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October 3, 2025Open Access

Noise is All You Need: rethinking the value of noise on seismic denoising via diffusion models

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Authors

DZDonglin ZhuPLPeiyao LiGJGe Jin

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Overview

Diffusion models improve seismic denoising performance in field data, suggesting noise modeling advantages.

Key Points

  • The novel SeisDiff-denoNIA framework shows strong performance in seismic denoising, particularly under low SNR conditions.
  • Results indicate that leveraging field noise as training data significantly enhances noise distribution learning.
  • The diffusion model outperformed traditional methods when tested on field DAS-VSP data contaminated by various noise types.
  • This approach highlights the viability of modeling noise directly, presenting a shift from reliance on synthetic datasets.

Cite This Study

Zhu et al. (2025) studied this question.

synapsesocial.com/papers/68e034f7f0e39f13e7fa2fc5https://doi.org/10.48550/arxiv.2509.03629
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