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Record W2616777513 · doi:10.5006/c2014-3809

Corrosion Management and Mechanism Study on SAGD Brackish Water System

2014· article· en· W2616777513 on OpenAlexaffabout
Jack Whittaker, Qiang Liu, Dave J. Brown, R. Sydney Marsden

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMaterials Science
TopicCorrosion Behavior and Inhibition
Canadian institutionsCenovus Energy (Canada)
Fundersnot available
KeywordsCorrosionBrackish waterMechanism (biology)Petroleum engineeringProduced waterEnvironmental scienceMetallurgyMaterials scienceGeologySalinity

Abstract

fetched live from OpenAlex

Abstract Brackish water (BW) is used to supplement boiler feed water in SAGD processes. In Alberta, water quality from the McMurray (McM) and Grand Rapids (GR) formations typically consists of approximately 1% salinity, 750 ppm bicarbonate and 15 ppm H2S. The carbon steel (CS) piping originally used in this service experienced severe corrosion and failures after only five years of service. General corrosion rates (CR) based on CS corrosion coupons were as high as 8 mm/year (320 mpy). Many of the failures occurred on elbows, tees and reducers. A detailed analysis of the overall process and chemistry identified unique corrosion mechanisms that existed in certain process stages. Depending upon the needs of the process, the corrosion could in fact be mitigated by controlling specific process parameters. Failure analysis showed siderite to be the main corrosion product. A novel mechanism of CO2 corrosion with impingement was proposed and manifested. In rotating cylinder electrode (RCE) tests, bicarbonate/CO2 corrosion rates accelerated from 0.125 to 1.75 mm/year (5 to 70 mpy) by increasing the cylinder rotating speed from 2,000 to 5,000 rpm. These results supported the theory that CO2 cavitation significantly aggravated corrosion. As a result, a caustic injection program was implemented in the field to control pH to 9.0 to suppress the CO2 release from the aqueous phase. Subsequent corrosion coupon data indicates a dramatic drop in corrosion rates to a range of 0.025 to 0.125 mm/year (1 to 5 mpy). In piping stages where pH control wasn’t possible for process reasons, the piping was replaced with duplex piping materials.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.013
GPT teacher head0.232
Teacher spread0.218 · 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 designObservational
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

Citations7
Published2014
Admission routes2
Has abstractyes

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