Comparative Study of SAGD and Solvent and Water Assisted Electrical Heating: Effect of Shale Layers
Bibliographic record
Abstract
Abstract Bitumen recovery using solvent and water assisted electrical heating has shown promise to be more efficient than the current thermal recovery method of steam assisted gravity drainage (SAGD). Solvent and water assisted downhole electrical heating has potential to eliminate large steam generation plant and water treatment facilities and greatly reduce the capital and operating costs during oil sands development. It is demonstrated that in this process, a hot vapor chamber analogous to that created in SAGD is formed using downhole heaters and injection of a moderate volume of water and liquid solvent as working fluids. In this work, a kinetic model was integrated into reservoir simulation model to describe aquathermolysis and thermal cracking of bitumen at reservoir conditions. The solubility of gases in both oil and water were included in the simulation. Solvent and water assisted electrical heating was then modeled for oil sand reservoirs with shale layers and the performance was compared with SAGD process. Various distributions of shale layers were introduced through experimental design using different lengths and distances to injector. Results indicated that production rates by SAGD were greatly affected by shale layers. Production rates were reduced when the steam chamber reached a low-permeability shale layer, especially if the shale layer was wide and close to the injector. However, production rates by solvent and water assisted electrical heating were quite steady even if a vapor chamber met a shale layer. This process led to a box-shaped vapor chamber which was able to grow horizontally and bypass shale layers quickly. In addition, it was found that production rates by SAGD were high in the early stage but declined over time whereas production rates by solvent and water assisted electrical heating were steady and did not change much over the life of the process.
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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) | 0.001 | 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".