Sensitivity analysis of low salinity waterflood alternating immiscible CO2 injection (Immiscible CO2-LSWAG) performance using machine learning application in sandstone reservoir
Author:
Funder
Yayasan Universiti Teknologi PETRONAS
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s13202-024-01849-w.pdf
Reference53 articles.
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2. AlQuraishi AA et al (2019) Low salinity water and CO2 miscible flooding in Berea and Bentheimer sandstones. J King Saud Univ Eng Sci 31(3):286–295. https://doi.org/10.1016/j.jksues.2017.04.001
3. Al-Saedi, HN. et al (2019) A new design of low salinity-CO2-different chemical matters. In: Society of petroleum engineers - Abu Dhabi international petroleum exhibition and conference 2019, ADIP 2019. https://doi.org/10.2118/197118-MS
4. Al-Saedi HN, Flori RE (2019) Novel coupling smart water-CO2 flooding for sandstone reservoirs. Petrophysics 60(04):525–535
5. Asante J, Ampomah W, Tu J, Cather M (2024) Data-driven modeling for forecasting oil recovery: a timeseries neural network approach for tertiary CO2 WAG EOR. Geoenergy Sci Eng 233:212555
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