Characterization of Wormhole Growth and Propagation Dynamics During Cold Heavy Oil Production with Sand (CHOPS) Processes by Integrating Rate Transient Analysis and a Pressure-Gradient-Based Sand Failure Criterion
Bibliographic record
Abstract
Summary In this work, theoretical models have been formulated, validated, and applied to characterize the dynamic wormhole growth and propagation dynamics during cold heavy oil production with sand (CHOPS) processes by integrating rate transient analysis (RTA) and a pressure-gradient-based (PGB) sand failure criterion. More specifically, a coupling fluid-solid flow model is proposed by incorporating the recently proposed PGB sand failure criterion with sand production. Then, the source function method is applied to solve the fluid flow problem in the matrix subsystem by considering each generated wormhole segment as a sink source, while the finite difference method is applied to solve the fluid-sand flow problem in the wormhole subsystem. The sand failing at each segment is induced and propagated once the PGB sand failure criterion has been reached. Furthermore, transient-rate-type curves are generated to determine the dynamic wormhole network conditioned to the measured fluids and sand production profiles. Also, effects of the PGB sand failure criterion and reservoir properties on the transient rate behavior for CHOPS wells can be examined and analyzed. A gradual increase in the production rate profile occurs at the early times due to the wormhole growth and propagation. The wormhole network can be dynamically characterized by matching both the sand production rate and transient fluid production rate. The former is found to be greatly affected by the breakdown pressure gradient, while the effective wormhole coverage and intensity dominate the latter. Once the transient rate responses for both static and dynamic wormhole networks are validated with numerical simulation, the newly proposed method has been extended to field applications under various constraints, demonstrating that the fluid and sand production data of CHOPS wells can be integrated to accurately characterize the dynamic wormhole network within a unified, consistent, and efficient framework.
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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 | 0.001 |
| 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) | 0.000 | 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".