Geophysical well-log montage for the Aurora/JOGMEC/NRCan Mallik 2L-38 gas hydrate production research well
Bibliographic record
Abstract
In the winters of 2007 and 2008, Japan Oil, Gas and Metals National Corporation, Natural Resources Canada, and Aurora Research Institute jointly conducted a full-scale depressurization test on a gas-hydrate-bearing formation in the Aurora/JOGMEC/NRCan Mallik 2L-38 gas hydrate production research well, located in the Mackenzie Delta, Northwest Territories. In addition to production testing, an extensive wireline-logging program was carried out to evaluate reservoir properties and understand gas hydrate dissociation behaviour throughout the production test. In the open-hole environment, the logging program included elemental capture spectroscopy, dipole sonic imaging, triaxial induction scanning, magnetic resonance scanning, fullbore formation microimaging, epithermal neutron scanning, and conventional logs such as gamma ray, neutron density, and laterolog resistivity. In the cased-hole environment, reservoir saturation, epithermal neutron, and sonic scanning data were acquired to evaluate property changes after casing placement, and then again after the production test. To facilitate the understanding of the above measurements, and their applicability to this scientific program, a composite geophysical well log was created to show the data for the sediments and gas-hydrate-bearing intervals between 880 and 1220 m. Included are numerous reservoir parameters, such as porosity, gas hydrate saturation, and permeability.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.016 | 0.003 |
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".