Seismic Attenuation Compensation with Spectral-Shaping Regularization
Why this work is in the frame
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Bibliographic record
Abstract
Summary Due to the viscoelasticity of subsurface medium, seismic waves will inherently attenuate during propagation, which leads to a lower resolution of acquired seismic records. Methods of attenuation compensation can efficiently recover high-resolution seismic data from attenuation. The stability of amplitude compensation and the widening of effective frequency-bandwidth are critical aspects to evaluate the effectiveness of these methods. In this abstract, we propose a compensation scheme that promotes the preservation of low-frequency energy of seismic data. Based on the spectral shaping regularization, we construct an adaptive shaping operator by tailoring the frequency spectra of seismic data and perform inverse-Q filtering in an inversion scheme. This data-driven shaping operator can regularize and balance the spectral-energy distribution for the compensated records, which can maintain the low-frequency ratio by constraining over-compensation for high-frequency energy. Synthetic tests and application on pre-stack common-reflection-point gathers indicate that the proposed method can preserve the relative energy of low-frequency components, while fulfilling stable high-frequency compensation.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it