A review of time-frequency analysis for seismic signal
Ding Meng
Tian Lin
Abstract：Time-frequency analysis is vital in seismic data processing,and the need for high-resolution technique is intensifying as exploration advances.This paper traces the evolution of time-frequency methodologies beginning with the inherent limitations of traditional methods,particularly between temporal and spectral resolution.Recent progress is examined along two major fronts:fractional-domain analysis and compressive sensing.Fractional-order methods introduce fractional calculus to achieve more nuanced representation of seismic signals,thereby exposing their complex structural attributes compressive sensing theory uses signal sparsity algorithms optimization to enable efficient re-construction and enhanced time-frequency characterization.In parallel,deep learning has emerged as a transformative tool,offering robust representation and generalization capabilities for sparse analysis,denoising,signal enhancement,and reservoir prediction.These advances mark significant breakthroughs in seismic exploration.This paper concludes with a synthesis of current methodologies and a perspective on future research directions,aiming to provide comprehensive reference for the continued development of seismic exploration technologies.
Keywords：fractional time-frequency analysiscompressed sensingdeep learningseismic signal
Publication Date：2026-01-25
Online Publishing Date：2026-03-03(First online date of this platform, not the publication date of the document)
Pages：9( 1-9 )