Density of High Pressure and Temperature Gas Reservoirs: Effect of Non-hydrocarbon Contaminants on Density of Natural Gas Mixtures
Bibliographic record
Abstract
Abstract New experimental density data are generated in this study for light and heavy dry gas mixtures. The light mixtures consist mostly of methane and small fractions of ethane, propane, and nitrogen. Normal alkanes up to C6, iso-butane and iso-pentane together with carbon dioxide form the heavier gas mixtures. For each mixture, isothermal gas density is measured from 3.45 MPa to 140 MPa at temperatures of 423.15 K and 478.15 K. Effects of CO2 and N2 as two non-hydrocarbon contaminants, on density of gas mixtures are examined in steps of 5 mol%, 10 mol%, and 20 mol%. In addition, water vapor influence on gas phase density of water-saturated gas mixtures is also investigated. Different correlations for sweet and sour gas critical properties are combined with the most widely used equations of state (Hall-Yarborough and Dranchuk-Abou-Kassem) to predict density data for comparison with 450 experimental measurements. The most important results demonstrated from this study are: Among all correlations, the combination of the Hall-Yarborough equation with the pseudo-critical properties correlated by Sutton generates the lowest average absolute deviation (AAD) between predicted and experimental density data. The correction term developed by Wichert and Aziz to modify the pseudo-critical properties due to the presence of non-hydrocarbon compounds in the gas mixture, drastically improves the prediction of density data. At very high pressure and temperature conditions, effect of water vapor becomes more significant on gas phase density and it should be considered in density related correlations.
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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) | 0.001 | 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 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".