Automatic identification of multiply diffracted waves and their ordered scattering paths.

Area of Science:

• Geophysics
• Acoustics
• Signal Processing

Background:

• Understanding wave propagation in heterogeneous media is crucial for geophysical exploration and imaging.
• Traditional methods often rely on explicit models of the subsurface, which can be limiting in complex environments.
• Multiply scattered acoustic waves contain valuable information but are challenging to isolate and interpret.

Purpose of the Study:

• To develop an automated algorithm for analyzing multiply scattered acoustic waves.
• To estimate wave arrival times, scattering order, and diffractor sequences without a predefined medium model.
• To enable the identification of multiply diffracted waves of any order in recorded acoustic data.

Main Methods:

• Utilizes recordings from a spatially distributed acoustic array.
• Identifies individual diffractors using single-scattering relative travel-time curves (move-outs).
• Employs semblance analysis on temporally offset primary move-outs to detect twice-scattered waves.

Main Results:

• The algorithm successfully estimates travel times and scattering paths for multiply diffracted waves.
• It can identify these complex wave events within recorded data.
• Demonstrated effectiveness on synthetic datasets with varying heterogeneity and non-hyperbolic move-outs.

Conclusions:

• The developed automated algorithm provides a robust method for analyzing multiply scattered acoustic waves.
• It overcomes the limitations of model-dependent approaches in heterogeneous media.
• This technique enhances the capability to extract detailed information from acoustic wave propagation data.