A magnetic resonance study of pore filling processes during spontaneous imbibition in Berea sandstone
Bibliographic record
Abstract
A new magnetic resonance technique, DDIF (the decay of magnetization due to diffusion in the internal field), was combined with mercury porosimetry to investigate pore geometry, including pore- and throat-size distribution, and pore connectivity for porous media. A comparison of DDIF spectra for a fully water saturated Berea sandstone, with the partially saturated sample by centrifugation in air, indicated that DDIF can be used for the measurement of water filled pore size distribution in partially saturated porous media. Dynamic water imbibition into air-filled Berea sandstone was studied using the DDIF technique. Simultaneously, in situ three-dimensional saturation and capillary driven water penetration were monitored using Conical-SPRITE, which is a rapid, centric scanning, spin-density weighted single point three-dimensional magnetic resonance imaging technique. These measurements provide direct evidence for differences in the pore filling mechanisms for co-current imbibition and counter-current imbibition in Berea sandstone. During co-current imbibition, water flows through the pores and connected throats with a piston-type mechanism. Air is displaced from the sample by the leading edge of the waterfront, resulting in a macroscopic piston-like flow through the entire sample. During counter-current imbibition, water flows through the pores and connected throats with a film-like structure along the corners and surfaces of the pore space. Air escapes from the sample by flowing through the center of the pores and pore throats, in the opposite direction. Once the penetrating waterfronts meet, at the sample center, there is a global, uniform increase in water content.
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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) | 0.000 | 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".