SAGD Wind-Down: Lab Test and Simulation
Bibliographic record
Abstract
Abstract As SAGD moving from pilot test to commercial operation, a number of areas need to be dealt with. These include diagnosing and solving operational problems and improving energy efficiency. One of the methods of improving energy efficiency is to prolong oil production after steam injection stops by using energy in place. The results of a laboratory experiment and corresponding numerical history matching are reported in this paper. The study showed that the hot chamber continued its expansion after steam injection was stopped and a gas injection was initiated. The continuous expending period represented the most productive period in the gas injection wind-down process. A total of 12.5% of OOIP was recovered during wind-down. Successful history matching of both oil production curve and temperature profiles at different times demonstrated that the numerical simulation could handle the gas/steam mixing phenomena. Gas concentration profile from numerical simulation indicated that gas was concentrated at the region where oil saturation was experiencing big changes. Introduction The successful tests of the SAGD process at UTF (1, 2) and other pilot projects (3, 4) have established SAGD as a viable technology for in situ recovery of the huge heavy oil and bitumen resources in western Canada. A number of commercial SAGD projects in Western Canada are in the operation, construction, or planning stages (5). However, the SAGD technology is still in the transition from pilot to commercial operation. The development of the technology is currently focusing on two areas. The first is to diagnose and solve operational problems. In field operations, many projects have encountered difficulties, such as lower than expected oil production rate, higher than expected steam-oil ratio (SOR), or premature production rate decline. In each case, the cause of the problem needs to be identified in order to develop methods to deal with the problem and avoid the problem in the future. The second area of SAGD development is to improve energy efficiency as the costs of fuel and associated water treatment account for a large portion of the oil production cost. These developments include hybrid processes using co-injection of steam and solvent (6, 7, 8), or steam and non-condensable gas (9). The hybrid processes take advantage of both heating by steam and dilution by solvent. The injection of non-condensable gas is intended to reduce heat loss to the overburden therefore improve SOR. With this idea in mind, efforts have been directed to developing SAGD wind-down methods. At a certain stage of SAGD operation, as instant SOR increases, there is no more economic benefit to continue pure steam injection. At this stage, a wind-down process can be started to utilize energy in place and to continue oil production. A numerical simulation and economic evaluation study (10) showed that a co-injection of steam and non-condensable gas gave the best result. Recently, the results of co-injection of steam with flue gas into UTF Phase B as a wind-down process was reported (11). The wind-down process performed better than expected.
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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) | 0.005 | 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".