Pore−Throat Combination Characteristics and Their Impact on Fluid Mobility in Water-Bearing Tight Sandstones

High Resolution Image Download MS PowerPoint Slide The heterogeneity of nanoscale pore-throat structures controls fluid trapping and gas productivity in tight sandstone reservoirs, but a quantitative method to relate pore−throat combination to movable fluid distribution is lacking. This study integrates multiscale techniques, including high-pressure mercury intrusion (HPMI), nuclear magnetic resonance (NMR), X-ray microcomputed tomography (Xμ-CT), and core flooding experiments to classify tight sandstone reservoirs into three types based on initial water saturation ( S iw ) and reveal how pore−throat size and combinations control fluid mobility. Key findings include the following: (1) LowWater-Saturation Reservoirs (LSwR, S iw <30%) exhibit large primary pores, with 20.2% of connected pores having a pore−throat radius ratio <2; MediumWater-Saturation Reservoirs (MSwR), dominated by secondary dissolution pores with complex pore−throat networks and strong heterogeneity; HighWater-Saturation Reservoirs (HSwR, S iw >60%) are dominated by nanopores (<100 nm) and high pore-throat ratios. (2) Larger pore radii and long throats reduce capillary resistance, lowering S iw . The pore−throat radius ratio governs capillary resistance via the Jamin effect─low ratios (<2) favor gas displacement, whereas high ratios (>10) cause water retention; poor pore-throat connectivity and clay minerals types are the main causes of high S iw . (3) A novel multiparameter method is developed to quantify movable fluid saturation within specific pore-size ranges, showing that >80% of movable water in LSwR resides in pores >100 nm, whereas HSwR requires high displacement pressure (>10 MPa) to mobilize only 28.12% of fluids, primarily from 1 to 100 nm pores. The heterogeneity varies among different types of reservoirs, and the heterogeneity of large pores and small pores also has different effects on the movable water saturation. The integrated framework provides a quantitative tool for predicting movable fluids and optimizing recovery in heterogeneous tight reservoirs.