Independent of the adopted methodology to perform the seismic facies analysis, the geological oriented spatial and temporal segmentation of the reservoir region should be carefully done. Depending on the complexity of the reservoir system, seismic data quality, and the experience of the interpreter, the level of confidence in an interpretation can vary from very high to very low. Therefore, any interpretation error could lead to wrong or noisy results. Specially, when using seismic trace shapes, defined by the values of the seismic samples along each segmented trace, as the seismic input attributes to the chosen seismic facies algorithm. These facies analysis artifacts are introduced because seismic waveform in the reservoir delimited area changes quickly as a function of the interpretation, then waveforms with almost the same shape could be assigned to different classes due only to their different phases. It is known that variations of the frequency content of a seismic trace with time carry information about the properties of the subsurface reflectivity sequence. Consequently, seismic trace time- frequency analyses could provide an unconventional way to reservoir characterization. Specifically, in this work we propose to use the time-frequency properties of the atoms obtained after the matching pursuit signal representation and the singularities identified by wavelet transform, jointly with Self Organizing Maps as an unsupervised seismic facies analyses system.