Qualification and Deployment of a Novel Frac Sleeve System for Extended Reach Wells in Canada's HPHT Duvernay and Montney Formations: A Joint KEC/AU Progression Case Study
Bibliographic record
Abstract
Abstract Kiwetinohk Energy Corp. (KEC), a Canadian energy producer operating in some of the country's most technically demanding unconventional reservoirs, partnered with Advanced Upstream (AU) to trial and deploy a novel, unlimited frac sleeve completion system. The project was initiated to address the persistent operational risks encountered when applying conventional plug-and-perf completion techniques in Canada's Duvernay and Montney formations, with the Duvernay being characterized as a high-pressure, high- temperature (HPHT) environment. Duvernay presents challenges associated with extreme bottomhole pressures, ultra-long laterals, and an elevated risk of casing deformation. In contrast, Montney has pushed the limits of exceptionally high frac slurry rates, heightening the risk of sleeve erosion during stimulation. Together, these factors significantly increase completion complexity, operational risk, and overall cost Conventional plug-and-perf methods, while widely adopted in unconventional plays, become increasingly less effective as lateral lengths exceed coiled tubing (CT) operational limits and as casing integrity is threatened by seismic activity or high-pressure stimulation events. In such cases, operators risk partial or complete wellbore loss, reduced stimulation effectiveness, and diminished recovery factors. This paper presents a comprehensive qualification-to-deployment workflow for the AU Sleeve system. The qualification process incorporated an iterative engineering design review, rigorous surface validation, and multiple field-scale trials, culminating in novel in- situ pressure and real-time erosion testing. These efforts aimed to determine the optimal fluid velocity window that ensures reliable stage isolation under the extreme conditions present in KEC's operational areas. The AU system demonstrated exceptional performance in both laboratory and field environments, meeting stringent mechanical and operational criteria. Following the successful validation phase, the system has been installed and stimulated in four Duvernay and two Montney wells. Results indicate that the technology can maintain effective stage isolation and withstand the erosive forces of high-rate fracturing operations without compromising sleeve functionality. Montney deployments introduced further complexity due to extremely high frac rates and slurry velocities, conditions that are known to accelerate erosion and reduce the reliability of conventional sleeves. To address this, a full-scale surface erosion simulation using a complete frac spread was executed prior to field deployment. The outcome was a 100% success rate in sleeve activation and isolation integrity, enabling KEC to optimize stimulation designs for the most demanding operating scenarios.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".