Seismic facies discrimination is usually performed based on a rock-physics-driven quantitative interpretation approach. The accuracy of the study of rock physics largely impacts the reservoir and fluid recognition. However, the study is commonly conducted with absolute well logs without removing the trend effect. Such an approach may introduce inappropriate low-frequency information and bias further analysis of seismic data (crossplotting, facies probability density function generation, and projection angle determination). By contrast, relative rock physics with the trend decomposed reflects the rock-property variation of the overburden and underlying formation. The relative portions are more consistent with the seismic reflectivity, providing an alternative tool to facies interpretation through a seismic inversion scheme. A workflow for seismic facies discrimination has been investigated that incorporates relative rock physics, long short-term memory-based nonlinear seismic inversion, and Bayesian classification. This workflow is employed in a case study from Songliao Basin in northeast China, through which the results of relative and absolute approaches in key steps are analyzed and compared. The consistency of facies, determined through relative and absolute methods with petrophysical interpretation, is calculated. The relative analysis exhibits improved agreement with petrophysical interpretation in overall facies and reservoir sand discrimination of the blind wells. This indicates the potential to minimize the trend bias by integrating relative rock physics in quantitative interpretation.