An Integrated Reservoir Model for Sand Production and Foamy Oil Flow During Cold Heavy Oil Production
Bibliographic record
Abstract
Abstract Continuous sand production and foamy oil behavior are both believed to be key factors for the enhanced non-thermal fluid production in unconsolidated heavy oil reservoirs in Canada (Alberta and Saskatchewan). The same mechanisms are likely to be active in similar heavy oil strata in Venezuela (Faja del Orinoco), Oman, China (Bohai Bay), and elsewhere. Field experience indicates that fundamental understanding of sand production mechanisms, reservoir fabric alteration, foamy oil behavior, pressure gradient changes, and stress changes are key to successful operations involving massive continuous sanding. Inter-relating these factors requires coupling of geomechanics and fluid flow processes. An integrated approach incorporating a three-phase, three-dimensional black-oil model coupled with a geomechanics model is introduced in this article. Piping channels ("wormholes") are postulated to develop from perforations when pressure gradients exceed the residual cohesion of the sand. An elastoplastic constitutive model is used to describe the reservoir material before seepage forces liquefy and suspend the sand particles at the advancing tips of wormholes. The hemispherical wormhole tip is postulated to propagate as long as a critical tip pressure gradient is exceeded. A slurry transport model is used to describe the flow inside the wormholes. Field data from Frog Lake, Alberta are used to validate the model, and it appears that the simulation can match the field data remarkably well.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".