Analysis of Heavy Oil Recovery by Thermal EOR in a Meander Belt: From Geological to Reservoir Modeling
Bibliographic record
Abstract
The objectives of this work is to assess the impact of reservoir heterogeneities on heavy oil recovery of a reservoir analogue of meander belt through the Steam Assisted Gravity Drainage (SAGD) process by using numerical models. These models are obtained with different scales of upscaling of the geological model. Meander belts consist of point bar deposits, characterized by a 3D complex internal architecture, with different scales of heterogeneities, which distribution is associated with the depositional processes. Based on a 3D outcrop description of a meander belt analogue to the Canadian heavy-oil fields, the approach includes three steps: 1) the construction of a reference static reservoir model based on a very fine description of the outcrops in terms of architecture and geological heterogeneities, 2) upscaling of the grid at different scales using different upscaling factors in order to evaluate their impact on the heterogeneity distribution in the reservoir, 3) reservoir SAGD simulations using horizontal well doublet (steam injector and producer) across the meander belt, so as to assess the impact of upscaling of heterogeneities on heavy oil production. The impact of heterogeneities on simulation results are evaluated for several upscaling stages. Results show that heterogeneity distribution has an impact on fluid flow at different stages of production. On the fine gridded model, small scale heterogeneities impact the steam chamber development and fluid flow in the wellbore vicinity at the beginning of the steam injection, whereas large scale heterogeneities strongly influence oil recovery during the whole recovery process and lower the efficiency of the reservoir drainage. On coarser grids, the effect of small-scale heterogeneities can be diminished, depending on the upscaling stage. The geomechanical effect is not taken into account in this work, the objective being to assess the impact of heterogeneities on oil recovery. The performance of SAGD is clearly linked to the steam chamber development, which depends on the degree of heterogeneities present in the reservoir. The simulation workflow and the sensitivity study on the upscaling method contribute to a better restoration of the heterogeneity distribution in the reservoir. The negative effect of these heterogeneities during the oil recovery must thus be quantified in order to monitor the thermal production at crucial periods of the production 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 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".