A physics-informed deep learning method for dispersive processing of borehole dipole wave data using synthetic dataset

Key Points

• The method enhances the processing of borehole dipole wave data with notable accuracy.
• Key performance metrics indicate a significant improvement over traditional processing methods.
• Analysis employs a physics-informed deep learning framework to model wave data effectively.
• This approach suggests potential advancements for subsurface investigations in geophysics.