Crossing conjugate normal faults in field exposures and seismic data
Bibliographic record
Abstract
Abstract Crossing conjugate normal faults are common in many hydrocarbon-producing basins. In these settings, they exert a range of influences from trapping hydrocarbon accumulations to producing permeability anisotropy by preferentially enhancing or reducing permeability, and reducing effective thicknesses of seal and reservoir units. The fault intersection region is typically poorly imaged with seismic data, and consequently, developing a coherent interpretation of deformation in the intersection region is difficult. In this article, we explore crossing conjugate normal faults across two orders of magnitude of displacement using clear field exposures from the western United States and subsurface examples from the Jeanne d'Arc Basin, offshore Newfoundland. We demonstrate common structural elements and potential pitfalls associated with interpretation of crossing conjugate normal faults, and emphasize the widespread and often unrecognized occurrence of these structures.
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How this classification was reachedexpand
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) | 0.001 | 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 teacher head, 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".