Applicability of micro‐FTIR in detecting shale heterogeneity
Bibliographic record
Abstract
Samples of Late Devonian/Early Mississippian New Albany Shale from the Illinois Basin, having maturities ranging from early mature to postmature, were analysed using micro-Fourier transform infrared (FTIR) spectroscopy, ImageJ processing software and scanning electron microscopic X-ray spectroscopy to explore the distribution, connectivity and chemical composition of organic matter, clay minerals, carbonate minerals and quartz, and to further test the applicability of micro-FTIR mapping to study shale heterogeneity. Each sample was analysed in planes parallel and perpendicular to the bedding to investigate anisotropy in component distribution, with a possible implication for better understanding anisotropy in porosity and permeability in organic-matter-rich shales. Our results show that for low-maturity samples, organic matter is better connected in the plane parallel to the bedding than in the plane perpendicular to the bedding. Organic matter connectivity decreases with increasing maturity as a result of kerogen transformation. Clay minerals are very well connected in both planes, whereas carbonate minerals are not abundant whilst dominantly isolated in most samples, independent of maturity. This study demonstrates that micro-FTIR mapping is a valuable tool for studying shale heterogeneity on a micrometre to millimetre scale that becomes even more powerful in combination with scanning electron microscopy techniques, which extend observations to a nanometre scale. However, to obtain meaningful and comparable results, micro-FTIR mapping requires very careful standardization, precise selection of peak heights/areas and mapping conditions (such as aperture size, scan numbers, resolution, etc.) well suited for the analysed samples.
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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 | 0.001 | 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) | 0.001 | 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".