Down-hole-monitoring data analysis and interpretation for the JOGMEC/NRCan/Aurora Mallik 2007-2008 Gas Hydrate Production Research Well Program
Bibliographic record
Abstract
Permanently installed monitoring-sensor cables behind the production-well casings were used to acquire distributed-temperature data, and electrical potentials were passively monitored at the down-hole electrodes in the winters of 2007 and 2008 for the JOGMEC/NRCan/Aurora Mallik Gas Hydrate Production Research Well Program. The data could be almost continuously acquired during the production-test periods without interfering with production operations once the down-hole-sensor cables were connected to the surface system. Some useful information related to production activities was obtained from the distributed-temperature data. The temperature-depth profiles obtained during the depressurizations in the 2008 test indicated a promising potential for tracking of the fluid levels in the annulus, which qualitatively corresponds to the fluid-volume change estimated from the differential pres-sures. Temperature profiles also contributed a complementary estimation of production parameters, such as the water-production rate under assumed conditions. The temperature disturbance observed during cement curing suggests a thermal impact on the gas hydrate by the heat of cement hydration. Passive electrical-potential measurement is considered a promising candidate for further development. The measurement was attempted to acquire streaming-potential signals from formation-fluid movement in porous media under the pressure gradient during various operations. Qualitative observation shows a rela-tionship between signal-polarity change and the direction of possible fluid flows in the formation, which suggests local-scale fluid flow near the electrodes.
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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 | 0.001 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".