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1. ARRU Phase Picker: Attention Recurrent-Residual U-Net for Picking Seismic P - and S -Phase Arrivals

   https://doi.org/10.1785/0220200382  

   Liao, Wu-Yu; Lee, En-Jui; Mu, Dawei; Chen, Po; Rau, Ruey-Juin (March 2021, Seismological Research Letters)

   null (Ed.)

   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 were 96.72% for P waves and 90.07% for S waves. The ARRU phase picker also shown a great generalization capability, when handling unseen data. When applied the model trained with Taiwan data to the southern California data, the ARRU phase picker shown no cognitive downgrade. Comparing with manual picks, the arrival times determined by the ARRU phase picker shown a higher consistency, which had been evaluated by a set of repeating earthquakes. The arrival picks with less human error could benefit studies, such as earthquake location and seismic tomography. 

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2. Seismic Tomography 2024

   https://doi.org/10.1785/0120230229  

   Fichtner, Andreas; Kennett, Brian_L N; Tsai, Victor C; Thurber, Clifford H; Rodgers, Arthur J; Tape, Carl; Rawlinson, Nicholas; Borcherdt, Roger D; Lebedev, Sergei; Priestley, Keith; et al (May 2024, Bulletin of the Seismological Society of America)

   ABSTRACT Seismic tomography is the most abundant source of information about the internal structure of the Earth at scales ranging from a few meters to thousands of kilometers. It constrains the properties of active volcanoes, earthquake fault zones, deep reservoirs and storage sites, glaciers and ice sheets, or the entire globe. It contributes to outstanding societal problems related to natural hazards, resource exploration, underground storage, and many more. The recent advances in seismic tomography are being translated to nondestructive testing, medical ultrasound, and helioseismology. Nearly 50 yr after its first successful applications, this article offers a snapshot of modern seismic tomography. Focused on major challenges and particularly promising research directions, it is intended to guide both Earth science professionals and early-career scientists. The individual contributions by the coauthors provide diverse perspectives on topics that may at first seem disconnected but are closely tied together by a few coherent threads: multiparameter inversion for properties related to dynamic processes, data quality, and geographic coverage, uncertainty quantification that is useful for geologic interpretation, new formulations of tomographic inverse problems that address concrete geologic questions more directly, and the presentation and quantitative comparison of tomographic models. It remains to be seen which of these problems will be considered solved, solved to some extent, or practically unsolvable over the next decade. 

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3. Tilt Corrections for Normal Mode Observations on Ocean Bottom Seismic Data, an example from the PI-LAB experiment

   https://doi.org/10.26443/seismica.v1i1.196  

   Harmon, Nicholas; Laske, Gabi; Crawford, Wayne; Rychert, Catherine (October 2022, Seismica)

   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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4. 2D Near‐Surface Full‐Waveform Tomography Reveals Bedrock Controls on Critical Zone Architecture

   https://doi.org/10.1029/2023EA003248  

   Eppinger, B. J.; Holbrook, W. S.; Liu, Z.; Flinchum, B. A.; Tromp, J. (February 2024, Earth and Space Science)

   Abstract For decades, seismic imaging methods have been used to study the critical zone, Earth's thin, life‐supporting skin. The vast majority of critical zone seismic studies use traveltime tomography, which poorly resolves heterogeneity at many scales relevant to near‐surface processes, therefore limiting progress in critical zone science. Full‐waveform tomography can overcome this limitation by leveraging more seismic data and enhancing the resolution of geophysical imaging. In this study, we apply 2D full‐waveform tomography to match the phases of observed seismograms and elucidate previously undetected heterogeneity in the critical zone at a well‐studied catchment in the Laramie Range, Wyoming. In contrast to traveltime tomograms from the same data set, our results show variations in depth to bedrock ranging from 5 to 60 m over lateral scales of just tens of meters and image steep low‐velocity anomalies suggesting hydrologic pathways into the deep critical zone. Our results also show that areas with thick fractured bedrock layers correspond to zones of slightly lower velocities in the deep bedrock, while zones of high bedrock velocity correspond to sharp vertical transitions from bedrock to saprolite. By corroborating these findings with borehole imagery, we hypothesize that lateral changes in bedrock fracture density majorly impact critical zone architecture. Borehole data also show that our full‐waveform tomography results agree significantly better with velocity logs than previously published traveltime tomography models. Full‐waveform tomography thus appears unprecedentedly capable of imaging the spatially complex porosity structure crucial to critical zone hydrology and processes. 

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5. Comparison of Automated Seismic Event Detection Approaches in East Antarctica

   Ho, L.; Walter, J.I.; Hansen, S.E.; Peng, Z. (December 2022, 2022 American Geophysical Union Fall Meeting)

   Antarctica is almost completely covered by the world’s largest ice sheet, and its hidden geologic structure partially controls the behavior of the ice layer. Recent advances in geophysical and remote sensing tools have allowed us to observe various transient phenomena, such as tectonic earthquakes, glacial bed slip events, and iceberg calving signals, all of which can be used to investigate solid Earth – cryosphere interactions. We analyzed seismic data collected by the TAMNNET temporary deployment as well as other stations in East Antarctica to identify and locate local icequakes, earthquakes, and other seismic events that occurred between 2012-2015. We employ two event detection approaches. The first is based on phase match filtering and waveform cross-correlation, which uses known events as templates to search through continuous data and to identify similar seismic signals. The second uses EQtransformer, a deep-learning-based event signal detector and phase picker. Event detections identified with both approaches will be compared to assess the effectiveness of these methods in East Antarctica. We also plan to use the combined constraints from our initial approaches to train a new machine-learning model and to assess its performance. Ultimately, our results will be used to evaluate automated event detection approaches for polar environments and to address fundamental questions related to tectonic-cryospheric interactions. 

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