Applications of high-resolution time-frequency transforms to attenuation estimation
Bibliographic record
Abstract
ABSTRACT Attenuation estimates quantify the loss of energy of propagating seismic waves due to anelastic processes. It is often carried out in the frequency domain. The most well-known methods for attenuation estimation, such as the spectral ratio and frequency-shift methods, compare spectral shapes of waveforms along a given raypath. They require broad spectra such as those obtained with the Fourier transform and the continuous wavelet transform. These methods are incompatible with high-resolution time-frequency transforms, which drastically localize time-frequency information. On the other hand, these transforms indicate stronger resistance to noise and can be used in combination with the peak frequency method to estimate attenuation. We have applied high-resolution transforms, namely the synchrosqueezing transform, basis pursuit, and complete ensemble empirical-mode decomposition, to a synthetic wedge example and two seismic data set examples, a seismic reflection profile, and a vertical seismic profile (VSP). Results for the synthetic example find that most high-resolution transforms are able to reliably estimate quality factors. Using centroid frequencies, the seismic reflection profile exhibits local increases in centroid frequencies, which likely indicates imprints from apparent attenuation over intrinsic attenuation. Centroid frequencies and effective quality factors for the VSP are consistent for the different spectral estimation techniques. These three examples illustrate the value of high-resolution transforms for frequency and quality factor measurements.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".