Experimental Study of Co-Injection of Potential Solvents with Steam to Enhance SAGD Process
Bibliographic record
Abstract
Abstract Steam-Assisted Gravity Drainage (SAGD) is the preferred in-situ technology to recover heavy oil and bitumen from Canadian reservoirs. It is commercially proven, delivers high oil rates and high ultimate recoveries. Given the large energy requirement and the volume of emitted greenhouse gases from SAGD process, there is a strong motivation to develop enhanced oil recovery processes with lower energy and emission intensities. Addition of potential alkane solvents to steam in processes such as ES-SAGD can reduce the high use of energy and green-house emissions in SAGD. Potential hydrocarbon additives provide an additional means to raise oil phase mobility beyond that achieved by heat. Numerous simulation studies are published on the effect of hydrocarbon additives on SAGD process but few experimental results exist in public domain. Often, Conflicting results exist both in simulation studies and even field tests. In addition, numerical simulations are unable to fully capture the mechanism of hybrid steam solvent processes. This paper summarizes experimental results of addition of potential solvents to steam in SAGD process. N-hexane was selected as the preferred additive to be co-injected with the steam and the experimental result are compared with pure steam injection process. Experiments were conducted using a scaled two dimensional cylindrical model. Peace River Bitumen samples were used to conduct the experiments at 80 psia. Experimental results were analyzed to determine the key parameters involved in solvent assisted SAGD processes. Experimental results confirmed the effectiveness of hydrocarbon additives to enhance SAGD process. Co-injection of potential solvents led to accelerated oil production rate, higher oil recovery and lower energy to oil ratio.
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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".