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Record W2069599024 · doi:10.2118/121723-ms

Biodegradable Alternatives for Scale Control in Oilfield Applications

2009· article· en· W2069599024 on OpenAlexaff
Stuart Holt, Jannifer Sanders, Klin Rodrigues, Matthew Vanderhoof

Bibliographic record

VenueSPE International Symposium on Oilfield Chemistry · 2009
Typearticle
Languageen
FieldMaterials Science
TopicCalcium Carbonate Crystallization and Inhibition
Canadian institutionsAkzoNobel (Canada)
FundersAkzoNobel
KeywordsScale (ratio)Biochemical engineeringBiodegradationPolymerEcotoxicityProcess engineeringEnvironmental scienceChemistryEngineeringOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract Environmental legislation has significantly reduced the variety of scale inhibitor chemistries that can be used to prevent inorganic scale formation during the production and separation of crude oil from produced water. Poor ecotoxicity has severely impeded the use of phosphonates, while many polymers, the other traditional approach to scale control, fail to meet minimum biodegradation requirements. We have developed biopolymers based on synthetic/natural polymer hybrids that show enhanced biodegradation, are environmentally benign and are much less reliant on non-renewable monomer feedstocks than classical polymer scale inhibitors. As well as being more sustainable, this novel technology allows the inclusion of a broad range of functional groups that can be designed to meet the varying technical demands of oilfield scale inhibitor application environments. Various hybrid polymers have shown excellent performance under standard oilfield performance testing conditions versus a range of currently used chemistries. Some distinct benefits of hybrid technologies pertaining to oilfield scale control will also be expanded upon.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

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)0.0020.000

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 head0.008
GPT teacher head0.254
Teacher spread0.246 · 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 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

Citations16
Published2009
Admission routes1
Has abstractyes

Explore more

Same venueSPE International Symposium on Oilfield ChemistrySame topicCalcium Carbonate Crystallization and InhibitionFrench-language works237,207