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Record W2799866148 · doi:10.4043/28695-ms

Hebron Offshore Development Project Overview

2018· article· en· W2799866148 on OpenAlexaffabout
K.J. Wolfe, G. J. Parker, Sandra Sellars

Bibliographic record

VenueOffshore Technology Conference · 2018
Typearticle
Languageen
FieldEngineering
TopicOffshore Engineering and Technologies
Canadian institutionsExxonMobil (Canada)
Fundersnot available
KeywordsSubmarine pipelineGeologyOceanography

Abstract

fetched live from OpenAlex

The Hebron Offshore Development Project, offshore Eastern Canada, is one of the world's most ambitious oil projects. In November 2017 ExxonMobil Canada Properties (EMCP) commenced oil production from this world scale engineering marvel located in 93m of water approximately 350 kilometers southeast of St. John's NL in an area known as the Grand Banks. The Hebron platform consists of a Gravity Based Structure (GBS) with a storage capacity of 1.2 million barrels of oil and an integrated steel topsides structure. The integrated topsides design with total operating weight capacity of ~65,000 t contains drilling and production facilities with a peak production capacity of 150,000 barrels per day (bpd) and a living quarters for 220 people. The field infrastructure also includes a subsea Offshore Loading System (OLS) providing crude offloading capability to tankers and a fiber optic cable loop linking the offshore platform to an onshore network enabling enhanced digital technology implementation. The project was sanctioned on 31 December 2012 and first oil occurred on 27 November 2017, ahead of schedule. This paper discusses the Project from design through execution and highlights several of the unique design features, execution sequence and specific challenges which were faced. Special technologies were employed and project management initiatives implemented which enabled the success of the project.

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)0.002
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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.235
Threshold uncertainty score0.468

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0020.000
Scholarly communication0.0040.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0360.010

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 head0.031
GPT teacher head0.254
Teacher spread0.223 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations7
Published2018
Admission routes2
Has abstractyes

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