| Autor: |
Aymen Harrouz, Houari Toubakh, Redouane Kafi, Moamar Sayed-Mouchaweh, Hajer Salem |
| Rok vydání: |
2022 |
| Předmět: |
|
| Zdroj: |
Annual Conference of the PHM Society. 14 |
| ISSN: |
2325-0178 |
| Popis: |
The production of Oil & Gas from underground reservoirs involves chemical and mechanical processes that affect well drilling and operation. Many of these processes may eventually cause a problem with the well, resulting in a decrease in production or in equipment failure. This paper deals with fault prognosis during the practical operation of Oil & Gas wells. This work focus on the remaining useful life prediction of the “Spurious Closure of the Downhole Safety Valve” fault. This paper proposes a scheme based on the use of unsupervised machine learning approach and a drift detection mechanism is employed in order to predict the time to failure, real fault scenarios data are used, the proposed scheme is evaluated using different prognosis performance metrics. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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