An integrated ichnological and sedimentological comparison of non-deltaic shoreface and subaqueous delta deposits in Permian reservoir units of Australia
Bibliographic record
Abstract
Abstract Permian sequences in the Denison Trough of Queensland, eastern Australia, are productive conventional gas reservoirs. Previous attempts to interpret the reservoir bodies in terms of depositional environments have relied largely on sedimentary facies analysis and palynology. Sequences have been re-evaluated from a detailed, integrated ichnological and sedimentological perspective, resulting in a significant increase in the precision and resolution of the palaeoenvironmental interpretation. Various marine, coastal and upper delta plain deposits are recognized. Ichnological signatures have facilitated the differentiation of subaqueous delta deposits from those deposited in non-deltaic offshore and shoreface environments. Delta front facies are further subdivided by integrating ichnological and sedimentological data. Permian offshore and shoreface successions in the Denison Trough contain ichnological signatures that exhibit high diversities (25 ichnogenera comprising 32 ichnospecies), moderate to intense levels of bioturbation, uniformity of burrowing, and a wide variety of structures representing specialized feeding strategies. Examples from an additional reservoir dataset, the Tern Formation from the offshore Bonaparte Basin in north Western Australia, also clearly demonstrate the ichnological complexity of Permian shoreface successions. In contrast, Permian deltaic deposits contain ichnological signatures that reflect stressed environmental conditions. Assemblage diversity is reduced (16 ichnospecies), bioturbation intensity is significantly reduced, and uniformity of burrowing is sporadic.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".