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Record W2746247899 · doi:10.1016/j.egypro.2017.03.1671

Corrosion and Failure Assessment for CO2 EOR and Associated Storage in the Weyburn Field

2017· article· en· W2746247899 on OpenAlexfundno aff
Jason Laumb, Kyle Glazewski, John Hamling, Alexander Azenkeng, Nicholas Kalenze, Theresa L. Watson

Bibliographic record

VenueEnergy Procedia · 2017
Typearticle
Languageen
FieldEngineering
TopicDrilling and Well Engineering
Canadian institutionsnot available
FundersPetroleum Technology Research CentreU.S. Department of Energy
KeywordsCasingCorrosionPetroleum engineeringEnhanced oil recoveryWellboreOil fieldFossil fuelEnvironmental scienceWaste managementEngineeringMaterials scienceMetallurgy

Abstract

fetched live from OpenAlex

Many depleted oil and gas reservoirs are targets for commercial CO2 enhanced oil recovery, resulting in associated CO2 storage which occurs as part of the process. These oil fields have legacy wellbores that may contain a leakage pathway. Corrosion or degradation can occur anywhere along the wellbore through or along the cement, casing, tubing, or plugs and is a challenging issue facing the oil and gas industry. Two case studies presented here are legacy wells in the Weyburn oil field with substantially different CO2 injection rates. These case studies aim to help understand casing corrosion in CO2-rich environments.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.388
Threshold uncertainty score0.284

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 head0.006
GPT teacher head0.217
Teacher spread0.211 · 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

Citations15
Published2017
Admission routes1
Has abstractyes

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