Gas Liquefaction Research Articles

Abstract In the recent past, the cryogenic system has become significant because of its extensive applications across various industries, including liquefaction, medical imaging, aerospace, etc There are many thermodynamic cycles used to achieve ultra-low temperatures, but the Linde-Hampson cycle is known for its simplicity compared to other complex cycles, such as the Claude or Kapitza cycles. The present study focuses on the design and development of a cryocooler using the Linde-Hampson refrigeration cycle to achieve ultra-low temperatures. A thermodynamic analysis of the Linde-Hampson cryogenic refrigeration cycle has been carried out using an isenthalpic expansion via a Joule-Thomson (JT) valve. The study investigates the behavior and performance of four different working gases: nitrogen, oxygen, methane, and air. Simulations were carried out using Engineering equation Solver (EES) to evaluate each gas under actual operating conditions. The work input, COP, liquefaction fraction, exergy efficiency, and efficiency are identified as key performance metrics for assessing system performance. Nitrogen and oxygen exhibited higher liquefaction efficiencies; however, methane shows more refrigeration potential. Further, an experimental setup has been developed to achieve ultra-low temperatures with certain limitations of the compressor. Experiments were conducted using air and water as a secondary fluid in the evaporator to carry the refrigeration. The water medium showed a higher COP than air. These findings help to improve the efficiency and viability of gas liquefaction operations by providing a better understanding of gas-specific thermodynamic behaviour.

Magnetic refrigeration using the magnetocaloric effect (MCE), where the temperature of a material changes as a magnetic field is applied, is a promising technology to increase the energy efficiency of commodity gas liquefaction at cryogenic temperatures. Currently, the most commonly studied materials for this application utilize rare-earth elements in nonporous forms. The continued development of magnetocaloric materials could benefit from (1) the discovery of materials with high surface areas capable of condensing substantial quantities of gas using minimal energy inputs and (2) the use of cheap and abundant precursors instead of utilizing rare-earth metals. We show here that microporous copper-halide perovskites, which form a layered structure with accessible crystalline voids between copper-halide sheets, demonstrate large entropy changes upon applying a magnetic field at temperatures relevant for H2 condensation. This is the first demonstration of the magnetocaloric effect for a transition-metal-based porous material. Furthermore, tuning the halide composition gives fundamental insight into how to control both the ferromagnetic transition temperature and the magnetic entropy change within this class of materials.

A Thermo-economic optimization of dual multicomponent refrigerant Cycles: Minimizing operational expenditure (OPEX) in natural gas liquefaction

Summary In this study, we propose a systematic method for optimizing the scanning strategy of pan-tilt tunable diode laser absorption spectroscopy (TDLAS) detection devices to enhance inspection efficiency. Gas leakage scenarios are identified and then simulated using computational fluid dynamics (CFD) to predict concentration distributions across the monitoring area. A multicondition data extraction model is developed to process and retrieve the CFD data. The optimization goal is framed as the minimum cumulative detection time considering scenario probabilities (MCDT-SP), with an enhanced particle swarm optimization (PSO) solution algorithm used to simultaneously optimize scanning points and sampling durations. The approach is demonstrated through a case study at a natural gas liquefaction plant, where results show significant improvements in detection efficiency, including reduced scanning points and faster leak detection. This method holds significant potential for application in industrial scenarios utilizing TDLAS technology for detection and is expected to provide actionable insights and effective support for the development of inspection strategies in the oil and gas industry.

Analysis of the influence of mixed refrigerant pressure on performance of natural gas liquefaction process from a new view of interactions among process parameters

A multi-criteria evaluation on the selected liquefied natural gas (LNG) liquefaction process designs integrating process safety and economic aspects

This research explores supersonic cyclonic separation for natural gas liquefaction (LNG). A 3D computational model was developed using the Eulerian–Eulerian two-fluid framework to simulate spontaneous gas condensation. The model tracks droplet formation/growth mechanisms and employs Reynolds stress modeling (RSM) for turbulence, implemented in Fluent via user-defined functions (UDFs). Validated against experimental data, it accurately predicted condensation onset and shock wave behavior. A prototype separator designed for a natural gas peak-shaving station demonstrated lower temperatures than throttling valves but modest liquefaction efficiency (4.28% at 5 MPa inlet pressure). Two enhancement strategies were tested: (1) injecting submicron LNG condensation nuclei (radius < 1 × 10−9 m) significantly boosted liquefaction by reducing nucleation energy barriers and suppressing condensation shocks; (2) a multi-stage configuration increased total liquefaction by 156% versus single-stage operation. These findings highlight the technology’s potential for energy-efficient gas processing.

Design and theoretical analysis of a high-performance heat-driven thermoacoustic cryocooler for natural gas liquefaction

A review of the state of the art of the cryogenic magnetocaloric systems for gas liquefaction

This work investigates the effect of imbalance and bearing wear on the vibration of rotating shafts at a southern Iraqi natural gas liquefaction plant. This experimental study examines the impact of wear on couplings and uneven weight on the vibration of a two-stage gas turbine’s shaft, taking measurements during operation. The experimental procedure involves the use of proximity probes and the ADRE-408 Bentley Nevada system to measure vibrations along the X and Y axes. The study focuses on a two-stage gas turbine supported by four journal bearings and analyses the effects of coupling imbalance and erosion. The results show that adding 10 g and 20 g weights at 0° and 30° anticlockwise considerably increases the vibration amplitude, from 22.46 µm at 113.75 Hz to 24.35 µm at 117.5 Hz. Replacing worn couplings and bearings led to system stabilisation, vibration reductions, and a shift in critical frequencies. The data confirm that mass loss and bearing wear greatly affect the dynamics of rotating machinery. These findings emphasise the importance of predictive maintenance and diagnostic monitoring to prevent mechanical failures and maintain system stability.

The increasing global demand for natural gas as a cleaner energy alternative has intensified the need for more energy-efficient liquefaction technologies. One of the key components in natural gas liquefaction is the refrigeration cycle, where the choice of refrigerant significantly influences system performance. Propane is widely used due to its favorable thermodynamic properties. However, there is growing interest in optimizing its performance through refrigerant blending. This study investigates the impact of different propane-based refrigerant mixtures, namely propane-NH₃, Propane-SO₂, and propane-CO₂ on the coefficient of performance (COP) in a natural gas liquefaction cooling cycle. Simulation results at two operating temperatures (-15.11°C and -20°C) demonstrate that refrigerant composition plays a crucial role in determining system efficiency. At -15.11°C, pure propane exhibited a COP of 2.79, while mixtures with NH₃ and SO₂ significantly improved performance, achieving peak COPs of 6.25 and 6.42, respectively, at a 1:9 mixing ratio. Similar trends were observed at -20°C, where the highest COP values for propane-NH₃ and propane-SO₂ mixtures were 5.79 and 5.96, respectively. In contrast, the propane-CO₂ mixture consistently yielded the lowest COP values, indicating inferior energy efficiency. These findings suggest that incorporating NH₃ or SO₂ into propane-based refrigeration cycles can substantially enhance the energy performance of natural gas liquefaction processes, whereas propane-CO₂ blends may increase energy consumption and operational costs.

This study evaluates the efficiency of cryogenic energy storage systems from energy, exergy, and economic perspectives. Cryogenic energy storage systems that store energy through gas liquefaction and regasification, offer high energy capacity but face challenges in storage efficiency. The authors propose a comprehensive performance indicator that integrates these factors, addressing limitations of traditional metrics like the round-trip efficiency, which fails to account for external heat/cold sources. Analysis of 30 installations reveals that systems utilizing compression heat and cryogenic cold achieve up to 70% efficiency, while those relying solely on electricity average 25%. Key findings highlight the trade-offs between energy density, cost, and thermodynamic perfection, with advanced configurations (e.g., hybrid systems with LNG cold recovery) achieving round-trip efficiency more than 100% but lower exergy efficiency (10.4%). A novel composite metric balances , exergy efficiency, and specific energy capacity, identifying optimal designs. The study concludes that integrating auxiliary heat/cold storage and external energy sources (e.g., geothermal, LNG) enhances performance, though practical constraints like regenerative heat exchanger stability persist.

Multi-effect distillation with novel liquid vapor ejector utilizing the waste heat from intercoolers of a single mixed refrigerant cycle for natural gas liquefaction

This study focuses on designing and evaluating a process plant for liquefied natural gas (LNG) boil-off gas (BOG) recovery. The lightest hydrocarbons included in LNG, such as methane and ethane, are often included in Boil-off Gas (BOG). Flaring and contamination of the environment are unavoidable in the absence of an effective BOG recovery system. Using Aspen HYSYS, a natural gas liquefaction process was simulated, emphasizing the recovery and utilization of BOG generated during various stages of LNG processing, including liquefaction, depressurization, storage, and shipping. The material and energy balances for the process were meticulously calculated to ensure accuracy in flow rates and heat exchange efficiencies. The simulation results indicate that the liquefied natural gas produced contains a methane 2473oncentrationn of 96.64% with minor amounts of ethane. BOG, mainly consisting of methane (100% purity), was effectively recovered and conditioned for reuse or flaring. An economic analysis was conducted to assess the profitability of BOG recovery, highlighting an estimated annual income of $138,121,200, with a gross profit margin of 97.3%. The total capital investment required for BOG recovery equipment amounted to $3,790,605. This study demonstrates that BOG recovery can significantly enhance the economic viability and environmental sustainability of LNG operations by reducing methane emissions and providing a valuable energy resource.

The increasing demand for energy-efficient and environmentally friendly liquefied natural gas (LNG) production has led to the exploration of alternative refrigerants in cascade liquefaction systems. This study presents a comparative thermodynamic analysis of inorganic refrigerants in cascade liquefied natural gas (LNG) liquefaction systems, focusing on performance metrics. The research aims to evaluate the exergy losses, coefficient of performance (COP), energy requirements, and overall thermodynamic efficiency of various refrigerants, including Argon, Krypton, Xenon, Nitrogen, and the conventional C3MR (Propane Mixed Refrigerant). Results reveal significant variations in refrigerant performance. C3MR demonstrates the highest COP (4.25) but exhibits moderate exergy efficiency (63%) and high energy losses in compressors. Noble gases show contrasting trends: argon achieves exceptional exergy efficiency (83%) but poor COP (1.38), while xenon has low exergy efficiency (36%) but a competitive COP (2.99). Nitrogen incurs catastrophic exergy losses during depressurization (345,439 kJ/hr), highlighting operational challenges. The study underscores the need for component-specific refrigerant optimization and suggests hybrid systems combining C3MR’s heat transfer advantages with argon’s exergy efficiency. These findings advance LNG liquefaction technology by providing a nuanced framework for balancing thermodynamic performance, environmental impact, and operational feasibility

Precise calculations of thermodynamic properties are essential for enhancing the efficiency of natural gas liquefaction and regasification processes. These calculations play a vital role in understanding phase equilibria, which is critical for ensuring optimal performance in both the liquefaction of natural gas, transforming it into a liquid state for easier storage and transport and the regasification process, which converts it back into a gaseous state for use. By accurately determining properties such as temperature, pressure, and chemical potential, engineers can design more effective systems that maximize energy efficiency and reduce operational costs, ultimately leading to improved overall performance in natural gas processing. This study aims to improve predictive accuracy by utilizing a set of 16 fundamental equations that describe the behavior of real gases. These equations take into account various factors such as pressure, temperature, and volume, allowing for a more precise representation of gas behavior under different conditions. By employing these established equations, the study enhances the reliability of predictions related to gas dynamics, making it possible to achieve more accurate modeling in practical applications and scientific research. The analysis focuses on the variations from optimal conditions in high-pressure cryogenic environments. It employs a range of theoretical tools, including virial coefficients to understand interactions among particles, as well as Helmholtz and Gibbs energies to assess the system's thermodynamic stability and equilibrium. Furthermore, the study integrates correlations of heat capacity to evaluate the thermal properties and behavior of materials under extreme conditions. The study further enhances the understanding of LNG pipeline flow modeling by incorporating detailed calculations of both the speed of sound and the bulk modulus. This integration allows for more accurate simulations of flow dynamics, enabling better design and optimization of pipeline systems to ensure safety and efficiency during transport. The research focuses on enhancing phase equilibrium modeling, essential in optimizing energy consumption within liquefied natural gas (LNG) processes. The study aims to minimize energy losses during the production and transportation of LNG. Furthermore, this approach improves the design of LNG processes by increasing its overall efficiency, contributing to more sustainable practices in the industry.

As the demand for Liquefied Natural Gas (LNG) continues to rise, the need for efficient and environmentally friendly refrigeration technologies has become more critical. This study presents a comprehensive review of inorganic refrigerants used in Liquefied Natural Gas (LNG) liquefaction cycles, concentrating on their thermodynamic performance and environmental effects. Using a thorough literature study, important refrigerants such as nitrogen, argon, krypton, xenon, and ammonia were examined in terms of efficiency, energy consumption, and sustainability. The findings show that inorganic refrigerants can improve energy efficiency by lowering power consumption and increasing exergy performance. Nitrogen was found to require the least amount of energy, whereas ammonia significantly increased the coefficient of performance (COP) in mixed refrigerant applications. Krypton and xenon both demonstrated great exergy efficiency, making them attractive candidates for future LNG operations. While these refrigerants have a lesser environmental effect than standard hydrocarbons, more advances are needed. The study recommends optimizing hybrid refrigerant systems, including renewable energy, and improving safety measures. Advancing these strategies can make LNG production more sustainable, reducing its carbon footprint while maintaining efficiency.

The liquefied natural gas (LNG) floating production storage and offloading (FPSO) unit is a new type of floating production device developed for the exploitation, pretreatment, liquefaction, and storage of offshore natural gas. In this study, the shell side structure of the spiral-wound heat exchanger is analyzed, and the effects of varying the Reynolds number (Re), tube outer diameter, and number of distributors on the thickness of the shell-side liquid film are investigated. The results show that as the fluid flows down from the distributor, it hits the upper wall of the pipeline and diffuses evenly to both sides, before converging in between the two distributors. In the axial direction, the thickness of the liquid film increases first, reaches the highest at the peak, then decreases, reaches the lowest at the trough, and then increases again, forming a secondary peak at the drop. The thickness of the liquid film changes periodically, and the period is the distance between the two distributors. The thickness of the circumferential liquid film is negatively correlated with the circumferential angle, α. Moreover, the liquid film is thinnest at α = 120°, and is positively correlated with both the liquid mass flow rate and the outer diameter of the tube. The most uniform liquid film thickness is obtained when Re = 1500, the tube outer diameter is 12 mm, and the number of distributors is 6. The results from this study can guide the design of spiral-wound heat exchangers and facilitate their safe and efficient operation in natural gas liquefaction processes.

Risk analysis is crucial in industrial conception. HAZOP is the top risk analysis method for the oil and gas sector. This paper presents a semi-automatic method to address HAZOP's limitations and produce automatic results. The method uses a knowledge base, initially filled with gas liquefaction data, and is enhanced with subsequent case studies. An inference engine processes this data to conduct a HAZOP study. Propagation rules identify potential deviation paths, enabling risk analysis and consequence prediction based on the knowledge base. This method uniquely illustrates deviation paths and introduces nodes along these paths for further study. The findings derive from dynamic knowledge of each system in the knowledge base and can be reviewed and amended by experts.

Natural gas processing includes an array of operations, including natural gas dehydration, sweetening, liquefaction, fractionation, knockout of inert gases, transportation, and transmission to sales point. These processes require interactions of different phases of dry-gas and wet-gas pressure, volume, and temperature. These interactions are demonstrated using equations of state, simulations, and models. Recently, artificial intelligence (AI), deep learning (DL), and machine learning (ML) have taken natural gas processing and handling on a new trajectory, replacing complex simulation runs. Challenges related to natural gas processing and handling such as gas leaks, carbon emission, and gas flaring are being managed using innovative processes developed through the operations of AI, ML, and DL. In reviewing a collection of SPE papers with top-notch innovations in natural gas processing operations, it is clear that technologies have become smart, with researchers and technology experts moving with the trends to make improvements on previous operations. Researchers and technology experts have made novel and innovative contributions to natural gas processing and handling using robotic and smart technologies for leak detection, carbon footprinting, and flare management. Smart technologies have also improved the operation processes around gas dehydration, sweetening, liquefaction, and fractionation. These have replaced complex backend simulations and have made natural gas processing seamlessly automated. Truly, AI, DL, and ML may not be optimally efficient in other climes, but they have shown reasonable efficiency in surface production operations, especially natural gas processing, because many of these operations have been automated. This trend is seen in the papers summarized here. Summarized papers in this April 2025 issue. OTC 34756 - Deep-Learning Image-Processing Model Uses Optical Gas-Imaging Camera To Detect Leaks by Mehdi Korjani, Clean Connect, et al. SPE 222264 - Zero-Flaring Technology Reduces Greenhouse-Gas Emissions by Zeeshan Ahmad, ADNOC, et al. SPE 222818 - Study Explores Carbon-Capture Options for Gas‑Processing Facilities by Srihari Kannan, Shell, et al. Recommended additional reading at OnePetro: www.onepetro.org. SPE 218939 - Advancements in Gasfield Operations: A Path to Achieving Zero Flaring by Zaid Alsuhali, Saudi Aramco, et al. SPE 222919 - A Study on Supply-Chain Management of LNG Using Artificial Intelligence by Nicy Susan Koshy, Trafigura Global Services SPE 218564 - Optimizing Gas-Pipeline Operations With Machine Learning: A Case Study of a North American Energy Company by S. Saboo, Amazon Web Services