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Record W2059329283 · doi:10.2118/163499-ms

Subsea Cap & Contain Method for a Deepwater Tension Leg Platform

2013· article· en· W2059329283 on OpenAlexaff
John Henley, Tammy Webb, Chris Wibner, James Soliah

Bibliographic record

VenueAll Days · 2013
Typearticle
Languageen
FieldEngineering
TopicOffshore Engineering and Technologies
Canadian institutionsDelmar (Canada)
Fundersnot available
KeywordsSubseaContainment (computer programming)Marine engineeringStack (abstract data type)Software deploymentClearanceEngineeringComputer science

Abstract

fetched live from OpenAlex

Abstract A tremendous amount of effort has been placed on subsea cap and containment in order to demonstrate the exploration and production industry's response to a subsea well control event. This paper will focus on the methods and processes planned to contain a subsea blow out beneath a Tension Leg Platform (TLP) in deepwater Gulf of Mexico. Response to a well control event of this type is divided into 3 major categories: 1) TLP Health and Stability Monitoring - Understanding the structure stability is key in planning the response and determining the time allowed to deploy containment assets, 2) Debris Clearing-a path must be cleared into the well pattern horizontally and vertically for the capping stack to be deployed and 3) Stack Deployment - with the TLP still floating above the well pattern the stack must be deployed laterally under the facility and onto the well. Several challenges were encountered during the design and approval of this containment method, leading to the development of alternative capping strategies, purpose built capping stacks, installation of permanent monitoring / response equipment and use of Delmar's Heave Compensated Landing System (HCLS) to accomplish these critical subsea tasks.

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.

How this classification was reachedexpand

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.513
Threshold uncertainty score0.535

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 head0.024
GPT teacher head0.243
Teacher spread0.219 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2013
Admission routes1
Has abstractyes

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