Sonic waveform attenuation in gas hydrate‐bearing sediments from the Mallik 2L‐38 research well, Mackenzie Delta, Canada
Bibliographic record
Abstract
The Mallik 2L‐38 research well was drilled to 1150 m under the Mackenzie Delta, Canada, and penetrated a subpermafrost interval where methane hydrate occupies up to 80% of the pore space. A suite of high‐quality downhole logs was acquired to measure in situ the physical properties of these hydrate‐bearing sediments. Similar to other hydrate deposits, resistivity and compressional and shear sonic velocity data increase with higher hydrate saturation owing to electrical insulation of the pore space and stiffening of the sediment framework. In addition, sonic waveforms show strong amplitude losses of both compressional and shear waves in intervals where methane hydrate is observed. We use monopole and dipole waveforms to estimate compressional and shear attenuation. Comparing with hydrate saturation values derived from the resistivity log, we observe a linear increase in both attenuation measurements with increasing hydrate saturation, which is not intuitive for stiffening sediments. Numerical modeling of the waveforms allows us to reproduce the recorded waveforms and illustrate these results. We also use a model for wave propagation in frozen porous media to explain qualitatively the loss of sonic waveform amplitude in hydrate‐bearing sediments. We suggest that this model can be improved and extended, allowing hydrate saturation to be quantified from attenuation measurements in similar environments and providing new insight into how hydrate and its sediment host interact.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".