Model-Based Health Monitoring of Annular Blowout Preventers
- Taoufik Wassar (University of Houston) | Mete Mutlu (Transocean Inc.) | Matthew A. Franchek (University of Houston) | Oussama Hattab (University of Houston)
- Document ID
- Society of Petroleum Engineers
- SPE Drilling & Completion
- Publication Date
- December 2019
- Document Type
- Journal Paper
- 458 - 467
- 2019.Society of Petroleum Engineers
- health monitoring, annular elastomer, physics-based modeling, degradation detection, blowout preventer
- 3 in the last 30 days
- 156 since 2007
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Presented here is an adaptive model-based approach for the real-time condition and health monitoring of annular blowout-preventer (BOP) functions. The proposed approach fuses a first-principles model with in-field data by adapting the model coefficients to match the data. These adapted coefficients are directly interpreted as the annular preventer health indicators. The performance of the proposed adaptive model was evaluated using an annular-BOP digital twin (i.e., Virtual Annular Preventer) implemented in a simulation environment. The model was then adapted using data collected from six different offshore rigs. The resultant model coefficients indicated that the proposed methodology might detect degradation of annular preventers and, hence, provide drillers and subsea engineers with real-time information about the health of the annular-BOP function.
|File Size||905 KB||Number of Pages||10|
API STD 53, Blowout Prevention Equipment Systems for Drilling Wells. 2016. Washington, DC: API.
Carter, K. M., van Oort, E., and Barendrecht, A. 2014. Improved Regulatory Oversight Using Real-Time Data Monitoring Technologies in the Wake of Macondo. Presented at the SPE Deepwater Drilling and Completions Conference, Galveston, Texas, 10–11 September. SPE-170323-MS. https://doi.org/10.2118/170323-MS.
Cheng, S., Azarian, M. H., and Pecht, M. G. 2010. Sensor Systems for Prognostics and Health Management. Sensors 10 (6): 5774–5797. https://doi.org/10.3390/s100605774.
Chze, L. P. and Liam, C. W. 2016. Optimising Data Processing for Subsea System Surveillance Through Subsea Condition Monitoring. Presented at the Offshore Technology Conference Asia, Kuala Lumpur, 22–25 March. OTC-26842-MS. https://doi.org/10.4043/26842-MS.
Ding, S. X. 2008. Model-Based Fault Diagnosis Techniques. London: Springer-Verlag.
Fisher, R. A. 1936. The Use of Multiple Measurements in Taxonomic Problems. Ann Eugen 7 (2): 179–188. https://doi.org/10.1111/j.1469-1809.1936.tb02137.x.
Holand, P. 1989. Subsea BOP Systems, Reliability and Testing—Phase V. SINTEF Report STF75 A89054, Trondheim, Norway.
Holand, P. 1999. Reliability of Subsea BOP Systems for Deepwater Application, Phase II DW (Unrestricted Version). SINTEF Report STF38 A99426, Trondheim, Norway (November 1999).
Holand, P. and Awan, H. 2012. Reliability of Deepwater Subsea BOP Systems and Well Kicks. Report ES 201252/02, ExproSoft, Trondheim, Norway (August 2012).
Holand, P. and Molnes, E. 1986. Reliability of Subsea BOP Systems—Phase III, Testing and Maintenance, Main Report. SINTEF Report STF75 F86004, Trondheim, Norway (February 1986).
Hwang, H. 2015. Introduction to a Condition-Based Maintenance Solution for Offshore Platforms. Presented at the International Society of Offshore and Polar Engineers, The Twenty-Fifth International Ocean and Polar Engineering, Kona, Hawaii, 21–26 June. ISOPE-I-15-041.
Martins, F. B., Cardoso, R., Tammela, I. et al. 2018. Applying CBM and PHM Concepts With Reliability Approach for Blowout Preventer (BOP): A Literature Review. Braz J Oper Prod Manag 15 (1): 78–95. https://doi.org/10.14488/BJOPM.2018.v15.n1.a8.
MathWorks. 2016. MATLAB and Simscape Toolbox Release 2016a. MATLAB is a registered trademark, and Simscape is an unregistered trademark of The MathWorks, Inc., Natick, Massachusetts.
Mutlu, M., Arnold, Z., Franchek, M. A. et al. 2017. Qualitative Fault Tree Analysis of Blowout Preventer Control System for Real Time Availability Monitoring. Presented at the Offshore Technology Conference, Houston, 1–4 May. OTC-27814-MS. https://doi.org/10.4043/27814-MS.
Mutlu, M., Tang, Y., Franchek, M. A. et al. 2018a. Dynamic Performance of Annular Blowout Preventer Hydraulic Seals in Deepwater Environments. J Offshore Mech Arct Eng 140 (6), 12 pages. OMAE-17-1136. https://doi.org/10.1115/1.4040391.
Mutlu, M., Wassar, T., Franchek, M. A. et al. 2018b. Condition and Performance Analysis of a Subsea BOP Control System Pressure Regulator. Presented at the Offshore Technology Conference, Houston, 30 April–3 May. OTC-28861-MS. https://doi.org/10.4043/28861-MS.
Mutlu, M., Wassar, T., Franchek, M. A. et al. 2018c. Real-Time Condition and Performance Monitoring of a Subsea Blowout Preventer Pipe Ram. SPE Drill & Compl 33 (1): 50–62. SPE-189987-PA. https://doi.org/10.2118/189987-PA.
Rausand, M. and Engen, G. 1983. Reliability of Subsea BOP Systems. Presented at the Offshore Technology Conference, Houston, 2–5 May. OTC-4444-MS. https://doi.org/10.4043/4444-MS.
Stigler, Stephen M. 1981. Gauss and the Invention of Least Squares. Ann Stat 9 (3): 465–474. https://www.jstor.org/stable/2240811.
Sandtorv, H. A., Hokstad, P., and Thompson, D. W. 1996. Practical Experiences With a Data Collection Project: The OREDA Project. Reliab Eng Syst Safe 51 (2): 159–167. https://doi.org/10.1016/0951-8320(95)00113-1.
Wassar, T., Mutlu, M., Franchek, M. A. et al. 2018. Leakage Monitoring of Subsea Blowout Preventer Control System. Presented at the Offshore Technology Conference, Houston, 30 April–3 May. OTC-28955-MS. https://doi.org/10.4043/28955-MS.