Multi-scale geochemical, mineralogical and petrographical dataset for the shale oil-bearing reservoir potential: an example from the Lower Jurassic Datta Formation in the Upper Indus Basin, Pakistan
Bibliographic record
Abstract
The organic-rich shale facies of the Lower Jurassic Datta Formation in the Upper Indus Basin in Pakistan was studied using geological and geochemical investigations to assess the unconventional shale oil reservoir potential. The Datta shale facies is a promising oil-prone stratum, consisting of total organic carbon (TOC) exceeding 2 wt%, and primarily comprising Type II and II/III kerogens, with a hydrogen index (HI) exceeding 250 mgHC g −1 TOC. The Datta shale facies is also characterized by higher free hydrocarbon (S 1 ) content than TOC, resulting in a high oil saturation index (OSI) between 30.81 and 298.7 mgHC g −1 TOC, wherein the high OSI of more than 100 mgHC g −1 TOC indicates a strong potential for oil production. This finding is consistent with the current thermally mature oil window, which ranges between early mature and peak mature, as supported by vitrinite reflectance (%VR o ) values of up to 0.82. This main oil-generation window leads to the conversion of extensive hydrogen-rich kerogen for commercial oil generation, with a transformation ratio (TR) of up to 65%, as demonstrated by 1D basin modelling. Maximum oil generation, with TR values exceeding 50%, leads to high pressure and results in microfracture pores in the Datta shale facies. The presence of non-fabric-fracture pores is confirmed by high-resolution petrographical scanning electron microscopy (SEM). Consequently, these findings highlight that the Datta shale facies should be considered for use as an unconventional shale oil reservoir, with the suggestion of hydraulic fracturing techniques for production purposes.
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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 | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".