Nuclear magnetic resonance permeability calculation method based on pore-throat connectivity constraints: A case study of sandstone reservoirs in the Bozhong Sag

In strongly diagenetically altered low-to medium-permeability sandstone reservoirs, disconnected pores are widely developed, making it difficult for conventional nuclear magnetic resonance (NMR)-based permeability evaluation methods to accurately reflect the true seepage capacity of the reservoir. These methods generally use an empirical T₂ cutoff to partition free fluid volume (FFV) and bound volume irreducible (BVI), and then estimate permeability using the classical Timur-Coates model. However, because they cannot effectively distinguish connected pores from disconnected pores, the predicted permeability is often systematically overestimated. To address this issue, this study proposes a pore-throat-connectivity-constrained method for determining the T₂ cutoff and incorporates it into the Timur-Coates permeability calculation workflow. First, core NMR T₂ spectra and high-pressure mercury intrusion capillary pressure data are jointly utilized and transformed into equivalent pore-size distributions and cumulative distribution curves. By quantitatively analyzing the correspondence between these two types of curves, the volume of disconnected pores and the associated critical pore-size range are identified, thereby determining a free-fluid T₂ cutoff with clear physical significance. Based on this cutoff, FFV and BVI are reclassified and then substituted into the Timur-Coates model to recalculate permeability. A case study from sandstone reservoirs in the Bozhong Sag, Bohai Bay Basin, demonstrates that the proposed method effectively reduces the interference of disconnected pores in FFV estimation and transforms the T₂ cutoff from an empirical selection into a quantitatively determined parameter constrained by pore-throat connectivity. Compared with the conventional empirical cutoff method, the proposed approach yields permeability predictions that are in much better agreement with measured core permeability, with the logarithmic root mean square error reduced from 1.079 to 0.104. These results indicate that the proposed method significantly improves the accuracy and stability of permeability evaluation in reservoirs affected by complex diagenesis, and provides a more geologically meaningful and practically valuable approach for the refined permeability characterization of low-permeability complex sandstone reservoirs.