Seismic stratigraphy and attenuation of gas-hydrate zones within Hikurangi and Gondwana margins, eastern New Zealand
Bibliographic record
Abstract
SUMMARY Gas hydrates that occur on many continental margins have received global attention. In reflection seismic imaging, the bottom-simulating reflector (BSR) is a common indicator of gas hydrates. However, it is difficult to identify gas hydrates and quantify their amounts through the BSR alone. For gas-hydrate characterization, it is therefore useful to measure seismic stratigraphic and attenuation attributes. Short-scale patterns of layering that contain information about the amount and mechanism of gas hydrates can be identified through stratigraphic and attenuation attributes. We measure the complete time-variant spectra by using sparse strongest peaks, and the spectral differences at different times through attenuation parameters Q–1 and γ. The traditional Q–1 is associated with the attenuation of the frequency-dependent part of wavefield, and the γ characterizes the frequency-independent attenuation. The measurement approach is straightforward and requires no sophisticated inverse algorithm and is applied to surface seismic data acquired over the Hikurangi and Gondwana margins, eastern New Zealand. High-quality spectral and attenuation images are obtained. Spectral attributes correlate with BSRs and large positive Q–1 and negative γ-values are below and above the BSRs, which are interpreted as being related to free-gas and gas-hydrate accumulations. These results will aid the quantification of gas hydrates and the assessment of their roles as an energy resource, as a potential geological hazard, and in climate change and ocean warming.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), 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".