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AIC-based diffraction stacking for local earthquake locations at the Sumatran Fault (Indonesia)
(2018)
We present a new workflow for the localization of seismic events which is based on a diffraction stacking approach. In order to address the effects from complex source radiation patterns, we suggest to compute diffraction stacking from a characteristic function (CF) instead of stacking the original waveform data. A new CF, which is called in the following mAIC (modified from Akaike Information Criterion) is proposed. We demonstrate that both P- and S-wave onsets can be detected accurately. To avoid cross-talk between P and S waves due to inaccurate velocity models, we separate the P and S waves from the mAIC function by making use of polarization attributes. Then, the final image function is represented by the largest eigenvalue as a result of the covariance analysis between P-and S-image functions. Results from synthetic experiments show that the proposed diffraction stacking provides reliable results. The workflow of the diffraction stacking method was finally applied to local earthquake data from Sumatra, Indonesia. Recordings from a temporary network of 42 stations deployed for nine months around the Tarutung pull-apart basin were analysed. The seismic event locations resulting from the diffraction stacking method align along a segment of the Sumatran Fault. A more complex distribution of seismicity is imaged within and around the Tarutung basin. Two lineaments striking N-S were found in the centre of the Tarutung basin which support independent results from structural geology.