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对于DAS-VSP数据解散的扩散模型
Donglin Zhu1, Lei Fu1, Vladimir Kazei1
1Aramco Americas-Houston Research Center, Houston, TX 77084, USA.
Sensors (Basel, Switzerland)
|October 28, 2023
概括
本研究介绍了扩散模型,用于消除分布式声学传感 (DAS) 垂直地震概况 (VSP) 数据的噪声. 这种新方法有效地消除了地震数据中的噪声,同时保持了信号完整性.
科学领域:
- 地质物理学 地质物理学
- 获取地震数据的方法
- 信号处理 信号处理
背景情况:
- 分布式声学传感 (DAS) 是地震数据采集的关键技术.
- DAS数据中的噪声阻碍了精确的地震分析,需要先进的无声化方法.
研究的目的:
- 率先应用扩散模型来消除DAS垂直地震概况 (VSP) 数据的噪声.
- 评估扩散模型在合成和现场DAS-VSP数据集中抑制噪声的有效性.
主要方法:
- 在一个合成数据集上训练了一个扩散模型,具有各种采集参数.
- 训练有素的扩散网络被应用到合成和现场DAS-VSP数据中.
主要成果:
- 扩散模型有效地抑制了DAS-VSP数据中的各种噪音类型.
- 该方法表明信号泄漏最小,并且性能优于传统的无噪技术.
结论:
- 扩散模型显示了增强DAS数据处理的巨大潜力.
- 这种方法为提高使用DAS获得的地震数据质量提供了一个有希望的解决方案.
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