Investigation of Steam Assisted Gravity Drainage (SAGD) and Expanding Solvent-SAGD (ES-SAGD) Processes in Complex Fractured Models: Effects of Fractures' Geometrical Properties
Bibliographic record
Abstract
Abstract The Steam Assisted Gravity Drainage (SAGD) process has been studied theoretically and experimentally in conventional models and reservoirs and is found a promising EOR method for certain heavy oil reservoirs, but its applicability for fractured systems has not yet been investigated. In this work simulation studies of the SAGD process were made on different fractured models consisting of fractures in both Near Well Region (NWR) and Above Well Region (AWR) and also in the presence of networked fractures. Double porosity/double permeability fractured models were developed and results were compared with conventional non-fractured model. Various fracture geometries such as orientation, length, discontinuity, dispersion, location, and networking were studied. Results indicated a better performance in terms of oil recovery and sweep efficiency in the presence of vertical fractures. Longer vertical fractures seemed to have even more beneficial effects. Horizontal fractures revealed detrimental effect on oil recovery and the performance became worse for longer horizontal fractures. Discontinuous horizontal fractures produced a better performance especially when combined with continuous vertical fractures (networking). Vertical fractures helped growth of steam chamber in vertical direction which resulted in higher oil recovery. However, horizontal fractures seemed to inhibit growth of the steam chamber in vertical direction, hence retarding oil recovery. In addition to SAGD, ES-SAGD process has also been investigated for both conventional and fractured simulation models. Simulation analysis confirmed the synergetic effect of solvent injection along with steam since for both conventional and fractured models ES-SAGD had a higher rate of production and higher ultimate oil recovery.
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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 | 0.001 |
| 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 | 0.001 | 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".