Structural styles in the Papuan Fold Belt, Papua New Guinea: constraints from analogue modelling
Bibliographic record
Abstract
Abstract Cross sections, seismic data and centrifuge analogue modelling reveal the structural styles in the oil-producing areas of the Papuan Fold Belt. They include inverted basement faults, detachment faults in the Jurassic section 1–2 km beneath the Neocomian Toro Sandstone reservoir, and tight, overturned folds in the reservoir sequence with stretched and boudinaged forelimbs, cut by break-thrusts. Additional features include highly variable thicknesses in the Cretaceous Ieru Formation, the regional seal sequence, including through-going detachments that isolate the overlying thick Miocene Darai Limestone. Centrifuge analogue modelling of intact, plane-layered strata determined that the mechanical stratigraphy and the thickness of weak beds above the lower décollement horizon exert the greatest control on the structural style. Large-offset thrust faults were only produced in models with pre-cut faults, generating early inversion and then large ramp anticlines, similar to those in the Kutubu Oilfield, which has reserves of >350 million barrels. It is suggested that the Kutubu Oilfield trend was underlain by a large normal fault and that, by analogy with the Vulcan Sub-basin, oil-rich source rocks may be confined to the hanging wall or north side of this fault. Oil would have been generated and expelled during thin-skinned deformation.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.003 | 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".