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Record W2030416238 · doi:10.2118/74651-ms

Innovative Concept to Reduce the Total Cost of Scale Management through the Capture and Re-Use of Chemical Inhibitors

2002· article· en· W2030416238 on OpenAlexaff
N. D. Feasey, G. C. Graham, G. Seland, Robert Stalker

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMaterials Science
TopicCalcium Carbonate Crystallization and Inhibition
Canadian institutionsNalcor Energy (Canada)
Fundersnot available
KeywordsBrineProcess engineeringSCALE-UPEnvironmental scienceScale (ratio)ChemistryComputer scienceEngineering

Abstract

fetched live from OpenAlex

Abstract Conventional scale inhibitor squeezes are widely used to prevent or delay scale formation. Although long established the process can be wasteful of chemical used. In common with the use of most production chemicals such treatments are ‘once through’ and non-recoverable with high operating costs. In addition in offshore operations such production chemicals are discharged into the sea. Such discharges are also subject to environmental legislation with associated costs. Increasingly there is a need to avoid such discharges. Modifications of the squeeze procedure have been introduced to extend squeeze lifetime but further improvements are still sought. This paper describes the results of a study to investigate the potential for membrane separation to capture a representative scale inhibitor from brine. Over a range of temperatures, scale inhibitor concentrations and brine chemistries more than 96% of the scale inhibitor was captured. This was obtained without any attempt to optimise operating conditions. The resulting captured material was compared to the original product using dynamic tube blocking tests and static barium sulphate tests. The static tests showed similar performance for recovered and initial material, while the dynamic tests showed a marginal increase in performance for the recovered material in some cases. This increase in performance correlates with the retention factor for each given test run. It is believed that this is due to a slight purification of the inhibitor during the separation process, as shown by Dionex Ion Chromatography. The effective performance of the recovered inhibitor suggests that it could be re-used in a similar manner to the original product.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.039
Threshold uncertainty score0.682

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)0.0010.000

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 head0.029
GPT teacher head0.254
Teacher spread0.225 · 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 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
Published2002
Admission routes1
Has abstractyes

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