Oil-Viscosity Predictions From Low-Field NMR Measurements
Why this work is in the frame
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Bibliographic record
Abstract
Summary Canada contains vast reserves of heavy oil and bitumen. Viscosity determination is key to the successful recovery of this oil, and low-field nuclear magnetic resonance (NMR) shows great potential as a tool for estimating this property. An NMR viscosity correlation previously had been developed that is valid for order-of-magnitude estimates over a wide range of viscosities and temperatures. This correlation was built phenomenologically, using experiments relating NMR spectra to viscosity. The present work details a more thorough investigation into oil viscosity and NMR, thus providing a theoretical justification for the proposed correlation. A novel tuning procedure is also presented, whereby the correlation is fitted using the Arrhenius relationship to improve the NMR viscosity estimates for single oils at multiple temperatures. Tuning allows for NMR to be potentially used in observation wells to monitor thermal enhanced oil recovery (EOR) projects or online to monitor the viscosity of produced-fluid streams as they cool.
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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