TY - JOUR
T1 - Predictive surface complexation model of the calcite-aqueous solution interface
T2 - The impact of high concentration and complex composition of brines
AU - Vinogradov, Jan
AU - Hidayat, Miftah
AU - Sarmadivaleh, Mohammad
AU - Derksen, Jos
AU - Vega-Maza, David
AU - Iglauer, Stefan
AU - Jougnot, Damien
AU - Azaroual, Mohamed
AU - Leroy, Philippe
N1 - Publisher Copyright:
© 2021 Elsevier Inc.
PY - 2022/3
Y1 - 2022/3
N2 - Electrochemical interactions at calcite-water interface are characterized by the zeta potential and play an important role in many subsurface applications. In this work we report a new physically meaningful surface complexation model that is proven to be efficient in predicting calcite-water zeta potentials for a wide range of experimental conditions. Our model uses a two-stage optimization for matching experimental observations. First, equilibrium constants are optimized, and the Stern layer capacitance is optimized in the second stage. The model is applied to a variety of experimental sets that correspond to intact natural limestones saturated with equilibrated solutions of low-to-high salinity, and crushed Iceland Spar sample saturated with NaCl at non-equilibrium conditions. The proposed linear correlation of the Stern layer capacitance with the ionic strength is the main novel contribution to our surface complexation model without which high salinity experiments cannot be modelled. Our model is fully predictive given accurately known conditions. Therefore, the reported parameters and modelling protocol are of significant importance for improving our understanding of the complex calcite-water interfacial interactions. The findings provide a robust tool to predict electrochemical properties of calcite-water interfaces, which are essential for many subsurface applications including hydrology, geothermal resources, CO2 sequestration and hydrocarbon recovery.
AB - Electrochemical interactions at calcite-water interface are characterized by the zeta potential and play an important role in many subsurface applications. In this work we report a new physically meaningful surface complexation model that is proven to be efficient in predicting calcite-water zeta potentials for a wide range of experimental conditions. Our model uses a two-stage optimization for matching experimental observations. First, equilibrium constants are optimized, and the Stern layer capacitance is optimized in the second stage. The model is applied to a variety of experimental sets that correspond to intact natural limestones saturated with equilibrated solutions of low-to-high salinity, and crushed Iceland Spar sample saturated with NaCl at non-equilibrium conditions. The proposed linear correlation of the Stern layer capacitance with the ionic strength is the main novel contribution to our surface complexation model without which high salinity experiments cannot be modelled. Our model is fully predictive given accurately known conditions. Therefore, the reported parameters and modelling protocol are of significant importance for improving our understanding of the complex calcite-water interfacial interactions. The findings provide a robust tool to predict electrochemical properties of calcite-water interfaces, which are essential for many subsurface applications including hydrology, geothermal resources, CO2 sequestration and hydrocarbon recovery.
KW - Aqueous solutions
KW - Calcite
KW - Complex composition
KW - High salinity
KW - Predictive model
KW - Stern layer capacitance
KW - Surface complexation model
KW - Zeta potential
UR - http://www.scopus.com/inward/record.url?scp=85120381218&partnerID=8YFLogxK
U2 - 10.1016/j.jcis.2021.11.084
DO - 10.1016/j.jcis.2021.11.084
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C2 - 34839916
AN - SCOPUS:85120381218
SN - 0021-9797
VL - 609
SP - 852
EP - 867
JO - Journal of Colloid and Interface Science
JF - Journal of Colloid and Interface Science
ER -