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Record W2883959992 · doi:10.1038/s41598-018-29321-w

Spotlight on the New Natural Surfactant Flooding in Carbonate Rock Samples in Low Salinity Condition

2018· article· en· W2883959992 on OpenAlexaff
Mohammad Ali Ahmadi, Seyed Reza Shadizadeh

Bibliographic record

VenueScientific Reports · 2018
Typearticle
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsSalinityCarbonateFlooding (psychology)Pulmonary surfactantGeologyNatural (archaeology)Hydrology (agriculture)Environmental scienceMineralogyGeochemistryChemistryGeotechnical engineeringOceanographyPaleontology

Abstract

fetched live from OpenAlex

Abstract Recently, utilization of surfactant for EOR purposes in carbonate petroleum reservoirs has received the attention of many researchers. Surfactants generally appear to improve oil production through wettability alteration and reduction of interfacial tension (IFT) between oil and water phases. Loss of surfactant due to adsorption process is considered as an unfavorable phenomenon in surfactant flooding while conducting an EOR operation. In this study, a new plant-derived surfactant, called Zyziphus Spina Christi (ZSC), with various magnitudes of salinity is employed. The adsorption behavior of this surfactant is investigated using the conductivity approach to explore the impacts of salt concentration on adsorption rate through batch tests. Core flooding tests are also conducted to study the effects of surfactant/salinity on recovery factor and relative permeability. Employing the kinetics and isotherm models, MgCl 2 and KCl exhibit the greatest and lowest influence on the adsorption phenomenon, respectively. It is also concluded that the pseudo-second order kinetics and Freundlich isotherm model can satisfactorily describe the adsorption behavior of the surfactant onto carbonates in the presence of salt for the kinetics and equilibrium tests conditions, respectively. According to the production history, it is found that increasing surfactant concentration leads to a considerable increase in oil relative permeability and consequently improvement of oil recovery.

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 score0.072
Threshold uncertainty score0.478

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.012
GPT teacher head0.239
Teacher spread0.227 · 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

Citations80
Published2018
Admission routes1
Has abstractyes

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