Bibliographic record
Abstract
Abstract Opportunity to improve rig floor safety, reduce technical casing running risk and reduce cost has motivated operators to utilise the top drive for casing running operations. Simple and easy approaches for applying make-up torque and hoisting loads to the casing string have been used with some success, but in some applications performing these functions safely, economically, and without connection damage has not been trivial. Operational logistics, management of loads that cause casing thread damage, and prevention of pipe body damage are examples of challenges requiring sound technical solutions. Pipe handling logistics, including engagement of the casing grip, must be executed efficiently without damaging casing threads or sealing surfaces. Similarly, bending loads resulting from rig misalignment or casing curvature can initiate thread damage if uncertainties remain unmanaged. Finally, local cold working of pipe body material increases stress cracking susceptibility, particularly on inner surfaces, and will reduce casing string reliability. Successful use of casing running technology depends on selecting a system that meets the technical requirements of the application. A sound understanding of casing thread make-up, drilling rig operations, and the interaction between the two enables critical evaluation of emerging technology and reduces the risk of commercial failure. This paper presents the background behind such evaluation and discusses a range of technologies in the context of that background. Introduction A desire to improve rig floor safety and eliminate unnecessary expenses has motivated oilfield operators to utilise the top drive for casing running operations. Applying make up torque and hoisting the casing string can be accomplished quite easily, but performing these functions safely, economically, and without damaging the casing body or connections is a nontrivial task. Several top drive casing running systems are commercially available, but consistently successful deployment requires that users carefully match technology with applications. Technical challenges are described here and solutions characterized in application-specific context. Successful exploitation of this emerging technology will occur more reliably with an understanding of the relationships between pipe, casing threads, running equipment, and drilling rig operations. The simplest way to transfer torsion and axial load from the top drive quill to the casing is with a crossover, commonly referred to as a nubbin or make up quill, from the top drive to the casing thread. This approach is widely used in Western Canadian shallow hole applications, but fails to capture the full safety and economic benefit available through top drive casing running systems that engage the pipe body, rather than the casing threads.1 Purpose specific top drive casing running tools are used in a broad range of applications. Success has been reported for casing runs in:highly deviated Gulf of Mexico wells2,river crossings2,onshore horizontal wells2,desert wells3, andthe North Sea4. Compelling business cases for adopting top drive casing running systems have been published previously1,2,3,4 and the subject will be treated here at a summary level only. The economic impact of using top drive casing running systems is positive in three areas. Reduction in manpower requirements is reflected directly in labor, mobilization/demobilization, and accommodation costs.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.013 | 0.004 |
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".