A Correlation of the Interfacial Tension between Supercritical Phase CO2 and Equilibrium Brines as a Function of Salinity, Temperature and Pressure
Bibliographic record
Abstract
Abstract The modeling of CO2 sequestration in saline aquifers is becoming increasingly important as this method emerges as the prime technology available for the disposal of large volumes of anthropogenically-generated CO2, thus reducing atmospheric CO2 emissions. The interfacial tension between the saline brine in the aquifer and the injected CO2 phase has a strong effect on the capillary pressure and relative permeability characteristics of the CO2-brine displacement, and proper understanding of the IFT level is necessary for accurate modeling and evaluation of such a process. This paper provides a summary of 168 brine-CO2 interfacial tension measurements conducted using a drop pendant interfacial tension apparatus at temperatures ranging from 41 to 125 °C, pressures from 2,000 to 27,000 kPag and salinities from 0 ppm (distilled water) to over 334,000 ppm. The dataset was regressed to develop an empirical correlation to predict the brine-CO2 IFT over the range of conditions evaluated in this work. The correlation, including temperature, pressure and salinity dependence, fits the measured data with an overall regression coefficient in excess of 0.94. In addition, a very strong relationship was found between computed gas-water ratio (dissolved CO2) and interfacial tension. An additional correlation was developed to model this effect, also with a high regression coefficient of 0.92. Since the gas-water ratio is a much easier parameter to measure than IFT, this provides a rapid and inexpensive method to estimate in-situ IFT from available or CO2 solubility data.
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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 | 0.000 | 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 | 0.001 |
| 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".