Characterization of seismic waveforms and classification of seismic events using chirplet atomic decomposition. Example from the Lacq gas field (Western Pyrenees, France)

SUMMARY In the present paper, we present a generalization of the wavelet transform, known as chirplet transform, specially designed to quantify the morphological attributes of individual seismic sections (packets) constituting the seismic waveforms. The proposed transform relies on an atomic decomposition of individual seismograms based on local multiscale chirps (swept frequency wave packets) of various shape and duration. We developed an algorithm that provides an optimal representation of the waveform packets in terms of (i) arrival time, (ii) central frequency, (iii) modulus, (iv) phase, (v) duration, (vi) envelope shape and (vii) frequency modulation compacting the information contained in each seismogram into a reduced set of parameters particularly well suited to describe seismic waveforms. In the present work, we focus on the ability of atomic decomposition to classify seismic events. We illustrate the developed methodology and resulting hierarchical classification scheme (agglomerative clustering displayed as a dendrogram) to seismograms of the induced seismicity recorded in the Lacq gas field between 1989 and 1997 by a local seismic network. For the present case-study, the resulting classification reveals different levels of similarity between seismic events of a same swarm. Accurate analysis of the subsequences of seismic events associated to an injection well shows temporal changes in the morphological attributes of the recorded seismic waveforms. These changes are highly correlated with water over-pressure records of the reservoir demonstrating the capability of the method to guide investigation of the underlying processes (properties of propagation media, source, rupture processes), and in a general manner the physical properties of the reservoir.