Seismic attribute expression of differential compaction
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Bibliographic record
Abstract
In a marine environment, topographic features on the sea floor will usually be covered by a thick layer of shale with the rise of sea level, resulting in a uniform, nearly flat surface. Evaporating seas may bury sea-floor topography with a thick layer of salt. In a fluvial-deltaic environment, channels are cut and filled with a lithology that may be different from that through which it is cut, followed by subsequent burial with (perhaps) a more uniform sedimentary layer. With continued burial and overburden, pore sizes are reduced and water is squeezed out of the rocks, reducing the rock volume. Different lithologies have different original porosity, pore shapes, and mineral matrix composition, and thus different responses to burial. Lateral changes in lithology give rise to lateral changes in compaction, or simply “differential compaction.” For this reason, easily mapped flooding and other surfaces that were originally flat can exhibit measurable, and often significant structural relief. These maps give rise to lateral “structural” anomalies. Recognition of differential compaction forms a key component in modern seismic interpretation workflows based on geomorphology with excellent publications showing the expression of differential compaction on vertical slices. Mapping the 3D expression of compaction features takes considerable time and is thus less well reported while the use of 3D geometric attributes to map compaction features is underutilized. In this article, we illustrate the attribute expression of the more common differential compaction features over channels and carbonate reefs using examples from the Western Canadian Sedimentary Basin.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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 it