Bibliographic record
Abstract
Abstract A majority of heavy oil reservoirs in Saskatchewan are thin and shaly, and are not suitable for thermal recovery methods. For these reservoirs, enhanced oil recovery by an immiscible gas process could potentially recover an additional 200 million m3 of oil. This paper presents the results of a laboratory investigation, including pressure-volume-temperature studies and twodimensional physical model experiments, for evaluating the flue gas injection process for heavy oil recovery. The study examined the effects on viscosity reduction and oil swelling of the presence of O2 and of CO2 content in the flue gas. Physical model tests were carried out to investigate the effects on oil recovery of injection rate, injection mode (vertically downward, vertically upward, and horizontal injection), and slug size. The free-gas mechanism in the flue gas injection process was also studied. Introduction In Saskatchewan and Alberta, there are many thin-pay, heavy and medium oil reservoirs that are unsuitable for thermal recovery techniques. The estimated recovery by primary production and secondary methods is only about 5 - 8% of the initial oil-in-place (IOIP) for the heavy oil reservoirs and about 25% IOIP for the medium oil reservoirs(1). For these reservoirs, enhanced oil recovery (EOR) by an immiscible gas process offers a strong potential to recover more oil. It could, according to previous studies(2–6), recover up to an additional 30% IOIP incremental over that recovered by initial waterflood for some moderately viscous oils. Flue gas injection for heavy oil recovery received a great deal of attention in the 1960s(7, 8). However, it has not been studied in detail. A previous comparative study on immiscible gas injection agents for heavy oil recovery showed that CO2 is the best recovery agent among the three gases tested, and produced gas is slightly more effective than flue gas(9). CO2 has a higher solubility in oil and higher viscosity reduction efficiency than the other two gases. From the theory of fractional flow for viscous fingering(10), it is expected that CO2 will give field applications a better sweep efficiency than the other two gases. However, natural CO2 sources are not available to most oil reservoirs. The cost for CO2 capture from flue gas and other sources may range from $25 to $70/tonne(11). Produced and flue gases are available in large quantities at a much lower cost. With this consideration, produced gas and flue gas can be economically effective agents for heavy oil recovery by immiscible gas injection(9). In a previous study(9), linear coreflood tests were conducted with live and dead Senlac oil/flue gas to compare the relative effectiveness of secondary vs. tertiary flooding and WAG vs. slug injection. In these tests, a total of 0.40 PV flue gas was injected either as a continuous slug in slug floods or in a WAG mode. In secondary tests, gas was injected into the oil-saturated sandpack, whereas in the tertiary injection mode, it was injected into the initially waterflooded core. The WAG tests employed a WAG ratio of 4:1, an even slug size, and a 4-cycle operation.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.004 | 0.001 |
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".