Direct Measurement of Pore Size and Surface Relaxivity with Magnetic Resonance at Variable Temperature
Bibliographic record
Abstract
A variety of magnetic resonance relaxometry methods have been developed to determine pore size in porous rocks. Uncertainties in pore-size estimates may occur due to uncertainty in the relaxation-diffusion regime. We have developed a direct and rapid one-dimensional method based on Brownstein-Tarr theory to help remedy this problem. The correlation between magnetic resonance relaxation behavior and the temperature-dependent self-diffusion coefficient of pore fluids was employed to estimate the pore size and surface relaxivity of a series of reservoir rocks. Relaxation is anticipated to depend on diffusion in the intermediate regime of Brownstein-Tarr theory. Water-saturated glass-bead packs were employed in initial Carr-Purcell-Meiboom-Gill experiments at variable temperature. The calculated pore size matches the estimated geometric pore size. The proposed method was applied to determine the pore size of Berea, Buff Berea, and Nugget sandstones. The pore sizes determined with the three pore geometries are in good agreement with scanning electron microscopy and micro-computed-tomography measurements. The experimentally observed changes in relaxation times and their corresponding intensities indicate an intermediate Brownstein-Tarr regime for all systems examined in this work.
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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 | 0.001 | 0.002 |
| 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 | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".