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Record W3134152133 · doi:10.2118/204017-ms

Increasing Well Efficiencies While Lowering Carbon Emissions Through the Use of Releasable Mooring System

2021· article· en· W3134152133 on OpenAlexaff
Jason Pasternak, John T. Shelton, Jan Petter Leirvåg

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicOffshore Engineering and Technologies
Canadian institutionsDelmar (Canada)
Fundersnot available
KeywordsCarbon footprintEnvironmental scienceMarine engineeringMooringSubmarine pipelineOperational costsEngineeringGreenhouse gasOceanographyGeologyGeotechnical engineeringOperations research

Abstract

fetched live from OpenAlex

Abstract Releasable Mooring Systems ("RMS") have been in use for over 35 years in the offshore industry, with an original purpose of rapidly releasing lines to avoid weather events, such as ice floes, hurricanes, or cyclones. With the recent introduction to industry of fully redundant release tools with higher release load capabilities, the RMS concept is now being used in well planning efficiencies. The objective of the paper is to show the effectiveness of the latest enabling tool and RMS concept in reducing the time to unmoor, removing the requirement for an Anchor Handling Tow Supply (AHTS) vessel, and assisting Dynamically Positioned (DP)/Moored semisubmersibles in lowering their carbon footprint, operational costs and HSE exposure.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.499
Threshold uncertainty score0.467

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 head0.026
GPT teacher head0.196
Teacher spread0.170 · 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 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

Citations1
Published2021
Admission routes1
Has abstractyes

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