Nonionic Surfactant for Enhanced Oil Recovery from Carbonates: Adsorption Kinetics and Equilibrium
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.
Bibliographic record
Abstract
Around 40% of the current world conventional oil production comes from carbonate reservoirs, dominantly mature and declining giant oilfields. Tertiary oil production methods as part of an Enhanced Oil Recovery (EOR) scheme are inevitable after primary and secondary oil production. The goal of surfactant flooding is to reduce the mobility ratio by lowering the interfacial tension between oil and water and mobilizing the residual oil. This paper highlights adsorption kinetics and equilibrium of Glycyrrhiza Glabra, a novel surfactant, in aqueous solutions for EOR and reservoir stimulation purposes. A conductivity technique was used to assess adsorption of the surfactant in the aqueous phase. Batch experimental runs were also performed at various temperatures to understand the effect of adsorbate dose on the sorption efficiency. The adsorption kinetics was experimentally investigated at room temperature (27 °C) by monitoring the uptake of the Glycyrrhiza Glabra as a function of time. The adsorption data were examined using different adsorption equilibrium and kinetic models. The Langmuir isotherm suits the equilibrium data very well. A pseudo-second order kinetic model can satisfactorily estimate the kinetics of the surfactant adsorption on carbonates. Results obtained from this research can help in selecting appropriate surfactants for design of EOR schemes and reservoir stimulation plans for carbonate reservoirs.
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 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 | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| 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