Characterization of the Cascadia ocean margin methane hydrates using prestack waveform inversion and reverse time migration
Bibliographic record
Abstract
Cascadia ocean margin, offshore Washington, USA poses a major seismic and environmental hazard to the population centers of the northwestern United States and western Canada with 10,000-year record of magnitude 9 or greater earthquakes occurring in every 500-year intervals that ruptured the entire Western United States and Vancouver Island. Additionally, within the accretionary prism, the area contains high concentrations of methane hydrates with clear observational records of continuous methane seepage. In the event of a major earthquake, the gas-hydrate stability field is likely to be disturbed, release large quantities of methane into the atmosphere, and cause major impacts to the climate. Here, we apply prestack waveform inversion and reversetime migration to estimate the depth image and visco-elastic model of the methane hydrates and the associated zones at the Cascadia margin. Combining the estimated visco-elastic model with the methane hydrate stability as functions of temperature and pressure, we also estimate the upper and lower bounds of the subsurface temperatures. Furthermore, we also propose a new approach to combine seismic analysis with fluid-flow and geomechanical simulations which can help analyzing the dynamic behavior of the accretionary prism methane hydrates at the Cascadia and other active ocean margins. Presentation Date: Monday, October 15, 2018 Start Time: 1:50:00 PM Location: Poster Station 7 Presentation Type: Poster
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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 | 0.000 |
| 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".