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Record W2064103634 · doi:10.2118/170600-ms

Floating LNG Chain - Finally a Reality

2014· article· en· W2064103634 on OpenAlexaff
Michael S. Choi

Bibliographic record

VenueSPE Annual Technical Conference and Exhibition · 2014
Typearticle
Languageen
FieldEngineering
TopicOffshore Engineering and Technologies
Canadian institutionsConocoPhillips (Canada)
FundersConocoPhillips
KeywordsSubseaCatenaryMarine engineeringWellheadSubmarine pipelineEngineeringLiquefied natural gasWinchEnvironmental scienceAeronauticsPetroleum engineeringMechanical engineeringNatural gasWaste management

Abstract

fetched live from OpenAlex

Abstract It was more than a decade ago that the visionaries of Project Azure predicted that possibly by 2004, a complete floating LNG chain could be built including floating FPSO (FLNG) and a floating LNG FSRU (Floating Storage, Regasification Unit), linked by LNG shuttle tankers transporting LNG from the FLNG to the FSRU. Today in 2014, the chain still does not exist. Although there are many floating LNG receiving terminals operating successfully around the world, the elusive FLNG has still not materialized. However, now that construction has started on Shell’s Prelude and Petronas’s PFLNG-1, realization of the vision of floating LNG chain is imminent. Many technology advancements have combined to make floating LNG chain a reality. Maturation of subsea well and control systems have mitigated the risks of subsea well operations. Proven glycol (MEG) and other regenerative hydrate management systems have allowed longer tie-back distance. Cost-effective mooring systems for large FPSO, flexible flow-lines and catenary risers have enabled floating system of FLNG size to be seriously considered. However, it is the advance of floating LNG technologies that have evolved over the past 20 years that finally tipped the risk-reward equation. Technologies such as offshore ship-to-ship LNG transfer, motion tolerant processing and rotating equipment, LNG spill and gas safety, and deep water cooling water lift systems have matured to an acceptable level. The rewards of FLNG are very compelling. Major cost savings can be achieved by eliminating: Well head/production platform(s)Processing platform to facilitate gas treating, liquids recovery and stabilizationFSO for condensate and NGL productsGas compressor and pipeline to transport gas to an onshore LNG plant and replace with a FLNG system located in the field. There are also the intangible cost savings such as efficiency gains by constructing the entire system in a ship yard, material and manpower logistics, and shorter project duration. In places where space constraint and regulatory restrictions make land-based LNG liquefaction and regasification difficult, FLNG and FSRU are cost-effective alternatives. This paper will present the economics drivers that make floating LNG chain attractive to producers and buyers alike, and the many conventional production technologies and those unique to FLNG that combined to enable FLNG chain to be developed with confidence. The realization of floating LNG chain will enhance the economics of LNG as a preferred fuel.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.483
Threshold uncertainty score0.527

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 head0.016
GPT teacher head0.228
Teacher spread0.212 · 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 designTheoretical or conceptual
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

Citations0
Published2014
Admission routes1
Has abstractyes

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