Imaging the P‐Wave Velocity Structure of Arctic Subsea Permafrost Using Laplace‐Domain Full‐Waveform Inversion
Bibliographic record
Abstract
Abstract Climate change in the Arctic has recently become a major scientific issue, and detailed information on the degradation of subsea permafrost on continental shelves in the Arctic is critical for understanding the major cause and effects of global warming, especially the release of greenhouse gases. The subsea permafrost at shallow depths beneath the Arctic continental shelves has significantly higher P‐wave velocities than the surrounding sediments. The distribution of subsea permafrost on Arctic continental shelves has been studied since the 1970s using seismic refraction methods. With seismic refraction data, the seismic velocity and the depth of the upper boundary of subsea permafrost can be determined. However, it is difficult to identify the lower boundary and the internal shape of permafrost. Here, we present two‐dimensional P‐wave velocity models of the continental shelf in the Beaufort Sea by applying the Laplace‐domain full‐waveform inversion method to acquired multichannel seismic reflection data. With the inverted P‐wave velocity model, we identify anomalous high seismic velocities that originated from the subsea permafrost. Information on the two‐dimensional distribution of subsea permafrost on the Arctic continental shelf area, including the upper and lower bounds of subsea permafrost, are presented. Also, the two‐dimensional P‐wave velocity model allows us to estimate the thawing pattern and the shape of subsea permafrost structures. Our proposed P‐wave velocity models were verified by comparison with the previous distribution map of subsea permafrost from seismic refraction analyses, geothermal modeling, and well‐log data.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".