11:00 AM - 11:15 AM
[SSS09-02] Estimation of subsurface motion from surface seismic records (3): introduction of an empirical formula for the evaluation at any depth
Keywords:seismic motion, plane wave, strong motion, subsurface wavefield
Subsurface seismic motion or incident wavefield on the bedrock level is needed to evaluate the response of buildings and the seismic stability of the shallow sedimentary structure through numerical simulation of seismic wave propagation. It is conventional that the subsurface motion is estimated from a seismic record at a free surface position assuming a vertical plane-wave incidence, which means that the vertical and horizontal components of the seismic waves independently propagate as P-wave and S-wave, respectively, so this assumption is theoretically incorrect. We proposed a new method to evaluate subsurface wavefields from a surface record without the assumption of plane-wave incidence (Takenaka et al., 2019, SSJ Fall meeting). Our method uses the effective source time function (ESTF), which is extracted from a surface record, to evaluate the subsurface motion. Therefore, we have investigated the shape of the window function that extracts the ESTF by quantifying the difference between the actual subsurface records and the estimated motions (Watanabe et al., 2020, JpGU; Watanabe et al., 2021, JpGU; Watanabe et al., 2022, JpGU). In this study, we construct an empirical formula of the window function for the evaluation at arbitrary depth.
Our method uses a horizontally-layered model including both the station and the source. We calculate synthetic seismograms assuming the focal mechanism and impulsive source at the surface and the subsurface points. We then deconvolve the surface record with the surface synthetic seismogram after synchronizing them by matching the S wave arrivals each other. This deconvolved waveform includes the actual source time function around 0 sec and the effect due to the difference between the structural model and real structure. We employ the window function, which has a peak at 0 sec and long side lobes extensively in the time domain, to extract the ESTF. The amplitude of the side robes corresponds to that of the part of later phases of the estimated waveform. Finally, we convolve the ESTF with the subsurface synthetic seismogram to derive the target motion or incident wave at the evaluation point.
Applying to surface records at five stations with different depth subsurface receivers, we found that an appropriate shape of the window function is controlled by both the seismic velocity and depth at the evaluation point. For instance, we need to use the window function with small amplitudes in its side lobes when we try to evaluate subsurface wavefields at the bedrock level. We formulate the window function through trial and error to estimate the appropriate motions at any depth. Fig. 1 is an application example to surface records at KiK-net station OSKH05, NIED of the Mj 5.1 event occurring in the Nara Prefecture on July 21, 2010 at depth of 65 km with an epicentral distance 59 km. Fig. 1(a) shows the extraction of the ESTF from the deconvolved waveforms using the proposed window function. Fig. 1(b) illustrates the subsurface motion observed and estimated by our method and conventional one assuming vertical plane-wave incidence. The misfit values indicate that the estimated waveforms by our method can recover the observed ones better than by the conventional method. We check the feasibility of our method applied to records at other stations.
Our method uses a horizontally-layered model including both the station and the source. We calculate synthetic seismograms assuming the focal mechanism and impulsive source at the surface and the subsurface points. We then deconvolve the surface record with the surface synthetic seismogram after synchronizing them by matching the S wave arrivals each other. This deconvolved waveform includes the actual source time function around 0 sec and the effect due to the difference between the structural model and real structure. We employ the window function, which has a peak at 0 sec and long side lobes extensively in the time domain, to extract the ESTF. The amplitude of the side robes corresponds to that of the part of later phases of the estimated waveform. Finally, we convolve the ESTF with the subsurface synthetic seismogram to derive the target motion or incident wave at the evaluation point.
Applying to surface records at five stations with different depth subsurface receivers, we found that an appropriate shape of the window function is controlled by both the seismic velocity and depth at the evaluation point. For instance, we need to use the window function with small amplitudes in its side lobes when we try to evaluate subsurface wavefields at the bedrock level. We formulate the window function through trial and error to estimate the appropriate motions at any depth. Fig. 1 is an application example to surface records at KiK-net station OSKH05, NIED of the Mj 5.1 event occurring in the Nara Prefecture on July 21, 2010 at depth of 65 km with an epicentral distance 59 km. Fig. 1(a) shows the extraction of the ESTF from the deconvolved waveforms using the proposed window function. Fig. 1(b) illustrates the subsurface motion observed and estimated by our method and conventional one assuming vertical plane-wave incidence. The misfit values indicate that the estimated waveforms by our method can recover the observed ones better than by the conventional method. We check the feasibility of our method applied to records at other stations.