Li, Didi and Jiang, Xi (2017) Numerical investigation of the partitioning phenomenon of carbon dioxide and multiple impurities in deep saline aquifers. Applied Energy, 185 (2). pp. 1411-1423. ISSN 0306-2619
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Abstract
The partitioning behaviours of CO2 with three kinds of common impurities, i.e., N2, CH4 and H2S, in the formation brine are investigated by numerical simulations. The results indicate that the effects of N2, CH4 or the mixture of N2 and CH4 at the same concentrations are generally similar. The leading gas front is usually made up of less soluble impurities, such as N2, CH4 or the mixture of N2 and CH4, while more soluble species such as H2S has dissolved preferentially in the formation brine. The separations between different gas species increase as the gas displacement front migrates forwards and contacts more of the aqueous phase. Compared with the partitioning results of the 98% CO2 and 2% H2S mixture, the results indicate that the inclusion of less soluble N2 and/or CH4 results in an earlier gas breakthrough and a longer delay between the breakthrough times of CO2 and H2S. The early breakthrough of the gas phase is mainly because that the addition of N2 and/or CH4 lowers the viscosity of the gas phase, resulting in a higher gas velocity than that of the CO2–H2S mixture. Meanwhile, the mobility ratio is higher and the gas mixture contacts the formation brine over a larger area, giving rise to more efficient stripping of the more soluble gas species like H2S and thus larger separations. In the meantime, with the same total concentrations of impurities (12%), when 2% H2S is contained in the CO2 streams, gas phase flows slower and thus the breakthrough time is later. Furthermore, the effects on the partitioning phenomenon are weaker with decreasing concentrations of N2 and/or CH4 (from 10% to 2%) with fixed concentrations of other impurity like H2S (2%). The migration distances and the separations between different gas species change linearly with time on the whole, as confirmed by a simulation in a longer model.