Stochastic volume estimation and connectivity analysis at the Mallik gas hydrate field, Northwest Territories, Canada
Bibliographic record
Abstract
Gas hydrates located offshore and onshore beneath thick permafrost areas constitute one of the largest untapped natural gas resources. Yet, gas hydrate in place (GHIP) estimation at the scale of a field is not common in the scientific literature but is required to realistically assess the economical potential of specific accumulations. Progress in the last decade in Alaska and Canada has shown that gas hydrate accumulations beneath thick permafrost can be mapped at depth using conventional seismic attributes (Inks et al., 2009; Riedel et al. 2009). To evaluate the economic potential of gas hydrates in this environment, a test site at Mallik, Northwest Territories, Canada, was extensively surveyed (three-dimensional seismic, full set of logs in two wells, etc.) and a production test was realized in high gas-hydrate horizons. At Mallik, high P- and S-wave velocities, high acoustic impedances, and strong seismic amplitude reflections were all linked to sand-rich sediments with a high saturation of gas hydrates (Bellefleur et al. 2006; Riedel et al.). This relationship provides a strong basis for an integrated data characterization of this gas hydrate deposit.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".