Benchmarking Automated Rayleigh-Wave Arrival Angle Measurements for USArray Seismograms

2021 ◽  
Author(s):  
William D. Frazer ◽  
Adrian K. Doran ◽  
Gabi Laske
Keyword(s):  
Rayleigh Wave ◽  
3D Structure ◽  
Free Fall ◽  
Ocean Bottom ◽  
High Quality ◽  
Arrival Angle ◽  
Geographic Coordinate System ◽  
Seismic Networks ◽  
Arrival Angles ◽  
Wave Arrival

Abstract Surface-wave arrival angles are an important secondary set of observables to constrain Earth’s 3D structure. These data have also been used to refine information on the alignments of horizontal seismometer components with the geographic coordinate system. In the past, particle motion has been inspected and analyzed on single three-component seismograms, one at a time. But the advent of large, dense seismic networks has made this approach tedious and impractical. Automated toolboxes are now routinely used for datasets in which station operators cannot determine the orientation of a seismometer upon deployment, such as conventional free-fall ocean bottom seismometers. In a previous paper, we demonstrated that our automated Python-based toolbox Doran–Laske-Orientation-Python compares favorably with traditional approaches to determine instrument orientations. But an open question has been whether the technique also provides individual high-quality measurements for an internally consistent dataset to be used for structural imaging. For this feasibility study, we compared long-period Rayleigh-wave arrival angles at frequencies between 10 and 25 mHz for 10 earthquakes during the first half of 2009 that were recorded at the USArray Transportable Array—a component of the EarthScope program. After vigorous data vetting, we obtained a high-quality dataset that compares favorably with an arrival angle database compiled using our traditional interactive screen approach, particularly at frequencies 20 mHz and above. On the other hand, the presence of strong Love waves may hamper the automated measurement process as currently implemented.

scholarly journals Observations of Earth’s Normal Modes on Broadband Ocean Bottom Seismometers

2021 ◽  
Vol 9 ◽  
Author(s):  
Gabi Laske
Keyword(s):  
Normal Modes ◽  
Low Frequency ◽  
Free Fall ◽  
Ocean Bottom ◽  
High Quality ◽  
Broadband Seismometer ◽  
The Pacific ◽  
Ocean Bottom Seismometers ◽  
The Pacific Ocean ◽  
First Time

It is generally thought that high noise levels in the oceans inhibit the observation of long-period earthquake signals such as Earth’s normal modes on ocean bottom seismometers (OBSs). Here, we document the observation of Earth’s gravest modes at periods longer than 500 s (or frequencies below 2 mHz). We start with our own 2005–2007 Plume-Lithosphere-Undersea-Mantle Experiment (PLUME) near Hawaii that deployed a large number of broadband OBSs for the first time. We collected high-quality normal mode spectra for the great November 15, 2006 Kuril Islands earthquake on multiple OBSs. The random deployment of instruments from different OBS groups allows a direct comparison between different broadband seismometers. For this event, mode S06 (1.038 mHz) consistently rises above the background noise at all OBSs that had a Nanometrics Trillium T-240 broadband seismometer. We also report observations of other deployments in the Pacific ocean that involved instruments of the U.S. OBS Instrument Pool (OBSIP) where we observe even mode S04 (0.647 mHz). Earth’s normal modes were never the initial target of any OBS deployment, nor was any other ultra-low-frequency signal. However, given the high costs of an OBS campaign, the fact that data are openly available to future investigators not involved in the campaign, and the fact that seismology is evolving to investigate ever-new signals, this paper makes the case that the investment in a high-quality seismic sensor may be a wise one, even for a free-fall OBS.

Seismically Derived Ground Tilts Related to the 2010 Chilean Tsunami

2021 ◽  
Author(s):  
Jui-Chun Freya Chen ◽  
Wu-Cheng Chi ◽  
Chu-Fang Yang
Keyword(s):  
Deep Ocean ◽  
Propagation Model ◽  
Ocean Bottom ◽  
Ocean Bottom Seismometer ◽  
Tsunami Propagation ◽  
Ground Tilt ◽  
Tsunami Waves ◽  
The Pacific ◽  
Seismic Networks ◽  
Back Azimuth

Abstract Developing new ways to observe tsunami contributes to tsunami research. Tidal and deep-ocean gauges are typically used for coastal and offshore observations. Recently, tsunami-induced ground tilts offer a new possibility. The ground tilt signal accompanied by 2010 Mw 8.8 Chilean earthquake were observed at a tiltmeter network in Japan. However, tiltmeter stations are usually not as widely installed as broadband seismometers in other countries. Here, we studied broadband seismic records from Japan’s F-net and found ground tilt signals consistent with previously published tiltmeter dataset for this particular tsunamic event. Similar waveforms can also be found in broadband seismic networks in other countries, such as Taiwan, as well as an ocean-bottom seismometer. We documented a consistent time sequence of evolving back-azimuth directions of the tsunami waves at different stages of tsunami propagation through beamforming-frequency–wavenumber analysis and particle-motion analysis; the outcomes are consistent with the tsunami propagation model provided by the Pacific Tsunami Warning Center. These results shown that dense broadband seismic networks can provide a useful complementary dataset, in addition to tiltmeter arrays and other networks, to study or even monitor tsunami propagation using arrayed methods.

Determination of New Zealand Ocean Bottom Seismometer Orientation via Rayleigh-Wave Polarization

2012 ◽  
Vol 83 (4) ◽  
pp. 704-713 ◽  
Author(s):  
J. C. Stachnik ◽  
A. F. Sheehan ◽  
D. W. Zietlow ◽  
Z. Yang ◽  
J. Collins ◽  
...  
Keyword(s):  
New Zealand ◽  
Rayleigh Wave ◽  
Ocean Bottom ◽  
Ocean Bottom Seismometer ◽  
Wave Polarization ◽  
Seismometer Orientation

Shear attenuation and anelastic mechanisms in the central Pacific upper mantle

2020 ◽  
Author(s):  
Zhitu Ma ◽  
Colleen Dalton ◽  
Joshua Russell ◽  
James Gaherty ◽  
Greg Hirth ◽  
...  
Keyword(s):  
Grain Boundary ◽  
Rayleigh Wave ◽  
Rayleigh Waves ◽  
Plane Waves ◽  
Shear Velocity ◽  
Grain Boundary Sliding ◽  
Absorption Peak ◽  
Ocean Bottom ◽  
Central Pacific ◽  
Transition Depth

<p>We determine the mantle attenuation (1/Q) structure beneath 70 Myr seafloor in the central Pacific. We use long-period (33-100 sec) Rayleigh waves recorded by the NoMelt array of broadband ocean-bottom seismometers. After the removal of tilt and compliance noise, we are able to measure Rayleigh wave phase and amplitude for 125 earthquakes. The compliance correction for ocean wave pressure on the seafloor is particularly important for improving signal-to-noise at periods longer than 55 sec. Attenuation and azimuthally anisotropic phase velocity in the study area are determined by approximating the wavefield as the interference of two plane waves. We find that the amplitude decay of Rayleigh waves across the NoMelt array can be adequately explained using a two-layer model: in the shallow layer, in the deeper layer, and a transition depth at 70 km, although the sharpness of the transition is not well resolved by the Rayleigh wave data. Notably, observed in the NoMelt lithosphere is significantly higher than values in this area from global attenuation models. When compared with lithospheric measured at higher frequency (~3 Hz), the frequency dependence of attenuation is very slight, revising previous interpretations. The effect of anelasticity on shear velocity (V<sub>S</sub>) is estimated from the ratio of observed velocity to the predicted anharmonic value. We use laboratory-based parameters to predict attenuation and velocity-dispersion spectra that result from the superposition of a weakly frequency dependent high-temperature background and an absorption peak. We test a large range of frequencies for the position of the absorption peak (<em>f</em><sub>e</sub>) and determine, at each depth, which values of <em>f</em><sub>e</sub> predict and V<sub>S</sub> that can fit the NoMelt and V<sub>S </sub>values simultaneously. We show that between depths of 60 and 80 km the seismic models require an increase in <em>f</em><sub>e</sub> by at least 3-4 orders of magnitude. Under the assumption that the absorption peak is caused by elastically accommodated grain-boundary sliding, this increase in <em>f</em><sub>e</sub> reflects a decrease in grain-boundary viscosity of 3-4 orders of magnitude. A likely explanation is an increase in the water content of the mantle, with the base of the dehydrated lid located at ~70-km depth.   </p>

scholarly journals Reconstruction of the mass and geometry of snowfall particles frommulti angle snowflake camera (MASC) images

2021 ◽  
Author(s):  
Jussi Leinonen ◽  
Jacopo Grazioli ◽  
Berne Alexis
Keyword(s):  
Total Mass ◽  
3D Structure ◽  
Free Fall ◽  
Maximum Size ◽  
Internal Mass ◽  
Generative Adversarial Network ◽  
Adversarial Network ◽  
Retrieval Algorithms ◽  
Field Campaigns ◽  
Power Law Parameters

Abstract. This paper presents a method named 3D-GAN, based on a generative adversarial network (GAN), to retrieve the total mass, 3D structure and the internal mass distribution of snowflakes. The method uses as input a triplet of binary silhouettes of particles, corresponding to the triplet of stereoscopic images of snowflakes in free fall captured by a Multi-Angle Snowflake Camera (MASC). 3D-GAN is trained on simulated snowflakes of known characteristics whose silhouettes are statistically similar to real MASC observations and it is evaluated by means of snowflake replicas printed in 3D at 1 : 1 scale. The estimation of mass obtained by 3D-GAN has a normalized RMSE (NRMSE) of 40 %, a mean normalized bias (MNB) of 8 % and largely outperforms standard relationships based on maximum size and compactness. The volume of the convex hull of the particles is retrieved with MNRSE of 35 % and MNB of +19 %. In order to illustrate the potential of 3D-GAN to study snowfall microphysics and highlight its complementarity with existing retrieval algorithms, some application examples and ideas are provided, using as showcases the large available datasets of MASC images collected worldwide during various field campaigns. The combination of mass estimates (from 3D-GAN) and hydrometeor classification or riming degree estimation (from independent methods) allows for example to obtain mass-to-size power law parameters stratified on hydrometeor type or riming degree. The parameters obtained in this way are consistent with previous findings, with exponents overall around 2 and increasing with the degree of riming.

scholarly journals Improved Gossypium Raimondii Genome Using a Hi-C-based Proximity-Guided Assembly

2020 ◽  
Author(s):  
Huoli Song ◽  
Qiuhong Yang ◽  
Dongyun Zuo ◽  
Qiaolian Wang ◽  
Hailiang Cheng ◽  
...  
Keyword(s):  
Genome Sequence ◽  
Upland Cotton ◽  
Reference Genome ◽  
3D Structure ◽  
High Quality ◽  
Heat Map ◽  
Gossypium Raimondii ◽  
Guided Assembly ◽  
Structure Research

Abstract Genome sequence plays an important role both in basic and applied studies. Gossypium raimondii, the putative contributor of the D subgenome of Upland cotton (G. hirsutum), highlights the need to improve the genome quality in a rapid and efficient way. Here, we performed Hi-C sequencing of G. raimondii and reassembled its genome based on new Hi-C data and previously published scaffolds. We identified and corrected errors of initial scaffolds before reassembled into chromosomes. In total 98.42% of sequence was clustered successfully, among which 99.72% of the clustered sequence was ordered and 99.92% of the ordered sequence was oriented with high-quality. Further evaluation of results by heat-map and collinearity analysis revealed that the current reassembled genome is significantly improved than previous one. This improvement in G. raimondii genome not only provides a better reference genome to increase study efficiency, but also offers a new way to assemble cotton genomes. Furthermore, Hi-C data of G. raimondii may be used for 3D structure research or regulating analysis.

The value of high-density blended OBN seismic for drilling and reservoir description at the Tangguh gas fields, Eastern Indonesia

2020 ◽  
Vol 39 (8) ◽  
pp. 574-582
Author(s):  
Christopher Birt ◽  
Danang Priyambodo ◽  
Simon Wolfarth ◽  
Johnathan Stone ◽  
Ted Manning
Keyword(s):  
Reservoir Characterization ◽  
Survey Design ◽  
Seismic Energy ◽  
Ocean Bottom ◽  
High Quality ◽  
Eastern Indonesia ◽  
Seismic Image ◽  
Simple Processing ◽  
Reservoir Description ◽  
Gas Fields

The Tangguh gas fields in Eastern Indonesia are overlain by a complex overburden, including a thick, heavily faulted, and intensely karstified carbonate interval that tends to scatter and attenuate seismic energy. Development drilling is challenging, with the potential for pack-offs and stuck pipe when drilling into unstable, partially collapsed caves or karstified fault planes while on total losses. Ideally, these karst features are to be avoided when planning and drilling wells, but avoiding them depends on having a well-resolved seismic image. Historical towed-streamer and sparse ocean-bottom cable seismic is low fold and does not give a satisfactory image for well planning. Advances in ocean-bottom node technology, computer processing, and capacity coupled with efficient survey design and blended acquisition utilizing multiple source vessels allowed a step change in data density. This provided a new high-quality seismic image to support future development activities. The advantages of densely sampled, full-azimuth data include rapid delivery of fast-track products (because high-quality images can be constructed with relatively simple processing flows), greatly improved overburden imaging, and a corresponding uplift in deeper imaging leading to enhanced reservoir characterization.

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