Abstract
The separation of signal and noise is a central issue in seismic data processing. The noise is both random and coherent in nature, the coherent part often masquerading as signal. In this tutorial, we present some approaches to 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 transforms. We end with the notion of risk, baseball, and the Stein estimator.
This content is PDF only. Please click on the PDF icon to access.
You do not have access to this content, please speak to your institutional administrator if you feel you should have access.
