Modeling CHOPS Using a Coupled Flow-Geomechanics Simulator With Nonequilibrium Foamy-Oil Reactions: A Multiwell History Matching Study
Bibliographic record
Abstract
Abstract Cold Heavy Oil Production with Sand (CHOPS) has been widely and successfully applied for the last three decades in the Heavy Oil Belt region that straddles the provinces of Alberta and Saskatchewan in Canada. As its name suggests, the method relies on continuous production of sand to improve the recovery of oil from the reservoir. In CHOPS, a significant pressure drawdown around the wellbore is created by using progressive cavity pumps, which causes the loosely consolidated formation to fail, creating increased permeability channels, usually called wormholes, through which, a slurry-like mixture of sand, oil and water flows. Many attempts have been made to use conventional numerical reservoir simulators to model the CHOPS process. However, many of the commercial finite-difference reservoir simulators do not incorporate capabilities to model the complex geomechanical processes responsible for the failure of poorly consolidated formations in CHOPS. To circumvent these limitations, several approaches have been proposed. The most common relies on explicitly defining high permeability channels that radiate from the producing wells in an attempt to mimic wormholes created during CHOPS production. In this paper, we present a different, more rigorous approach that relies on the coupling of a finite-element geomechanical simulator with a finite-difference reservoir simulator. In the coupling process, the geomechanical simulator uses the pressure gradients calculated by the reservoir simulator to determine changes in the stress regime of the reservoir. In the case of CHOPS, these changes cause failure in the loosely consolidated formation, which in turn induces sand production with a corresponding increase in porosity and permeability. The new porosity and permeability values in the affected gridblocks are then fed back to the reservoir simulator, which is now capable of incorporating the effects of formation failure into fluid flow calculations. This process is then repeated at user-controlled intervals during the course of the simulation. The methodology has been validated by successfully history matching the production data from a section of a heavy oil field operated by Husky Energy in Western Canada. In this paper we compile the data integration efforts to create a coupled geomechanical model and the results of the history match.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.001 |
| 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".