Evaluation of Neoproterozoic source rock potential in SE Pakistan and adjacent Bikaner–Nagaur Basin India
Bibliographic record
Abstract
Abstract Discoveries of heavy crude oil in the Neoproterozoic rocks (Infracambrian rock sequence) from the Bikaner-Nagaur Basin of India emphasize the significance of studying and exploring the Neoproterozoic source rock potential in the southeastern part of Pakistan. This study evaluates the potential of the source rock in the Infracambrian rock sequence (Salt Range Formation) based on surface geochemical surveys, Rock–Eval pyrolysis, source biomarkers, geophysical characterization, and seismic inversion using machine learning for maturity index estimation. Core samples of Infracambrian rock were extracted for Rock–Eval pyrolysis and biomarker characterization. Additionally, 81 geomicrobial soil and gas samples were collected from the surface to explore the petroleum system and potential source rocks in the subsurface. Advanced interpretation techniques were used to investigate the origin and concentration of hydrocarbon gases at the surface, including Rock–Eval pyrolysis, thermal maturity, source biomarkers, and the environment of deposition of organic matter. The results show that the investigated samples are characterized by restricted marine clay devoid of sedimentary carbonate facies with thermal maturity in the early stage of the oil generation window. The seismic inverted maturity index profile demonstrates a reasonable correlation of thermal maturity with the biomarkers and Rock–Eval pyrolysis. Further scrutiny of the surface geochemical samples confirms the presence of higher concentrations of thermogenic C2–C4 hydrocarbons in the vicinity of anticlinal structures, suggesting the existence of an effective migration path along deep-seated faults to the surface. This study concludes that the Infracambrian rocks on the eastern flank of Pakistan are thicker, thermally mature, and have deep-seated structural closures, indicating a greater probability of heavy and light oil in this area than in the Bikaner–Nagaur Basin, India.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".