Article

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.

^*Correspondence: Xiang Rao, E-mail: raoxiang0103@163.com

Received: 2026-01-21Accepted: 2026-01-26Published: 2026-02-28

AESIG 2026, 2(1), 67-82; https://doi.org/10.58244/aesig.263533

Funding

This research was no funding provided.

Abstract

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.

Keywords: Nanoparticle-enhanced oil recovery; Numerical simulation; CMG-STARS; Parameter sensitivity analysis; Heterogeneous reservoir; Reservoir simulation

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Funding

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