Optimization of the Match‐Filtering Method for Robust Repeating Earthquake Detection: The Multisegment Cross‐Correlation Approach

Waveform match‐filtering (MF), based on cross‐correlation between an earthquake pair, is a powerful and widely used tool in seismology. However, its performance can be severely affected by several factors, including the length of the cross‐correlation window, the frequency band of the applied digital filter, and the presence of a large‐amplitude phase(s). To optimize the performance of MF, we first systematically examine the effects of different operational parameters and determine the generic rules for selecting the window length and the optimal frequency passband. To minimize the influence of a large‐amplitude phase(s), we then propose a new approach, namely, MF with multisegment cross‐correlation (MFMC). By equally incorporating the contributions from various segments of the waveforms, this new approach is much more sensitive to small separation between two sources compared to the conventional MF method using the entire waveform template. To compare the reliability and effectiveness of both methods in capturing interevent source separation and identifying repeating earthquakes, we systematically conduct experiments with both synthetic data and real observations. The results demonstrate that the conventional MF method can detect the existence of an event but sometimes lacks the resolution to tell whether the template and detected events are co‐located or not, whereas MFMC works in all cases. The far‐reaching implication from this study is that inferring source separation between an earthquake pair based on the conventional MF method, particularly with data from a single channel/station, may not be reliable.