Enhanced Gas Recovery and CO2 Sequestration by Injection of Exhaust Gases from Combustion of Bitumen
Bibliographic record
Abstract
Abstract Enhanced gas recovery by gas-gas displacement can be achieved economically in several situations. For mature volumetric gas reservoirs suffering from low productivity due to low reservoir pressure, injection of waste gas can increase the ultimate gas recovery by maintaining gas production rates and preventing premature well abandonment. For water-driven gas reservoirs, pressure maintenance by gas injection will serve to (1) retard the influx of aquifer and (2) partially mitigate water coning caused by excessive pressure drawdown. This paper presents the results of laboratory core displacement tests conducted to investigate the feasibility of enhanced natural gas production by using exhaust gas from combustion of bitumen in an oxygen rich atmosphere. A synthetic gas mixture containing carbon dioxide, nitrogen and sulfur dioxide was used to represent the exhaust gas of interest. Displacement tests were conducted in Berea core and in porous media prepared with silica sand as well as crushed carbonate rocks at pressures ranging from 0.69 to 6.2 MPa. The objectives of the experiments were to determine the effects of (1) pressure, (2) displacing gas composition (3) formation water and (4) rock mineralogy on recovery efficiency of uncontaminated methane from the porous media. Several interesting phenomena were observed during the course of this investigation. Separation of injection gas components was observed in the effluent gas during displacement. Breakthrough of carbon dioxide and sulfur dioxide were delayed relative to nitrogen. This can be attributed to the higher solubility of CO2 and SO2 in water relative to nitrogen. These results are beneficial to natural gas production as they reduce the operating costs associated with corrosion during production of CO2 and SO2. The amount of green house gases and acid gases being sequestered in the reservoir will also increase due to these effects.
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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".