کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
4768349 | 1424954 | 2017 | 10 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Modeling of mixed-gas adsorption on shale using hPC-SAFT-MPTA
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موضوعات مرتبط
مهندسی و علوم پایه
مهندسی شیمی
مهندسی شیمی (عمومی)
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: Modeling of mixed-gas adsorption on shale using hPC-SAFT-MPTA Modeling of mixed-gas adsorption on shale using hPC-SAFT-MPTA](/preview/png/4768349.png)
چکیده انگلیسی
Knowledge of mixed-gas adsorption behavior on shale is important for reserve estimation, production forecast, and carbon dioxide sequestration. In this work, we combined the multicomponent potential theory of adsorption (MPTA) with the hybrid perturbed-chain statistical associating fluid theory equation of state (hPC-SAFT EOS) to describe mixed-gas adsorption on shale. In the hPC-SAFT-MPTA model, the fluid-solid interaction is modeled using the Dubinin-Radushkevich-Astakhov (DRA) potential and the fluid-fluid interaction is described by the hPC-SAFT EOS. Extending the hPC-SAFT-MPTA model to excess adsorption is straightforward and has no need to estimate the adsorbed phase density. Experimental data on the pure-component and mixture adsorption of CH4, C2H6, CO2, and N2 on activated carbon and shale were used to test the hPC-SAFT-MPTA model. Activated carbon was employed as a reference adsorbent because its pore structure is simpler than that of shale. The hPC-SAFT-MPTA model can predict the mixture adsorption with average relative errors of 10.34%-17.12% on the basis of the pure gas adsorption data. The hPC-SAFT-MPTA model provides an alternative approach to modeling mixed-gas adsorption on shale and complements sophisticated methods such as density functional theory and the grand canonical Monte Carlo simulation method. The hPC-SAFT-MPTA model is anticipated to be useful in simulations of shale gas production and CO2 sequestration in shale.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Fuel - Volume 210, 15 December 2017, Pages 535-544
Journal: Fuel - Volume 210, 15 December 2017, Pages 535-544
نویسندگان
Wenxi Ren, Shouceng Tian, Gensheng Li, Mao Sheng, Ruiyue Yang,