Upscaling study of the cyclic solvent injection process for post‐chops reservoirs through numerical simulation
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Bibliographic record
Abstract
Abstract The cyclic solvent injection (CSI) process has been suggested as the most promising solvent‐based recovery method for post‐CHOPS reservoirs. Six CSI experiments were performed in three sandpacks with different scales and wormhole locations. Numerical simulations were conducted to history‐match the six CSI experiments. The effects of uncertain parameters such as relative permeability, capillary pressure, reaction rate (foamy oil model), and dispersion coefficient on the history‐matching were studied. The sensitivity analysis indicated that relative permeability and capillary pressure significantly affected the production performance of the CSI process in the numerical simulation. In particular, capillary pressure played the greatest role in upscaling in both axial and radial directions. Furthermore, capillary pressure effects were aggravated when the wormhole was located in the top of the experimental model. Thus, all CSI experimental production data were matched successfully by tuning the capillary pressure based on the same matched relative permeability curves. A heavy oil post‐CHOPS reservoir in western Canada was evaluated for the CSI process at field scale. Wormholes were considered by applying the multi‐lateral well model. Post‐CHOPS conditions were established by history‐matching the field's production of oil and water. The parameters obtained from the history match upscaling studies were adopted in simulating the subsequent CSI process and were set with certain constraints to consider its uncertainty at field scale. The recovery factor after ten years of the CSI process was in the range of 13.5–16.0 %.
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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) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
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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 it