Active ions’ impact in the enhanced oil recovery process: a microfluidic-based approach
Bibliographic record
Abstract
Abstract More than 50% of the crude oil is trapped inside the pores of the rock after the primary and the secondary oil recovery stage, various methods have been currently used for enhanced oil recovery (EOR) to recover the trapped oil. Brine injection, as the most commonly used approach in EOR, was heavily influenced by the concentration of active ions like Ca2+, Mg2+, and SO42−. In this study, two kinds of polydimethylsiloxane (PDMS)-based microfluidic devices were designed and fabricated to mimic the porous structure in order to study the active ion’s impact in the brine flooding process. Since the PDMS is transparent in the visible range, the fluid flow inside the fabricated porous structure can be observed directly during the brine flooding process. The effect of active ions including Ca2+, Mg2+, and SO42− in the brine flooding process was studied in detail with the microfluidic devices. The proposed method could have wide application potential in the screening of flooding reagents in the oil industry.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".