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Record W2079225999 · doi:10.2118/172895-ms

Organic Alkali for Heavy Oil Chemical EOR Improves the Performance Over Inorganic Alkali

2014· article· en· W2079225999 on OpenAlexafffund
Dong Xie, Jian Hou, Ankit Doda, Japan Trivedi

Bibliographic record

VenueSPE International Heavy Oil Conference and Exhibition · 2014
Typearticle
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaChina Scholarship CouncilCarbon Management CanadaSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungUniversity of Alberta
KeywordsAlkali metalEthanolaminePolymerPulmonary surfactantChemical engineeringEnhanced oil recoveryMaterials scienceChemistryInorganic chemistryChromatographyOrganic chemistryComposite material

Abstract

fetched live from OpenAlex

Abstract Alkali is an important component for alkali/surfactant/polymer technology for enhanced oil recovery. The mechanism and advantages of traditional inorganic alkali for enhanced oil recovery (EOR) was reviewed in this paper. But the weakness of inorganic alkali, such as scaling, corrosion and high cost of water treatment, are significant too. This paper comparesthe use of a type of organic alkali ethanolamine for EOR with inorganic alkali (NaOH) for alkali-polymer (AP) and alkali-surfactant-polymer flooding. The solution of 0.1 wt% polymer (FLOPAAM 3130S) was mixed with different concentrations of ethanolamine and NaOH respectively. The rheological and dynamic properties of the combination of alkali and polymer were analyzed. The results show that the polymer solution with ethanolamine has better shear viscosity and elasticproperties at room temperature. Surfactant (Alfaterra 123-8S-90) with concentration of 0.15 wt% was added into each alkali-polymer solution. No significant change was observed in rheological properties of alkali-polymer solutions with and without surfactant. Emulsification test shows that ethanolamine has better performance with oil. Injectivity tests were also conducted. The results indicated that RRF for ethanolamine-polymer solution is always higher at each flow rate tested in comparison to NaOH AP solution which is beneficial for oil recovery. Core flooding experiments were tested in homogeneous sand pack and the performance of ethanolamine-polymer and NaOH-polymer was compared. The pressure comparison during flooding shows that it has higher injection pressure in ethanolamine conditions which result in good sweep efficiency. The ethanolamine-polymer flooding showed a significant increase in oil recovery (15.33%) over NaOH-polymer flooding. After addition of surfactant, the total recovery improves by 14.8% for ethanolamine-polymer-surfactant flooding over its inorganic counterpart. The results of core flooding indicate that ethanolamine has better performance in EOR for AP flooding and ASP flooding. Ethanolamine can become a potential alkali and can replace NaOH for EOR.

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 score0.006

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 head0.010
GPT teacher head0.233
Teacher spread0.223 · 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

Citations10
Published2014
Admission routes2
Has abstractyes

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