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Record W2043091482 · doi:10.4043/23849-ms

A New High Strength Drill Pipe Maximizing Safety and Performance in Low Temperature Environment

2012· article· en· W2043091482 on OpenAlexaboutno aff
Kamal El Bachiri, Philippe Machecourt

Bibliographic record

VenueOTC Arctic Technology Conference · 2012
Typearticle
Languageen
FieldMaterials Science
TopicMaterial Properties and Failure Mechanisms
Canadian institutionsnot available
Fundersnot available
KeywordsDrillArcticDrillingEnvironmental scienceSubmarine pipelineThe arcticDrill pipeFossil fuelPetroleum engineeringMarine engineeringMining engineeringGeologyOceanographyEngineeringWaste managementMechanical engineering

Abstract

fetched live from OpenAlex

ABSTRACT The five Arctic regions of Russia, Alaska, Norway, Greenland and Canada holda tremendous potential for both discovered and undiscovered reserves of Oil andGas. The USGS estimates 160 BBO, and 1,670 TCF of natural gas reserves in theArctic, with most of these reserves being located offshore. The Arctic region, however, presents its own unique challenges; extreme low surface temperatures, a highly fragile environment protected by strict regulatory controls, very highcost of operations - and of failure prevention, and a narrow weather window tooperate. Combined, these challenges leave no room for complacency whileplanning an Arctic drilling campaign. The drilling tubular risks are mainlyaccentuated during transportation, storage, and surface handling in thepermafrost region. In order to drill safely and reliably in such harsh surfaceconditions, ordinary drillstring solution is neither considered safe norreliable due to the adverse and unpredictable effect of extereme lowtemperatures on mechanical properties of steel. VAM Drilling has successfullydeveloped and deployed proprietary Arctic steel grades that deliver a greatcombination of strength and ductilitly at temperatures as low as −60°C(−76°F).

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.999

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)0.0020.000

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 head0.007
GPT teacher head0.177
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.

Study designBench or experimental
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
Published2012
Admission routes1
Has abstractyes

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