5:15 PM - 7:15 PM
[STT42-P03] Focal mechanism estimation using Distributed Acoustic Sensing: A comparative analysis of S/P amplitude ratios and polarity flips
A focal mechanism represents the movement of a fault during an earthquake rupture and provides valuable insights into the physical mechanisms, as well as details regarding the surrounding structure, including the fault geometry and stress fields. Focal mechanisms are determined from observed seismic waves. These mechanisms can be derived from the moment tensor solutions for moderate to large earthquakes. For smaller earthquakes (M<4), we can primarily obtain only the first motion mechanisms, and the accuracy of mechanisms that utilize these methods depend on the coverage of seismic stations and the quality of the data acquired. These involve large uncertainties in estimating the parameters, particularly for very small events, due to unclear initial motion and limited data availability.
Distributed acoustic sensing (DAS) is a novel technology for earthquake observation. A DAS-interrogator unit measures the strain or strain rate along a fiber optic cable by sending laser pulses into the cable and measuring the phase changes in the Rayleigh backscattered signals caused by intrinsic fiber-cable impurities. Unlike conventional seismic sensors that monitor specific points, DAS measures the strain or strain rate along sections of the cable with a given gauge length. For example, by measuring a 50 km cable buried underground at 5 m intervals, we can gather ground motion data equivalent to 10,000 individual sensor deployments.
We proposed a method for estimating focal mechanisms using a large number of observation channels based on S/P maximum amplitude ratios from DAS records [Funabiki & Miyazawa, 2024, SSJ meeting]. We successfully determined the mechanisms of four shallow earthquakes in central Japan, with magnitudes ranging from M2.2 to 3.4. The estimated mechanisms were consistent with P-wave initial motion distribution from seismic networks, relocated hypocenters of earthquake sequence using the waveform correlation of DAS records, and the stress fields in this region.
A previous study estimated the focal mechanism from the polarity of DAS records. Li et al. (2023) introduced a method for identifying the P-wave polarity of each channel by obtaining relative polarities through cross-correlation of P-waveforms between the same and adjacent DAS channels for each event pair, solving the observation equation for the polarities at each channel for each event, and using first motions of P-waves picked by conventional seismic stations. During this process, DAS records are used only to correlate, and this process estimates not the absolute polarity but the "channel-consistent" relative polarity. Therefore, their method primarily identifies "which channels exhibit polarity flips and where the nodal line is located." The precision of this approach is one of its key advantages.
To test our method using S/P amplitude ratio, we obtained the relative polarity following approach for the events, whose focal mechanisms were estimated from S/P amplitude ratio of DAS records, and determined the channel in which polarity-flips occur. The polarity-flips identified by the method of Li et al. (2023) support the polarity-flips inferred from our methods, while several polarity-flips obtained by their methods do not align with ours, which may not be attributed to the focal mechanism. Moreover, an interesting difference of several hundred channels exists for the M2.2 & M3.4 event, between the polarity-flips and the nodal line estimated from the S/P amplitude ratio. We will discuss why this difference occurs.
Distributed acoustic sensing (DAS) is a novel technology for earthquake observation. A DAS-interrogator unit measures the strain or strain rate along a fiber optic cable by sending laser pulses into the cable and measuring the phase changes in the Rayleigh backscattered signals caused by intrinsic fiber-cable impurities. Unlike conventional seismic sensors that monitor specific points, DAS measures the strain or strain rate along sections of the cable with a given gauge length. For example, by measuring a 50 km cable buried underground at 5 m intervals, we can gather ground motion data equivalent to 10,000 individual sensor deployments.
We proposed a method for estimating focal mechanisms using a large number of observation channels based on S/P maximum amplitude ratios from DAS records [Funabiki & Miyazawa, 2024, SSJ meeting]. We successfully determined the mechanisms of four shallow earthquakes in central Japan, with magnitudes ranging from M2.2 to 3.4. The estimated mechanisms were consistent with P-wave initial motion distribution from seismic networks, relocated hypocenters of earthquake sequence using the waveform correlation of DAS records, and the stress fields in this region.
A previous study estimated the focal mechanism from the polarity of DAS records. Li et al. (2023) introduced a method for identifying the P-wave polarity of each channel by obtaining relative polarities through cross-correlation of P-waveforms between the same and adjacent DAS channels for each event pair, solving the observation equation for the polarities at each channel for each event, and using first motions of P-waves picked by conventional seismic stations. During this process, DAS records are used only to correlate, and this process estimates not the absolute polarity but the "channel-consistent" relative polarity. Therefore, their method primarily identifies "which channels exhibit polarity flips and where the nodal line is located." The precision of this approach is one of its key advantages.
To test our method using S/P amplitude ratio, we obtained the relative polarity following approach for the events, whose focal mechanisms were estimated from S/P amplitude ratio of DAS records, and determined the channel in which polarity-flips occur. The polarity-flips identified by the method of Li et al. (2023) support the polarity-flips inferred from our methods, while several polarity-flips obtained by their methods do not align with ours, which may not be attributed to the focal mechanism. Moreover, an interesting difference of several hundred channels exists for the M2.2 & M3.4 event, between the polarity-flips and the nodal line estimated from the S/P amplitude ratio. We will discuss why this difference occurs.