Downhole nuclear magnetic resonance logging in glaciomarine sediments near Ottawa, Ontario, Canada
Bibliographic record
Abstract
ABSTRACT Downhole nuclear magnetic resonance technology was applied in four boreholes intersecting glaciomarine sediments of the Ottawa Valley, Ontario. The study evaluated the ability of slim‐hole nuclear magnetic resonance tools to measure in situ volumetric water contents (porosities in saturated sediments) for geohazard and hydrogeological applications. The sediments are composed of clay‐ and silt‐sized grains of glacially eroded rock flour derived from the Precambrian Shield containing trace amounts of magnetic minerals, and porosities ranging from 40 to 74 porosity units (PU, 1% porosity = 1 PU). Two nuclear magnetic resonance instruments were deployed with echo times of 0.5 and 1.0 ms, and diameters of investigation ranging from 14.0 to 30.5 cm. Quantitative nuclear magnetic resonance porosities in the sediments were typically within ±5 PU (95% within ±10 PU) of core calibration data sets in the silty clays where threshold bulk magnetic susceptibility values were <30 × 10 −4 SI. This was found to deviate, however, where the concentration and mineralogy of magnetic particles changed, interpreted to be shortening relaxation times which led to underestimation of true water contents. This effect is correlated with a change in depth from magnetite to superparamagnetic nanoparticles of greigite (low‐temperature iron monosulphide) magnetism, interpreted to occur at the sulphate‐methane interface. Clay mineralogy and pore water chemistry were also examined as contributing factors, but were not found to significantly shorten nuclear magnetic resonance relaxation responses. Very short T 2 times (<2 ms) are typical in these particular silty clays, requiring a tool with an echo spacing of <1.0 ms. Due to increased potential for sediment disturbance around a well caused by the geotechnical sensitivity of the sediments, a nuclear magnetic resonance instrument with multiple frequencies provided signal penetration out to various diameters around the tool, giving needed information about the size of the disturbed zone surrounding the casing.
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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 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".