Preliminary study on the pore characterization of lacustrine shale reservoirs using low pressure nitrogen adsorption and field emission scanning electron microscopy methods: a case study of the Upper Jurassic Emuerhe Formation, Mohe basin, northeastern China
Bibliographic record
Abstract
In this study, we investigate the pore systems in lacustrine shales from the Upper Jurassic Emuerhe Formation, Mohe basin, northeastern China using organic geochemistry analysis, X-ray diffraction, field emission scanning electron microscopy, and low pressure nitrogen adsorption analysis. Because of the large amount of terrestrial input, the organic matter in these lacustrine shales are dominated by type III-kerogen, which have moderate total organic carbon contents ranging between 0.37 wt.% and 4.13 wt.% and thermal maturity ranging from 0.6 %Ro to 1.15 %Ro. Brittle minerals including quartz and feldspar in the Emuerhe Formation comprise >50% of the samples by weight and illite dominates the clay minerals with the relative content ranging from 45% to 95%. The dominant pore types in the Emuerhe Formation shale reservoir are interparticle pores between clay mineral crystals and intraparticle pores within feldspar grains. Pores that are larger than 20 nm primarily contribute to the total pore volume, whereas pores that are less than 10 nm primarily contribute to the specific surface area. The major storage and flow space for hydrocarbon in these lacustrine shales largely resides in inorganic matter porosity and partially in microfacture porosity. Organic matter pores are rare in the lacustrine shales of the Emuerhe Formation, attributed to the humic organic matter and the relatively low thermal maturity. The negative correlation between the total organic carbon and nitrogen BET surface area also indicate that the organic fractions have no significant influence to the petroleum storage potential of these shales. In this case, the clay minerals, specifically illite, could be the major medium for gas adsorption.
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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".