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Go to Editorial ManagerThe growing demand for energy, coupled with the continued dominance of fossil fuels as the primary energy source, necessitates eco-friendly technologies that simultaneously enhance oil recovery (EOR) and reduce the impact of their emissions. Only one task, which is the CO2-EOR project, can combine these two sustainable development goals. Further, employing green nanotechnology, including nanoparticles and nanofluids, ensures a sustainable approach to controlling and enhancing rock wettability, thereby enhancing hydrocarbon production and carbon storage. However, the performance of nanofluids in subsurface formations is limited by the stability of these nano-dispersions at the harsh conditions of reservoirs. This work thus synthesizes silica nanoparticles from waste bentonite as a green source and modifies the surface properties with a silane group to formulate a stable nanofluid for subsurface applications. The produced nanoparticles were characterized via Fourier Transform Infrared (FTIR) spectroscopy, X-ray diffraction (XRD), scanning electron microscopy (SEM), zetasizer, and dynamic light scattering (DLS). Moreover, the efficiency of nanoparticles as wettability-modifying agents was studied using contact angle and spontaneous imbibition tests. FTIR measurements confirmed the presence of silane on the surface of hybrid silica nanoparticles, as indicated within the Wavenumber 2950 cm-1. Moreover, XRD measurements revealed that hybrid nanoparticles showed lower noise than pure ones. Results also showed that silane-treated nanoparticles (hybrid) are more tolerant to high salinity (≥ 0.5wt% brine), and green-synthesized nanoparticles have a drastic ability to invert the wettability of oil-wet surfaces (θ≥123°) to water-wet (θ ≤ 28°) at ambient conditions and also reduce the contact angle from 175° to 68°) at CO2-EOR conditions. The study concludes that these green nanofluids are highly efficient for EOR and carbon geosequestration projects when properly formulated.
The objective of the current study is to determine the accuracy of a computational model that has been developed to simulate polyurethane foaming reactions by comparing its results with experimental findings on the system using both physical and chemical blowing agents. There was high concordance between the model outputs and the laboratory results in regard to the temporal development of reaction temperature as well as the resulting foam density, both of which were highly faithful recreations. The discussion provided further information about the optimization of the performance of cyclohexane, particularly when used in synergy with chemically active blowing agents, which speed up foaming. Besides, the polymerization dynamics were contained in the simulation, thus providing rich information on the structural changes that occur during the foaming process. Taken together, the results present a strong basis for the process performance optimization, as well as the predictive modeling of the blowing agent behavior. In the future, it will involve expanding the simulation model to include a wider range of agents, reaction mechanisms, and kinetics.