Development and field installation of a monitoring system for the JOGMEC/NRCan/ Aurora Mallik 2007-2008 Gas Hydrate Production Research Well Program
Bibliographic record
Abstract
Design and construction of long-term gas hydrate production facilities requires assessment of the in situ formation response to production at a field scale. Fundamental properties, such as tem-perature and pressure, are critical for the determination of phase conditions. Other properties, such as formation resistivity, formation acoustic properties, and fluid mobility, support the inference of forma-tion permeability, porosity, and gas hydrate saturation. An ability to continuously monitor the changes in these properties during the course of a production test will facilitate tracking of the dissociation front and yield valuable information for engineering design and verification of numerical reservoir simulators. Such a monitoring system was designed, developed, and introduced as a part of the Mallik Gas Hydrate Production Research Well Program, carried out by the Japan Oil, Gas and Metals National Corporation, Natural Resources Canada, and Aurora College in the winters of 2007 and 2008 in the Mackenzie Delta, Northwest Territories. Although the deployment of some sensors and the acquisition of some data were limited by various operational challenges encountered during the field program, considerable experience was gained during all phases of the research program. In particular, the acquisition and interpretation of down-hole temperature profiles and changes in formation electrical potentials during testing provided use-ful insight into the stimulation-response behaviour of the reservoir, assisted in the understanding of a range of operational conditions, and supported critical decision-making processes at the well site.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".