Generative wave propagator
📰 ArXiv cs.AI
Learn how to simulate seismic wavefields using a generative wave propagator, improving upon conventional finite-difference methods
Action Steps
- Implement a conditional diffusion-based wavefield propagator to advance seismic wavefields recursively
- Compare the results with conventional finite-difference methods to evaluate numerical dispersion and stability constraints
- Apply the generative wave propagator to real-world seismic data to test its effectiveness
- Configure the propagator to optimize performance for specific seismic wavefield simulations
- Test the propagator's ability to handle complex seismic wavefields and large datasets
Who Needs to Know This
Seismologists and researchers in the field of geophysics can benefit from this new approach to simulate seismic wavefields, enabling more accurate and efficient inversion workflows
Key Insight
💡 The generative wave propagator can efficiently simulate seismic wavefields while reducing numerical dispersion and stability constraints
Share This
🌎 Introducing a generative wave propagator for seismic wavefield simulation! 🚀 Improves upon conventional finite-difference methods 📈 #seismology #geophysics
Key Takeaways
Learn how to simulate seismic wavefields using a generative wave propagator, improving upon conventional finite-difference methods
Full Article
Title: Generative wave propagator
Abstract:
arXiv:2607.04440v1 Announce Type: cross Abstract: Seismic wavefield simulation is fundamental to seismology, but conventional finite-difference (FD) methods remain limited by numerical dispersion and stability constraints, which often require dense spatial grids and small time steps and thereby severely limit the effectiveness of iterative inversion workflows. We introduce a conditional diffusion-based wavefield propagator that advances seismic wavefields recursively from one time step to the ne
Abstract:
arXiv:2607.04440v1 Announce Type: cross Abstract: Seismic wavefield simulation is fundamental to seismology, but conventional finite-difference (FD) methods remain limited by numerical dispersion and stability constraints, which often require dense spatial grids and small time steps and thereby severely limit the effectiveness of iterative inversion workflows. We introduce a conditional diffusion-based wavefield propagator that advances seismic wavefields recursively from one time step to the ne
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