Abstract
Waterflooding is crucial for China's oil and gas industry, but it induces dynamic heterogeneity in reservoir properties, which commercial simulators fail to model accurately. To address this, we propose a multi-scale simulation method incorporating time-varying absolute permeability (k) and relative permeability (k(r)) driven by surface flux. An improved multi-scale finite volume (IMsFV) method solves pressure equations on multi-scale grids, enhancing computational efficiency. SPE10 benchmark validation shows 95.07% reduction in total simulation time and 98.19% in linear solver time versus the fully implicit method, with errors < 5%. Unlike commercial simulators neglecting dynamic heterogeneity, this approach captures opposing mechanisms: dynamic k exacerbates water channeling, reducing recovery, while dynamic k(r) enhances fluid mobility and reduces residual oil saturation. Crucially, dynamic k(r)'s positive effect dominates during high water-cut stages, ultimately improving recovery. Sensitivity analysis confirms: (1) Dynamic heterogeneity primarily benefits mid-high water-cut stages, reducing water cut and increasing oil production; (2) At 99% water cut, it enhances recovery by 28.88-32.87% across permeabilities (400-2000 md), with greater gains in higher-permeability reservoirs; (3) Under increasing injection rates (50 → 200 m(3)/day), recovery gains amplify from 18.07 to 45.49%. This approach provides an efficient, accurate tool for predicting remaining oil in high-water-cut reservoirs.