Nanoscience Applied to Oil Recovery and Mitigation: A Multiscale Computational Approach
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Nanoscience Applied to Oil Recovery and Mitigation: A Multiscale Computational Approach Raphael S. Alvim1, Vladivostok Suxo1, Oscar A. Babilonia1, Yuri M. Celaschi2, and Caetano R. Miranda1 1 DFMT, Instituto de Física, Universidade de São Paulo, São Paulo, SP, 05508-090, Brazil. 2 PG-NMA, Universidade Federal do ABC, Santo André, SP, 09210-580, Brazil. ABSTRACT With emergence of nanotechnology, it is possible to control interfaces and flow at nanoscale. This is of particular interest in the Oil and Gas industry (O&G), where nanoscience can be applied on processes such as Enhance Oil Recovery (EOR) and oil mitigation. On this direction, one of potential strategies is the so called Nano-EOR based on surface drive flow, where mobilization of hydrocarbons trapped at the pore scale can be favored by controlling by the chemical environment through “wettability modifiers”, such as functionalized nanoparticles (NP) and surfactants. The challenge consists then to search for optimal functionalized NP for oil recovery and mitigation at the harsh conditions found in oil reservoirs. Here, we introduce a hierarchical computational protocol based on the role of NP interfacial and wetting properties within oil/brine/rock interfaces to the fluid displacement in pore network models (PNMs). This integrated multiscale computational protocol ranges from first principles calculations, to determine and benchmark interatomic potentials, which are coupled with molecular dynamics (MD) to characterize the descriptors (interfacial properties and viscosity). The MD results are then mapped into Lattice Boltzmann method (LBM) simulation parameters to model the oil displacement process in PNMs at the microscale. Here, we show that this multiscale protocol coupled with Machine Learning techniques can be a resourceful tool to explore the potentialities of chemical additives, such as NP and surfactants, for the oil recovery process and investigate the effects of interfacial tension and wetting properties on the fluid behavior at both nano and microscales. INTRODUCTION Among other applications, nanotechnology can help the O&G industry for understanding the behavior of NP and confined fluids at nanoscale, contributing to processes for exploration and production at macroscale. As oil recovery processes involve the interaction between mineral and hydrocarbons, the optimization of oil production requires deep understanding of reservoir properties at different scales. For a case-test, the adsorption of functionalized NP onto representative clays and at the brine/oil/clay interfaces and their effect EOR process were studied through a combined multiscale molecular modeling (Figure 1) ranging from first principles calculations, molecular dynamics, Lattice Boltzmann method and machine learning techniques. Montmorillonite (MMT) is layered aluminosilicate clay classified as the smectite group that coats pores of sandstone natural reservoirs. The oil-wettability of the rock is determined by the MMT (001) surface [1]. Particularly for enhanced oil recovery process
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