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Record W2383961276 · doi:10.1021/acs.iecr.6b01187

Role of Particle Size and Surface Acidity of Silica Gel Nanoparticles in Inhibition of Formation Damage by Asphaltene in Oil Reservoirs

2016· article· en· W2383961276 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueIndustrial & Engineering Chemistry Research · 2016
Typearticle
Languageen
FieldChemistry
TopicPetroleum Processing and Analysis
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of CanadaEcopetrolUniversidad Nacional de Colombia
KeywordsAsphalteneNanoparticleDynamic light scatteringAdsorptionChemical engineeringParticle sizeDesorptionNanofluidChemistryMaterials scienceChromatographyAnalytical Chemistry (journal)Organic chemistry

Abstract

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The main objective of this study is to evaluate the effect of particle size and surface acidity of synthesized silica gel nanoparticles on the inhibition of formation damage caused by asphaltene precipitation/deposition. Silica gel nanoparticles were synthesized through the sol–gel method, and their characterization was performed via N 2 physisorption at −196 °C, field emission scanning electron microscopy (FESEM), dynamic light scattering (DLS) measurements, and NH 3 temperature-programmed desorption (TPD). The size of the synthesized nanoparticles ranged from 11 to 240 nm. The ability of the nanoparticles to adsorb asphaltenes and to reduce asphaltene self-association was evaluated using batch-mode experiments. The kinetics of asphaltene aggregate growth in the presence and absence of nanoparticles were evaluated using DLS measurements in different Heptol solutions. The smallest nanoparticles (11 nm) had the highest adsorptive capacity for n -C 7 asphaltenes among the nanoparticles studied. Therefore, these nanoparticles were modified using acid, base, and neutral treatments, which showed the following order S11A ≫ S11B ≃ S11N ≃ S11 according to the n -C 7 asphaltene affinity and the reduction of its mean aggregate size in the bulk phase. The surface acidity values obtained through of temperature-programmed desorption test ranged from 1.07 and 1.32 mmol/g. In general, the asphaltene self-association was reduced to a higher degree as the amount of adsorbed asphaltene increased. Additionally, in this study, the performance of a nanofluid treatment was tested under flow conditions in porous media under typical reservoir conditions using the nanoparticles with the best performance in batch-mode experiments. Indeed, nanofluid treatment with silica nanoparticles increased the effective permeability to oil and enhanced the oil recovery with an increase in the recovery factor of 11% under the conditions reported here. This approach has the major benefit of being scalable to a producing field, and the study provides an understanding of the roles of size and surface acidity of silica nanoparticles in the wettability alteration and inhibition of formation damage caused by asphaltenes and their influences on asphaltene aggregate size in the oil matrix and the adsorbed phases.

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.

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)0.002
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 score0.006
Threshold uncertainty score0.379

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
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 head0.034
GPT teacher head0.281
Teacher spread0.247 · 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