Huff-n-puff recovery performance and mechanism analysis of black nanosheets in low-permeability reservoirs based on NMR technology

Black nanosheets (BNs), as a highly promising fracturing-EOR integrated enhancement material, require further study of their huff-n-puff performance and mechanism. This work characterized nanoscale structure, stability, and interfacial properties of BNs, then evaluated their huff-and-puff performance through NMR-assisted core flooding experiments. The adaptability of BNs in low-permeability reservoirs with different permeabilities, as well as the effect of huff-n-puff cycles on their oil recovery performance, were analyzed. Results show that anionic modified BNs maintained nanoscale flake structure with enhanced electrostatic repulsion. The BNs with an extremely low concentration of 0.002 wt% exhibited excellent emulsification and stabilization effects on crude oil and wettability alteration of the rock surface. Compared with injection water, BNs had excellent huff-n-puff oil recovery effects, reaching 22.1% original oil in place (OOIP) after the first huff-n-puff cycle. BNs had good adaptability in low-permeability cores (i.e., 0.1 × 10⁻³ to 10 × 10⁻³ μm²). Increasing the huff-n-puff cycle significantly improved the oil recovery effect of BNs, and the optimal performance was at 4 cycles. As the huff-n-puff cycle increased from 3 to 4, the ability of BNs to “automatic oil-seeking” in micropores became more prominent. This paper also innovatively combined core nuclear magnetic resonance (NMR) T₂ analysis, nuclear magnetic imaging analysis, and longitudinal T₂ signal analysis along the core (i.e., along the core injection length). It can not only more accurately quantify the huff-n-puff recovery effect of low-permeability cores but also quantitatively analyze the penetration depth and microscopic huff-n-puff mechanism of BNs from a microscopic perspective. These findings are helpful for the selection of nanomaterials and mechanism analysis in the design of integrated fracturing-flooding schemes and processes.