Molecular dynamics modeling and simulation of silicon dioxide-low salinity water nanofluid for enhanced oil recovery

Enhanced oil recovery promoted by aqueous deep eutectic solvents on silica and calcite surfaces: a molecular dynamics study

Enhanced oil recovery (EOR) plays a critical role in optimizing oil extraction from existing fields to satisfy global energy demands while mitigating environmental impact. One promising EOR technique involves injecting water with reduced surface tension utilizing deep eutectic solvents (DESs). Despite early experimental support, the efficacy of aqueous-DES EOR varies and depends on factors such as connate water saturation, water salinity, and reservoir wettability. The recovery mechanisms for aqueous DESs are poorly understood due to the intricate nature of oil components and reservoir formation. In this paper, we investigate the role of DESs in the EOR process through molecular dynamics (MD) simulations. Three different types of DES molecules, such as choline chloride : urea (ChCl : U), choline chloride : ethylene glycol (ChCl : EG), and menthol : salicylic acid (M : SA) are used, for the recovery of dodecane (C12H26) oil from silica and calcite confined surfaces. We have demonstrated the structural characteristics of these systems by examining various physical properties, including interaction energies, density profiles, hydrogen bonds, and interfacial tension (IFT). Different concentrations (10 and 25 wt%) of DESs have been considered to unravel the effect of concentration on oil removal. The wettability of the substrate and the IFT between oil and aqueous DESs are critical physical properties that play a crucial role in influencing EOR phenomena. The IFT between water and oil decreases with the addition of DESs for all DES molecules, leading to a shift in surface behavior from oleophilic to oleophobic and ultimately facilitating the removal of oil from the substrate. Additionally, hydrogen bond formation between DESs and water has been calculated to elucidate its influence on the water/oil interface and substrate wettability. The study provides insights into the fundamental aspects of EOR processes for more effective and sustainable oil extraction.

A systematic and critical review of application of molecular dynamics simulation in low salinity water injection

Low Salinity Water Injection (LSWI) has been a well-researched EOR method, with several experimental and theoretical scientific papers reported in the literature over the past few decades. Despite this, there is still an ongoing debate on dominant mechanisms behind this complex EOR process, and some issues remain elusive. Part of the complexity arises from the scale of investigation, which spans from sub-pore scale (atomic and electronic scale) to pore scale, core scale, and reservoir scale. Molecular Dynamics (MD) simulation has been used as a research tool in the past decade to investigate the nano-scale interactions among reservoir rock (e.g., calcite, silica), crude oil, and brine systems in presence of some impurities (e.g., clay minerals) and additives (e.g., nanoparticles). In this paper, fundamental concepts of MD simulation and common analyses driven by MD are briefly reviewed. Then, an overview of molecular models of the most common minerals encountered in petroleum reservoirs: quartz, calcite, and clay, with their most common types of potential function, is provided. Next, a critical review and in depth analysis of application of MD simulations in LSWI process in both sandstone and carbonate reservoirs in terms of sub-pore scale mechanisms, namely electrical double layer (EDL) expansion, multi-ion exchange (MIE), and cation hydration, is presented to scrutinize role of salinity, ionic composition, and rock surface chemistry from an atomic level. Some inconsistencies observed in the literature are also highlighted and the reasons behind them are explained. Finally, a future research guide is provided after critically discussing the challenges and potential of the MD in LSWI to shed more light on governing mechanisms behind LSWI by enhancing the reliability of MD outcomes in future researches. Such insights can be used for design of new MD researches with complementary experimental studies at core scale to capture the main mechanisms behind LSWI.