Accurate Porosity Measurement in Gas Bearing Formations
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Porosity is a key reservoir parameter and high accuracy is needed to properly estimate reserves. But even though there is a long history of porosity measurements and various tools from which to derive it, this can still remain a difficult task. None of the logging tools directly measure porosity but instead respond to density, lithology and fluid. Combining different measurements can help to solve for porosity but also brings the complexity of invasion as all the tools do not have the same radial response. This problem is even more complex when dealing with gas formations as the fluid effect on the measurements is very high. This paper looks at various methods to improve porosity computations via the integration of Nuclear Magnetic Resonance (NMR) and other porosity measurements in South China Sea gas reservoirs.
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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) | 0.003 | 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