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Record W2748217070 · doi:10.1071/aj13030

Environmentally acceptable surfactants applied for water-based paraffin control—novel technologies sustaining production of challenging Australian crudes

2014· article· en· W2748217070 on OpenAlexaff
Farrell Backus, Hans Oschmann, M. Gunn, Evan Harvey

Bibliographic record

VenueThe APPEA Journal · 2014
Typearticle
Languageen
FieldChemistry
TopicPetroleum Processing and Analysis
Canadian institutionsNalco (Canada)
Fundersnot available
KeywordsEnvironmentally friendlyWaxParaffin waxEnvironmental scienceProduced waterWaste managementPetroleum engineeringPulp and paper industryMaterials scienceEnvironmental engineeringGeologyEngineeringComposite material

Abstract

fetched live from OpenAlex

The use of environmentally acceptable surfactants in water-based products—as opposed to hydrocarbon-based products—offers significant benefits both from an environmental and performance perspective. Water, being a polar solvent, has a very limited capacity to dissolve non-polar hydrocarbons; however, a new generation of environmentally acceptable, novel surfactants has allowed the development of water-based wax removal technology that effectively penetrates layers of waxy deposits, and dissolves and disperses the removed paraffin. A conspicuous property of this new water-based paraffin remover is its ability (similar to some corrosion inhibitors) to migrate over surfaces resulting in the treatment of deposits not originally wetted by the product. The continuous application of environmentally acceptable surfactants in multiphase transport systems has not only prevented paraffin deposit formation but also has allowed for the removal of persistent paraffin deposits. These new chemistries have had excellent success in many areas, including Australian production fields. Cooper Basin field studies have shown that the application of these surfactants have significantly increased production through reduced downtime during winter months where high wax content producing wells traditionally would shut down due to flow line restrictions. This paper will review the selection and the application of these new surfactants in two Australian field locations.

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)0.001
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 score0.026
Threshold uncertainty score0.418

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.015
GPT teacher head0.228
Teacher spread0.213 · 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
Published2014
Admission routes1
Has abstractyes

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