Noise is a never-ending problem for seismic processing due to the complex acquisition environment and loopn processing pipeline. This project tries to alleviate the noise challenge by looking at the intrinsic characteristic of siemsic signal. Signal correaltion and machine-learned dictionaries are studied to find the best space for signal-noise separation of targed seismic sections or images.