Optimization of Steam-Assisted Gravity Drainage in McMurray Reservoir
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Many field tests of the Steam-Assisted Gravity Drainage (SAGD) process have been conducted and have shown that the process is a technically effective one at extracting oil from heavy oil and bitumen reservoirs. However, it has not been firmly established whether the technology is operated at optimized conditions to yield maximum economic returns. This is especially important because typically SAGD depends on combustion of natural gas to generate steam and this is the dominant cost. This is especially important when natural gas prices are high. This research evaluates the use of a genetic algorithm optimization scheme to control a commercially available thermal reservoir simulator to optimize the steam injection strategy to reduce the cumulative oil to steam ratio (cSOR). The reservoir description is typical of that from Athabasca reservoirs. The results show that the injectionstrategy, for an individual wellpair, can be altered to reduce the cSOR up to 50% from a uniform injection pressure strategy to one after the steam injection strategy has been optimized. The optimized profile has high steam injection pressure at the beginning of the process before the steam chamber reaches the top of the reservoir. Before the chamber reaches the overburden, with high injection pressure, the saturation temperature is high and there are no thermal losses to theoverburden. After the chamber reaches the top of the formation, the injection pressure is lowered throughout the remainder of the process. This reduction of injection pressure implies that the saturation temperature falls and consequently the losses to the overburden are lowered. Thus the overall thermal efficiency of the process is enhanced. The optimized strategy is compared to processes operating at 1000 and 2000kPa constant injection pressure. Introduction Steam-Assisted Gravity Drainage (SAGD) has now been extensively tested and in commercial production in the Athabasca and Cold Lake regions of Alberta (Komery et al., 1999; Butler, 1997; AED, 2004; Yee and Stroich, 2004; Scott, 2002). The majority of existing SAGD projects are based in Alberta, Canada: more than nine are located in the Athabasca region (the McMurray formation), one in the Peace River region, (the Bluesky formation), four are in the Cold Lake region (the Clearwater formation, one other in the Grand Rapids formation), and five are in Saskatchewan (the Grand Rapids formation). The SAGD process, displayed in Figure 1, was developed by Butler (1997) while at Imperial Oil in the late 1970s. The process consists of two aligned horizontal wellbores: steam is injected into the top one whereas reservoir fluids are produced from the bottom one. The process is non-cyclic, that is, steam is continuously injected and fluids are continuously produced. Around and above the injection well, a steam chamber grows. The injected steam flows into the steam chamber and eventually comes into contact with oil sand at its edge. The steam thenreleases its latent heat to the oil sand, the oil heats up, its viscosity drops, and it flows (with water condensate) under gravity down the inclined chamber edge to the production well.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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) | 0.001 | 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 it