Factors affecting the chromatographic partitioning of CO2 and H2S injected into a water-saturated porous medium
Bibliographic record
Abstract
Acid gas comprising 98% CO2 and 2% H2S has been injected since 2002 in a depleted gas reservoir in Alberta, Canada, that has 20% water saturation. Carbon dioxide broke through first at producing wells, while H2S broke through after CO2. It was hypothesized that the delayed breakthrough of H2S was due to its greater solubility in reservoir water than that of CO2. Static laboratory experiments at in-situ conditions confirmed the higher solubility of H2S in brine than that of CO2. The solubility of the injected gas seems to increase linearly with the mole fraction of H2S in the gas stream; however, due to preferential H2S solubility, the dissolved gas has a greater proportion of H2S than CO2 compared with the injected gas. Dynamic laboratory experiments of the flow of CO2 containing H2S through a 24 m long coil tube packed with silica sand and saturated with brine at in-situ conditions of pressure and temperature have shown that the higher solubility of H2S in contrast to that of CO2 results in suppressed H2S concentrations at the leading edge of the breakthrough gas phase at outlet. Additional laboratory experiments with variable composition of the injected CO2 and H2S stream, and different conditions of temperature, pressure and water salinity have shown that these factors affect the breakthrough of the two gases and the time lag between them. Subsequently, the laboratory experiments were replicated using a compositional numerical simulator. Sensitivity analysis of the numerical simulations has shown that the CO2 and H2S breakthrough at the outlet is affected also by factors affecting the length of the twophase region such as medium relative permeability and flow direction with respect to gravity. Dispersion does not affect the timing of the gas breakthrough, but reduces the lag between the CO2 and H2S breakthrough. The results of these laboratory and numerical experiments should impact injection and monitoring strategies for impure CO2 streams.
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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 | 0.000 |
| 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".