Space-time continuum in seismic stratigraphy: Principles and norms
Bibliographic record
Abstract
Seismic stratigraphy is not only a geometric understanding of a stratigraphic succession, but it also has a close link to the space-time continuum started by H. E. Wheeler (1907–1987). The science follows the fundamental principles of stratigraphy, and the norms that govern seismic interpretation play a fundamental role due to their practical significance. The birth of computer-aided algorithms paved a new platform for seismic interpretation. The ideas from A. W. Grabau (1870–1946) and Wheeler were brought to a new level when space-time continuum was represented using 3D seismic data. This representation is commonly referred to as the Wheeler transformation, and it is based on flattening theories. Numerous algorithms have been introduced. Each suffers from its own problem and follow some assumption. The hydrocarbon industry, as well as academia, should seek a solution that is globally applicable to a stratigraphic succession irrespective of resolution, geologic challenges, and depositional settings. We have developed a review of the principles and norms behind these algorithms assisting in developing the space-time continuum of a stratigraphic succession using 2D/3D seismic data.
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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 | 0.006 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.002 | 0.018 |
| Scholarly communication | 0.006 | 0.009 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".