Combining State-of-the-Art Hybrid Bit and Positive Displacement Motors Saves 863,670 CAD Over 20 Wells in Northern Alberta, Canada
Bibliographic record
Abstract
Abstract A Canadian oil & gas operator has been setting new benchmarks drilling the vertical and tangent section of Montney horizontal wells in the Placid field of Northern Alberta. Initially, the operator drilled vertical wells to kick off point (KOP) with polycrystalline diamond compacts (PDC) and conventional mud motors. As a result of increasing well density, however, the well plans consistently required a 15° to 30° tangent section. With PDC drilling, toolface and build up rates were problematic and the sliding rate of penetration (ROP) was slow. A Rotary Steerable System (RSS) was introduced, but despite the improved performance, the technology came at a premium cost and the severity of drilling dysfunctions generated an increase in tool failures. With falling oil prices, a more cost effective solution was required. Hybrid bit technology, which combines the cutting mechanism of both fixed cutter and roller-cone bits, has been extensively utilized in Canada to drill build sections, providing outstanding results. They have not, however, been commonly used to drill the vertical (drill-out) and tangent sections. The operator combined a state-of-the-art hybrid bit with a mud motor to drill the interval with an 85% success rate. The combination of the hybrid bit and conventional motor, compared to PDC and RSS, resulted in a 30% cost savings to complete the interval. The present case study outlines how hybrid bit technology development, driven by field data in a continuous improvement cycle, identifies performance opportunities, which have a significant impact on drilling time and cost savings in drill out sections. The overall objective of this current case study is to highlight the results and lessons learned throughout the implementation process.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.017 | 0.003 |
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".