The First Use of Gravity MWD in Offshore Drilling Delivers Reliable Azimuth Measurements in Close Proximity to Sources of Magnetic Interference
Bibliographic record
Abstract
Abstract Measurement While Drilling (MWD) is the preferred method of surveying a well bore when drilling deviated wells. MWD has an advantage over other types of surveying in that the tools are part of the Bottom Hole Assembly (BHA) and surveys can be obtained quickly without the need for interrupting the drilling operation to run a separate surveying tool. However, like all magnetic survey instruments, MWD is susceptible to magnetic interference. The directional azimuth information becomes unreliable when in close proximity to sources of magnetic interference such as casing strings or adjacent wells. This paper describes a new method of MWD surveying which includes a second accelerometer sensor package to derive azimuth rather than using magnetometers. It is therefore not prone to magnetic interference and the same drawbacks as conventional MWD. The technique uses the inherent bending of a BHA between the two sets of accelerometers in order to measure the relative change in azimuth. Two case histories are outlined where this technique was successfully used to sidetrack two near vertical wells from directly below existing casing strings despite the presence of magnetic interference. In both cases, the ability to initiate the build as early as possible was important as it provided the greatest possible chance of achieving the relatively tight directional plan. The use of Gravity MWD may provide considerable cost savings compared to alternative techniques that could incur additional rig time, be sensitive to movement and may not be capable of including real time Logging While Drilling (LWD).
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".