Abnormally pressured beds as barriers to diffusive solute transport in sedimentary basins
Bibliographic record
Abstract
Abstract Diffusion can drive significant solute transport over millions of years, but ancient brines and large salinity gradients are still observed in deep sedimentary basins. Fluid flow within abnormally pressured beds may prevent diffusive transfer over geologically significant periods, if the abnormally pressured bed is surrounded by normally pressured beds. Analytic solutions based on sediment loading and unloading demonstrate that this effect should be considered in beds with a compressibility exceeding 10−8 Pa−1, with a thickness of 100 m or more, or a sedimentation rate exceeding 10−5 m year−1. Conditions favourable for our model of abnormally pressured beds appear common in sedimentary basins. Large salinity gradients associated with clay beds have previously been attributed to membrane effects, but flow patterns associated with abnormally pressured beds appear more robust in the presence of heterogeneity and discontinuities than membrane effects. Calculations suggest that thick underpressured shales in the Alberta basin may have allowed ancient evaporatively concentrated brines to be preserved beneath a vigorous topography‐driven flow system over the last 60 My. In the Illinois basin, drained overpressured beds may have limited solute transport across the New Albany shale until approximately 250 Ma. It is unlikely, however, that overpressures could have persisted long enough to explain concentration gradients observed in the modern basin. These gradients may instead reflect relatively recent halite dissolution above the New Albany shale.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".