Impacts of Gas on SAGD: History Matching of Lab Scale Tests
Bibliographic record
Abstract
Abstract This study addresses the importance of initial GOR in SAGD heavy oil recovery operations. By history matching two laboratory scale experiments one with dead oil and the other with live oil we corroborated the theoretical and numerical prediction that gas would accumulate at the front of a steam chamber. This gas accumulation could slow down oil production as well as heat loss to the overburden. It is suggested that monitoring gas production during SAGD field operations may be critical for the investigation of impacts of gas, and for developing strategies for performance improvement. Introduction It was generally believed that gas could have positive impacts on SAGD operation. The negative impacts of gas on SAGD operation have also been noticed, but are usually considered minor(1–15). Recently, however, a theoretical and numerical study has shown that the negative impacts of gas on SAGD could be critical(16). Two lab scale experiments concerning this issue have been conducted at Alberta Research Council. One was with dead oil and the other was with live oil. Results of these experiments were then history matched and analyzed using CMG's thermal reservoir simulator, STARS. In this report, we summarize the results from the study. Experimental The physical model was a rectangular stainless steel cell 80 cm in length, 24 cm in height, and 10 cm thick. The cell was packed with 220 Darcy Ottawa sand saturated with water and bitumen. The production well was placed at the centre across the length, 2.2 cm above the bottom of the cell and parallel to the thickness of the cell. The injection well was placed 5 cm above the production well. The cell was carefully wrapped with multiple layers of Nomax insulation. Two layers of Nomax and one layer of 1.9 cm thick plywood were used for the front wall and for the back wall. The heat transfer coefficient for one layer of Nomax was 0.08184 J/cm2-min- °?C and for one layer of plywood was 0.02684 J/cm-2 min- ° C. The cell was confined in a pressure vessel filled with nitrogen so that the overburden pressure of the cell was controlled. The viscosity of the dead oil used in the two tests was 32,500 cP at 15 °C, and was a sample from Cold Lake. In the dead oil experiment, the initial cell pressure was 2,168 kPa and the initial cell temperature was 22 °C. The sandpack porosity was 36.7%. The initial oil saturation was 87%. The steam was slightly superheated and injected at an average rate of 33 cc/min, except during the first 10 min. During the first 10 min, steam was circulated into the injection and production wells, with the steam injection rate being at an average value of 68 cc/min. The experiment lasted 450 min. In the live oil experiment, the initial cell pressure was 2,184 kPa and the initial cell temperature was 22 ° C. The sandpack porosity was 36.3%. The initial oil saturation was 89%.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".