Numerical Simulation and Sensitivity Analysis of Key Parameters for Modified Silicon-Based Nanoparticle Enhanced Oil Recovery in Low-Permeability Reservoirs
Chen Zhang, Xiang Rao*
School of Petroleum Engineering, Yangtze University, Wuhan 430100, China.
To solve the low recovery rate of low-permeability heterogeneous reservoirs in mid-late oilfield development, this study focuses on modified silicon-based nanoparticle EOR technology (strong migration, good environmental compatibility). A 3D two-phase two-component model was built via CMG-STARS (single-well homogeneous & single-injection four-production heterogeneous scenarios). Sensitivity analysis of 5 key parameters (injection concentration/rate/timing, reservoir permeability/porosity) was conducted by orthogonal tests. Results: Optimal parameters raise cumulative recovery to 65.8% (13.6 pts higher than water flooding); high-permeability/porosity reservoirs perform better; nanoparticle plugging increases low-permeability zone recovery by 10.2% in heterogeneous reservoirs. This work quantifies the coupling mechanism between injection parameters and reservoir properties, advances the simulation system, and supports on-site injection scheme design.
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Funding
This research was no funding provided.
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