Hierarchical Pore Morphology of Cretaceous Shale: A Small-Angle Neutron Scattering and Ultrasmall-Angle Neutron Scattering Study
Bibliographic record
Abstract
Shale reservoirs are becoming an increasingly important source of oil and natural gas supply and a potential candidate for CO 2 sequestration. Understanding the pore morphology in shale may provide clues to making gas extraction more efficient and cost-effective. The porosity of Cretaceous shale samples from Alberta, Canada, collected from different depths with varying mineralogical compositions, has been investigated by small- and ultrasmall-angle neutron scattering. The samples come from the Second White Specks and Belle Fourche formations, and their organic matter content ranges between 2 and 3%. The scattering length density of the shale specimens has been estimated using the chemical composition of the different mineral components. Scattering experiments reveal the presence of fractal and non-fractal pores. It has been shown that the porosity and specific surface area are dominated by the contribution from meso- and micropores. The fraction of closed porosity has been calculated by comparing the porosities estimated by He pycnometry and scattering techniques. Although there is no correlation between total porosity and mineral components, a strong correlation has been observed between closed porosity and major mineral components in the studied specimens.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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".