The Role of Shale Pore Structure on the Sensitivity of Wire-Line Logs to Overpressure
Bibliographic record
Abstract
Abstract Petrophysical characteristics of shales have been analyzed to improve our understanding of wire-line log response to overpressure. Bulk density and neutron porosity logs sometimes mask pore-pressure increases that are clearly evident on sonic and resistivity logs. This may be because sonic and resistivity logs respond to transport properties, whereas neutron and density logs reflect bulk properties. Results of this study indicate that shale pore structure can be characterized by a storage-connecting pore system, with connecting pore sizes on the order of 2–20 nm. Laboratory compaction tests indicate that connecting pores are mechanically more flexible compared to storage pores and are likely to have lower aspect ratios. Consequently, connecting pores are likely to undergo more elastic rebound (widening) compared to storage pores as a result of effective stress reductions caused by overpressure. Essentially, these results provide evidence that suggest sonic and resistivity logs respond to transport properties, whereas neutron and density logs reflect bulk properties, as previously proposed. This suggests that, whereas overpressure resulting from compaction disequilibrium may be detected by all four logs, fluid expansion overpressure may be best detected by sonic and resistivity logs.
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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 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".