Efficient Removal of Magnetic Contamination From Drilling Fluids: The Effect on Directional Drilling
Bibliographic record
Abstract
Abstract Magnetic debris in a drilling fluid have a significant influence on the ability of the drilling fluid to maintain its function. Down hole logging can suffer from poor signal to noise ratios. Directional drilling in areas close to the magnetic North Pole, such as in the Barents Sea, Northern Canada, or Russia, can suffer because of magnetic contamination in the drilling fluid. Magnetic particles in the drilling fluid introduce additional errors to the magnetic surveying compared to those normally included in the ellipsoid of uncertainty calculation. On many offshore drilling rigs, there are mounted ditch magnets to remove metallic swarf from the drilling fluid. These magnets normally only remove the coarser swarf. In this project, we use a combination of strong magnets and flow directors to significantly improve the performance of the ditch magnets. This combination, together with proper routines for cleaning the ditch magnets, significantly helps to clean the drilling fluid. Through the combined use of flow directors and ditch magnets, it was possible to extract more than five times as much magnetic contamination from the drilling fluid as normal compared with other proper ditch magnet systems. This is verified by comparing the ditch magnet efficiencies from two drilling rigs drilling extended reach drilling (ERD) wells in the North Sea area. In this paper, it is discussed how the accuracy of directional drilling and well position effected by various interferences can be improved by the use of a drilling fluid with minimal effect to the measurement while drilling (MWD) measurement.
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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 | 0.000 | 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".