To address the issues of reservoir blockage and sharp decline in fluid output of production wells in the polymer injection zone of the Henan oilfield, physical modeling has been used to study the blockage mechanism and blockage locations of the polymer-flooded reservoir based on oil reservoir characteristics and blockage knowledge. The results show that all the constant pressures in the low, moderate, and high permeability cores subjected to polymer injection and subsequent waterflooding were higher than the constant pressure during primary waterflooding; hence, polymer retention and blockage phenomena were obvious in the cores; in the high permeability core, the pore surface adsorbed more polymer molecules though pore throat radii were still much greater than the size of the polymer molecule, suggesting that polymer blockage is mainly caused by adsorption and retention. For the low permeability core, the specific surface area of the inlet end was much larger than that in the high permeability core, leading to more serious capture of polymer molecules at the small pores, indicating that blockage under polymer injection is mainly caused by capture and retention; for the lower permeability (91.81 mD) core, as compared with the case prior to polymer injection, the polymer-injected core had fewer large pores and throats, the mean pore throat radius decreased from 42.2 μm to 39.9 μm, and the mean throat-to-pore coordination number decreased from 3.36 to 3.19; thus, polymer capture and retention led to core blockage; the leftward shift of the curve corresponding to the porosity component, high porosity peak weakening after polymer injection, moderate and low porosity peaks appearing after polymer injection, and enhancement of lower porosity peaks indicate that, after polymer injection and subsequent waterflooding, polymer adsorption and capture led to blockage of some large pores; the highest pressure gradient, i.e., 6.3 MPa/m, was achieved at the P2-P3 segment; thus, the worst blockage occurred at the P2-P3 stage, or 1/8-1/4 of the sandpack length. In this paper, Nanbaxian oil and gas field, China, was taken as an example to investigate the interpretation method of gas saturation in a complex pore structure. The “four properties” relationship of the formation reservoir in the Nanbaxian oil and gas field was studied in depth according to the conventional logging data and core analysis data. The neural network algorithm was used to reconstruct the resistivity curve of the water layer to eliminate the influence of lithology, shale content, and pore structure on the resistivity. The difference between the reconstructed curve and the measured resistivity curve was used to identify the gas and water, and the ratio of the two was used to calculate the gas saturation, and good results were achieved. It was found that the sedimentary types of the Nanbaxian oil and gas field cause the reservoir to be thin, numerous, and dispersed; the lateral correlation is difficult. In addition, the structural features lead to the reservoir types being various in the vertical direction, which makes the identification of reservoir fluid more difficult. The results revealed that the rock compaction, poor physical properties, complex pore structure, high resistivity of surrounding rocks, and low formation water salinity make the water layer with high resistivity and difficult to identify gas and water.