Characterization of Wormhole Growth and Propagation Dynamics During CHOPS Processes by Integrating Rate Transient Analysis and a Pressure-Gradient-Based Sand Failure Criterion in the Presence of Foamy Oil Flow
Bibliographic record
Abstract
Abstract Characterization of the wormhole growth and propagation dynamics has been made possible with the semi-analytical models developed in this work by integrating both rate transient analysis (RTA) and a pressure-gradient-based (PGB) sand failure criterion in the presence of foamy oil flow. As for the theoretical RTA models incorporated with a PGB sand failure criterion and foamy oil properties, the nonlinearity caused by the latter is linearized by using the pseudofunctions. A sequential method is adopted to solve the coupling fluid-solid problem, while the source function and finite difference methods are applied to obtain the solutions for fluid flow in the matrix and wormhole subsystems, respectively. New wormhole segments can be generated once the PGB sand failure criterion has been achieved, while their updated petrophysical properties conditioned to the new pressure field can be sent back to obtain the solutions for the fluid flow in the next time interval. Furthermore, influence of sand failure/fluidizing and foamy oil properties on the dynamic wormhole network can be investigated with the generated type curves. Both wormhole growth and foamy oil flow dictate an upward fluid production at the early times, while the production-induced pressure depletion dominates the declining production at the late times. The fractal wormhole networks can be dynamically characterized by history matching the field fluid and sand production profiles. Both the sand failure degree and foamy oil properties dictate the effective wormhole coverage and intensity. Sand production is found to be influenced by both the breakdown pressure gradient and wormhole conductivities, while oil production rate can be dominated by the wormhole coverage and intensity. Foamy oil flow can increase oil production rate and increase the wormhole coverage compared with the conventional oil. The newly developed method in this work has been validated and then applied in field-scale to dynamically characterize the wormhole growth and propagation by considering both sand failure phenomenon and foamy oil properties within a unified, consistent, and accurate framework. In this work, a rigorously semi-analytical method has been proposed to dynamically characterize the wormhole growth and propagation for the first time by incorporating the RTA, PGB sand failure criterion, and foamy oil properties. Compared to the conventional numerical simulations, not only is this proposed method accurate for wormhole characterization conditioned to fluid and sand production profiles, but also such delineated wormholes can be readily integrated with any reservoir numerical simulators to assess and optimize any potential EOR methods in post-CHOPS reservoirs.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".