Interventions in Challenging Low Pressure Horizontal Producers with Known Casing Deformation: A Case Study Comparing Conveyance Methods for Successful Installation of Toe Gas Lift Systems
Bibliographic record
Abstract
Abstract This paper presents a case study of intervention/workover operations from a nine-well pad in the Montney formation, in British Columbia, Canada. The operational objective was to land artificial lift near the toe of each wellbore. Several conveyance methods were evaluated, and jointed pipe was ultimately selected. This paper highlights key learnings gathered throughout the operation. Outputs from real-time Electronic Drilling Recorder (EDR) data are included and contrasted with other intervention methods. Torque and drag simulations showed the desired depth was achievable using offset friction factors that were calibrated using coiled tubing conveyance during initial post-frac plug drillout operations. Jointed pipe intervention was selected to reduce uncertainty and understand limitations of installing artificial lift at depths near the toe of a low-pressure wellbore with known casing deformation. A telescopic-double workover rig package was utilized throughout operations along with rig-assisted snubbing on early wells where surface pressure existed. A confirmation run was made using a mock assembly to gauge reach capabilities prior to running the final assembly. Overall, the program was a success with seven of nine wells achieving 85% lateral coverage. Major scope changes were encountered on Wells 1 and 2, requiring sixteen and nine days to complete, respectively, and a stuck pipe event on Well 6 will be discussed. Key challenges include sub-optimal bottomhole assembly selection, poor circulating efficiencies, variable subnormal bottomhole pressure, and casing deformation. Real-time hook load data correlated to the Torque and Drag model. However, observed torque was significantly higher than presented by the model. This is suspected to have been caused by micro-tortuosity and localized doglegs. Despite challenges on several wells, key optimizations were quickly implemented to accelerate the learning curve towards ultimate positive economic results. Learning how to select the right conveyance method based off changing well conditions is a key driver in minimizing risk, optimizing profitability, and maximizing the chance of success. Learnings and results from this nine-well program will provide a framework for success in future jointed pipe interventions.
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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 | 0.001 | 0.000 |
| 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)
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".