Estimating clean seismic signals from noisy single-channel records is a hot research topic in the field of microseismic data processing. Due to the existence of strong random noise, the signal-to-noise ratio of such data is low, presenting a challenge for signal restoration. In this paper, we propose a denoising method of microseismic data based on a single-channel phase space reconstruction and independent component analysis algorithm. Specifically, we first apply the phase space reconstruction to transform the one-dimensional seismic signal into a high-dimensional phase space in which signal and noise have different trajectories. We then employ independent component analysis to the reconstructed data for noise separation. Experimental results on real microseismic data verify that our proposed denoising method is useful for noise suppression and can enhance the signal-to-noise ratio of data, which can be further used for signal identification and event positioning in microseismic monitoring.

中文翻译：

---

基于单通道相空间重构和独立分量分析算法的微震数据去噪方法

从噪声单道记录中估计干净的地震信号是微地震数据处理领域的热门研究课题。由于强随机噪声的存在，此类数据的信噪比较低，给信号恢复带来了挑战。本文提出一种基于单通道相空间重构和独立分量分析算法的微震数据去噪方法。具体来说，我们首先应用相空间重构将一维地震信号变换到信号和噪声具有不同轨迹的高维相空间。然后，我们对重建数据进行独立分量分析以进行噪声分离。真实微震数据的实验结果验证了我们提出的去噪方法对于噪声抑制是有用的，并且可以提高数据的信噪比，可进一步用于微震监测中的信号识别和事件定位。