A Comparison Study between the Newly Developed Vertical Wells Steam Assisted Gravity Drainage and the Conventional SAGD Process
Bibliographic record
Abstract
A numerical simulation study using the CMG-STAR Simulator was performed to compare the performance of the newly developed process (VWSAGD) utilizing vertical wells to enhance heavy oil recovery during steam assisted gravity drainage against the conventional steam assisted gravity drainage process which utilized horizontal wells (HWSAGD) under the same operating conditions. Two identical reservoir models were simulated for the two processes using 3-Dimensional, black heavy oil model (14° API). Each reservoir type consists of 49 × 49 × 20 grid blocks on a 5-acre model, which incorporated a typical heavy oil reservoir rock and fluid properties taken from the SPE case study, stspe001.dat (CMG 2015 release). A sensitivity analysis for both processes was performed for the grid density, soaking time, steam quality, bottom hole producing pressure, steam injection rate, reservoir thickness, reservoir area, and horizontal to vertical permeability anisotropy. More preferable reservoir conditions are those such as high horizontal to vertical permeability ratio, thick reservoir oil zones, as well as improved reservoir recovery for the VWSAGD process. Under unfavorable conditions such as thin reservoir oil zones, an improved reservoir recovery response was limited for the VWSAGD process and could be uneconomical in real field cases. Finally, the simulation results from this study include cumulative recoveries, Steam oil ratios, produced water-oil ratios, pressure and temperature distributions, and production rates. In addition, the results from this study have shown that the new VWSAGD process is more favorable than the conventional HWSAGD process.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), 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".