Year: 2026
Type: article
Abstract: Conventional seismic data often suffer from narrow bandwidth and limited resolution due to subsurface absorption and acquisition constraints, hindering the precise characterization of thin-interbedded reservoirs and subtle lithologic traps. Traditional compressed sensing-based bandwidth extension methods typically employ $$L_{1}$$ norm regularization and soft-thresholding operators. However, these approaches often exhibit a “constant bias” defect, which complicates the balance between noise suppression and amplitude fidelity. Furthermore, the Fast Iterative Soft-Thresholding Algorithm (FISTA) is prone to convergence oscillations, leading to increased computational overhead. To address these challenges, this study proposes a seismic bandwidth extension method based on a Restarted FISTA framework. This study introduce a non-convex “limited shrinkage” thresholding operator, categorized into three functional zones—denoising, transition, and amplitude preservation—to optimize the trade-off between noise attenuation and signal fidelity. Concurrently, a restart mechanism is integrated to stabilize the convergence trajectory and mitigate momentum-induced oscillations. Numerical simulations and field data applications demonstrate that the proposed method achieves faster convergence with fewer iterations than standard FISTA. Moreover, the method yields a lower normalized root-mean-square error (NRMSE) under noisy conditions. Field results confirm a significant broadening of the effective frequency range while maintaining physical amplitude consistency.
Source: Scientific Reports
Language: English
Subfield: Geophysics
Field: Earth and Planetary Sciences
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,690
Funder: PetroChina Company Limited
OpenAlex ID: W7204194875
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