Fast Fluorescence-Based Microfluidic Method for Measuring Minimum Miscibility Pressure of CO<sub>2</sub> in Crude Oils
Bibliographic record
Abstract
Carbon capture, storage, and utilization has emerged as an essential technology for near-term CO2 emission control. The largest CO2 projects globally combine storage and oil recovery. The efficiency of this process relies critically on the miscibility of CO2 in crude oils at reservoir conditions. We present a microfluidic approach to quantify the minimum miscibility pressure (MMP) that leverages the inherent fluorescence of crude oils, is faster than conventional technologies, and provides quantitative, operator-independent measurements. To validate the approach, synthetic oil mixtures of known composition (pentane, hexadecane) are tested and MMP values are compared to reported values. Results differ by less than 0.5 MPa on average, in contrast to comparison between conventional methods with variations on the order of 1-2 MPa. In terms of speed, a pressure scan for a single MMP measurement required less than 30 min (with potential to be sub-10 min), in stark contrast to days or weeks with existing approaches. The method is applied to determine the MMP for Pennsylvania, West Texas, and Saudi crudes. Importantly, our fluorescence-based approach enables rapid, automated, operator-independent measurement of MMP as needed to inform the world's largest CO2 projects.
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How this classification was reachedexpand
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".