Gas Science and Engineering最新文献

{"title":"Coreflooding with sub-core scale characterization for analysis of water encroachment in a gas reservoir","authors":"Yanjing Wei ,&nbsp;David DiCarlo ,&nbsp;Avinoam Rabinovich","doi":"10.1016/j.jgsce.2025.205781","DOIUrl":"10.1016/j.jgsce.2025.205781","url":null,"abstract":"<div><div>Understanding gas-brine two-phase flow and residual gas is essential for evaluating and optimizing reservoir gas recovery and storage. Coreflooding experiments and simulations offer insight into multiphase flow behavior, yet most studies focus on core-scale characterization, often overlooking smaller, sub-core scale phenomenon. This work investigates drainage and imbibition gas-brine flow and residual gas trapping in a core sample, focusing on the sub-core effects that influence fluid distribution. We conduct vertical coreflooding experiments on a sample from a gas reservoir, with the application of water encroachment in mind. Experimental and simulation results are presented considering multiple scales: voxel, slice, and core, using X-ray computed tomography (CT) to reveal the distribution of porosity and steady-state gas saturation inside the rock sample. It is shown that residual gas saturation is controlled by sub-core scale capillary heterogeneity, even within a core that appears homogeneous. Capillary pressure is immaterial in homogeneous models but becomes significantly impactful at the sub-core scale, where heterogeneities influence fluid behavior. A one-dimensional heterogeneous model incorporating spatial relationship between capillary pressure and permeability is used to estimate permeability distribution and found to be able to capture some of the gas variations in the core, which indicates that the presence of capillary heterogeneity effects are responsible for the sub-core saturation variations.</div></div>","PeriodicalId":100568,"journal":{"name":"Gas Science and Engineering","volume":"145 ","pages":"Article 205781"},"PeriodicalIF":5.5,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145121061","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integrating nature-inspired optimization techniques and machine learning for accurate CO2/brine interfacial tension estimation: Implications for CO2 sequestration and uncertainty analysis","authors":"Joshua Nsiah Turkson ,&nbsp;Muhammad Aslam Md Yusof ,&nbsp;John Oluwadamilola Olutoki ,&nbsp;Bennet Nii Tackie-Otoo ,&nbsp;Caspar Daniel Adenutsi ,&nbsp;Ingebret Fjelde ,&nbsp;Yen Adams Sokama-Neuyam ,&nbsp;Victor Darkwah-Owusu","doi":"10.1016/j.jgsce.2025.205796","DOIUrl":"10.1016/j.jgsce.2025.205796","url":null,"abstract":"<div><div>Understanding interfacial behavior between CO₂, in-situ fluids, and porous media is key to ensuring safe containment. However, conventional methods for determining CO₂/brine interfacial tension (IFT) are resource-intensive. To overcome the limitations, we integrated Decision Tree, Support Vector Regression (SVR), Random Forest (RF), and Extreme Gradient Boosting (XGBoost) paradigms with nature-inspired optimizers: <em>Particle Swarm Optimization</em>, <em>Gene</em><em>tic Algorithm, Grey Wolf Optimizer (GWO),</em> and <em>Harris Hawks Optimization</em>, utilizing the most extensive eight-parameter CO₂/brine IFT dataset. We juxtaposed the outstanding model's performance with traditional methods and assessed variable influence via multiple methods. Furthermore, the model was deployed for uncertainty analysis and computation of key parameters that dictate storage integrity. Statistical tests confirmed that model choice had a significant impact on performance, while the effect of the optimizer varied depending on the model. XGBoost achieved the highest predictive accuracy (R² <span><math><mrow><mo>≥</mo></mrow></math></span> 0.98), with minimal gains from tuning. It also outperformed existing correlations, achieving R² &gt; 0.94 for diverse CO₂/brine systems, compared to correlations' 0.50–0.90. SVR exhibited the largest performance boost, improving from weak default metrics (R² = 0.80) to competitive results (R² = 0.96) post-tuning. Spearman correlation, permutation importance, and Shapley Additive Explanations identified density difference as the most significant predictor of IFT, while salt type had the least impact. XGBoost–GWO/Monte Carlo simulation yielded P10, P50, and P90 IFT estimates of ∼39, 49, and 63 mN/m, translating to quintessential storage column heights of 4150–6809 m and capacities of 97–159 metric tons/m², demonstrating practical utility. The modeling approach provides an accurate and resource-efficient framework for predicting and optimizing CO₂/brine IFT for safe geo-storage. It could also be applied in early-stage storage site appraisal where limited experimental data are available.</div></div>","PeriodicalId":100568,"journal":{"name":"Gas Science and Engineering","volume":"145 ","pages":"Article 205796"},"PeriodicalIF":5.5,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145424811","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Study on the diffusion pattern of sulfur-containing natural gas leakage based on infrared monitoring technology","authors":"Le Hao ,&nbsp;Xiaowei Zhai ,&nbsp;Anshan Xiao ,&nbsp;Zhen Wang ,&nbsp;Guohua Luan ,&nbsp;Xin Li","doi":"10.1016/j.jgsce.2025.205797","DOIUrl":"10.1016/j.jgsce.2025.205797","url":null,"abstract":"<div><div>Hydrogen sulfide in sulfur-containing natural gas is a highly toxic acidic gas that can cause corrosion in natural gas gathering and transportation pipelines, potentially leading to large-scale gas leakage and poisoning incidents. Therefore, investigating the leakage and dispersion patterns of sulfur-containing natural gas holds significant importance for personnel safety and environment protection. Given the multiple factors affecting sulfur-containing natural gas leakage, this study conducted experiments using mid-infrared remote sensing lasers and thermal infrared imager. The experiments analyzed the effects of hydrogen sulfide concentration, leak aperture, flow rate, and environmental wind speed on the dispersion range and gas concentration. The results revealed that during atmospheric dispersion, leaking sulfur-containing natural gas exhibits intrinsic motion and dilution phenomena independent of other parameter variations. As the jet kinetic energy gradually diminishes, the migration of leaked gas within the experimental setup is primarily governed by environmental wind speed and gravitational effects. Notably, increased environmental wind speed was observed to reduce plume dispersion at equivalent positions within the experimental platform. This study quantitatively determined the influence range of different hydrogen sulfide concentrations, leakage aperture, flow velocity, and wind speed, and supplemented the study of the transport of toxic mixed gases in the atmosphere from the perspective of simulation experiments. The relevant experimental process ideas can be further extended to the study of the laws of other types of leaks.</div></div>","PeriodicalId":100568,"journal":{"name":"Gas Science and Engineering","volume":"145 ","pages":"Article 205797"},"PeriodicalIF":5.5,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145474385","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Deep learning schemes for predicting deliverability from different underground gas storage reservoir types","authors":"Shadfar Davoodi ,&nbsp;Hung Vo Thanh ,&nbsp;David A. Wood ,&nbsp;Mohammad Mehrad ,&nbsp;Mohammed Al-Shargabi ,&nbsp;Valeriy S. Rukavishnikov","doi":"10.1016/j.jgsce.2025.205805","DOIUrl":"10.1016/j.jgsce.2025.205805","url":null,"abstract":"<div><div>Underground gas storage (UGS) is vital for maintaining energy security and grid stability. Accurate forecasting of maximum daily deliverability (MDD) is crucial for optimizing UGS operations. However, traditional methods for forecasting MDD are often time-consuming or rely on difficult-to-obtain reservoir data, creating a need for more efficient and accessible predictive tools. This study develops robust deep learning (DL) models to predict MDD using a large dataset of over 3000 samples from UGS facilities across the USA. The models utilize only four publicly available features: field type (FTP), working gas capacity (WGC), base gas volume (BG), and total field storage capacity (TFC). Standalone long short-term memory (LSTM) and convolutional neural network (CNN) models are implemented, then hybridized with grey wolf optimization (GWO) and growth optimizer (GO) to fine-tune their hyperparameters and internal weights. A comprehensive evaluation, including a detailed error distribution analysis, demonstrates that hybrid models significantly outperform standalone ones. The LSTM-GO model achieves the highest prediction performance (test root mean square error: 25.98 million cubic feet (MMcf)/day) and superior generalization with the lowest overfitting index. Interpretability analysis (Shapley additive explanation/partial dependent plot) identifies FTP as the most influential feature on MDD, with salt caverns yielding the highest deliverability. This work provides a novel, accurate, and efficient DL framework for screening-level UGS deliverability forecasting, offering a valuable tool for energy planners to enhance the reliability and integration of natural gas storage within the evolving energy landscape.</div></div>","PeriodicalId":100568,"journal":{"name":"Gas Science and Engineering","volume":"145 ","pages":"Article 205805"},"PeriodicalIF":5.5,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145623524","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Temperature-pressure field evolution of hydrate-bearing sediments: A comparative study of depressurization strategies for gas recovery using a novel fan-shaped simulator","authors":"Ling-Ban Wang,&nbsp;Yi-Fei Sun,&nbsp;Yu-Hao Bu,&nbsp;Zhen-Bin Xu,&nbsp;Xian Sun,&nbsp;Han-Feng Shao,&nbsp;Chang-Yu Sun,&nbsp;Guang-Jin Chen","doi":"10.1016/j.jgsce.2025.205802","DOIUrl":"10.1016/j.jgsce.2025.205802","url":null,"abstract":"<div><div>The development of natural gas hydrates is a cutting-edge area of research in the energy field today, with scientific studies and new technology development increasingly relying on large-scale simulators. In this study, a novel partial-dimensional fan-shaped simulator with a radius of 3 m was first used for near-field-scale simulation of methane hydrate exploitation at large spatial and temporal scales. Temperature-pressure field evolution of hydrate-bearing sediments was systematically investigated during gas production by different depressurization strategies. The results indicate that as the depressurization steps increased from 1 to 4, the peak depressurization rate decreased from 144 kPa/min to 81 kPa/min, while the minimum temperature rose from 2.93 °C to 4.15 °C. This effectively mitigated the risk of sand migration and reduced the adverse impact of low temperatures on hydrate dissociation. A linear correlation was identified between pressure differential and depressurization rate under a multi-step depressurization strategy, offering predictive potential for production control. Spatially, the formation and expansion of an “adequate heat supply zone” was observed, enhancing thermal balance by reducing the Coefficient of Variation of reservoir temperature by ∼30 %. These findings provide technical guidance for optimizing the depressurization-induced production of hydrate resources.</div></div>","PeriodicalId":100568,"journal":{"name":"Gas Science and Engineering","volume":"145 ","pages":"Article 205802"},"PeriodicalIF":5.5,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145579302","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Experimental and molecular simulation study of in-situ self-growing nano-liquid crystal for smart water management in natural gas reservoirs","authors":"Rui Liu ,&nbsp;Jipeng Shi ,&nbsp;Qin Peng ,&nbsp;Zezhou Chen ,&nbsp;Mingqi Sun ,&nbsp;Kang Liu ,&nbsp;Wanfen Pu","doi":"10.1016/j.jgsce.2025.205767","DOIUrl":"10.1016/j.jgsce.2025.205767","url":null,"abstract":"<div><div>Natural gas reservoir development faces significant challenges from water invasion due to reservoir heterogeneity. Thus, effectively controlling water invasion while simultaneously facilitating gas production presents a significant historical mission and a vital research hotspot. A key research gap exists in developing water control agents for natural gas reservoirs that combine smart selective plugging and efficient profile control, with limited understanding of GO-based nanocomposites mechanisms and functionalization. Thus, this study pioneers a novel method for designing graphene oxide (GO)-based nano-liquid crystal sheets (GOLC) to address this issue. The design was inspired by the in-situ scale growth due to the association with inorganic salt ions in the formation water and hydrocarbon dissociation of polyethylene glycol (PEG) hybrid GO nanocomposite. Experimental and molecular simulation characterizations were employed to elucidate and investigate the intelligent water control and gas evacuation mechanism of GOLC. GOLC exhibits excellent dispersion in polar solvents. The in-situ growth of GOLC, driven by electrostatic interactions between PEG and metal cations (Ca²⁺ &gt; Mg²⁺ &gt; Na⁺), enlarges GOLC sheets from 50 nm to 3500 nm, achieving an 84.81 % plugging rate in porous media. Interestingly, these self-growing GOLC structures dissociate upon contact with methane (CH₄), showcasing effective water blocking and gas drainage characteristics, which results in a 12.9 % increase in recovery rate. This research will provide an innovative perspective for the synthesis and application of newly generated nanomaterials following a de novo design to intelligently control water in natural gas reservoirs.</div></div>","PeriodicalId":100568,"journal":{"name":"Gas Science and Engineering","volume":"144 ","pages":"Article 205767"},"PeriodicalIF":5.5,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144917679","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A hybrid physics-machine learning model to predict density of mixtures of CO2 with impurities","authors":"Mohamad Hussein Makke,&nbsp;Kassem Ghorayeb","doi":"10.1016/j.jgsce.2025.205768","DOIUrl":"10.1016/j.jgsce.2025.205768","url":null,"abstract":"<div><div>Carbon Capture, Utilization, and Storage (CCUS) plays a pivotal role in reducing greenhouse gas emissions, essential for limiting global warming to below 1.5 °C by 2100 and achieving carbon neutrality by 2050. Modeling carbon dioxide (CO₂) density is crucial for optimizing CO₂ transportation and storage systems. However, captured CO₂ streams from power sources often contain impurities such as Oxygen, Nitrogen, Carbon Monoxide, Argon, Sulfur Dioxide, Hydrogen, Methane, Water, and Hydrogen Sulfide. These impurities significantly impact transmission properties and challenge the predictive capabilities of equations of state (EoSs) thermodynamic models.</div><div>This study investigates the effects of impurities on CO₂ stream density using a comprehensive dataset of 134,204 density data points. Fourteen EoSs, including cubic, virial, physical, and multi-parameter equations, were evaluated to determine optimal modeling conditions. Moreover, machine learning models trained with experimental and synthetic data from equation of state (EoS) models were employed towards a high predictive capability model. This synthetic data was generated, within CCUS pipeline operating conditions, using the best-performing EoSs, primarily multiparameter equations with an Absolute Average Relative Deviation &lt;3 %. Random Forest and Artificial Neural Networks provided robust density predictions, even in complex thermodynamic regions with a Coefficient of Determination &gt;0.96.</div><div>This hybrid approach offers a novel pathway for improving density predictions of CO₂-rich systems, supporting more efficient and reliable transportation models. To the best of our knowledge, no previous study considered such a comprehensive dataset and EoSs for predicting the density of CO₂ rich mixtures using this hybrid approach.</div></div>","PeriodicalId":100568,"journal":{"name":"Gas Science and Engineering","volume":"144 ","pages":"Article 205768"},"PeriodicalIF":5.5,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144932901","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Review on the loss during hydrogen storage in depleted gas reservoirs","authors":"Gang Chen,&nbsp;Shilai Hu,&nbsp;Wei Zhang,&nbsp;Jingang Fu,&nbsp;Jiqiang Li","doi":"10.1016/j.jgsce.2025.205759","DOIUrl":"10.1016/j.jgsce.2025.205759","url":null,"abstract":"<div><div>Underground hydrogen storage (UHS) is essential for large-scale energy storage as it can address the intermittency of renewable energy sources and support the transition to a low-carbon energy structure. Compared with other suitable sites for UHS, depleted gas reservoirs may be the best due to their large storage capacity, numerous potential options and complete surface facilities. However, the lack of practice and theory about the loss during hydrogen storage in depleted gas reservoirs (HSDGs) hinders its development and large-scale utilization. This review aims to minimize the loss and improve withdrawal efficiency via analyzing and discussing previous works on hydrogen loss during HSDGs. To fill this gap, according to the mechanisms of hydrogen loss during HSDGs, the loss is classified into two categories in this work, real loss and fake loss. Real loss is the complete reduction in hydrogen caused by chemical reactions, gas diffusion, and geological leakage. Fake loss means that hydrogen stored in gas reservoirs can't be withdrawn under the specific conditions due to gas dissolution in formation water, residual trapping, adsorption in rock minerals, and other engineering factors, such as cushion gas, well perforation and cyclic operation. Given two categories of hydrogen loss, the pathways, mechanisms, quantity and influencing factors were evaluated and discussed critically, and specific strategies were also proposed to minimize the loss. Finally, the limitations of current valuable works were highlighted, and future works were developed. This review can help scientists and engineers maximize the withdrawal efficiency of HSDGs.</div></div>","PeriodicalId":100568,"journal":{"name":"Gas Science and Engineering","volume":"144 ","pages":"Article 205759"},"PeriodicalIF":5.5,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144891839","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Molecular insights into the stability of CO2 hydrate in variable-diameter nano-slit","authors":"Xu Li ,&nbsp;Han Jia ,&nbsp;Qiuxia Wang ,&nbsp;Yuanbo Wang ,&nbsp;Fangning Fan ,&nbsp;Bowen Wang ,&nbsp;Qiang Wang ,&nbsp;Yurong Zhao ,&nbsp;Pan Huang","doi":"10.1016/j.jgsce.2025.205763","DOIUrl":"10.1016/j.jgsce.2025.205763","url":null,"abstract":"<div><div>Most literatures focused on the stability of CO₂ hydrate in uniform-diameter nano-slits, while variable-diameter nano-slits may be more prevalent in the realistic environments for CO₂ storage processes. This study employs molecular dynamics (MD) simulations to systematically explore the effects of various factors (disordered water, slit size, and wettability) on hydrate stability in variable-diameter nano-slits. It is revealed that the variable-diameter nano-slit affects the activity of disordered water, rather than altering the hydrate crystal structure, to dominate the hydrate stability. The presence of disordered water decreases hydrate stability, with the melting point dropping from 282 K to 269 K when disordered water in large slits, and further declining to 267 K when it in small slits. The Vertical surfaces in the nano-slits induce heterogeneity in disordered water activity, and its proportion dominates the further depression of melting points for hydrates in large slits. The slit surface-water interaction caused by the wettability variation hardly impact the hydrate stability, whereas the differences in nanobubbles distribution significantly influence the stability of hydrates in the small slits. This study firstly offers valuable insights into the complex interactions affecting CO₂ hydrate stability in more realistic porous media environments, uncovering the mechanisms by which geometric heterogeneity and interfacial behavior influence hydrate stability.</div></div>","PeriodicalId":100568,"journal":{"name":"Gas Science and Engineering","volume":"144 ","pages":"Article 205763"},"PeriodicalIF":5.5,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144889194","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Investigation of hydrate formation and flow characteristics within multiphase transmission pipelines employing a constant pressure visualization loop system","authors":"Xi Wang ,&nbsp;Kaibang Liu ,&nbsp;Shouyi Ma ,&nbsp;Linan Guan ,&nbsp;Zherui Chen ,&nbsp;Yan Qin ,&nbsp;Jingyue Sun ,&nbsp;Cong Chen","doi":"10.1016/j.jgsce.2025.205747","DOIUrl":"10.1016/j.jgsce.2025.205747","url":null,"abstract":"<div><div>Hydrate blockages during oil and gas transportation severely affect flow safety. An innovative, fully visual flow loop was utilized to systematically evaluate and quantify the individual effects of pressure, temperature, flow velocity, and liquid loading on hydrate formation, flow characteristics, and morphological evolution. The results indicate that hydrate growth progresses through the stages of initial formation, slurry stable flow, and aggregation and blocking, with the water conversion fraction and differential pressure exhibiting pronounced stage-dependent evolution features. Increased pressure augments the fugacity gradient, thereby reducing the hydrate formation time and blocking time, exacerbating particle aggregation, and facilitating hydrate generation. At constant pressure, high subcooling accelerates gas consumption and lengthens hydrate formation time, promoting the development of microporous aggregate network structures. The water conversion fraction increases with subcooling but remains insensitive to variations in subcooling during the blocking stage. A critical flow velocity exists, above which hydrate can continue to be transported in suspension in the main pipeline, although deadlegs remain susceptible to blockage. Furthermore, flow velocities exceeding 0.27 m/s can postpone blockage when below the critical threshold. High liquid loading delays hydrate formation time but shortens blocking time, and the maximum water conversion fraction occurs at a liquid loading of 60 vol%. During the slurry stable flow stage, hydrate conversion above this critical value is governed by particle aggregation and continued hydrate formation. These experimental findings advance the understanding of hydrate behavior in multiphase flow systems under constant pressure, providing a foundation for improving risk assessment and flow assurance strategies.</div></div>","PeriodicalId":100568,"journal":{"name":"Gas Science and Engineering","volume":"144 ","pages":"Article 205747"},"PeriodicalIF":5.5,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144860848","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}