【摘要】 在研究地震勘探中,随机噪声是一种频带较宽的干扰波,常规的去噪方法效果不理想。为对方位提高识别能力,首先根据具有多尺度与多方向性的Curvelet变换的基本原理及其实现方法。采用块阈值法应用于地震数据随机噪声衰减中,并进行了仿真计算和实际资料的处理。结果证明利用Curvelet变换块阈值法能比较彻底地去除噪声,去噪后的图像边缘保持良好,滤除噪声同时还保留了有效部分,去噪效果良好,具有小波变换无可比拟的优势,且易于实现,在地震资料处理中具有一定的可行性和应用价值。更多还原

【Abstract】 In the seismic exploration,random noise is a wide band disturbing wave,which is not ideal when denoised by conventional means. The basic principle and realization of curvelet transform,which has multi-scale and multi-direction characteristics,were introduced. And it was applied in the random noise decaying of seismic data by adopting lump threshold,and in the simulation and real data processing. The result proved that curvelet transform can relatively completely remove the noise while the edge of picture kept well and the detail part also kept at the same time. The result of noise decaying was good and better than wavelet and easy to realize,so that curvelet transform has the feasibility and prospect in the seismic data processing.更多还原