摘要：It is an important research topic in the field of microseismic data to estimate clean seismic event signals from noisy single-channel records. This is also essential in other applications including the identification and positioning of events. Due to the low signal-to-noise ratio (SNR) of microseismic data, denoising processing is an indispensable procedure. In this paper, we present a novel denoising technique for SNR enhancement of microseismic data based on a local projection (LP) algorithm. Using the LP algorithm, a one-dimensional seismic signal can be processed to form a high-dimensional phase space in which signal and noise have different attractor orbits. Utilizing these different distribution characteristics, we can achieve denoising by reconstructing the phase space of the signal. The LP algorithm requires the determination of three key parameters: embedding dimension, delay time and neighborhood radius. We implement an estimation method for these three parameters for the local projection denoising (LPD) method, and a real field data processing workflow is achieved. Using the LPD method, a synthetic seismic trace with different SNR level is applied to test the validity of the proposed denoising method. Results from the synthetic example indicate that weak signals can be recovered from amongst strong ambient noises. Furthermore, an application to field microseismic data verifies that the proposed method can significantly suppress noise and hence enhance the SNR of data. The denoised data can be further used for signal recognition and event positioning in microseismic monitoring.

关键字：denoising local projection signal-to-noise ratio (SNR) microseismic data phase space reconstruction

ISSN号：1742-2132

卷、期、页：卷: 15 期: 6

发表日期：2018-12-01

影响因子：0.994000

期刊分区（SCI为中科院分区）：四区

收录情况：SCIE（科学引文索引网络版）,ESI（基本科学指标数据库）

发表期刊名称：Journal of Geophysics and Engineering

参与作者：Zhong, Qingliang

通讯作者：孟会杰

第一作者：陈双全,李向阳

论文类型：期刊论文

论文概要：陈双全,孟会杰,Zhong, Qingliang,李向阳，Microseismic data SNR enhancement using local projection denoising method，Journal of Geophysics and Engineering，2018，卷: 15 期: 6

论文题目：Microseismic data SNR enhancement using local projection denoising method