Analytical Prediction of Gas Hydrate Formation Conditions for Oil and Gas Pipeline
Abstract: Oil and gas production operations, particularly those involving subsea production systems, are frequently subjected to harsh underwater conditions characterized by low temperatures and high pressures, owing to the placement of most subsea facilities on the seabed. These challenging environ...
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2025
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my.uniten.dspace-371022025-03-03T15:47:30Z Analytical Prediction of Gas Hydrate Formation Conditions for Oil and Gas Pipeline Ismail F.B. Yuhana M.I.F. Mohammed S.A. Sabri L.S. 58027086700 59155962700 57189212521 57201654441 Feedforward neural networks Gases Hydration Wireless sensor networks Analytical predictions Flow assurance Gas hydrates formation Hydrate formation Hydrate formation conditions Oil and gas production Oil-and-Gas pipelines Production operations Subsea production systems Underwater wireless sensor networks Gas hydrates Abstract: Oil and gas production operations, particularly those involving subsea production systems, are frequently subjected to harsh underwater conditions characterized by low temperatures and high pressures, owing to the placement of most subsea facilities on the seabed. These challenging environmental factors often lead to the formation of gas hydrates, especially in the presence of moisture within the production fluidIn this study, A suggestion is made to employ an underwater wireless sensor network (UWSN) to showcase the viability of real-time monitoring of pipeline health conditions, aiming to mitigate problems associated with hydrate formation in oil and gas pipelines. Additionally, A predictive analytical model for gas hydrate formation in these pipelines is crafted using Aspen HYSYS simulation and Feed-Forward Artificial Neural Network (ANN) modeling. The development of this prediction model and the potential application of UWSN technology in the oil and gas production field could assist operators in making informed decisions regarding intervention processes for addressing hydrate-related challenges in pipelines. ? Pleiades Publishing, Ltd. 2024. Final 2025-03-03T07:47:30Z 2025-03-03T07:47:30Z 2024 Article 10.1134/S107042722401004X 2-s2.0-85195139667 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85195139667&doi=10.1134%2fS107042722401004X&partnerID=40&md5=0ea26b9cf677235759c1e7fa0bd83faf https://irepository.uniten.edu.my/handle/123456789/37102 97 1 36 45 Pleiades Publishing Scopus |
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Feedforward neural networks Gases Hydration Wireless sensor networks Analytical predictions Flow assurance Gas hydrates formation Hydrate formation Hydrate formation conditions Oil and gas production Oil-and-Gas pipelines Production operations Subsea production systems Underwater wireless sensor networks Gas hydrates |
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Feedforward neural networks Gases Hydration Wireless sensor networks Analytical predictions Flow assurance Gas hydrates formation Hydrate formation Hydrate formation conditions Oil and gas production Oil-and-Gas pipelines Production operations Subsea production systems Underwater wireless sensor networks Gas hydrates Ismail F.B. Yuhana M.I.F. Mohammed S.A. Sabri L.S. Analytical Prediction of Gas Hydrate Formation Conditions for Oil and Gas Pipeline |
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Abstract: Oil and gas production operations, particularly those involving subsea production systems, are frequently subjected to harsh underwater conditions characterized by low temperatures and high pressures, owing to the placement of most subsea facilities on the seabed. These challenging environmental factors often lead to the formation of gas hydrates, especially in the presence of moisture within the production fluidIn this study, A suggestion is made to employ an underwater wireless sensor network (UWSN) to showcase the viability of real-time monitoring of pipeline health conditions, aiming to mitigate problems associated with hydrate formation in oil and gas pipelines. Additionally, A predictive analytical model for gas hydrate formation in these pipelines is crafted using Aspen HYSYS simulation and Feed-Forward Artificial Neural Network (ANN) modeling. The development of this prediction model and the potential application of UWSN technology in the oil and gas production field could assist operators in making informed decisions regarding intervention processes for addressing hydrate-related challenges in pipelines. ? Pleiades Publishing, Ltd. 2024. |
| author2 |
58027086700 |
| author_facet |
58027086700 Ismail F.B. Yuhana M.I.F. Mohammed S.A. Sabri L.S. |
| format |
Article |
| author |
Ismail F.B. Yuhana M.I.F. Mohammed S.A. Sabri L.S. |
| author_sort |
Ismail F.B. |
| title |
Analytical Prediction of Gas Hydrate Formation Conditions for Oil and Gas Pipeline |
| title_short |
Analytical Prediction of Gas Hydrate Formation Conditions for Oil and Gas Pipeline |
| title_full |
Analytical Prediction of Gas Hydrate Formation Conditions for Oil and Gas Pipeline |
| title_fullStr |
Analytical Prediction of Gas Hydrate Formation Conditions for Oil and Gas Pipeline |
| title_full_unstemmed |
Analytical Prediction of Gas Hydrate Formation Conditions for Oil and Gas Pipeline |
| title_sort |
analytical prediction of gas hydrate formation conditions for oil and gas pipeline |
| publisher |
Pleiades Publishing |
| publishDate |
2025 |
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1826077560803426304 |
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13.244413 |