Abstract: Near-surface layers are typically characterized by loose structures and significant vertical and lateral variations in both thickness and velocity. These characteristics result in marked absorption of seismic wave energy and severe phase distortion, substantially reducing the signal-to-noise ratio (SNR) and resolution of acquired seismic records. The absorption properties of these layers can be described by the quality factor (Q-value). Given the complex structures of near-surface layers, constructing a precise quality factor field requires simultaneous consideration of their pronounced vertical and lateral variations. This study first summarized an optimization strategy for quality factor inversion based on data from uphole surveys by analyzing the applicability of common Q-value inversion methods. To further enhance the accuracy of near-surface quality factor field modeling, this study proposed a method for constructing precise quality factor field models. This method integrates high-resolution information from uphole survey data with high sampling-rate information from reflection wave data. Tests on real data demonstrate that the proposed method effectively captures detailed variations in lateral Q-values of the layers. The compensated seismic waves exhibited broadened effective frequency bands and significantly improved seismic resolution, thereby validating the effectiveness of the presented approach.