Streamline-based simulation of nanoparticle transport in field-scale heterogeneous subsurface systems

•Robust and efficient streamline-based method for large-scale nanoparticle (NP) transport modeling.•Modeling of smart NP transport physics including encapsulation, multi-site retention and permeability loss.•Competitive accuracy and efficiency against finite-difference-based academic and commercial codes.•Pilot field-scale engineering design case of NP-based enhanced-oil-recovery. Nanoparticle (NP) transport is increasingly relevant to subsurface engineering applications such as aquifer characterization and enhanced oil recovery. An efficient field-scale simulation framework is critical for predicting NP performance and designing subsurface applications. In this work, for the first time, a streamline-based model is presented to simulate NP transport in field-scale subsurface systems with heterogeneous permeability. It considers a series of smart behaviors exhibited by engineered nanoparticles (NPs), including time-triggered encapsulation, retention, formation damage effects and variable nanofluid viscosity. The key methods employed by the algorithm are streamline-based simulation (SLS) and an operator-splitting (OS) technique for modeling NP transport. The model is implemented in an in-house streamline-based code, which is verified against analytical solutions, commercial simulator and academic codes. Simulations on a synthetic three-dimensional (3D) nanocapsule application engineering design case, are also performed to investigate the effect of fluid and NP properties on the displacement pattern of an existing subsurface fluid.