Sand on Demand for Horizontal Wells: Tracking Behaviour with the CT Scanner
Bibliographic record
Abstract
Abstract The cold production recovery process is successful in vertical wells in western Canada. In this process, large amounts of sand are produced on a continuing basis along with heavy oil. Attempts at cold production in horizontal wells have not been particularly successful. When sand production has been generated in horizontal wells, these wells have tended to become plugged with sand. This paper presents the results of experiments performed to assess the feasibility of applying cold heavy oil production with horizontal wells using less aggressive (i.e., managed) sand production strategies. Specifically it describes the impact of relatively small changes in flow rate on sand production behaviour. The effects on the porosity distribution within the sand pack due to sand production were monitored during one experiment through computed tomography (CT) imaging. The experimental results indicated that the effects of sand production were confined to localized regions (channels) within the sand pack where there was a large permeability and porosity increase. Outside these regions no changes in permeability and or porosity were observed. Channel growth could be controlled successfully (i.e. stopped/started) through flow rate changes. Another experiment demonstrated that continuing sand production at low sand cuts could be achieved if the initial flow rates were low and later increased in small increments. This suggests that if the latter operating strategy is implemented in the field, sand production may be sufficiently high to generate regions (wormholes) with high permeability but sufficiently low to allow produced sand to be transported along a horizontal 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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".