2020
DOI: 10.1021/acs.energyfuels.9b04528
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Atomistic Molecular Dynamics Simulations of Surfactant-Induced Wettability Alteration in Crevices of Calcite Nanopores

Abstract: Wettability alteration is an important mechanism in surfactant-facilitated enhanced oil recovery (EOR) in oil-wet carbonate reservoirs. An in-depth understanding of how surfactants influence the wettability of calcite surfaces is of crucial importance. In this study, atomistic molecular dynamics simulations were used to elucidate how the nonionic and anionic surfactants influence the wettability at the corners of angular calcite pores. A multicomponent oil model was constructed based on a chemical analysis of … Show more

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Cited by 24 publications
(17 citation statements)
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“…For calcite, the “rigid model” of Sedghi et al was used, which combines CHARMM Lennard-Jones terms with the bonded parameters and partial charges of Raiteri and Gale, and harmonic position restraints on carbon atoms and calcium ions. Simple point charge/flexible water (SPC-FW) model was used for water, as it is superior to most other commonly used water models in the description of the liquid water properties, and for back-compatibility with our earlier studies. ,, The nonbonded cutoff was 1.4 nm, and the particle mesh Ewald (PME) summation was employed for the long-range electrostatic interactions. Periodic boundary conditions (PBCs) in all three dimensions were imposed.…”
Section: Methodsmentioning
confidence: 99%
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“…For calcite, the “rigid model” of Sedghi et al was used, which combines CHARMM Lennard-Jones terms with the bonded parameters and partial charges of Raiteri and Gale, and harmonic position restraints on carbon atoms and calcium ions. Simple point charge/flexible water (SPC-FW) model was used for water, as it is superior to most other commonly used water models in the description of the liquid water properties, and for back-compatibility with our earlier studies. ,, The nonbonded cutoff was 1.4 nm, and the particle mesh Ewald (PME) summation was employed for the long-range electrostatic interactions. Periodic boundary conditions (PBCs) in all three dimensions were imposed.…”
Section: Methodsmentioning
confidence: 99%
“…Different surface planes generally have significantly different physical properties, which are key to the practically meaningful modeling of the wettability. In addition, the positive surface charge and the thin layer of “surface water”, both experimentally observed and supremely important for the surface interactions, are neglected. The oil is approximated by a single aliphatic hydrocarbon (e.g., dodecane), whose molecules are assumed to adhere to the surface laterally along the length of the aliphatic chain.…”
Section: Introductionmentioning
confidence: 99%
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“…There is still a need to understand the influence of immersion time and material properties such as crystal orientation to the rate of ion exchange. Ionic adsorption on various planar surfaces of muscovite [5], kaolinite [6] and calcite [7] had been studied through molecular dynamics simulations. However, the rate at which Sn 2+ and Sr 2+ ions are diffused in calcite at (100) and (001) orientations were not explored in these simulations nor in experiments.…”
Section: Introductionmentioning
confidence: 99%
“…Polymers and their effects on wettability, interfacial tension, and liquid mobility can be screened in molecular dynamics (MD) simulations, which provide a detailed picture of molecular interactions and dynamics at the polymer–oil–water–solid interfaces at high pressures and temperatures typical of oil reservoirs. , For example, simulations previously showed that the addition of surfactants can lead to oil detachment from the rock surface with altered wettability of rock surfaces through mediating the interface between oil, water, and solid phases, where a thin water layer leads to oil mobility inside nanopores. This molecular insight is in agreement with the observations that polymer/surfactant flooding results in the reduction of interfacial tension between oil and water, oil detachment from the rock surface, and easier deformation and mobilization of trapped oil droplets inside planar and constricted nanopores . In combination with machine learning techniques, such MD simulations can also provide fast and cost-effective screening of conditions inside oil reservoirs …”
Section: Introductionmentioning
confidence: 99%