Comparison of Riser and Well System Response Predictions to Full-Scale Measurements in a Shallow Water Harsh Environment
Bibliographic record
Abstract
Well system fatigue accumulated during drilling operations from mobile offshore drilling units (MODUs) has been a topic of intensive study in recent literature. A variety of efforts from individual operator studies to industry-wide joint industry projects have been launched in an effort to improve understanding of both the load and resistance elements of well system fatigue assessment. A key uncertainty in current predictive modeling practice is the level of conservatism inherent in that modeling, as compared to real-life system response. Collection of good quality, full-scale field measurement data is a key component in evaluating this uncertainty. A full-scale measurement campaign was recently conducted on a 6th generation MODU during drilling operations in a shallow water region with a harsh environment. The measurement system on board the vessel captured vessel, riser and lower marine riser package (LMRP) accelerations and angular rates, along with riser tensioner pressures. Concurrent environmental measurements were acquired via wave rider buoy and acoustic Doppler current profiler (ADCP) located near the mobile offshore drilling unit (MODU), capturing wave height, period and direction, and full-depth current profiles. This paper focuses on data collected for one well during the winter months where significant wave heights at the drilling site varied from 6ft to 26ft. In this paper, a comparison between measured and predicted riser and well system loading is presented. The predicted riser and well system response is based upon global riser analyses performed in both the frequency and time domains to evaluate the effect of linearization in the modeling process. Loading demand on the well system is also presented as cycle-range histograms. This paper also summarizes the conclusions from the comparisons of these measurements with other published measurement campaign data. While loading derived from previous riser analysis studies have been found to be “conservative” as compared to full-scale measurements, this study finds that the predicted and measured responses match quite well. Furthermore, it is also shown that the frequency domain results are adequate for this study, suggesting that the nonlinearity within the riser and well system for the conditions studied is relatively minor.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 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".