Recordings of the Earth’s surface oscillation (seismograms) can be sonified such that most of the signal’s frequency spectrum falls in the audible range. Then, the pattern-recognition capabilities of the human auditory system can be applied to auditory analysis of seismic data. We sonify seismograms associated with a magnitude 5.6 earthquake. A group of volunteers listen to our sonified data set via headphones and software allowing them to reproduce each signal as many times as they want by clicking on the corresponding icon. Following the “free categorization” approach, listeners are asked to group icons corresponding to sounds perceived as “similar.” The goal of this test is to determine whether the human auditory system can perceive relevant “clues” in sonified seismograms, and whether humans can group such stimuli accordingly. Our results suggest that this is indeed the case, and allow us to identify at least one categorization strategy followed by the majority of listeners, which suggests that auditory analysis of seismic data is feasible and possibly useful. Our findings encourage further work, where we plan to take advantage of recent progress in auditory scene synthesis algorithms and spatial audio technology.