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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Schultz, R.L. de Jess, O. |
| Copyright Year | 2002 |
| Description | Author affiliation: Halliburton Energy Services, Carrollton, TX, USA (Schultz, R.L.) |
| Abstract | In this paper a new method of early detection of bearing failure in roller-cone oilwell drill bits is described. Acoustic signals produced by the bit during drilling are monitored remotely and analyzed to detect the onset of bit failure. A simple, unique method of signaling the surface operator to warn of bit failure is also described. It is highly desirable to avoid drilling until a catastrophic bit failure occurs. Catastrophic failures can dramatically impede the progress made in drilling a well, thereby greatly increasing drilling costs. This method avoids the complication of placing sensors in the bit by passively monitored acoustic signals generated by the bit during normal drilling. Acoustic spectral power ratios between discrete frequency bands are constantly computed and analyzed to detect failure. As a bit begins to experience bearing failure the ratio of high frequency spectral power to low-frequency spectral power increases indicating a bearing failure in progress. The effectiveness of this method has been verified experimentally by recording acoustic data produced by actual bits during drilling. The bits were tested until a bearing failure occurred. A theoretical explanation of the method and experimental results are presented. |
| Sponsorship | American Autom. Control Council IFAC SICE |
| Starting Page | 2603 |
| Ending Page | 2608 |
| File Size | 579244 |
| Page Count | 6 |
| File Format | |
| ISBN | 0780372980 |
| ISSN | 07431619 |
| DOI | 10.1109/ACC.2002.1025178 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2002-05-08 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | American Automatic Control Council(AACC) |
| Subject Keyword | Acoustic signal detection Drilling Condition monitoring Failure analysis Frequency Remote monitoring Signal analysis Surface impedance Costs Acoustic sensors |
| Content Type | Text |
| Resource Type | Article |
| Subject | Electrical and Electronic Engineering |
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