Nanoparticles for Inhibition of Asphaltenes Damage: Adsorption Study and Displacement Test on Porous Media
Why this work is in the frame
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Bibliographic record
Abstract
The deposition of asphaltenes is one of the most difficult problems to overcome in oil production and processing. The presence of asphaltenes in crude oil, and consequently, the adsorption and deposition of asphaltenes on the rock surfaces, affects the rock properties, such as porosity, permeability, and wettability. This study aims at analyzing the effect of the chemical nature of 12 types of nanoparticles on asphaltenes adsorption; hence, the delay or inhibition of deposition and precipitation of asphaltenes on porous media under flow conditions at reservoir pressure and temperature were investigated. The adsorption equilibrium of asphaltenes onto nanoparticles was effectively achieved within relatively short times (approximately 2 min), which indicates the promising nature of adsorbents for delaying the agglomeration and inhibiting the precipitation and deposition of asphaltenes. The adsorption equilibrium of asphaltenes for the nanoparticles was determined using a batch method in the range 150–2000 mg/L. The equilibrium adsorption data were fit to both the Langmuir and Freundlich models. Additionally, in this study, the transport of nanoparticles in a porous media at a typical reservoir pressure and temperature was investigated. As a result, the use of nanoparticles allowed the system to flow successfully, which demonstrated the inhibition of precipitation and deposition and the enhanced perdurability against asphaltene damage in the porous media.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it