Pore Habit of Gas in Gassy Sediments
Bibliographic record
Abstract
Abstract Gas bubbles are widespread in seafloors and lakebeds and typically found in shallow and fine‐grained sediments. Sediment properties control gas nucleation and gas migration. Gas migration and pathways have been studied mostly in clean coarse particles or fine‐grained matrices. Nevertheless, both cases show very distinct geo‐behaviors. Pore habit is defined by the counteracting effects of effective stress and pore‐throat‐dependent capillary pressure. In this article, we explore gas nucleation by CO2 gas exsolution and its consequent gas‐driven fractures (open‐mode discontinuities) or pore invasion in binary sediments as a function of fines content (FC). We conducted physical test analogies for different FC subjected to gas exsolution. Our results highlight that the pore habit of gas in gassy sediments depends on its capability to invade a neighboring pore (capillarity) and burial depth (effective stress). We show that the load dominant fraction in binary soils can be used to estimate the dominant pore throat size. We then proposed a robust methodology to predict the pore habit of gassy sediments from its properties as defined in recent developments in soil behavior and characterization. Finally, we applied it to a real case offshore Vancouver Island.
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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 | 0.000 |
| 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".