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Record W1998630911 · doi:10.4043/22088-ms

Analysis and Solutions for Warm-Up of Insulated Offshore Arctic Pipelines During Winter Construction

2011· article· en· W1998630911 on OpenAlexaff
Ben Eisler, Mac McKee

Bibliographic record

VenueOTC Arctic Technology Conference · 2011
Typearticle
Languageen
FieldEngineering
TopicOffshore Engineering and Technologies
Canadian institutionsIntecsea (Canada)
Fundersnot available
KeywordsSubseaPipeline transportSubmarine pipelinePipingArcticMarine engineeringEnvironmental scienceThermal insulationPipeline (software)Flow assuranceHeat transferSeawaterPetroleum engineeringEngineeringGeologyGeotechnical engineeringMechanical engineeringOceanographyEnvironmental engineeringMaterials science

Abstract

fetched live from OpenAlex

Abstract Offshore Arctic development presents unique challenges. Typical oil and gas pipeline designs used in other regions of the world can bring with them unforeseen consequences in the arctic. Such is the case of pipeline thermal insulation. Thermal insulation, in the form of an external foam coating or a pipe-in-pipe (PIP) configuration limits heat transfer from warm operating pipelines to the colder environment and improves flow assurance performance. However, the insulation also slows the heat absorption by the pipeline as it enters the water during winter on-ice construction, which is a field-proven installation method used to install three subsea pipelines on the North Slope of Alaska. Historically, the industry assumed that un-insulated pipelines installed from floating ice into seawater filled trenches during winter will warm up from the subzero arctic air temperatures to the warmer seawater temperature in a matter of minutes. This assumption has been validated by thermo-dynamic calculations and OLGA verification simulations. These analyses also show that one or more days may be required to warm an insulated pipeline to the warmer seawater temperature during the same installation conditions. As a result, the pipeline steel may either need to be heated prior to lowering into the flooded trench or a lower as-installed pipeline temperature may need to be assumed in pipeline design calculations. An arctic pipeline that is installed and backfilled with a colder installation temperature than expected in design calculations will develop a larger differential temperature between its as-installed temperature and its maximum design operating temperature. Larger axial compressive forces will develop in a pipeline system with a larger differential temperature. These forces, combined with vertical imperfections in the pipeline trench, may lead to upheaval buckling and potential exposure of the pipeline to ice contact and other failure modes. Thus, properly accounting for the potential as- installed pipeline temperature is an important design task. This paper summarizes the analytical work for determining warm-up times and ultimate as-installed pipeline temperatures for arctic subsea pipelines installed in winter, as well as the application of pipeline heating solutions to the thermal challenges of constructing and installing an insulated arctic subsea pipeline in winter. Introduction Three offshore Beaufort Sea developments on Alaska's North Slope have had their associated subsea pipelines installed in the winter from floating and bottom fast ice. These three projects are BP Northstar (2000) [Ref. 6 & 7], Pioneer Oooguruk (2007) [Ref. 5], and Eni Nikaitchuq (2009) [Ref. 4]. Northstar had a 10-inch single phase oil pipeline and a 10-inch single phase gas pipeline, both un-insulated, installed as a bundle (Figure 1). Oooguruk and Nikaitchuq each had a three phase Pipe-In-Pipe (PIP) pipeline, a foam insulated water injection pipeline, a single phase gas / spare pipeline, and an arctic heating fuel pipeline (Figure 2).

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.020
GPT teacher head0.205
Teacher spread0.185 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations3
Published2011
Admission routes1
Has abstractyes

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