U/Сorg Ratio Within Unconventional Reservoirs: Indicator of Oil Generation Processes and Criteria for Productive Intervals Determination During the Bazhenov Formation Investigation
Bibliographic record
Abstract
Summary Spectral gamma-ray logging is widely used and yields reliable data on uranium distribution within oil source rocks. The spectral gamma-ray logging is an important method for the detailed study of wells. Today this method is mainly used for oil-source formation identification and for organic matter calculation. The accumulation process of organic matter and depositional environmental influences on the uranium content. We performed complex analysis of U/Corg variations with sulfur isotope, geochemical survey, and well logging data. U/Corg ratio in different rocks and sweet spots were under research. Investigation results proved that sweet spots have the minimal meaning of the U/Corg ratio and that there is a statistically significant correlation between the U/Corg curves and the sulfur isotope vertical variations. The following data were involved: pyrolysis results (Rock-Eval), profile of total organic matter content obtained from thermophysical core profiling, well logging data, isotope composition, and also the results of the X-ray fluorescence analysis.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".