Structural style and hydrocarbon prospectivity in fold and thrust belts: a global review
Bibliographic record
Abstract
Abstract A statistical analysis of reserves in fold and thrust belts, grouped by their geological attributes, indicates which of the world's fold and thrust belts are the most prolific hydrocarbon provinces. The Zagros Fold Belt contains 490f reserves in fold and thrust belts and has been isolated during the analysis to avoid bias. Excluding the Zagros Fold Belt, most of the reserves are in thin-skinned fold and thrust belts that have no salt detachment or salt seal, are partially buried by syn- or post-orogenic sediments, are sourced by Cretaceous source rocks and underwent their last phase of deformation during the Tertiary. A significant observation is that the six most richly endowed fold and thrust belts have no common set of geological attributes, implying that these fold belts all have different structural characteristics. The implication is that deformation style is a not critical factor for the hydrocarbon endowment of fold and thrust belts; other elements of the petroleum system must be more significant. Other fold and thrust belts may share the structural attributes but the resource-rich fold belts overwhelmingly dominate the total reserves in that group of fold belts. There is nothing intrinsic in fold and thrust belts that differentiates them from other oil- and gas-rich provinces other than the prolific development of potential hydrocarbon traps. Many of the prolific, proven fold and thrust belts still have significant remaining exploration potential as a result of politically challenging access and remote locations.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".