High Build Up Rate Rotary Steerable System Leads to Revolutionize Onshore Horizontal Drilling in Western Desert of Egypt
Bibliographic record
Abstract
Abstract The drilling in the Western Desert area of Egypt is experiencing a shift from vertical to horizontal drilling. Challenging geology, critical landing zones, complex well profiles, and tight lease boundaries lead to the requirement of High Build Up Rate (HBUR) values. This creates a drilling challenge with the limited capabilities of the current, commercial Rotary Steerable Systems (RSS). The maximum Dogleg Severity (DLS) output capability for a RSS drilling 8–1/2 in hole size from most major directional drilling service providers is about 6.5° /100 ft. In soft formations, these doglegs output drop significantly and the RSS is replaced by a mud motor assembly. To overcome these challenges, the operator and directional drilling service provider teamed up to strengthen performance and consistency utilizing a new HBUR RSS technology coupled with an optimized bit design. The operator and directional drilling service provider started a drilling campaign in 2013. The plan was to drill a HBUR curve in 8–1/2 in hole and land in the target zone with planned (DLS) in the range of 8.00 to 10.00° /100 ft. Then set a liner and drill 6 in lateral hole to the well TD. To date, this campaign has resulted in the successful drilling of three wells. The operator's costs were lowered through improved performance with the new HBUR RSS technology. The new technology reduced the number of trips and enabled faster curve drilling with pure rotary and better toolface control. The average number of drilling days per curve and lateral were reduced. In all cases, the curve HBUR planned rates were successfully achieved in a single run with optimum rate of penetration. This paper will discuss the case histories of the three successful wells. The benefits, cost savings and performance improvements of the HBUR RSS technology will be described for each well.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".