Application of a New Dynamic Tubular Stress Model With Friction
Bibliographic record
Abstract
Abstract A new dynamic model for casing and tubing design with friction has been developed. This paper applies the model to a field case study, an actual installation of a single trip, multizone completion in an offshore highly deviated ERD well. This is the first application of a comprehensive model with complete friction history to both installation and in-service loads. The field case demonstrates the results of a novel dynamic model for tubular stress and displacement with changing friction loads. Recorded hookload data during completion running and calibration of effective wellbore friction coefficients provided validation of the model. Accumulation of localized stresses at critical well locations is considered. The sensitivity of worst case downhole forces to the order of operational life cycle loads including stimulation, production and gas-lift was assessed. Stresses and displacements associated with each step of the setting process for multiple isolation packers were simulated. Theory and detailed description of the dynamic model are presented in an associated paper. A dynamic model of tubing forces is necessary to predict local pipe velocity which in turn determines the magnitude and direction of the local friction vectors. Distribution and orientation of wellbore friction contact is determined by the pipe running events but then is subject to change as cement and packers are set and as downhole operating conditions change. Order of life cycle conditions such as stimulation followed by production versus production followed by workover has significant impact on the magnitude of forces at worst-case locations. The investigation included the change in tubing wellbore frictional contact when completion brine is displaced with dry injection gas in conversion to gas-lift. The model demonstrated the significance of a different order of linked operations and showed that the standard available analysis tools may overlook or fail to identify worst case loads. Potential for acute load localization due to successive stimulation and production events was quantified. Impact of migration of friction loads during cyclical load events was also evaluated. The predicted initial axial load profiles were verified with recorded hook loads and corroborated with standard torque and drag model results. Comparisons are made against a previously published analytical technique. For the first time, a dynamic friction model enables seamless integration of running loads into a fully sequential analysis of subsequent well life cycle loads for landed strings. Current industry models tend to separate installation loads from the in-service life envelope. Ability to predict the changing friction orientation on installed tubulars is significant. Modelling life cycle loads in true sequence provides more accurate results for tubular design and enables a true analysis on the real-world order of well events.
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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 | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".