This Special Issue is dedicated to emerging research on advanced optimization methods in seismic applications, focusing on seismic signal processing, velocity model building, seismic imaging, and full-waveform inversion (FWI) in complex geological settings.

Areas of interest include, but are not restricted to, developing optimization techniques using model-driven or machine learning-based algorithms for topics such as

• Seismic signal processing and noise suppression
• Sparse regularization and compressed sensing
• Seismic velocity model building
• Uncertainty quantification and uncertainty-aware imaging
• Multi-scale and multi-parameter waveform inversion
• Elastic, anisotropic, and viscoelastic waveform inversion
• Wavefield reconstruction and imaging
• High-performance and distributed computing for inversion
• Reservoir characterization and subsurface property estimation
• Time-lapse (4D) seismic inversion
• Multiphysics and joint inversion methods
• Real-data and field-scale applications in complex media

This Special Issue seeks contributions in the form of original research, novel methodologies, and field applications in optimization-based techniques for seismic signal processing and waveform inversion.