Extended Reach Drilling - new solution with a unique potential
Bibliographic record
Abstract
Abstract The Reelwell Drilling Method (RDM) is a new drilling method, developed and qualified for commercial use during recent years. RDM is a multi-purpose drilling method with a unique flow arrangement. RDM is based on using a conventional drill string combined with an inner string to form a dual conduit drill string. This arrangement allows the return fluid, containing drill cuttings from the bottom of the well, to be transported back through the inside of the drill string. RDM has the potential to increase the envelope for Extended Reach Drilling (ERD) for several reasons: – Torque and Drag reduction, due to use of a flotation technique of the drill string. – Elimination of the dynamic Equivalent Circulating Density (ECD) gradient, since the ECD is screened from the formation. – Optional Hydraulic Weight On Bit (WOB), due to a piston type arrangement at the drill string. The following presents a case study for an ultra ERD RDM application. In this case, the RDM arrangement involves the use of a special dual conduit aluminium drill string and the use of two different density fluids in the well during drilling. A calculation example of a fully buoyant drill string is also presented. This situation indicates that the well can be drilled with very high operational margins on the equipment and at the same time, the wear will be very low. The simulations indicate that the extreme ERD well of 15.8 km depth can be drilled with good margins, mainly due to flotation of the drill string. It is shown that the well can be cased and lined, using conventional flotation techniques in combination with RDM.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".