Understanding the fundamental concepts of data processing and inverse theory and being able to put these concepts into practice.
Geophysics often requires the analysis of measured data. Raw data can hide the specific information one is interested in and prior data processing is necessary. We will review the fundamentals of geophysical data processing, starting with a detailed description of how to sample continuous functions, then progressing to the corresponding discrete Fourier transform. We will introduce the important concept of convolution and present linear filter theory. In the following, simple linear inverse theory will be discussed and the classical least squares and minimum norm problem will be introduced. We will show how to design optimal filters using basic inverse theory. During the course and computer practicals, examples will be taken from various fields of geophysics.