Physical properties and rock physics models of sediment containing natural and laboratory-formed methane gas hydrate
Bibliographic record
Abstract
This paper presents results of shear strength and acoustic velocity (p-wave) measurements performed on: (1) samples containing natural gas hydrate from the Mallik 2L-38 well, Mackenzie Delta, Northwest Territories; (2) reconstituted Ottawa sand samples containing methane gas hydrate formed in the laboratory; and (3) ice-bearing sands. These measurements show that hydrate increases shear strength and p-wave velocity in natural and reconstituted samples. The proportion of this increase depends on (1) the amount and distribution of hydrate present, (2) differences in sediment properties, and (3) differences in test conditions. Stress-strain curves from the Mallik samples suggest that natural gas hydrate does not cement sediment grains. However, stress-strain curves from the Ottawa sand (containing laboratory-formed gas hydrate) do imply cementation is present. Acoustically, rock physics modeling shows that gas hydrate does not cement grains of natural Mackenzie Delta sediment. Natural gas hydrates are best modeled as part of the sediment frame. This finding is in contrast with direct observations and results of Ottawa sand containing laboratory-formed hydrate, which was found to cement grains (Waite et al. 2004). It therefore appears that the microscopic distribution of gas hydrates in sediment, and hence the effect of gas hydrate on sediment physical properties, differs between natural deposits and laboratory-formed samples. This difference may possibly be caused by the location of water molecules that are available to form hydrate. Models that use laboratory-derived properties to predict behavior of natural gas hydrate must account for these differences.
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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 | 0.000 | 0.000 |
| 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".