کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
8089624 | 1521949 | 2018 | 8 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Reliable prediction of aqueous dew points in CO2 pipelines and new approaches for control during shut-in
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
علوم زمین و سیارات
فرآیندهای سطح زمین
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چکیده انگلیسی
Accurate predictions and precise control of the allowable water content in CO2-rich fluids are required in large-scale pipeline operations. Especially during transient shut-in and re-start operations, the pressure decrease associated with cooling may cause the CO2-rich mixture to pass through its dew point, producing an aqueous liquid phase. The pH of this liquid aqueous phase will rapidly decrease as carbonic acid is formed, greatly accelerating the corrosion rate of the carbon steel pipeline. The phase behaviour of CO2-rich fluid mixtures is qualitatively different to that of hydrocarbons, and standard oil and gas property packages in process simulation software may be inadequate for predicting dew points and other key properties. An extensive literature survey reveals 34 data sets where water contents of CO2-rich fluids have been measured near conditions relevant to CO2 pipelines. Following consistency tests, 23 data sets were found to be of good quality and 11 data sets were found to be of poor quality. The good-quality data were compared with predictions from 6 equations of state. Overall, Multiflash's RKS (Advanced) model was found to provide the best agreement with the aqueous dew point data of CO2-rich fluid phases. A case study is presented wherein it is demonstrated that the formation of a corrosive aqueous phase can be avoided during shut-in via introduction of a relatively small volume of ethanol.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: International Journal of Greenhouse Gas Control - Volume 70, March 2018, Pages 97-104
Journal: International Journal of Greenhouse Gas Control - Volume 70, March 2018, Pages 97-104
نویسندگان
Darren Rowland, John A. Boxall, Thomas J. Hughes, Saif Z.S. Al Ghafri, Fuyu Jiao, Xiong Xiao, Vijay Pradhan, Eric F. May,