Abstract: The Lower Paleozoic–Sinian lithologic traps on the northern slope of the Central Sichuan Paleouplift, at depths exceeding 6,000 m, exhibit significant high-frequency seismic attenuation. This is evidenced by dominant frequencies below 30 Hz and over 70% energy loss in the 60 Hz band. Furthermore, the P-impedance distributions of dolomites, limestones, and siliceous layers show an overlap over 70%, resulting in great uncertainties of lithologic trap identification. To address the challenges of ultra-deep weak signal recovery and complex lithology discrimination, this study proposes an integrated technical suite comprising true signal recovery, high-resolution imaging, intelligent interpretation, and quantitative evaluation. Intelligent denoising using a multi-scale information distillation network boosts the peak signal-to-noise ratio by over 10 dB. The wavelet transform-based time-frequency energy compensation technique elevates the dominant frequency to 35 Hz and broadens the effective band by 27%. The FWI-based multiple suppression technique, which reconstructs multiples' travel paths via wave equation-based forward modeling and FWI, achieves a 92% well-to-seismic correlation. These techniques collectively enable high-fidelity recovery of ultra-deep weak signals and accurate reconstruction of complex subsurface wavefields. The integration of phase rotation-based sequence interpretation (with vertical resolution of 10 m) and a geological-geophysical co-inversion strategy (with reservoir prediction error below 15%) facilitates a dramatic improvement in both qualitative and quantitative identification of ultra-deep complex lithologic traps. Field applications in the gas field demonstrate a significant increase in lithologic trap identification accuracy from 62% to 81%. This AI-driven seismic data processing and interpretation system provides an intelligent solution for ultra-deep weak signal recovery and lithology differentiation, and its success offers a valuable reference for the exploration of other complex hydrocarbon reservoirs in China.