一种用于低场核磁共振数据的混合无声化方法
Yongjie Zhao1, Ranhong Xie1, Ke Huang1,2
1State Key Laboratory of Petroleum Resources and Engineering, China University of Petroleum (Beijing), Beijing, 102249, China.
Magnetic resonance letters
|September 8, 2025
概括
一种新的混合方法结合了实证模式分解-单数值分解 (EMD-SVD) 以消除低信号噪声比 (SNR) 核磁共振 (NMR) 数据. 这提高了T2频谱逆转在非传统石油和天然气勘探中的准确性.
科学领域:
- 地质物理学 地质物理学
- 石油工程是石油工程中的一个.
- 信号处理 信号处理
背景情况:
- 低场核磁共振 (NMR) 对于非传统的石油和天然气库勘探至关重要.
- 在NMR回声信号中的低信号噪声比 (SNR) 阻碍了准确的T2频谱反转.
- 有效的无色化对于预处理低SNR NMR数据至关重要.
研究的目的:
- 提出和验证一种混合经验模式分解-单数值分解 (EMD-SVD) 方法,用于否定低SNR NMR数据.
- 为了提高T2频谱逆转在非常规储库中的精度.
- 为了提高NMR日志数据处理的质量.
主要方法:
- 经验模式分解 (EMD) 将NMR回声数据分解为内在模式函数 (IMF) 组件和残余.
- 单一价值分解 (SVD) 应用于国际货币基金组织的高频组件进行无效化.
- 通过对低频IMF,高频IMF和剩余的汇总来重建无效信号.
主要成果:
- 拟议的EMD-SVD方法有效地否定了低SNR的NMR数据.
- 数字模拟,实验数据和NMR日志数据处理证实了该方法的有效性.
- 使用EMD-SVD的倒置NMR光谱与独立的EMD或SVD方法相比显示出更高的质量.
结论:
- 混合EMD-SVD方法为在非传统水库勘探中否定NMR数据提供了显著的改进.
- 这种技术提高了T2频谱反转的可靠性和准确性.
- EMD-SVD方法为石油地质物理学和水库表征提供了有价值的工具.
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