MétaCan
Menu
Back to cohort
Record W2152740009 · doi:10.1093/gji/ggt165

On acoustic waveform tomography of wide-angle OBS data--strategies for pre-conditioning and inversion

2013· article· en· W2152740009 on OpenAlex
R. Kamei, R. G. Pratt, Takeshi Tsuji

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueGeophysical Journal International · 2013
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicSeismic Imaging and Inversion Techniques
Canadian institutionsWestern University
Fundersnot available
KeywordsGeologySeismologyWaveformInversion (geology)TomographySeismometerUndersamplingSeismic tomographyGeodesyAcousticsGeophysicsComputer scienceTectonicsOpticsMantle (geology)TelecommunicationsRadarPhysics

Abstract

fetched live from OpenAlex

We successfully apply the acoustic Laplace–Fourier waveform tomography method to delineate <it>P</it>-wave velocity structures of the mega-splay fault system in the central part of the seismogenic Nankai subduction zone offshore Japan, using densely sampled wide-angle ocean bottom seismograph (OBS) data originally acquired in 2004. Our success is due to new and carefully designed data preconditioning and inversion strategies to mitigate (i) the well-known non-linearity of waveform inversion, (ii) the challenges arising from crustal-scale survey designs (e.g. undersampling of the OBSs), and (iii) modelling errors due to the use of the acoustic assumption. We identify a sixfold set of key components that together lead to the success of the high-resolution waveform tomography image: (i) Availability of low-frequency components (starting at 2.25 Hz) reducing the non-linearity, and access to large offset data (up to 55 km) increasing the depth of illumination and the recovery of low wavenumber components. (ii) A highly accurate traveltime tomography result (with an rms error of approximately 60 ms) that further mitigates the non-linearity. (iii) A hierarchical inversion approach in which phase spectra are inverted first to reduce artefacts from the acoustic assumption, and amplitude information is only incorporated in the final stages. (iv) A Laplace–Fourier domain approach that facilitates a multiscale approach to mitigate non-linearity by restricting the inversion to the low frequency components and early arrivals first, and sequentially including higher frequencies and later arrivals. (v) A pre-conditioning strategy for eliminating undesirable high wavenumber components from the the gradient. (vi) A strategy for source estimation that reduce the influence of the instrumental design. In the OBS case study used for illustration purposes, Laplace–Fourier waveform tomography retrieves velocity anomalies as small as 700 m (horizontally) and 350 m (vertically) above the top of the Philippine Sea Plate. The resulting velocity structures include low-velocity zones and thrust structures which have not been previously identified clearly. The velocity models are validated by scrutiny of synthetic and observed waveforms, by evaluating the coherency of source estimates, and by comparison with 3-D pre-stack migrated (PreSDM) images. Chequerboard tests and point-scatter tests demonstrate both the reliability and the limitations of the acoustic implementation.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.532
Threshold uncertainty score0.684

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.016
GPT teacher head0.250
Teacher spread0.233 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it