Pore Structure Characterization of Shale Using Gas Physisorption: Effect of Chemical Compositions
Bibliographic record
Abstract
In this study, the pore structure characteristics of Canadian Horn River basin shales with various chemical compositions were evaluated using gas physisorption analyses. The samples used in this research were obtained from two different regions (shallow and deep regions) of rock cuttings during the drilling of the shale gas field located in Horn River basin. The pore size, specific surface area, total pore volume, micropore surface area, and micropore volume of the shale samples were measured using both nitrogen and CO2. The results indicated that the pore size was not a function of chemical composition, while distinct trends were observed for other macroscopic and microscopic pore-related properties. In particular, the greatest specific surface area and total pore volume were observed for silica-rich carbonate shales, while clay-rich siliceous shales exhibited the greatest micropore volume and micropore surface area. The trends clearly suggested that macroscopic and microscopic pore-related properties of the Canadian Horn River basin shales were closely related to their chemical composition. Furthermore, a stronger correlation was observed between the quartz content and the micropore-related physical properties of shales (i.e., the micropore surface area and micropore volume) in comparison to other properties.
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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 | 0.000 |
| 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) | 0.000 | 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".