Identifying and Addressing Drilling Dysfunctions in Long Horizontal Wells
Bibliographic record
Abstract
Abstract Horizontal Montney wells in the Albright field of Western Canada drilled by all operators are riddled with motor failures. In 2012, ConocoPhillips drilled two wells in the field that gave us significant insight into the drilling mechanics of slim hole horizontal wells. After 6 consecutive motor failures in the lateral of the first well in 2012, the decision was made to take steps to understand what was happening down hole. The paper will cover the findings as they relate to understanding and mitigating some of the common drilling dysfunctions in the field including vibration, buckling, and loss of WOB while rotating. This paper will provide some tools and ideas to identify and mitigate some drilling dysfunctions that cause drilling inefficiencies in fields all around the world. During the planning phase it was determined that the field had a history of drilling dysfunctions. Of these dysfunctions, buckling was identified and addressed in the planning phase. Vibration problems were confirmed while drilling, and steps were taken to mitigate the vibrations. Significant loss of WOB (over 20klbs) while rotating without buckling was observed, and steps were taken to compensate for this loss. Data will be presented to dispute the industry assumption that a well is axially "frictionless" while rotating; significant drag can in some cases exist in a well even while in rotary drilling mode. An alternate theory to relate axial friction to RPM will be presented. Various drilling dysfunctions are often common in the field, and often viewed as acceptable since the industry is still able to drill the wells. Dealing with the downhole dysfunctions our industry face will likely improve our drilling performance. The current theory on axial friction of rotating drill pipe is proven incorrect, which means a new mathematical model is needed for the torque and drag computer models. A practical method for measuring and dealing with the drag while rotating without the need for expensive BHA components will be presented.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".