Cauchy Norm-Constrained Nonstationary High-Resolution Processing for Seismic Data

Due to the intrinsic Q attenuation of geological formations, seismic waves experience amplitude and frequency attenuation during propagation, which results in reduced resolution and pronounced discrepancies between shallow and deep seismic data. Specifically, deep reflections exhibit weakened amplitudes and diminished high-frequency content. To mitigate these effects, a Q-compensation method based on nonstationary inversion is proposed to enhance seismic resolution and improve vertical consistency. A nonstationary reflectivity inversion framework is first established using a nonstationary convolution model with Cauchy norm regularization. The formation quality factor (Q) is then estimated from seismic data via the spectral ratio method using selected shallow and deep time windows. By incorporating the estimated Q value and an initial seismic wavelet, the proposed inversion simultaneously compensates for Q attenuation and wavelet effects, yielding a high-resolution reflectivity series. Q-compensated seismic data are subsequently reconstructed through the convolution of this reflectivity and an appropriate seismic wavelet. Both the model test and the field data application results demonstrate that the proposed method effectively compensates for Q attenuation, significantly enhances seismic resolution, and restores amplitude and frequency consistency between shallow and deep data.