Extending Lateral Length Using Casing Floatation to Reduce Field Development Cost in Shale Gas Plays
Bibliographic record
Abstract
Abstract Operating in a low margin gas environment, operators look for new ways to reduce costs and efficiently develop reserves. Shell Canada Limited ("Shell"), operating in the Montney shale gas field located in NE British Columbia, Canada, used casing floatation techniques to extend lateral lengths. Increasing lateral length reduces well cost per lateral meter. This is because drilling the reservoir section is the least expensive segment due to high penetration rates. Extended lateral lengths also create new options for more economical and sustainable field development as fewer wells are required to cover acreage and it reduces dead space. Shell uses a mono-bore casing design with average lateral lengths of 1800m at a TVD of 2300m. The goal of the project was to double lateral length to 3600m. At these depths, extending much beyond the current design is not possible due to theoretical casing lock-up from excess drag during conventional casing running. Casing floatation was chosen to extend the lateral reach of the wells and mitigate casing lock up because it is a cost effective, simple technology. Casing rotation and setting a deep intermediate string to reduce drag were also evaluated but deemed too cost prohibitive or technically unfeasible. This paper documents the process and successful results of Shell's undertaking in doubling lateral length using casing floatation technology on five test wells in the area. It also provides detailed evaluation of post-run data to calibrate casing running models and the future impact of these results on an economical field development.
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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 | 0.000 |
| 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".