FIB-SEM and TEM Investigations of an Organic-rich Shale Maturation Series from the Lower Toarcian Posidonia Shale, Germany
Bibliographic record
Abstract
Abstract Although shale gas systems constitute a new target for commercial hydrocarbon production, only a little attention has been paid to the evolution of these unconventional systems with increasing thermal maturation. This study reports the characterization of samples of the Lower Toarcian (Lower Jurassic) Posidonia Shale from northern Germany at varying levels of thermal maturity. Observations were made using an original combination of focused ion beam-scanning electron microscopy (FIB-SEM) and transmission electron microscopy (TEM). The paper documents the formation of microfracture-filling bitumen in close assotiation with kerogen residues with increasing maturity. Porosity evolves from mostly submicrometric interparticle pores in immature samples to intramineral and intraorganic pores in overmature (gas mature) samples. This intraorganic nanoporosity has most likely come about by the exsolution of gaseous hydrocarbon and been hydrocarbon wet during the thermal maturation processes. Although FIB-SEM and TEM images are small compared to field size, this study emphasizes the need for nanoscale imaging to better constrain hydrocarbon generation processes in gas shale systems.
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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".