Monitoring gas hydrate formation with magnetic resonance imaging in a metallic core holder
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Bibliographic record
Abstract
Methane hydrate deposits world-wide are promising sources of natural gas. Magnetic Resonance Imaging (MRI) has proven useful in previous studies of hydrate formation. In the present work, methane hydrate formation in a water saturated sand pack was investigated employing an MRI-compatible metallic core holder at low magnetic field with a suite of advanced MRI methods developed at the UNB MRI Centre. The new MRI methods are intended to permit observation and quantification of residual fluids in the pore space as hydrate forms. Hydrate formation occurred in the water-saturated sand at 1500 psi and 4 °C. The core holder has a maximum working pressure of 4000 psi between -28 and 80 °C. The heat-exchange jacket enclosing the core holder enabled very precise control of the sample temperature. A pure phase encode MRI technique, SPRITE, and a bulk T1-T2 MR method provided high quality measurements of pore fluid saturation. Rapid 1D SPRITE MRI measurements time resolved the disappearance of pore water and hence the growth of hydrate in the sand pack. 3D π-EPI images confirmed that the residual water was inhomogeneously distributed along the sand pack. Bulk T1-T2 measurements discriminated residual water from the pore gas during the hydrate formation. A recently published local T1-T2 method helped discriminate bulk gas from the residual fluids in the sample. Hydrate formation commenced within two hours of gas supply. Hydrate formed throughout the sand pack, but maximum hydrate was observed at the interface between the gas pressure head and the sand pack. This irregular pattern of hydrate formation became more uniform over 24 hours. The rate of hydrate formation was greatest in the first two hours of reaction. An SE-SPI T2 map showed the T2 distribution changed considerably in space and time as hydrate formation continued. Changes in the T2 distribution are interpreted as pore level changes in residual water content and environment.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.002 | 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 it