Effect Of Geomechanics On Optimization Of Solvent Assisted SAGD SA-SAGD in Oil Sands Reservoirs
Bibliographic record
Abstract
Abstract It is generally accepted that solvent-steam injection in heavy oil/bitumen reservoirs outperforms steam only injection in terms of oil recovery rate, ultimate oil recovery and steam oil ratio. Important parameters in SA-SAGD design are solvent selection, injection strategy and solvent retention in situ. The role of geomechanics in optimum application of SA-SAGD, however, remains largely unexplored. Recent studies suggest that solvent transport, solvent dilution effect and the temperature distribution around the edge of the steam chamber have major control over SA-SAGD performance. Solvent-steam injection significantly alters the temperature distribution around the chamber edge compared to steam only processes (SAGD). The temperature redistribution, in addition to the altered pore pressure, produces geomechanical effects such as porosity and permeability alteration, relative permeability changes and residual saturation alterations which in turn, influence solvent-steam-oil phase behavior and solvent transport and retention, among others. These chains of events affect the steam chamber growth and the solvent distribution, which affect optimum solvent selection and solvent-steam injection scenarios. These geomechanical considerations are of particular interest for bitumen deposits, both oil sands and carbonates, where chemical, thermal and fluid pressures can impose significant volume changes within the reservoir especially in shallower, lower confining stress settings. The role of geomechanics in SA-SAGD was explored numerically using a sequentially coupled modeling approach with STARS (CMG) and FLAC (Itasca). A 2D homogenous oil sands reservoir geomodel at a shallow depth was considered for the purpose of this paper. Studies were conducted at two scales: 1) edge of steam chamber and 2) reservoir scale including underburden and overburden. The results of these numerical studies revealed geomechanics considerations directly affect the optimum solvent type selection and injection strategy during high pressure SA-SAGD processes. These studies provide valuable direction for further detailed mechanistic studies (both numerically and experimentally) and provide valuable input to the challenges of optimizing SA-SAGD processes in oil sands.
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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 | 0.001 |
| 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".