摘要
基于非下采样shearlet变换的微地震资料去噪方法,相比于其他多尺度变换方法具有更好的方向敏感性和最优稀疏表示性能,具有更强的去除随机噪声的能力,信号保真度更好。同时较传统的shearlet变换具有平移不变性,克服了伪吉布斯现象。利用非下采样shearlet变换阈值去噪法与小波和曲波阈值变换方法对微地震仿真和实际资料的随机噪声的压制进行对比分析,结果表明非下采样shearlet变换具有更好的去噪能力。
Microseismic random noise attenuation based on non-subsampled shearlet transform is proposed, compared to other multi-scale transform method, it has better direction sensitivity, optimal sparse representation, stronger ability to remove the random noise and signal fidelity is better. At the same time, it has the translation invariance and eliminates the pseudo gibbs phenomenon. Random noise suppression of microseismic simulation and real data are analyzed by using the non-subsampled shearlet transform, wavelet and curvelet transform threshold denoising method. Results show that the sampling shearlet transform has better denoising ability.
出处
《煤炭技术》
CAS
北大核心
2016年第1期128-129,共2页
Coal Technology
基金
国家自然科学基金项目(41074074)
作者简介
刘昕（1989-），吉林公主岭人，硕士研究生，主要从事微地震噪声压制研究．电子信箱：liu_x512@163.com
