Rock Strength Prediction for CCS of Hith and Arab Evaporite Seals Based on Wireline Log Signature
Bibliographic record
Abstract
Summary It is very expensive to acquire core or side-wall core during drilling operations. However, for accurate rock strength prediction this is often a must. With the onset of projects for carbon capture and storage (CCS), it is becoming increasingly important to understand seal integrity of potential CO2 storage sites. This is also the case for the Hith and Arab anhydrite formations, that are being targeted as important seals for CO2 that is injected into the carbonates of the Arab Formation in Saudi Arabia and the wider Middle East region. Thus, developing methods that make it easier and faster to predict seal integrity during drilling operations, will help to mitigate the risks associated with seal failure that could result in harmful CO2 leakage to the surface. This paper focuses on using wireline logs to predict rock strength of the Hith and Arab Formation evaporites (anhydrites), without the need of taking costly and time consuming core during drilling. Since the anhydrite is a very hard lithology, any weakness in the seal will point to higher contents of carbonate and/or dolomite within the sealing formation and a potential hazard for seal failure when the CO2 is injected.
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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 | 0.001 | 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) | 0.002 | 0.001 |
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".