Flow characteristic and blockage mechanism with hydrate formation in multiphase transmission pipelines: In-situ observation and machine learning predictions

Wang, Ji‐Guang; Wang, Qi; Meng, Yang; Yao, Haiyuan; Zhang, Lunxiang; Jiang, Bo; Liu, Zaixing; Zhao, Jiafei; Song, Yongchen

doi:10.1016/j.fuel.2022.125669

Cited by 18 publications

(9 citation statements)

References 40 publications

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“…Natural gas hydrate is a nonstoichiometric crystal compound with the potential to serve as a sustainable energy source, owing to its widespread presence in subsea environments, high energy density and considerable gas storage capacity. − Nevertheless, the development of hydrocarbon and gas hydrate in deepwater poses the challenging problem of hydrate blockage in pipelines, precipitated by the conducive conditions for hydrate formation . Hydrate blockage has been considered as a significant flow assurance concern in deepwater hydrocarbon resources production and transportation. − …”

Section: Introductionmentioning

confidence: 99%

Characterization of Hydrate Formation and Flow Influenced by Hydrophilic–Hydrophobic Components within a Fully Visual Rocking Cell

Lang,

Han,

Zou

et al. 2024

Energy Fuels

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The intricate interplay of crude oil composition and additives critically affects hydrate formation and flow behavior, which is significant for flow assurance particularly in deepwater. To investigate, we varied the hydrophilic and hydrophobic properties by proportioning two nonionic surfactants (Span 80 and Tween 80) and conducting hydrate formation experiments in a visual rocking cell. The results show that the increasing hydrophilic−lipophilic balance (HLB) value shifted emulsions from water-in-oil to multiple and oil-in-water phases and significantly affected the hydrate formation among different emulsion types, with a marked increase in the hydrate formation rate in the HLB range of 9 to 11. Slurries maintained flowability due to low hydrate conversion, yet higher HLB (>11) led to slight agglomeration and deposition. In addition, the impacts of water conversion were investigated by multiple pressurization, showing that the hydrate formation amount affected slurry flowability but was primarily dependent on the hydrophilicity and hydrophobicity of the surfactants. When the HLB was below 11, the final water conversion was about 80%, but the formed hydrate still exhibited good dispersion and flowability. In contrast, HLB exceeding 13 resulted in extensive adhesion and deposition on the cell walls. When the water conversion reached about 40%, flowability was completely lost and hydrate blockage occurred.

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Section: Introductionmentioning

confidence: 99%

Characterization of Hydrate Formation and Flow Influenced by Hydrophilic–Hydrophobic Components within a Fully Visual Rocking Cell

Lang,

Han,

Zou

et al. 2024

Energy Fuels

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“…Furthermore, Wang et al [8] applied ML to assess the risk of hydrate formation and blockage in a pure water system. The multi-layer perceptron (MLP) model and the logistic regression (LR) model were used in this work.…”

Section: Introductionmentioning

confidence: 99%

Application of Machine Learning to Predict Blockage in Multiphase Flow

Saparbayeva,

Balakin,

Struchalin

et al. 2024

Computation

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This study presents a machine learning-based approach to predict blockage in multiphase flow with cohesive particles. The aim is to predict blockage based on parameters like Reynolds and capillary numbers using a random forest classifier trained on experimental and simulation data. Experimental observations come from a lab-scale flow loop with ice slurry in the decane. The plugging simulation is based on coupled Computational Fluid Dynamics with Discrete Element Method (CFD-DEM). The resulting classifier demonstrated high accuracy, validated by precision, recall, and F1-score metrics, providing precise blockage prediction under specific flow conditions. Additionally, sensitivity analyses highlighted the model’s adaptability to cohesion variations. Equipped with the trained classifier, we generated a detailed machine-learning-based flow map and compared it with earlier literature, simulations, and experimental data results. This graphical representation clarifies the blockage boundaries under given conditions. The methodology’s success demonstrates the potential for advanced predictive modelling in diverse flow systems, contributing to improved blockage prediction and prevention.

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“…Gas hydrate has been highly valued for its enormous potential as an important energy source. , However, there is a risk of hydrate blockage due to the hydrate formation conditions being met during deepwater oil and gas transportation . The occurrence of hydrate growth and blockage in wellbores and pipelines during gas and oil production may lead to production stoppage or even engineering disasters, such as oil and gas leaks or explosions. − …”

Section: Introductionmentioning

confidence: 99%

Flow Assurance of Hydrate Risk in Natural Gas/Oil Transportation: State-of-the-Art and Future Challenges

et al. 2023

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Deepwater oil and gas development is extremely difficult and challenging. One of the most critical challenges stems from hydrate deposition, aggregation, and the eventual blocking of the deepwater oil and gas transportation system. The low-temperature and high-pressure environment in the deepwater oil and gas field causes the combination of gas molecules and water molecules to form hydrate, thus affects the hydrocarbon transportation. In this Perspective, to discuss the commonly faced safety issues for deepwater oil, gas, and gas hydrate development, the following three critical problems are comprehensively summarized and analyzed. First, the mechanisms of phase transition, aggregation, and blockage of the hydrate in the multiphase transport system have been investigated from the microscopic perspective to macroscopic characteristics. Second, based on different theoretical models, the algorithms are discussed to introduce an online monitoring technique for hydrate blockage, which can detect the safety risks and provide early warnings. Furthermore, for hydrate blockage prevention and control, the active methods based on chemical injection and the passive methods based on the modification of physicochemical properties of pipeline surfaces are reviewed. Finally, an outlook is provided for the future development of deepwater oil and gas and for the schemes to mitigate hydrate blockage.

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Flow characteristic and blockage mechanism with hydrate formation in multiphase transmission pipelines: In-situ observation and machine learning predictions

Cited by 18 publications

References 40 publications

Characterization of Hydrate Formation and Flow Influenced by Hydrophilic–Hydrophobic Components within a Fully Visual Rocking Cell

Characterization of Hydrate Formation and Flow Influenced by Hydrophilic–Hydrophobic Components within a Fully Visual Rocking Cell

Application of Machine Learning to Predict Blockage in Multiphase Flow

Flow Assurance of Hydrate Risk in Natural Gas/Oil Transportation: State-of-the-Art and Future Challenges

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