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Record W2175436889 · doi:10.2118/175441-ms

Detailed Approach for the Assessment of Accumulated Wellhead Fatigue

2015· article· en· W2175436889 on OpenAlex
Kingsley Sunday, Phil Ward, Cary Griffin, Peter Lorenson

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSPE Offshore Europe Conference and Exhibition · 2015
Typearticle
Languageen
FieldEngineering
TopicOffshore Engineering and Technologies
Canadian institutionsApache (Canada)
Fundersnot available
KeywordsSubseaWellheadWorkoverReliability engineeringComputer scienceEngineeringMarine engineeringEnvironmental sciencePetroleum engineering

Abstract

fetched live from OpenAlex

Abstract This paper presents a case study of the use of an enhanced analytical approach, combined with the use of structural monitoring, as an enabling technique in the planning of sidetrack operations on a well in 110m water depth in the Northern North Sea. Subsea wellheads are fatigue sensitive structures due to their exposure to dynamic loading transferred from connected riser systems. Intervention and workover operations over the life span of the well each contribute to the total fatigue damage accumulated in components that cannot be readily inspected. Accurate assessment of fatigue damage accumulation in ageing wells using advanced analytical techniques is often necessary to quantify the residual life of these components. The ability to reliably estimate this life can greatly affect the planning and viability of operations to enhance the productivity of ageing wells, particularly in the North Sea. A simplified screening approach to wave and current fatigue assessment, typically applied to new-drill wells, with comparatively fatigue resistant hardware is unlikely to be sufficient to provide the level of confidence required when planning intervention operations on a brownfield development featuring less fatigue resistant hardware. Further sophistication, more involved than the typical approach, is necessary to avoid over-conservatism and to provide confidence to proceed with the planned operations. To thoroughly assess the fatigue accumulation in an ageing well, a detailed operational history including hindcast or measured weather data is usually sourced. The assessment is conducted to ensure that the actual operational conditions during periods when risers were connected are as accurately represented as possible. However, this may not be sufficient to bring the resulting fatigue damage within the allowable limits set using the traditional code-defined factor of safety approach. In this scenario further analytical methods are required. The use of pre and post-failure analysis and the development of a monitoring strategy to maximise both the likelihood of identifying a fatigue failure during the operations and the ability to subsequently calibrate the analytical models are discussed. The applicability of these techniques to other operations and geographical locations is also described.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.786
Threshold uncertainty score0.410

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.072
GPT teacher head0.279
Teacher spread0.207 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it