beyond traditional catalytic views; and (3) systematically evaluating the quantitative effects of secondary reactions under varied temperature, pressure, and atmosphere conditions [87,88,94,95,96,97,98]. Addressing these aspects will provide the necessary theoretical foundation for constructing more universally applicable kinetic and mechanistic models and will directly support the industrial application of oil shale pyrolysis.

6. Conclusions

Oil shale pyrolysis has seen considerable advancements in reaction mechanism understanding, process optimization, and technological innovation. The main conclusions are as follows:
(1)
The thermal decomposition process includes three stages—evaporation of moisture and light volatiles (150–200 °C), kerogen pyrolysis (300–520 °C), and mineral decomposition (>600 °C). TGA–DSC provides effective characterization of mass and heat changes across these stages, with DSC quantifying the endothermic demand of each stage (e.g., kerogen decomposition consumes ~36% of total pyrolysis heat) and TGA-DTG enabling deconvolution of overlapping reaction peaks to identify stage-specific kinetic contributions [17,21].
(2)
Reaction temperature, heating rate, and particle size critically influence product distribution. Optimal oil yields are achieved at 450–550 °C under moderate heating rates (1–7 °C/min), with particle size affecting heat and mass transfer efficiency. Smaller particles increase gas yield by enhancing secondary cracking, while larger particles (1–3 mm) maintain higher oil yield by reducing vapor residence time [58,60]. Notably, heating rate also modulates kinetic parameters: fast heating (>50 °C/min) causes thermal lag, increasing apparent Ea by up to 30 kJ/mol and leading to incomplete pyrolysis, while moderate rates balance primary reaction efficiency and secondary reaction inhibition [53,55].
(3)
Novel pyrolysis techniques—including steam-assisted, microwave, and autothermic methods—offer improved efficiency and selectivity. Each approach presents specific benefits and technical challenges, especially in energy management and control precision: microwave heating reduces Ea by 13–39% and shortens heating time (750 °C in 9 min vs. 55 min for conventional heating) but risks local overheating [73,74]; autothermic heating achieves an energy efficiency of 3.46 (6.78 times that of nitrogen injection) but requires precise oxygen control to avoid over-oxidation [84]; steam-assisted methods provide hydrogen radicals to lower secondary reaction Ea, increasing light oil yield by 15–20% [70,96].
(4)
Carbonate minerals promote hydrocarbon generation (e.g., increasing oil yield by 5–8% via catalytic kerogen cleavage), while silicates inhibit pyrolysis and lead to aromatization (e.g., quartz raises apparent Ea by 20–25 kJ/mol) [87,88]. Catalysts such as Fe2O3 and ZSM-5 regulate reaction pathways and lower activation temperatures: Fe2O3 reduces kerogen pyrolysis Ea by 13–39% to enhance oil yield, while ZSM-5 promotes cracking of long-chain hydrocarbons into light fractions (C5–C13) but may cause excessive secondary cracking, reducing oil yield by 5–10% [90,91].
(5)
The structural heterogeneity of kerogen limits unified kinetic modeling [107] —Type I kerogen (Green River) has Ea of 205–280 kJ/mol, Type II (Fushun) of 225–295 kJ/mol, and Type III (Yaojie) of 280–350 kJ/mol, while process controllability remains a challenge. Existing kinetic models often simplify multi-step reactions (primary + secondary) or rely on single mechanisms (e.g., Coats-Redfern), leading to Ea deviations of up to 40 kJ/mol for Type III kerogen compared to DAEM [18,38,87]. Advanced characterization tools (e.g., in situ TG-FTIR-MS) and molecular simulations (ReaxFF MD) are essential for mechanism elucidation, and real-time monitoring and intelligent systems (e.g., coupling kinetic models with reactor temperature control) are needed to enhance process regulation and efficiency.
In particular, recent insights emphasize that kerogen heterogeneity (driving kinetic parameter differences), mineral–organic interactions (modulating Ea and reaction pathways), and secondary reaction pathways (shaping product distribution via kinetic competition) are the three decisive factors shaping pyrolysis behavior. Their integration into next-generation kinetic models, along with in-semi-coke-situ experimental validation (e.g., tracking intermediate Ea via DSC) and multi-scale simulation approaches (molecular MD + macroscopic reactor modeling), will be crucial for bridging the gap between laboratory studies (e.g., TGA-based kinetic tests) and industrial practice (e.g., in situ retorting with controlled temperature/pressure).
In summary, oil shale pyrolysis research is shifting from empirical experimentation to mechanism-driven and technology-integrated approaches. Future work should prioritize interdisciplinary collaboration (combining materials science, chemical engineering, and computational chemistry), the development of multi-scale kinetic models (accounting for kerogen heterogeneity and mineral effects), and the integration of smart control and reactor design to enable efficient, clean, and scalable utilization of unconventional hydrocarbon resources.

Author Contributions

Conceptualization, X.L. and J.Z.; Methodology, R.Y.; Software, D.Z.; Validation, R.Y., D.Z. and W.L.; Formal analysis, R.Y.; Investigation, J.S.; Resources, X.L.; Data Curation, W.L.; Writing—Original Draft Preparation, R.Y.; Writing—Review and Editing, J.Z.; Visualization, L.H.; Supervision, J.Z.; Project Administration, X.L.; Funding Acquisition, J.Z. All authors have read and agreed to the published version of the manuscript.

Funding

This research was financially supported by the Open Project of the National Research Center for Oil Shale Exploitation and Development (Grant No. 3355F000-24-ZC0613-0062), the National Natural Science Foundation of China (Grant No. 42302188).

Data Availability Statement

Not applicable.

Acknowledgments

The authors would like to express our appreciation to the National Research Center for Oil Shale Exploitation and Development, Engineering Technology Management Center of Sinopec Shengli Oilfield Company, Research Institute of Petroleum Exploration and Development of Sinopec, and State Key Laboratory of Southwest Petroleum University for providing essential research platforms and support throughout this study.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Kılıç, M.; Pütün, A.E.; Uzun, B.B.; Pütün, E. Converting of oil shale and biomass into liquid hydrocarbons via pyrolysis. Energy Convers. Manag. 2014, 78, 461–467. [Google Scholar] [CrossRef]
  2. World Oil Group. EIA estimates global recoverable shale oil resources at 345 billion bbl. World Oil 2013, 234, 13. [Google Scholar]
  3. Energy Information Administration. Technically Recoverable Shale Oil and Shale Gas Resources: An Assessment of 137 Shale Formations in 41 Countries Outside the United States; US Department of Energy: Washington, DC, USA, 2013.
  4. Kang, Z.; Zhao, Y.; Yang, D. Review of oil shale in-situ conversion technology. Appl. Energy 2020, 269, 115121. [Google Scholar] [CrossRef]
  5. Pantilov, P.V.; Gorbunova, M.V.; Krivtsov, E.B. Influence of Mineral Components on the Composition of Oil Shale Organic Matter Cracking Products. Solid Fuel Chem. 2024, 58, 124–128. [Google Scholar] [CrossRef]
  6. Bai, F.; Liu, Y.; Lai, C.; Sun, Y.; Wang, J.; Sun, P.; Xue, L.; Zhao, J.; Guo, M. Thermal degradations and processes of four kerogens via thermogravimetric–fourier-transform infrared: Pyrolysis performances, products, and kinetics. Energy Fuels 2020, 34, 2969–2979. [Google Scholar] [CrossRef]
  7. Moratori, C.C.; Luz Lisbôa, A.C. Mass and heat transfer to and from oil shale exposed to a gas stream at constant temperature. Oil Shale 2023, 40, 151–165. [Google Scholar] [CrossRef]
  8. Wang, T.; Wang, X.; Zhang, D.; Chen, X.; Luo, H.; Wang, J.; Ma, Z.; Wang, Q.; Liu, P.; Chen, Z.; et al. Hydrocarbon generation-expulsion-retention mechanisms in marine organic-richmarl: Insights from semi-closed hydrous pyrolysis simulation experiments. J. Anal. Appl. Pyrolysis 2025, 107224. [Google Scholar] [CrossRef]
  9. Ma, Y.; He, L.; Li, S.; Teng, J. Heat transfer of oil shale in a small-scale fixed bed. J. Therm. Anal. Calorim. 2016, 124, 461–469. [Google Scholar] [CrossRef]
  10. Tiwari, P. Oil Shale Pyrolysis: Benchscale Experimental Studies and Modeling; Department of Chemical Engineering, University of Utah: Salt Lake City, UT, USA, 2012. [Google Scholar]
  11. Skala, D.; Kopsch, H.; Sokić, M.; Neumann, H.J.; Jovanović, J.A. Kinetics and modelling of oil shale pyrolysis. Fuel 1990, 69, 490–496. [Google Scholar] [CrossRef]
  12. Huang, Y.; Fan, C.; Han, X.; Jiang, X. A TGA-MS investigation of the effect of heating rate and mineral matrix on the pyrolysis of kerogen in oil shale. Oil Shale 2016, 33, 125–141. [Google Scholar] [CrossRef]
  13. Berkovich, A.J.; Levy, J.H.; Schmidt, S.J.; Young, B.R. Heat capacities and enthalpies for some Australian oil shales from non-isothermal modulated DSC. Thermochim. Acta 2000, 357, 41–45. [Google Scholar] [CrossRef]
  14. Zhao, X.; Feng, Y.; Fan, X.; Xu, M.; Pang, Y.; Wang, J.; Yang, S.; Shi, L. Covalent bonding structures of eight oil shales and the characteristics of bond cleavage during the pyrolysis process. Fuel 2024, 370, 131821. [Google Scholar] [CrossRef]
  15. Levy, M.; Riri, K. Comparative TGA and DSC studies of oil shales. Thermochim. Acta 1988, 134, 327–331. [Google Scholar] [CrossRef]
  16. Abduhani, H.; Tursun, Y.; Abulizi, A.; Talifu, D.; Huang, X. Characteristics and kinetics of the gas releasing during oil shale pyrolysis in a micro fluidized bed reactor. J. Anal. Appl. Pyrolysis 2021, 157, 105187. [Google Scholar] [CrossRef]
  17. Zhao, S.; Sun, Y.; Lü, X.; Li, Q. Energy consumption and product release characteristics evaluation of oil shale non-isothermal pyrolysis based on TG-DSC. J. Pet. Sci. Eng. 2020, 187, 106812. [Google Scholar] [CrossRef]
  18. Bai, F.; Guo, W.; Lü, X.; Liu, Y.; Guo, M.; Li, Q.; Sun, Y. Kinetic study on the pyrolysis behavior of Huadian oil shale via non-isothermal thermogravimetric data. Fuel 2015, 146, 111–118. [Google Scholar] [CrossRef]
  19. Warne, S.S.J.; Dubrawski, J.V. Applications of DTA and DSC to coal and oil shale evaluation. J. Therm. Anal. 1989, 35, 219–242. [Google Scholar] [CrossRef]
  20. Patterson, J.H. A review of the effects of minerals in processing of Australian oil shales. Fuel 1994, 73, 321–327. [Google Scholar] [CrossRef]
  21. Liu, Q.Q.; Han, X.X.; Li, Q.Y.; Huang, Y.R.; Jiang, X.M. TG–DSC analysis of pyrolysis process of two Chinese oil shales. J. Therm. Anal. Calorim. 2014, 116, 511–517. [Google Scholar] [CrossRef]
  22. Zhang, Y.; Zhao, Q.; Lu, H.; Wang, G.; Song, Z.; Jin, H.; Guo, L. Insight into kerogen II pyrolysis mechanism by master plot method based on TG-FTIR analysis. Fuel 2025, 395, 135237. [Google Scholar] [CrossRef]
  23. Palayangoda, S.S.; Nguyen, Q.P. Thermal behavior of raw oil shale and its components. Oil Shale 2015, 32, 160–171. [Google Scholar] [CrossRef]
  24. Yan, J.; Jiang, X.; Han, X.; Liu, J. A TG–FTIR investigation to the catalytic effect of mineral matrix in oil shale on the pyrolysis and combustion of kerogen. Fuel 2013, 104, 307–317. [Google Scholar] [CrossRef]
  25. Hao, J.; Feng, W.; Qiao, Y.; Tian, Y.; Zhang, J.; Che, Y. Thermal cracking behaviors and products distribution of oil sand bitumen by TG-FTIR and Py-GC/TOF-MS. Energy Convers. Manag. 2017, 151, 227–239. [Google Scholar] [CrossRef]
  26. Raja, M.A.; Zhao, Y.; Zhang, X.; Li, C.; Zhang, S. Practices for modeling oil shale pyrolysis and kinetics. Rev. Chem. Eng. 2017, 34, 21–42. [Google Scholar] [CrossRef]
  27. Wu, D.; Zhang, W.; Fu, B.; Hu, G. Chemical structure and gas products of different rank coals during pyrolysis: Based on in-situ FTIR and TG/MS analysis techniques. J. Therm. Anal. Calorim. 2019, 136, 2017–2031. [Google Scholar] [CrossRef]
  28. Han, F.; Meng, A.; Li, Q.; Zhang, Y. Thermal decomposition and evolved gas analysis (TG-MS) of lignite coals from Southwest China. J. Energy Inst. 2016, 89, 94–100. [Google Scholar] [CrossRef]
  29. Pan, L.; Dai, F.; Li, G.; Liu, S. A TGA/DTA-MS investigation to the influence of process conditions on the pyrolysis of Jimsar oil shale. Energy 2015, 86, 749–757. [Google Scholar] [CrossRef]
  30. Tian, B.; Qiao, Y.; Tian, Y.; Liu, Q. Investigation on the effect of particle size and heating rate on pyrolysis characteristics of a bituminous coal by TG–FTIR. J. Anal. Appl. Pyrolysis 2016, 121, 376–386. [Google Scholar] [CrossRef]
  31. Chen, B.; Han, X.; Jiang, X. In situ FTIR analysis of the evolution of functional groups of oil shale during pyrolysis. Energy Fuels 2016, 30, 5611–5616. [Google Scholar] [CrossRef]
  32. Liu, Z.; Ma, H.; Guo, J.; Liu, G.; Wang, Z.; Guo, Y. Pyrolysis Characteristics and Effect on Pore Structure of Jimsar Oil Shale Based on TG-FTIR-MS Analysis. Geofluids 2022, 2022, 7857239. [Google Scholar] [CrossRef]
  33. Kok, M.V.; Varfolomeev, M.A.; Nurgaliev, D.K.; Kandasamy, J. Application of TGA-MS technique for oil shale characterization and kinetics. J. Therm. Anal. Calorim. 2022, 147, 10767–10774. [Google Scholar] [CrossRef]
  34. Khraisha, Y.H. Flash pyrolysis of oil shales in a fluidized bed reactor. Energy Convers. Manag. 2000, 41, 1729–1739. [Google Scholar] [CrossRef]
  35. Ma, Y.; Zhou, S.; Li, J.; Li, Y.; Chen, K.; Zhang, Y.; Fu, D. Pyrolysis characteristics analysis of Chang-7 oil shale using thermal analysis and pyrolysis-gas chromatograph-mass spectrometry. Energy Explor. Exploit. 2018, 36, 1006–1021. [Google Scholar] [CrossRef]
  36. Williams, P.T.; Ahmad, N. Investigation of oil-shale pyrolysis processing conditions using thermogravimetric analysis. Appl. Energy 2000, 66, 113–133. [Google Scholar] [CrossRef]
  37. Al-Harahsheh, M.; Al-Ayed, O.; Robinson, J.; Kingman, S.; Al-Harahsheh, A.; Tarawneh, K.; Saeid, A.; Barranco, R. Effect of demineralization and heating rate on the pyrolysis kinetics of Jordanian oil shales. Fuel Process. Technol. 2011, 92, 1805–1811. [Google Scholar] [CrossRef]
  38. Pan, N.; Li, D.; Lü, W.; Dai, F. Kinetic study on the pyrolysis behavior of Jimsar oil shale. Oil Shale 2019, 36, 462–482. [Google Scholar] [CrossRef]
  39. Zhang, Y.; Zhao, M.; Linghu, R.; Wang, C.; Zhang, S. Comparative kinetics of coal and oil shale pyrolysis in a micro fluidized bed reaction analyzer. Carbon Resour. Convers. 2019, 2, 217–224. [Google Scholar] [CrossRef]
  40. Williams, P.T.; Ahmad, N. Influence of process conditions on the pyrolysis of Pakistani oil shales. Fuel 1999, 78, 653–662. [Google Scholar] [CrossRef]
  41. Nazzal, J.M. Influence of heating rate on the pyrolysis of Jordan oil shale. J. Anal. Appl. Pyrolysis 2002, 62, 225–238. [Google Scholar] [CrossRef]
  42. Lin, L.; Lai, D.; Guo, E.; Zhang, C.; Xu, G. Oil shale pyrolysis in indirectly heated fixed bed with metallic plates of heating enhancement. Fuel 2016, 163, 48–55. [Google Scholar] [CrossRef]
  43. Wang, C.; Zhu, J. Developments in the understanding of gas–solid contact efficiency in the circulating fluidized bed riser reactor: A review. Chin. J. Chem. Eng. 2016, 24, 53–62. [Google Scholar] [CrossRef]
  44. Maaten, B.; Siirde, A.; Vahur, S.; Kirsimäe, K. Influence of the end-temperature on the oil shale fast pyrolysis process and its products. J. Therm. Anal. Calorim. 2023, 148, 1647–1655. [Google Scholar] [CrossRef]
  45. Luo, W. Experimental Study on Pyrolysis Process and Product Precipitation Characteristics of Oil Shale. Ph.D. Thesis, Xi’an University of Architecture and Technology, Xi’an, China, 2016. [Google Scholar]
  46. Le Doan, T.V.; Bostrom, N.W.; Burnham, A.K.; Kleinberg, R.L.; Pomerantz, A.E.; Allix, P. Green River oil shale pyrolysis: Semi-open conditions. Energy Fuels 2013, 27, 6447–6459. [Google Scholar] [CrossRef]
  47. Li, J.; Shan, X.; Song, X.; He, W. Evaluation of the organic matter product of Huadian oil shale during pyrolysis using multiple approaches: Guidance for the in situ conversion of oil shale. J. Anal. Appl. Pyrolysis 2022, 167, 105656. [Google Scholar] [CrossRef]
  48. Zhang, Y.; Guan, J.; Qiao, P.; Li, J.; Zhang, W. Effects of secondary reaction of primary volatiles on oil/gas yield and quality in oil shale pyrolysis. J. Fuel Chem. Technol. 2021, 49, 924–932. [Google Scholar] [CrossRef]
  49. Ding, H.; Ma, Y.; Li, S.; Wang, Q.; Hong, W.; Jiang, H.; Li, H.; Jiang, M. Pyrolytic characteristics of Fushun oil shale and its by-products. J. Therm. Anal. Calorim. 2022, 147, 5255–5267. [Google Scholar] [CrossRef]
  50. Syed, S.; Qudaih, R.; Talab, I.; Janajreh, I. Kinetics of pyrolysis and combustion of oil shale sample from thermogravimetric data. Fuel 2011, 90, 1631–1637. [Google Scholar] [CrossRef]
  51. Yang, Q.; Qian, Y.; Kraslawski, A.; Zhou, H.; Yang, S. Framework for advanced exergoeconomic performance analysis and optimization of an oil shale retorting process. Energy 2016, 109, 62–76. [Google Scholar] [CrossRef]
  52. Foltin, J.P.; Lisboa, A.C.L.; de Klerk, A. Oil shale pyrolysis: Conversion dependence of kinetic parameters. Energy Fuels 2017, 31, 6766–6776. [Google Scholar] [CrossRef]
  53. Yang, S.; Wang, H.; Zheng, J.; Pan, Y.; Ji, C. Comprehensive review: Study on heating rate characteristics and coupling simulation of oil shale pyrolysis. J. Anal. Appl. Pyrolysis 2024, 177, 106289. [Google Scholar] [CrossRef]
  54. Shi, W. Investigation on Influencing Factors of Low-Temperature Retorting of Sunite Oil Shale. Coal 2013, 22, 20–21. [Google Scholar]
  55. Al-Ayed, O.S.; Al-Harahsheh, A.; Khaleel, A.M.; Al-Harahsheh, M. Oil shale pyrolysis in fixed-bed retort with different heating rates. Oil Shale 2009, 26, 139–147. [Google Scholar] [CrossRef]
  56. Zhang, Y.; Han, Z.; Wu, H.; Lai, D.; Glarborg, P.; Xu, G. Interactive matching between the temperature profile and secondary reactions of oil shale pyrolysis. Energy Fuels 2016, 30, 2865–2873. [Google Scholar] [CrossRef]
  57. Lisbôa, A.C.L. Investigations on Oil Shale Particle Reactions. Ph.D. Thesis, University of British Columbia, Vancouver, BC, Canada, 1997. [Google Scholar]
  58. Miura, K. Mild conversion of coal for producing valuable chemicals. Fuel Process. Technol. 2000, 62, 119–135. [Google Scholar] [CrossRef]
  59. Chang, Z.; Chu, M. The chemical composition and pyrolysis characteristics of thermal bitumen derived from pyrolyzing Huadian oil shale, China. Oil Shale 2019, 36, 62–75. [Google Scholar] [CrossRef]
  60. Ahmad, N.; Williams, P.T. Influence of particle grain size on the yield and composition of products from the pyrolysis of oil shales. J. Anal. Appl. Pyrolysis 1998, 46, 31–49. [Google Scholar] [CrossRef]
  61. Khalil, A.M. Oil shale pyrolysis and effect of particle size on the composition of shale oil. Oil Shale 2013, 30, 136–146. [Google Scholar] [CrossRef]
  62. Pan, L.; Dai, F.; Pei, S.; Huang, S.; Liu, S. Influence of particle size and temperature on the yield and composition of products from the pyrolysis of Jimsar (China) oil shale. J. Anal. Appl. Pyrolysis 2021, 157, 105211. [Google Scholar] [CrossRef]
  63. Burnham, A.K.; McConaghy, J.R. Comparison of the Acceptability of Various Oil Shale Processes; Elsevier: Amsterdam, The Netherlands, 2006. [Google Scholar]
  64. Sun, T.; Liu, H.; Zhang, Y.; Li, Y. Numerical simulation and optimization study of In-Situ Heating for three-dimensional oil shale exploitation with different well patterns. Case Stud. Therm. Eng. 2024, 55, 104089. [Google Scholar] [CrossRef]
  65. Xue, J.; Liu, Z. Numerical Simulation of Temperature Field Distribution in In-Situ Retorting of Oil Shale by Electric Heating Method. Chin. J. Undergr. Space Eng. 2015, 11, 669–672. [Google Scholar]
  66. Bai, Y.; Shu, Y.; Dang, H.; Yun, Y.; Tu, X.; Zhang, L.; Gao, T.; Zhang, M.; Zhao, X.; Yang, S. A review on the application of numerical simulation of oil shale electrical heating technology. Chem. Technol. Fuels Oils 2024, 60, 69–79. [Google Scholar] [CrossRef]
  67. Lei, G.; Li, Z.; Yao, C.; Zheng, Y.; Wang, N.; Wang, Z. Numerical simulation on in-situ upgrading of oil shale via steam injection. J. Univ. Pet. China 2017, 41, 100–107. [Google Scholar]
  68. Liu, S.; Gai, H.; Cheng, P. Technical scheme and application prospects of oil shale in situ conversion: A review of current status. Energies 2023, 16, 4386. [Google Scholar] [CrossRef]
  69. Wang, L.; Zhang, R.; Wang, G.; Zhao, J.; Yang, D.; Kang, Z.; Zhao, Y. Effect of long reaction distance on gas composition from organic-rich shale pyrolysis under high-temperature steam environment. Int. J. Coal Sci. Technol. 2024, 11, 34. [Google Scholar] [CrossRef]
  70. Inaba, H. New challenge in advanced thermal energy transportation using functionally thermal fluids. Int. J. Therm. Sci. 2000, 39, 991–1003. [Google Scholar] [CrossRef]
  71. Chen, J.; Li, X.; Gao, L.; Guo, S.; He, F. Microwave treatment of minerals and ores: Heating behaviors, applications, and future directions. Minerals 2024, 14, 219. [Google Scholar] [CrossRef]
  72. Lan, X.; Luo, W.; Song, Y.; Zhou, J.; Zhang, Q. Effect of the temperature on the characteristics of retorting products obtained by Yaojie oil shale pyrolysis. Energy Fuels 2015, 29, 7800–7806. [Google Scholar] [CrossRef]
  73. He, L.; Ma, Y.; Yue, C.; Li, S.; Tang, X. The heating performance and kinetic behaviour of oil shale during microwave pyrolysis. Energy 2022, 244, 123021. [Google Scholar] [CrossRef]
  74. Zhu, J.; Li, F.; Wang, H.; Yang, Z.; Chen, H.; Zhu, H. Numerical analysis of microwave-enhanced oil shale pyrolysis by rotation turntable based on the Arbitrary Lagrangian-Eulerian method. Fuel 2024, 371, 131925. [Google Scholar] [CrossRef]
  75. Zhu, J.; Yang, Z.; Li, X.; Qi, S.; Fang, Q.; Ding, Y. The experimental study of microwave heating on the microstructure of oil shale samples. Energy Sci. Eng. 2019, 7, 809–820. [Google Scholar] [CrossRef]
  76. Taheri-Shakib, J.; Shekarifard, A.; Naderi, H. The influence of electromagnetic waves on the gas condensate characterisation: Experimental evaluation. J. Pet. Sci. Eng. 2018, 166, 568–576. [Google Scholar] [CrossRef]
  77. Miura, M.; Kaga, H.; Sakurai, A.; Kakuchi, T.; Takahashi, K. Rapid pyrolysis of wood block by microwave heating. J. Anal. Appl. Pyrolysis 2004, 71, 187–199. [Google Scholar] [CrossRef]
  78. Chen, P.; Xie, Q.; Addy, M.; Zhou, W.; Liu, Y.; Wang, Y.; Cheng, Y.; Li, K.; Ruan, R. Utilization of municipal solid and liquid wastes for bioenergy and bioproducts production. Bioresour. Technol. 2016, 215, 163–172. [Google Scholar] [CrossRef] [PubMed]
  79. Mutyala, S.; Fairbridge, C.; Paré, J.R.J.; Bélanger, J.M.R.; Ng, S.H.; Hawkins, R. Microwave applications to oil sands and petroleum: A review. Fuel Process. Technol. 2010, 91, 127–135. [Google Scholar] [CrossRef]
  80. Xu, S.; Sun, Y.; Yang, Q.; Wang, H.; Kang, S.; Guo, W.; Shan, X.; He, W. Product migration and regional reaction characteristics in the autothermic pyrolysis in-situ conversion process of low-permeability Huadian oil shale core. Energy 2023, 283, 128525. [Google Scholar] [CrossRef]
  81. Yang, Q. Theoretical and Laboratory Experimental Study on In-Situ Pyrolysis of Oil Shale by Autogenous Heating Method. Ph.D. Thesis, Jilin University, Changchun, China, 2022. [Google Scholar]
  82. Guo, H.; Yang, Y.; Wang, K.; Pei, Y.; Wu, Q.; Liu, Y. Strengthening the applicability of self-heating retorting process to oil shale via co-retorting. Fuel 2015, 143, 1–8. [Google Scholar] [CrossRef]
  83. Yang, Q.; Guo, W.; Xu, S.; Zhu, C. The autothermic pyrolysis in-situ conversion process for oil shale recovery: Effect of gas injection parameters. Energy 2023, 283, 129134. [Google Scholar] [CrossRef]
  84. Sun, Y.H.; Bai, F.T.; Lü, X.S.; Li, Q.; Liu, Y.M.; Guo, M.Y.; Guo, W.; Liu, B.C. A novel energy-efficient pyrolysis process: Self-pyrolysis of oil shale triggered by topochemical heat in a horizontal fixed bed. Sci. Rep. 2015, 5, 8290. [Google Scholar] [CrossRef]
  85. Xu, S.T.; Lü, X.S.; Wang, H.; Sun, Y.H.; Kang, S.J.; Wang, Z.D.; Guo, W.; Deng, S.H. Characterization of oxygen initiation process in the autothermic pyrolysis in-situ conversion of Huadian oil shale. Pet. Sci. 2024, 21, 4481–4496. [Google Scholar] [CrossRef]
  86. Yu, D.; Fu, H.; Deng, S.; Xu, S.; Tang, W.; Sun, Y.; Guo, W. Effects of maturity on the oxidative pyrolysis characteristics and heat balance in autothermic in-situ conversion of low-medium maturity organic-rich shales. Energy 2025, 314, 134334. [Google Scholar] [CrossRef]
  87. Li, Y.; Li, J.; Zhou, S.; Meng, B.; Wu, T. A review on thermogravimetric analysis-based analyses of the pyrolysis kinetics of oil shale and coal. Energy Sci. Eng. 2024, 12, 329–355. [Google Scholar] [CrossRef]
  88. Chang, Z.; Chu, M.; Zhang, C.; Bai, S.; Lin, H.; Ma, L. Influence of inherent mineral matrix on the product yield and characterization from Huadian oil shale pyrolysis. J. Anal. Appl. Pyrolysis 2018, 130, 269–276. [Google Scholar] [CrossRef]
  89. Hetényi, M. Simulated thermal maturation of type I and III kerogens in the presence, and absence, of calcite and montmorillonite. Org. Geochem. 1995, 23, 121–127. [Google Scholar] [CrossRef]
  90. Yu, H.; Li, S.; Jin, G. Catalytic hydrotreating of the diesel distillate from Fushun shale oil for the production of clean fuel. Energy Fuels 2010, 24, 4419–4424. [Google Scholar] [CrossRef]
  91. Williams, P.T.; Chishti, H.M. Two stage pyrolysis of oil shale using a zeolite catalyst. J. Anal. Appl. Pyrolysis 2000, 55, 217–234. [Google Scholar] [CrossRef]
  92. Tissot, B.P.; Welte, D.H. Petroleum Formation and Occurrence; Springer Science & Business Media: Berlin, Germany, 2013. [Google Scholar]
  93. Behar, F.; Vandenbroucke, M.; Teermann, S.C.; Hatcher, P.G.; Leblond, C.; Lerat, O. Experimental simulation of gas generation from coals and a marine kerogen. Chem. Geol. 1995, 126, 247–260. [Google Scholar] [CrossRef]
  94. Zhong, M.; Huang, H.; Xu, P.; Hu, J. Catalysis of minerals in pyrolysis experiments. Minerals 2023, 13, 515. [Google Scholar] [CrossRef]
  95. Lai, D.; Shi, Y.; Geng, S.; Chen, Z.; Gao, S.; Zhan, J.H.; Xu, G. Secondary reactions in oil shale pyrolysis by solid heat carrier in a moving bed with internals. Fuel 2016, 173, 138–145. [Google Scholar] [CrossRef]
  96. Liu, Y.; Yao, C.; Meng, X.; Ma, Y.; Xu, L.; Du, X. Pyrolysis mechanism and reservoir simulation study of organic-rich shale during the in situ conversion via supercritical water heating. Energy Fuels 2024, 38, 14246–14261. [Google Scholar] [CrossRef]
  97. Zhang, X.; Guo, W.; Pan, J.; Zhu, C.; Deng, S. In-situ pyrolysis of oil shale in pressured semi-closed system: Insights into products characteristics and pyrolysis mechanism. Energy 2024, 286, 129608. [Google Scholar] [CrossRef]
  98. Shi, Y.; Weng, D.; Cai, B.; Zhang, Y.; Zhang, Y.; Wang, B.; Wang, H. Flow and Heat Transfer of Shale Oil Reservoir during CO2 Enhanced Pyrolysis: A Pore-Scale Modeling. Processes 2024, 12, 1694. [Google Scholar] [CrossRef]
  99. Lü, X.; Sun, Y.; Lu, T.; Bai, F.; Viljanen, M. An efficient and general analytical approach to modelling pyrolysis kinetics of oil shale. Fuel 2014, 135, 182–187. [Google Scholar] [CrossRef]
  100. Baruah, B.; Tiwari, P. Effect of high pressure on nonisothermal pyrolysis kinetics of oil shale and product yield. Energy Fuels 2020, 34, 15855–15869. [Google Scholar] [CrossRef]
  101. Pan, S.; Zhou, H.; Wang, Q.; Bai, J.; Cui, D.; Wang, X. Experimental and molecular simulation studies of Huadian oil shale kerogen. ACS Omega 2022, 7, 17253–17269. [Google Scholar] [CrossRef] [PubMed]
  102. Pan, S.; Zhang, Y.; Bai, J.; Wang, Z.; Cui, D.; Wang, Q. Pyrolysis mechanism of kerogen: Model construction and multi-scale molecular simulations. J. Anal. Appl. Pyrolysis 2024, 183, 106837. [Google Scholar] [CrossRef]
  103. Sun, B.; Liu, X.P.; Liu, J.; Liu, T.; Hua, Z.X.; Peng, W.D. Evolution and generation mechanism of retained oil in lacustrine shales: A combined ReaxFF-MD and pyrolysis simulation perspective. Pet. Sci. 2025, 22, 29–41. [Google Scholar] [CrossRef]
  104. He, H.; Gong, Y.; Peng, M.; Zheng, H.; Feng, T.; Zhang, M.; Li, Q.; Liu, P. Study on mechanism of in-situ hydrogen generation based on molecular dynamics simulation from pyrolysis of heavy oil. Fuel 2025, 398, 135534. [Google Scholar] [CrossRef]
  105. Meuwly, M.; Becker, O.M.; Stote, R.; Karplus, M. NO rebinding to myoglobin: A reactive molecular dynamics study. Biophys. Chem. 2002, 98, 183–207. [Google Scholar] [CrossRef]
  106. Liu, X.; Zhan, J.H.; Lai, D.; Liu, X.; Zhang, Z.; Xu, G. Initial pyrolysis mechanism of oil shale kerogen with reactive molecular dynamics simulation. Energy Fuels 2015, 29, 2987–2997. [Google Scholar] [CrossRef]
  107. Vandenbroucke, M. Kerogen: From types to models of chemical structure. Oil Gas Sci. Technol. 2003, 58, 243–269. [Google Scholar] [CrossRef]
Figure 1. Overview of Oil Shale Resources and Pyrolysis Technologies ((a) Oil shale combustion; (b) Surface pyrolysis of oil shale: refining; (c) Overview of oil shale distribution in China; (d) In situ underground pyrolysis of oil shale.).
Figure 1. Overview of Oil Shale Resources and Pyrolysis Technologies ((a) Oil shale combustion; (b) Surface pyrolysis of oil shale: refining; (c) Overview of oil shale distribution in China; (d) In situ underground pyrolysis of oil shale.).
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Figure 3. New-Type Laboratory Reaction Devices: Small-Scale Fixed-Bed Reactor and Micro Fluidized Bed Reaction Analyzer (MFBRA) ((a) Small-scale fixed-bed reactor; (b)micro fluidized bed reaction analyzer (MFBRA) system.).
Figure 3. New-Type Laboratory Reaction Devices: Small-Scale Fixed-Bed Reactor and Micro Fluidized Bed Reaction Analyzer (MFBRA) ((a) Small-scale fixed-bed reactor; (b)micro fluidized bed reaction analyzer (MFBRA) system.).
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Figure 6. Theoretical model of autothermic pyrolysis of oil shale and conventional dry distillation conversion [81].
Figure 6. Theoretical model of autothermic pyrolysis of oil shale and conventional dry distillation conversion [81].
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Figure 7. Structural and Reactivity Analysis of Type I (HDK) and Type II (YJK) Kerogen Models ((a) HOMO and LUMO orbitals; (b) Hirshfeld charge distributions; (c) Bond cleavage statistics and bond orders; (d) Representative bond breakages and corresponding BDEs [105,106]).
Figure 7. Structural and Reactivity Analysis of Type I (HDK) and Type II (YJK) Kerogen Models ((a) HOMO and LUMO orbitals; (b) Hirshfeld charge distributions; (c) Bond cleavage statistics and bond orders; (d) Representative bond breakages and corresponding BDEs [105,106]).
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Table 1. Typical Pyrolysis Products of Oil Shale at Different Temperature Ranges.
Table 1. Typical Pyrolysis Products of Oil Shale at Different Temperature Ranges.
Origin of Oil ShaleTemperature Range (°C)Main ProductsOptimal Temperature for Maximum Oil Yield (°C)
Yaojie, Gansu [45]300–1000Liquid: alkanes, cycloalkanes, aromatics, and other compounds;
Gases: CO2, CH4, C2–C6, C3H6, C3H8, sulfurous gases.
550
Green River, USA [46]150–600Early: low-molecular hydrocarbons, bitumen; Middle: CH4, C2H6, C3H8, NGLs, bitumen, coke;
Late: CO2, CH4, coke.
400–500
Huadian, Jilin [47,48]200–650Liquid: alkanes and derivatives, phenols, aromatics, oxides, PAHs, cycloalkanes, olefins;
Gases: H2, CO2, CO, CH4, C2H6, C2H4, sulfurous gases.
475
Fushun, Liaoning [49]200–700Early: mainly H2O; Middle: aromatics, saturated and unsaturated hydrocarbons, SO2, NO2, NH3;
Late: H2O, aromatics, CO2, saturated hydrocarbons, trace SO2 and NO2.
496
Lujjin, Jordan [50]20–83020–280 °C: H2O;
280–540 °C: hydrocarbons; 540–830 °C: CO2, CO.
420–550
Table 2. Comparison of Key Characteristics Among Conventional, Microwave, and Auto-Thermal Heating Methods for Oil Shale Pyrolysis.
Table 2. Comparison of Key Characteristics Among Conventional, Microwave, and Auto-Thermal Heating Methods for Oil Shale Pyrolysis.
Heating MethodEnergy EfficiencyLimitationsKey Mechanism
Conventional Heating
[63,64,65,66,67,68,69,70]
High heat loss in electric heating; improved but still limited in thermal fluid heating.-Electric heating: severe heat loss, prolonged heating time (9 years to reach 500 °C), uneven temperature distribution.
-Thermal fluid heating: large heat injection volume, significant heat loss along the path.
Relies on heat conduction and convection; steam provides hydrogen radicals to promote kerogen cracking.
Microwave Heating
[71,72,73,74,75,76,77,78,79]
750 °C reached in 9 min vs. 55 min in conventional heating; 13–39% lower activation energy.Local overheating at high power may cause secondary cracking of oil/gas, reducing oil yield.Volumetric heating via electromagnetic waves interacting with polar molecules/minerals.
Auto-Thermal Heating
[80,81,82,83,84,85,86]
Energy efficiency of 3.46, 6.78 times that of high-temperature nitrogen injection.Requires precise oxygen control to avoid under-oxidation or over-oxidation of organic matter.Heat from partial oxidation of organic matter/minerals drives pyrolysis; residual carbon oxidation sustains reaction.
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Liu, X.; Yi, R.; Zhao, D.; Luo, W.; Huang, L.; Su, J.; Zhu, J. Research Progress on the Pyrolysis Characteristics of Oil Shale in Laboratory Experiments. Processes 2025, 13, 2787. https://doi.org/10.3390/pr13092787

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Liu X, Yi R, Zhao D, Luo W, Huang L, Su J, Zhu J. Research Progress on the Pyrolysis Characteristics of Oil Shale in Laboratory Experiments. Processes. 2025; 13(9):2787. https://doi.org/10.3390/pr13092787

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Liu, Xiaolei, Ruiyang Yi, Dandi Zhao, Wanyu Luo, Ling Huang, Jianzheng Su, and Jingyi Zhu. 2025. "Research Progress on the Pyrolysis Characteristics of Oil Shale in Laboratory Experiments" Processes 13, no. 9: 2787. https://doi.org/10.3390/pr13092787

APA Style

Liu, X., Yi, R., Zhao, D., Luo, W., Huang, L., Su, J., & Zhu, J. (2025). Research Progress on the Pyrolysis Characteristics of Oil Shale in Laboratory Experiments. Processes, 13(9), 2787. https://doi.org/10.3390/pr13092787

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