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Record W2467419897 · doi:10.5006/c2016-07184

Corrosivity of Produced and Make-up Water in Oil Sands Thermal Water Treatment Systems

2016· article· en· W2467419897 on OpenAlexaff
Tesfaalem Haile, John Wolodko, Lisa Sopkow, Haralampos Tsaprailis

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldChemistry
TopicPetroleum Processing and Analysis
Canadian institutionsAlberta Innovates
Fundersnot available
KeywordsCorrosionProduced waterPetroleum engineeringThermalEnvironmental scienceWater coolingWater treatmentMaterials scienceMetallurgyWaste managementEnvironmental engineeringGeologyEngineeringMechanical engineeringMeteorology

Abstract

fetched live from OpenAlex

Abstract Water treatment systems used to recycle produced water and/or make-up water for the production of steam used in the SAGD and CSS processes have noted failures associated with erosion-corrosion, under deposit corrosion, and fouling/scaling. Oil sands operators employ corrosion monitoring tools, chemical treatment, and/or material selection to resolve integrity related issues. However, the unpredictable occurrences of serious corrosion issues related to the complex and constantly changing water chemistries make it difficult to choose the appropriate preventative and mitigation strategies. This is further complicated by the effects of operating conditions; such as temperature, pressure, and flow geometry. This paper presents the corrosivity of model/simulated produced and make-up (brackish) water to UNS G10180 carbon steel. Rotating cylinder electrode methodology was used to determine the general corrosion rates using linear polarization resistance technique. The corrosion rate in the model brackish water system was low for the investigated environmental conditions. However, as the pH of the systems was reduced from 8 to 6, the corrosion rate became high (0.8 mm/yr). Similarly, dissolved oxygen (DO) ingress was found to increase the general corrosion rate. However, only DO ≥ 8,000 ppb led to localized (pitting) corrosion (0.6 mm/yr). Contrary to model brackish water corrosivity, oxygen ingress as low as 120 ppb triggered localized corrosion in the simulated produced water system.

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 score0.006
Threshold uncertainty score0.012

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 head0.011
GPT teacher head0.217
Teacher spread0.206 · 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

Citations2
Published2016
Admission routes1
Has abstractyes

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