Real-Time Digital Interpretation of Subsea-Blowout-Preventer Tests
Bibliographic record
Abstract
Summary A computer-based method expedites interpretation of pressure data during subsea blowout-preventer (BOP) tests. This can reduce the time and cost of current subsea-BOP testing practices in a safe and objective manner. Currently, individual tests can require more than 1 hour of shut-in time, and a complete series of subsea-BOP tests may comprise at least 12 individual tests. The digital method employs computer software to produce an accurate model of the pressure-decline behavior relatively early in each test. The model can thus predict if future pressures will stabilize at an acceptable level. With regulatory approval and a reliable method to forecast pressure, the duration of subsea-BOP tests can be reduced significantly. Comparison of the digital method to conventional subsea-BOP testing on numerous field trials shows excellent agreement. If implemented, the digital method could save hours of valuable critical-path rig time during every series of subsea-BOP tests. Working in concert with regulatory authorities to gain endorsement of this method is integral to the project. Functionality of the software, example results, and implementation status are reported.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 | 0.001 |
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 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".