Successful Relief Well Drilling Utilizing Gyroscopic MWD (GMWD) for Re Entry into an Existing Cased Hole
Bibliographic record
Abstract
Abstract In late 2007, a blow out occured in a well in the Gulf of Mexico. The blow out was caused by a leak in the production casing, which broached the surface and caused the well structure to collapse. This SPE paper describes how the Apache Corporation utilized the latest state of the art Gyroscopic Measurement While Drilling (GMWD) tools to drill a relief well to stop the blow-out. The S-shaped relief well was drilled towards the blow-out-well to perform a planned wellbore intersection. When reaching the blow out well, the production casing was milled and kill weight mud was pumped. This action stopped the blow out and enabled the operator to regain full control over the wellbore. This paper also emphasizes the challenges while drilling this re-entry well: A 800 ft portion of the relief well had to be drilled with a closure distance of less than 40 ft to the pilot hole. Conventional MWD drilling systems which base their measurements on earth's magnetic field are incapable of providing reliable readings in areas with magnetic interference. Proximity to casing hinders the ability of conventional MWD tools to function and therefore, a drilling BHA with an integrating rate GyroMWD (GMWD) was deployed in this well. Rate gyro measurements are based on the earth's spin axis and can provide accurate real time survey data, including true north toolface and azimuth where earth's magnetic field is distorted. This paper details an efficient way to drill a relief well and focuses on the innovative GyroMWD (GMWD) instrument that works in magnetic environments and close to metal casings.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".