The Catalytic Effects of Nonhydrocarbon Contaminants on Equilibrium Water Vapor Content for a Dry Gas at HP/HT Reservoir Conditions
Bibliographic record
Abstract
Abstract This paper presents new laboratory data quantifying the catalytic effects of two common nonhydrocarbon contaminants (i.e., CO2 and N2) on the liquid water vaporization process as well as the water vapor content for natural gases at high-pressure, high-temperature (HP/HT) reservoir conditions. We conducted laboratory studies to measure the isothermal, equilibrium water vapor content for seven dry gas mixtures at pressures from 500 to 20,000 psia and temperatures of 300°F and 400°F. Gas mixtures evaluated in our study contained up to 20 mol% of either CO2 or N2 each. Principle results of our laboratory study demonstrate the following phase behavior: temperature has a significant impact on the water vaporization process and the quantity of water vapor dissolved in a natural gas with no nonhydrocarbon contaminants. Increasing the temperature from 300°F to 400°F increases the equilibrium water vapor content by more than 70% above that for the gas at 300°F; the presence of CO2 in the gas phase also enhances the solubility of water vapor in a natural gas. Increasing the CO2 content from 5 mol% to 20 mol% increases the maximum water vapor content by 20% to 40%, respectively, above that measured for the same gas with no CO2 These increases were observed at both 300°F and 400°F; the presence of CO2 in the gas phase combined with higher temperatures further augments water vapor solubility in a natural gas. For example, the equilibrium water vapor content for the gas with 20 mol% CO2 at 400°F increased by 80% above that measured for the same gas at 300°F; the presence of N2 in the gas phase suppresses the water vaporization process and reduces the quantity of water vapor dissolved in the gas. At 300°F, 5 mol% N2 reduces the water vapor content from 10% to 20% of that for the same gas with no N2. Further increases in N2 content reduce the water vapor content below that for the same gas with no N2; the enhanced water vapor solubility at higher temperatures counters the suppressive effects of N2 in the gas phase. Increasing the N2 content at 400°F increases the maximum water vapor content from 5% (20 mol% N2) to 10% (5 mol% N2) above that measured for the same gas with no N2.
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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 | 0.001 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".