Experimental Evaluation on the Oil Saturation and Movability in the Organic and Inorganic Matter of Shale
Bibliographic record
Abstract
Shale oil reservoirs are more complex and difficult to exploit than conventional and tight oil reservoirs because of low porosity, permeability, and rich organic matter. The presence of organic matter has great influence on the flow behaviors of oil in shale and the development methods for shale oil. In this work, the saturation and movability behaviors of oil in organic and inorganic matter of shale were investigated by experimental methods. First, vacuum-imbibition tests were carried out to evaluate the saturated oil amount at different states (in inorganic pores, organic pores, and adsorbed/dissolved in organic matter) in shale cores and to calculate the inorganic/organic saturation and inorganic/organic porosity. The results show that the imbibition volume of oil is 2.4–5.7 times as much as those of KCl solutions for the several shale cores. The excess of imbibition oil is adsorbed or dissolved into the organic matter and dispersed in the organic pores. The organic saturation of oil in the shale samples is from 58.9 to 82.6%, which is 1.4–4.7 times as much as that in inorganic matter. The inorganic porosity is from 1.9 to 4.4%, while the organic porosity is from 0.3 to 1.3%. Moreover, the oil movability under centrifugation in the organic and inorganic matter of shale was measured by nuclear magnetic resonance. The results show that the content of movable oil in inorganic pores is 20–80%, which is higher than that of organic matter with a value of lower than 10%. The total movable content of oil in shale is influenced greatly by the content of movable oil in organic matter. Therefore, how to displace the oil in organic matter is the main problem to be solved in developing shale oil.
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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 | 0.000 | 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) | 0.001 | 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".