Signal and noise separation: Art and science

The separation of signal and noise is a central issue in seismic data proce ssing. The noise is both random and coherent in nature, the coherent part o ften masquerading as signal. In this tutorial, we present some approaches t o signal isolation, in which stacking is a central concept. Our methodology is to transform the data to a domain where noise and signal are separable, a goal that we attain by means of inversion. We illustrate our ideas with some of our favorite transformations: wavelets, eigenvectors, and Radon tra nsforms. We end with the notion of risk, baseball, and the Stein estimator.