Validation of Global Riser/Wellhead Analysis Using Data from a Full-Scale Measurement Campaign
Bibliographic record
Abstract
Fatigue damage predictions of risers and wellhead/casing systems due to drilling operations require predictive modeling techniques for load calculation/estimation. This work attempts to address the uncertainty as to whether the global riser analyses are overly conservative due to model idealizations, analytical assumptions, the use of time- or frequency-domain techniques, and incorporation of certain linear or non-linear behavior. To address these questions, a field measurement program was executed to obtain vessel, riser and stack motions data, which were used to validate analytical models and procedures. A real-time monitoring system was deployed on a 6th generation semi-submersible mobile offshore drilling unit operating in a shallow water, harsh environment region. Accelerations and angular rates were captured on the Lower Marine Riser Package (LMRP), drilling riser and vessel. The metocean data consisting of measured seastates and full-depth current profiles, as well as riser tensions, mud weights, and vessel offsets were also concurrently recorded. The global models of the riser, wellhead, stack, casing and soils were created using two in-house software, DERP (frequency-domain) and RAMS (both frequency- and time-domain), using "as-designed" input information. Analytically predicted motions (displacements and rotations) of the LMRP, riser, and vessel were compared with the measured motions. It was found that the frequency-domain analytical results match the measured data well over all the measured significant wave heights, which ranged from 6.5-ft to 26-ft. Since the riser and LMRP RMS motions are well predicted by models, it follows that wellhead loads are well estimated from analytical models. The frequency-domain analytical results were further verified for a few cases by time-domain analyses. Both measured and analytical spectra generally exhibit peaks at similar frequencies. While the first analytical riser mode is clearly identified in the measured data, the analytical blow out preventer (BOP) stack/riser mode is not as evident in the measured data. Further, the measured peak close to the analytical stack/riser frequency is very broad. These observations and additional sensitivity studies showed that further investigation for sources of damping due to soil and/or stack hydrodynamics is required. This work shows that the modeling techniques used presently for analyzing the global riser/stack response in frequency- domain are reasonably accurate for the analyzed conditions.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".