Xiangfang Zeng

Phase‐Weighted Stacking Applied to Low‐Frequency Earthquakes

Abstract We apply phase‐weighted stacking (PWS) to the analysis of low‐frequency earthquakes (LFEs) in the Parkfield, California, region and central Cascadia. The technique uses the coherence of the instantaneous phase among the stacked signals to enhance the signal‐to‐noise ratio (SNR) of the stack. We find that for picking LFE arrivals for the Parkfield, California, region and for LFE template formation in central Cascadia, PWS is extremely effective. For LFEs in the Parkfield, California, region, PWS yields many more usable phases than standard linear stacking; and, for LFE detection in Cascadia, PWS produces templates with much higher SNR than linear stacking.

Pn Tomographic Velocity and Anisotropy beneath the Iran Region

We present tomographic velocity and anisotropy models of the uppermost mantle beneath the Iran region. A total of 74,375 Pn phase readings from 86 stations of the Iranian network and 133 stations of the International Seismological Centre are used in the investigation. The study uses the Pn travel‐time tomography method proposed by Hearn (1996). The tomography results show some interesting anomalies. The average Pn velocity under the Iran region is approximately 8.0  km/s, and the maximum velocity perturbations are approximately 3%–4%. High Pn velocities under the Zagros Mountains and the Caspian Sea may be due to the presence of oceanic crust/lithosphere material. Low Pn velocities were found under the Alborz and Caucasus regions and may be due to higher temperatures or partial melting resulting from volcanoes and mid‐Cenozoic volcanic/plutonic rocks in these regions. The inversion velocities support the idea that the subduction of the Arabian plate into the mantle beneath the Iranian plateau may have resulted in the upwelling of hot material. The well‐resolved Pn anisotropy model is jointly obtained with a velocity model for the areas with good ray‐path coverage. In the plate collision regions (Zagros and Alborz), the fast Pn anisotropy direction is oriented parallel to the collision arc and to large reverse faults due to pure shear deformation from cross‐fault compression and along‐fault extension. Under the Caucasus regions, the Pn anisotropy results indicate that the preferred alignment of olivine crystals is parallel to the plate movement direction; however, the surface fault strike is at an angle of nearly 45° with the crustal movement direction and anisotropy. These differing deformations suggest potential decoupling between the crust and upper mantle. The possible decoupling and differing deformation between the crust and upper mantle are easily enhanced under high temperatures due to volcanoes and supported by low velocities beneath the Caucasus. We validate the existence of Pn anisotropy under these regions by azimuthal averaging of the apparent Pn velocity.

A Graphics Processing Unit Implementation for Time–Frequency Phase‐Weighted Stacking

Stacking is an efficient approach to increase signal‐to‐noise ratio, which is a key issue in seismic data processing. The time–frequency domain‐ phase weighted stack (tf‐PWS) that uses coherency of instantaneous phase as a weighting function can significantly improve the stacked signal quality of many datasets. A graphics processing unit implementation was developed to reduce the heavy computational cost of tf‐PWS. Synthetic tests suggest the speed‐up factor is up to 20. Our real‐data test shows that the convergence of noise cross‐correlation functions can be substantially improved by tf‐PWS without a computational cost increase.

Focal mechanisms of the Lushan earthquake sequence and spatial variation of the stress field

Using broadband seismic records from regional networks, we determined the focal mechanisms and depths of 37 earthquakes in the 2013 M7.0 Lushan earthquake sequence (3.4⩽Mw⩽5.1) by fitting the three-component waveform data. The results show that the earthquakes are predominantly thrust events, with occasional strike-slip mechanisms. Most earthquakes occurred at depths of 10–20 km. We derived the regional distribution of the average stress field in this area using the damped linear inversion method and the focal mechanisms obtained in this study. The inversion results suggest that the Lushan region and the adjacent area are mostly under compression. The orientations of the maximum principal axes trend NW-SE, with some local differences in the stress distribution at different depths. Compared with the distribution of the stress field in the Wenchuan earthquake area, the stress field in the southwest section of the Longmenshan Fault zone (LFZ) share similar characteristics, predominantly thrust faulting with a few strike-slip events and the maximum compression axes being perpendicular to the LFZ.

Constraining shear wave velocity and density contrast at the inner core boundary with PKiKP/P amplitude ratio

Shear velocity and density contrast across the inner core boundary are essential for studying deep earth dynamics, geodynamo and geomagnetic evolution. In previous studies, amplitude ratio of PKiKP/PcP at short distances and PKiKP/P at larger distances are used to constrain the shear velocity and density contrast, and shear velocity in the top inner core is found to be substantially smaller than the PREM prediction. Here we present a large dataset of PKiKP/P amplitude ratio measured on 420 seismic records at ILAR array in Alaska for the distance range of 80°–90°, where the amplitude ratio is sensitive to shear velocity and density contrast. At high frequency (up to 6 Hz), mantle attenuation is found to have substantial effects on PKiKP/P. After the attenuation effects are taken into account, we find that the density contrast is about 0.2–1.0 g/cm3, and shear velocity of inner core is 3.2–4.0 km/s, close to the PREM (Preliminary Reference Earth Model) prediction (0.6 g/cm3 and 3.5 km/s, respectively). The relatively high shear velocity in inner core does not require large quantities of defects or melts as proposed in previous studies.

Active‐Source Seismic Tomography at the Brady Geothermal Field, Nevada, with Dense Nodal and Fiber‐Optic Seismic Arrays

We deployed a dense seismic array to image the shallow structure in the injection area of the Brady Hot Springs geothermal power plant in western Nevada. The array was composed of 238 threecomponent, 5 Hz nodal instruments, 8700 m of distributed acoustic sensing (DAS) fiber-optic cable (FOC) installed horizontally in surface trenches, and 400 m of FOC installed vertically in a borehole. The geophone array had about 60 m instrument spacing in the target zone, whereas DAS channel separations were about 1 m with an averaging (gauge) length of 10 m. The acquisition systems provided 15 days of continuous records, including active-source and ambient noise signals. A large vibroseis truck was operated at 196 locations, exciting a swept-frequency signal from 5 to 80 Hz over 20 s using three vibration modes (vertical, longitudinal, and transverse), with three sweeps per mode at each site. Sweeps were repeated up to four times at each site during four different stages of power plant operation: normal operation, shutdown, high and oscillatory injection and production, and normal operation. After removal of the sweep signal from the raw data, the first P-wave arrivals were automatically picked using a combination of methods. The travel times were then used to invert for the 3D P-wave velocity structure. Models with 100 m horizontal and 20–50m vertical node spacing were obtained, covering an area 2000 m by 1300 m, with acceptable resolution extending to about 250 m below surface. The travel-time data were fit to a root mean square (rms) misfit of 31 ms, close to our estimated picking uncertainty. Lateral boundaries between high and low velocity zones agree relatively well with the location of local faults from previous studies, and low near-surface velocities are associated with faults and fumarole locations. A sharp increase in velocity from < 1500 to > 2000 m=s at approximately 50 m below the ground surface in many parts of the study area may indicate a shallower water table than expected for the region.