Identifying a gas hydrate production zone using a cased-hole borehole acoustic-reflection survey, Aurora/JOGMEC/NRCan Mallik 2L-38 gas hydrate production research well
Bibliographic record
Abstract
In 2007, data were acquired from a borehole acoustic-reflection survey (BARS), using the latest Sonic Scanner tool, in a gas-hydrate-bearing formation in the Mallik field, Mackenzie Delta, Northwest Territories. The BARS data were logged in a cased-hole environment in which no azimuthal information could be recovered, thus limiting the final migration image-processing and interpretation. Performing BARS in a cased hole is less favourable than in an open-hole environment because the high-amplitude casing arrivals make the identification of reflected energy very challenging. In addition, no tool orientation data are usable in a cased hole due to the lack of reliable measurement of the Earth's magnetic field. In this paper, we present results acquired in a cased-hole environment and indicate correlations of BARS data with auxiliary logs. The perforation zone is identified in the raw and filtered wave-form BARS data. Energy in the 1098 to 1105 m depth interval is significantly stronger, and this zone of higher amplitudes appears to extend into the formation. This zone is assumed to be directly related to changes in the formation caused by the perforations and/or production in the lower half of the production-test interval. Several additional reflections can be observed in the raw and filtered wave forms. The gamma-ray and density logs indicate formation changes at the same depths at which these reflections occur. These formation boundaries and the reflections also correlate well with the fullbore microresistivity image logs. The results indicate that BARS data can be used to achieve a more complete, detailed, and thus enhanced log interpretation.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".