Abstract Seismograms are convolution results between seismic sources and the media that seismic waves propagate through, and, therefore, the primary observations for studying seismic source parameters and the Earth interior. The routine earthquake location and travel-time tomography rely on accurate seismic phase picks (e.g., P and S arrivals). As data increase, reliable automated seismic phase-picking methods are needed to analyze data and provide timely earthquake information. However, most traditional autopickers suffer from low signal-to-noise ratio and usually require additional efforts to tune hyperparameters for each case. In this study, we proposed a deep-learning approach that adapted soft attention gates (AGs) and recurrent-residual convolution units (RRCUs) into the backbone U-Net for seismic phase picking. The attention mechanism was implemented to suppress responses from waveforms irrelevant to seismic phases, and the cooperating RRCUs further enhanced temporal connections of seismograms at multiple scales. We used numerous earthquake recordings in Taiwan with diverse focal mechanisms, wide depth, and magnitude distributions, to train and test our model. Setting the picking errors within 0.1 s and predicted probability over 0.5, the AG with recurrent-residual convolution unit (ARRU) phase picker achieved the F1 score of 98.62% for P arrivals and 95.16% for S arrivals, and picking rates weremore »
Twenty-Thousand Leagues Under the Sea: Recording Earthquakes with Autonomous Floats
Much like medical doctors who use X-rays or acoustic waves to make three-dimensional images of our insides, geophysicists use the elastic wavefield generated by earth- quakes worldwide to scan the deep interior of our planet for subtle contrasts in the propagation speeds of seismic waves. To image the deep Earth using seismic tomography, over the years, seismologists have densely covered the continents with seismometers to measure ground motion. As with medical tomography, where sources and detectors are rotated all around to illuminate our bodies from all angles, achieving similarly evenly distributed geographical coverage for seismology requires making measurements all over the Earth surface, including the two-thirds that are covered by oceans. Yet, although some ocean islands do host geophysical observatories, gathering data over marine areas continues to present unique challenges.
- Award ID(s):
- 1917058
- Publication Date:
- NSF-PAR ID:
- 10249197
- Journal Name:
- Acoustics today
- Volume:
- 17
- Issue:
- 2
- Page Range or eLocation-ID:
- 42-51
- ISSN:
- 1557-0215
- Sponsoring Org:
- National Science Foundation
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Earth's normal modes are fundamental observations used in global seismic tomography to understand Earth structure. Land seismic station coverage is sufficient to constrain the broadest scale Earth structures. However, 70% of Earth's surface is covered by the oceans, hampering our ability to observe variations in local mode frequencies that contribute to imaging small-scale structures. Broadband ocean bottom seismometers can record spheroidal modes to fill in gaps in global data coverage. Ocean bottom recordings are contaminated by signals from complex interactions between ocean and solid Earth dynamics at normal mode frequencies. We present a method for correcting tilt on broadband ocean bottom seismometers by rotation. The correction improves the ability of some instruments to observe spheroidal modes down to 0S4. We demonstrate this method using 15 broadband ocean bottom seismometers from the PI-LAB array. We measure normal mode peak frequency shifts and compare with 1-D reference mode frequencies and predictions from 3-D global models. Our measurements agree with the 3-D models for modes between 0S14 - 0S37 with small but significant differences. These differences likely reflect real Earth structure. This suggests incorporating ocean bottom normal mode measurements into global inversions will improve models of global seismic velocity structure.
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SUMMARY In previous publications, we presented a general framework, which we called ‘box tomography’, that allows the coupling of any two different numerical seismic wave propagation solvers, respectively outside and inside a target region, or ‘box’. The goal of such hybrid wavefield computations is to reduce the cost of computations in the context of full-waveform inversion for structure within the target region, when sources and/or receivers are located at large distances from the box. Previously, we had demonstrated this approach with sources and receivers outside the target region in a 2-D acoustic spherical earth model, and demonstrated and applied this methodology in the 3-D spherical elastic Earth in a continental scale inversion in which all stations were inside the target region. Here we extend the implementation of the approach to the case of a 3-D global elastic earth model in the case where both sources and stations are outside the box. We couple a global 3-D solver, SPECFEM3D_GLOBE, for the computation of the wavefield and Green’s functions in a reference 3-D model, with a regional 3-D solver, RegSEM, for the computation of the wavefield within the box, by means of time-reversal mirrors. We briefly review key theoretical aspects, showing inmore »
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Seismic waves in earth media usually undergo attenuation, causing energy losses and phase distortions. In the regime of high-frequency asymptotics, a complex-valued eikonal is an essential ingredient for describing wave propagation in attenuating media, where the real and imaginary parts of the eikonal function capture dispersion effects and amplitude attenuation of seismic waves, respectively. Conventionally, such a complex-valued eikonal is mainly computed either by tracing rays exactly in complex space or by tracing rays approximately in real space so that the resulting eikonal is distributed irregularly in real space. However, seismic data processing methods, such as prestack depth migration and tomography, usually require uniformly distributed complex-valued eikonals. Therefore, we have developed a unified framework to Eulerianize several popular approximate real-space ray-tracing methods for complex-valued eikonals so that the real and imaginary parts of the eikonal function satisfy the classic real-space eikonal equation and a novel real-space advection equation, respectively, and we dub the resulting method the Eulerian partial-differential-equation method. We further develop highly efficient high-order methods to solve these two equations by using the factorization idea and the Lax-Friedrichs weighted essentially nonoscillatory schemes. Numerical examples demonstrate that our method yields highly accurate complex-valued eikonals, analogous to those from ray-tracing methods.more »
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Accepted Manuscript1.0
- Publisher's Version of Record
- https://doi.org/10.1121/AT.2021.17.2.42
