Remote Borehole Management Overcomes Strength Anisotropy and Enhances Hole Cleaning
Bibliographic record
Abstract
_ This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 223794, “Case Study—Efficient Drilling of High-Angle Wells: Overcoming Strength Anisotropy and Enhancing Hole Cleaning Through Remote Real-Time Borehole Management,” by Shekhar V. Gosavi, SPE, Amshith Adla, and Shanmukh Sripada, ExxonMobil, et al. The paper has not been peer reviewed. _ The authors of the complete paper describe a case study in which, through proper understanding of failure mechanisms, characterization of shale strength anisotropy, and implementation of strength-anisotropy incorporated models, drilling high-angle wells through a challenging shale formation was deemed feasible. Following a pilot well’s success, a high-angle well was drilled using optimized parameters and higher mud weight (MW), achieving drilling with no nonproductive time (NPT). Introduction Although anisotropy is well understood, misconceptions about instability mechanisms creating reluctance to use of higher MW often lead to wellbore failure, NPT caused by hole‑cleaning issues, and a reluctance to drill high-angle extended-reach-drilling wells. In the Hebron field in eastern Canada, a similar challenge arose. Previous drilling by offset operators in nearby fields suggested that wells through the Fortune Bay formation should not exceed 45° inclinations because of severe wellbore instability. The Hebron field includes three main producing formations: the Ben Nevis, the Hibernia, and the Jeanne d’Arc (JDA). Following initial shallower formation development, focus shifted to JDA formation development, which would require drilling the Fortune Bay shale at a high angle. The Fortune Bay shale in this region historically had caused significant NPT because of instability, requiring a detailed understanding of its properties to enable the safe drilling of high-angle wells. Pilot Well P4H-OP1 The pilot well was drilled through the anisotropic Fortune Bay shale at an intermediate angle (42°) to validate the feasibility of drilling beyond the inclination limits established by offset operators. Additionally, the well provided critical formation data necessary to develop a wellbore-stability model for future drilling operations. Well P4H‑OP1 also was the first well to target deeper production intervals from the Hebron Platform, specifically the Jeanne d’Arc sands. However, pressure depletion from nearby wells had reduced the fracture gradient in the shallow Ben Nevis sands, requiring a revised casing program to isolate these sands and allow for the use of higher MWs while drilling the Fortune Bay formation. The ability to increase MW to stabilize the wellbore was a critical design requirement based on the authors’ understanding of the primary failure mechanism of Fortune Bay. Ultimately, the decision was made to forego a test hole because of time and cost constraints. The pilot well’s lower completion required a 178‑mm cemented liner to enable a multizone intelligent well completion. The well was designed to be drilled at a 42° inclination, a limit set based on previous experience.
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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".