This article is a practical review of the different wave separation methods used in seismic. A wave is described by its propagation vector and its wavelet. The first part of the article shows how the propagation vector can be used to define both the type of propagation (plane or nonplane wave) and the characteristics of the medium (dispersive or faulted medium). Wave separation and wave-type identification can then be dealt with by studying the scalar product between two waves or between a wave and a reference model. The main filtering methods are described, in particular: f-k filtering, tau-p filtering, Karhunen-Loeve filtering and spectral matrix filtering. The efficiency of the different methods is assessed with synthetic data. The problem of extracting a wave from noise is also discussed and illustrated with a field example. The second part will be devoted to wave separation per se. The different methods described in the first part are applied to real data, in particular borehole survey seismic data. Special attention is given to the use of specific, less well-known methods such as spectral matrix filtering with adapted or constrained models.