Sustainable Performance with Motor Driven Rotary Steerable Systems in High Dogleg One Run Curve and Lateral Wells
Bibliographic record
Abstract
Abstract A major Permian operator is constantly pursuing opportunities to reduce well time by engineering sustainable solutions that will achieve consistent drilling performance in the basin. The operator partnered with a directional service provider for a one-run curve and lateral sustainable drilling solution with varying levels of complexity in the Delaware Basin. The case study illustrates the roadmap developed for achieving consistent performance. The challenges across various well designs were mapped to identify variances in well trajectory, bottom hole assembly (BHA) and bit design, automation, real-time drilling parameter optimization and vibration mitigation to achieve consistent drilling performance across multiple wells. Downhole tool failures because of vibration have affected drilling performance. The paper also illustrates improvements in reducing the severity of shocks from damaging vibration mechanisms with BHA design, Bit design and real time mitigation capabilities enabling consistency. The performance across multiple months was evaluated to further fine-tune the BHA design improving the steering capability of the bottom-hole assembly with advanced BHA modeling software. The methodology employed delivered consistent one-run curves with a stiff bottom hole assembly design planned on 8 to 9 degrees per 100’ and continued to drill two-mile laterals in the Delaware Basin. The team delivered further improvements within the stiff BHA design to achieve a planned 10-degree curve and continued to drill into the lateral across multiple wells on the pad. The BHA design had to incorporate the risks involved with motor-driven RSS applications in high DLS curves on BHA component failure related to fatigue. The paper will describe the modifications to the bit and BHA design, drilling surface parameter optimization, steering automation and automated controls for vibration mitigation, and effective communication between all stakeholders to mitigate dysfunctions leading to non-productive events, enabling the team to achieve consistency on well delivery. The performance reduced the well time by eliminating a dedicated conventional mud motor BHA assembly for drilling the curve section. There are future areas of improvement identified that will further enhance performance and decrease the risk involved in delivering one run curve lateral RSS solution. The paper describes all the critical parameters involved in delivering a one run high dogleg curve-lateral for the Permian Basin where horizontal reach is extending to three-mile laterals more frequently. The consistency is even more important today to reduce well delivery time with sustainable solutions to develop a methodology encompassing key drilling technologies, automation, and drilling practices to reduce our carbon footprint.
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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 | 0.001 | 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".