New Technologies to Enhance Performance of Section Milling Operations that Reduces Rig Time for P&A Campaign in Norway
Bibliographic record
Abstract
Abstract In 2008, ConocoPhillips completed the plug and abandonment (P&A) of two of eight water injection wells at the 2/4 W Platform in the Norwegian sector of the North Sea. The average performance was 65 days per well. One of the most challenging aspects of the 2008 P&A campaign was deep section milling of the casing to install the secondary reservoir barrier where multiple section mill runs were necessary. In mid-2009 ConocoPhillips resumed operations to P&A the remaining 6 wells. The scope to P&A the remaining 6 wells was increased to include a second barrier across the Miocene which called for more section milling than the first campaign. ConocoPhillips management challenged the rig team to significantly improve performance on the second campaign. Performance on the final six wells improved dramatically to an average of 46 days. P&A requirements called for section milling 165 feet of 9 7/8″ casing at depths ranging from 8,585 ft to 10,896 ft. A joint ConocoPhillips and Baker Hughes team was formed to seek a method to significantly reduce the time required to mill the casing for the second campaign. The team set an aggressive goal of milling the section in one run. In addition a plan would be needed for additional section milling to achieve the second Miocene plug as well as potential for 13-3/8″ milling to achieve adequate isolation. Two new technologies were implemented to improve the performance of section milling operations during the P&A campaign. A new cutter technology that had shown significant impact resistance and longer life than previous cutter technology was installed on the section mill blades which demonstrated increased resistance to wear and improved chip breaking ability. In addition, a new downhole optimization sub was included in the BHA that gathered information at the section mill and sent the data back to surface in real-time for on-site evaluation by engineers. These two technologies significantly reduced rig time due to the longer lasting cutters as well as the real-time data transmitted back to surface from the downhole optimization sub. The information from the optimization sub was evaluated onshore during the entire P&A campaign and operational improvements were made as each successive well was completed.
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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".