The Application of Solvent-Additive SAGD Processes in Reservoirs With Associated Basal Water
Bibliographic record
Abstract
Abstract This paper describes the results of a simulation and optimization study on the application of a solvent-additive steam-assisted gravity drainage (SAGD) process to reservoirs with associated basal water. A review of related studies is provided, together with a discussion of the pros and cons of potential alkane solvents in basal water reservoirs. Economics and the impact of dynamic and ultimate retention are discussed. A general conclusion drawn from literature is that optimal solvent application to SAGD in reservoirs will likely involve time variations in both rate and composition of the solvent. This is also the case for reservoirs with associated basal water. This results in an optimization problem that has a large number of dimensions, and is very nonlinear. Genetic algorithms, which mimic biological evolution, have been found to be extremely effective in addressing such problems. A key product of this effort, optimized for a simple clastic reservoir with associated basal water, is presented. The study produced an operable process, which could be described as a new combination of pre-existing concepts. The process offers material improvements in thermal bitumen supply costs, as well as recovery factor. Major reductions in the physical steam/oil ratio (SOR), (and therefore) capital intensity, water use and carbon emissions, are indicated.
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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".