| 000 | 01028nab a2200181 4500 | ||
|---|---|---|---|
| 005 | 20260520002208.0 | ||
| 008 | 260224s2022 xxu ing | ||
| 041 | _aInglés | ||
| 245 | 0 | 0 | _aMachine Learning Aids Early Detection of Stuck Pipe in Extended-Reach Wells |
| 260 |
_a _b _cMayo 2022 |
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| 270 | _a12/05/2022 ; 12/05/2022 | ||
| 300 | _a3 p. ; 82-84 | ||
| 520 | _aThe objective of this paper is to describe the experience of using a machine-learning model prepared by the ensemble method to prevent stuck-pipe events during construction of extendedreach wells. The tasks performed include collecting, analyzing, and cleaning historical data; selecting and preparing a machine-learning model; and testing it on real-time data by means of a desktop application. The idea is to display the solution at the rig floor, allowing the driller to take actions quickly for prevention of stuck-pipe events | ||
| 581 | _a5 | ||
| 773 | 0 |
_tJournal of Petroleum Technology _g |
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| 942 | _cARTICULO | ||
| 999 |
_c194664 _d194664 |
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