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Record W3132963576 · doi:10.2118/spe-169773-ms

Scale Inhibitor Residual Analysis: Twenty-first Century Approach

2014· article· en· W3132963576 on OpenAlexaff
Y.. Zhang, J. K. Daniels, J.. Hardy-Fidoe, C.. Durnell, M. E. Broussard, Edwin H. Hammond, Xiaoran Huang

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMaterials Science
TopicCalcium Carbonate Crystallization and Inhibition
Canadian institutionsNalco (Canada)
Fundersnot available
KeywordsSubseaPetroleum engineeringScale (ratio)Flow assuranceSubmarine pipelineEnvironmental sciencePetroleum industryInjection wellProcess engineeringMarine engineeringEngineeringChemistryEnvironmental engineeringGeotechnical engineering

Abstract

fetched live from OpenAlex

Abstract Control of inorganic scale deposition within the near well bore area under both natural depletion and injection water support has been a challenge to the oil industry for a number of decades. The application of scale inhibitor squeeze treatments to production wells to control the onset of inorganic scale within the near-wellbore and production tubing has been a common practice within the onshore and offshore oil and gas industry for over 30 years. The development of subsea fields require scale inhibitor squeeze treatments with extended squeeze lifetimes while limited number of flowlines to the host facility has increased the difficulty in obtaining and evaluating individual well water samples from which residual scale inhibitor concentrations are derived. Traditional analytical techniques, while robust and widely accepted, do not provide differentiation between scale inhibitors that belong to the same chemical family (i.e.: two or more phosphonates or two or more polymers). The individual analysis of phosphonate scale inhibitors in co-mingled flow backs from subsea wells is a particularly challenging application for analytical techniques in the industry. Advances in separation and mass detection techniques, however, provide new options to accurately measure the concentration of scale inhibitors in these fluids to very low detection limits. This paper will describe the analytical development of these new techniques and discuss its implication to the optimization of scale squeeze treatments in subsea, deepwater developments.

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 score0.254
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
Bibliometrics0.0000.001
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 head0.010
GPT teacher head0.220
Teacher spread0.210 · 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
Published2014
Admission routes1
Has abstractyes

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