Effect of Methane Gas Hydrate Content of Marine Sediment on Ocean Wave-Induced Oscillatory Excess Pore Water Pressure and Geotechnical Implications
Bibliographic record
Abstract
Methane gas hydrate-bearing sediments hold substantial natural gas reserves, and to understand their potential roles in the energy sector as the next generation of energy resources, considerable research is being conducted in industry and academia. Consequently, safe and economically feasible extraction methods are being vigorously researched, as are methods designed to estimate site-specific reserves. In addition, the presence of methane gas hydrates and their dissociation have been known to impact the geotechnical properties of submarine foundation soils and slopes. In this paper, we advance research on gas hydrate-bearing sediments by theoretically studying the effect of the hydromechanical coupling process related to ocean wave hydrodynamics. In this regard, we have studied two geotechnically and theoretically relevant situations related to the oscillatory wave-induced hydromechanical coupling process. Our results show that the presence of initial methane gas pressure leads to excessively high oscillatory pore pressure, which confirms the instability of submarine slopes with methane gas hydrate accumulation originally reported in the geotechnical literature. In addition, our results show that neglecting the presence of initial methane gas pressure in gas hydrate-bearing sediments in the theoretical description of the oscillatory excess pore pressure can lead to improper geotechnical planning. Moreover, the theoretical evolution of oscillatory excess pore water pressure with depth indicates a damping trend in magnitude, leading to a stable value with depth.
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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 | 0.001 |
| 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".