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HYDRATE PLUG FORMATION PREDICTION TOOL – AN INCREASING NEED FOR FLOW ASSURANCE IN THE OIL INDUSTRY

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Title: HYDRATE PLUG FORMATION PREDICTION TOOL – AN INCREASING NEED FOR FLOW ASSURANCE IN THE OIL INDUSTRY
Author: Kinnari, Keijo; Labes-Carrier, Catherine; Lunde, Knud; Hemmingsen, Pål V.; Davies, Simon R.; Boxall, John A.; Koh, Carolyn A.; Sloan, E. Dendy
Subject Keywords flow assurance;hydrate plugging;CSMHyK;ICGH;International Conference on Gas Hydrates
Issue Date: 2008-07
Publicly Available in cIRcle 2008-07-24
Citation: Kinnari, Keijo; Labes-Carrier, Catherine; Lunde, Knud; Hemmingsen, Pål V.; Davies, Simon R.; Boxall, John A.; Koh, Carolyn A.; Sloan, E. Dendy. 2008. HYDRATE PLUG FORMATION PREDICTION TOOL – AN INCREASING NEED FOR FLOW ASSURANCE IN THE OIL INDUSTRY. Proceedings of the 6th International Conference on Gas Hydrates (ICGH 2008), Vancouver, British Columbia, CANADA, July 6-10, 2008.
Abstract: Hydrate plugging of hydrocarbon production conduits can cause large operational problems resulting in considerable economical losses. Modeling capabilities to predict hydrate plugging occurrences would help to improve facility design and operation in order to reduce the extent of such events. It would also contribute to a more effective and safer remediation process. This paper systematically describes different operational scenarios where hydrate plugging might occur and how a hydrate plug formation prediction tool would be beneficial. The current understanding of the mechanisms for hydrate formation, agglomeration and plugging of a pipeline are also presented. The results from this survey combined with the identified industrial needs are then used as a basis for the assessment of the capabilities of an existing hydrate plug formation model, called CSMHyK (The Colorado School of Mines Hydrate Kinetic Model). This has recently been implemented in the transient multiphase flow simulator OLGA as a separate module. Finally, examples using the current model in several operational scenarios are shown to illustrate some of its important capabilities. The results from these examples and the operational scenarios analysis are then used to discuss the future development needs of the CSMHyK model.
Affiliation: Other
URI: http://hdl.handle.net/2429/1149
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