An Energy-Adaptive Chirp-Enhanced W-Transform Incorporating Chirp-Compensating Phase Modulation for High-Resolution Seismic Time-Frequency Analysis

Seismic signals display nonstationary properties essential for characterizing subsurface formations, including fluid saturation, lithological variations, and structural details. Conventional time-frequency analysis techniques often yield suboptimal resolution due to energy dispersion and inadequate adaptation to signal complexity. The W-transform addresses some limitations by dynamically adjusting the Gaussian window to dominant frequencies, but challenges persist in achieving optimal performance across diverse signal conditions. A chirp-enhanced W-transform (CEWT) advances this approach by integrating energy-based window refinement and adaptive phase modulation to better capture local nonstationarity. This framework produces more concentrated time-frequency representations, enhances robustness to noise, and enables accurate signal reconstruction. Synthetic tests involving Morlet wavelets, Ricker wavelet pairs, and noise-contaminated traces validate CEWT's superior performance in resolution and efficiency compared to standard and normalized W-transforms. Real-world applications on a marine dataset from the South Caspian Sea highlight improved low-frequency shadow detection for hydrocarbon indicators, while an onshore profile from the Dagang oil field demonstrates enhanced reservoir characterization through sharper iso-frequency sections and RGB composites, outperforming existing methods in anomaly delineation and stratigraphic imaging.