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Research advances in machine learning techniques in gas hydrate applications
The complex modeling accuracy of gas hydrate models has been recently improved owing
to the existence of data for machine learning tools. In this review, we discuss most of the …
to the existence of data for machine learning tools. In this review, we discuss most of the …
Enhanced regeneration of triethylene glycol solution by rotating packed bed for offshore natural gas dehydration process: experimental and modeling study
WC Chen, XG You, P Liu, BC Sun, GW Chu… - … and Processing-Process …, 2021 - Elsevier
To address the problems of confined space for offshore application, rotating packed bed
(RPB) was firstly used to enhance the regeneration of TEG solution in natural gas …
(RPB) was firstly used to enhance the regeneration of TEG solution in natural gas …
Prediction of industrial debutanizer column compositions using data-driven ANFIS-and ANN-based approaches
The work in this paper is based on an industrial debutanizer column in a petroleum refinery
located in Malaysia, which produces LPG (liquefied petroleum gas) as the top stream and …
located in Malaysia, which produces LPG (liquefied petroleum gas) as the top stream and …
Quantitative structure–activity relationships (QSARs) for estimation of activity coefficient at infinite dilution of water in ionic liquids for natural gas dehydration
Recently, ionic liquids (ILs) have been considered as alternative solvents to glycol in
dehydration of natural gas. However, due to the unlimited structural variations and possible …
dehydration of natural gas. However, due to the unlimited structural variations and possible …
The development of an AI-based model to predict the location and amount of wax in oil pipelines
J Kim, S Han, Y Seo, B Moon, Y Lee - Journal of Petroleum Science and …, 2022 - Elsevier
The petroleum that flows within pipelines can contain impurities to form a solid wax which,
when aggregated in sufficient qualities within the pipeline, can impair liquid flow and …
when aggregated in sufficient qualities within the pipeline, can impair liquid flow and …
Intelligent prediction of hydrate induction time in oil–water emulsion system based on data-driven and driving force
XF Lv, SK Chen, Y Liu, MG Peng, JM Duan… - Chemical Engineering …, 2025 - Elsevier
The prevention of natural gas hydrates is critical to oil and gas flow assurance. The
nucleation process of hydrates has always been a research hotspot, yet its randomness …
nucleation process of hydrates has always been a research hotspot, yet its randomness …
[HTML][HTML] Development of AI-based diagnostic model for the prediction of hydrate in gas pipeline
Y Seo, B Kim, J Lee, Y Lee - Energies, 2021 - mdpi.com
For the stable supply of oil and gas resources, industry is pushing for various attempts and
technology development to produce not only existing land fields but also deep-sea, where …
technology development to produce not only existing land fields but also deep-sea, where …
Adaptive predictive control based on adaptive neuro-fuzzy inference system for a class of nonlinear industrial processes
In present paper, a novel adaptive predictive control method is proposed for a class of
nonlinear systems via adaptive neuro-fuzzy inference system (ANFIS). In the proposed …
nonlinear systems via adaptive neuro-fuzzy inference system (ANFIS). In the proposed …
Performance of traditional and machine learning-based transformation models for undrained shear strength
In geotechnical engineering, transformation models are often used as first estimates of
parameters and to verify the order of magnitude of field and laboratory tests, which reliability …
parameters and to verify the order of magnitude of field and laboratory tests, which reliability …
Application of adaptive neuro-fuzzy inference system and optimization algorithms for predicting methane gas viscosity at high pressures and high temperatures …
Accurate estimation of methane viscosity is extremely important for petroleum engineers.
Methane viscosity as an important property is used to model multiphase fluid flow in porous …
Methane viscosity as an important property is used to model multiphase fluid flow in porous …