Multiple hydrocarbon charging events in <scp>K</scp>uh‐e‐<scp>M</scp>ond oil field, <scp>C</scp>oastal <scp>F</scp>ars: evidence from biomarkers in oil inclusions
Bibliographic record
Abstract
Abstract Oil inclusions were retrieved from dolomite and calcite fracture fills in upper, middle and lower reservoir zones in Kuh‐e‐Mond Field, Zagros Basin, Iran. They are assumed to be persevered samples of primary oil; hence, their biomarkers were analysed to determine the maturity gradient and source facies of petroleum at the time of migration. A variety of specific parameters were obtained including n‐alkanes, hopanes, steranes from aromatic hydrocarbons in oil inclusions and reservoir hydrocarbons petroleum. The Pr/Ph ratio varies from 0.5 to 1, which is indicative of dominant reducing conditions during source rock deposition. The fluid inclusion oils with dibenzothiophene/phenanthrene ratios ranging from 0.68 to 1.4, Pr/Ph ratios from 0.8 to 1.2 and with C34/C35 ratios of homohopanes in the range from 1.1 to 1.76, suggest regional variations of organic facies in their source rocks. Biomarker parameters obtained from fluid inclusion oils differ slightly from those of reservoired oil. The biomarker data indicate that the reservoir oil in the Kuh‐e‐Mond Field was generated and expelled predominantly from carbonate–marly sources deposited in anoxic environments. A terrestrial material source seems plausible here, and the presence of C29/C27 ααα 20R steranes supports this finding. The maturity levels of fluid inclusion oils inferred from C12+ parameters are slightly higher in the dolomite and calcite cements from the upper reservoir zone, which may be due to continuous reservoir filling.
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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 | 0.001 |
| Science and technology studies | 0.001 | 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".