Stable CO2/water Foam Stabilized by Dilute Surface‐modified Nanoparticles and Cationic Surfactant at High Temperature and Salinity
Journal of surfactants and detergents(2023)
Abstract
CO2 enhanced oil recovery and storage could see widespread deployment as decarbonization efforts accelerate to meet climate goals. CO2 is more efficiently distributed underground as a viscous foam than as pure CO2; however, most reported CO2 foams are unstable at harsh reservoir conditions (22 wt% brine, 2200 psi, and 80 degrees C). We hypothesize that silica nanoparticles (NP) grafted with (3-trimethoxysilylpropyl)diethylenetriamine ligands (N3), to improve colloidal stability, and dimethoxydimethylsilane ligands (DM), to improve CO2-phillicity, combined with the cationic surfactant N-1-alkyl-N-3, N-3-dimethylpropane-1,3-diamine (RCADA), will develop viscous, stable CO2 foams at reservoir conditions. We grafted NP with N3 and DM ligands. We verified NP stability at reservoir conditions with measurements of zeta potential, amine titration curves, and NP diameter. We measured NP water contact angles (theta(w)) at the water-air and water-liquid CO2 interfaces. In a high-temperature, high-pressure flow apparatus, we calculated the viscosity of CO2 foams across a beadpack and determined static foam stability with microscope observations. Modified NP were colloidally stable at reservoir conditions for 4 weeks, and had higher theta(w) in liquid CO2 than in air. Addition of at least 0.5 mu mol/m(2) DM silane (0.5DM) greatly improved foam stability. RCADA-only foam coarsening rates (dD(SM)(3)/dt) decreased 16-17x after adding 1 wt/vol% 8N3 + 1.5DM NP, and 5-10x with a 0.1-1 vol/vol% increase in RCADA concentration (with or without NP). 1 vol/vol% RCADA foam exhibited coarsening rates of 900 and 2400 mu m(3)/min with 1 and 0.2 wt/vol% 8N3 + 1.5DM NP, respectively. These results demonstrate impressive foam stabilities at harsh reservoir conditions.
MoreTranslated text
Key words
CO2,enhanced oil recovery,nanoparticles,Pickering foam,surfactants
AI Read Science
Must-Reading Tree
Example
![](https://originalfileserver.aminer.cn/sys/aminer/pubs/mrt_preview.jpeg)
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined