HPHT Well Integrity: Load-Resistance Monitoring and Predictive Analysis
- Bibek Das (SafeQ Services) | Robello Samuel (University of Houston)
- Document ID
- Offshore Technology Conference
- Offshore Technology Conference, 1-4 May, Houston, Texas, USA
- Publication Date
- Document Type
- Conference Paper
- 2017. Offshore Technology Conference
- 1.6 Drilling Operations, 2.10 Well Integrity, 7 Management and Information, 7.6.4 Data Mining, 2 Well completion, 7.6.6 Artificial Intelligence, 4.2.3 Materials and Corrosion, 7.6 Information Management and Systems, 6.3 Safety
- Real-Time Monitoring, Predictive Analytics, HPHT, Well Integrity
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In recent years, in the post Macondo era, the Bureau of Safety and Environmental Enforcement (BSEE) has come out with proposals and regulations that require monitoring of Deep Water (DW) and High Pressure/High Temperature (HPHT) wells in real-time. As new wells are being drilled in DW and HPHT environment, much of this drilling is supported from the Onshore Drilling Centers located onshore miles away from the offshore field. Real time monitoring (RTM) plays an important role in identifying leading and lagging indicators of barrier failure. High bandwidth fiber optic cables are now allowing high levels of communication and real time data.
Predictive Analytics is a natural step to follow RTM. However, the challenge that stills lies ahead is whether to apply Data-driven prognosis, Model-based prognosis or a fusion approach; and which Machine Learning Algorithm is best suited to address a specific well barrier reliability issue in HPHT environment.
Producing oil and gas from deepwater reservoirs with pressures greater than 15,000 psi and temperatures of 350°F at the mudline subjects the equipment to major loads. The major loads in HPHT conditions can be attributed to: (i) heat transfer between hot fluid and equipment leading to lateral expansion/contraction loads in response to the temperature changes of the fluid; (ii) high collapse pressure due to high formation pressure; (iii) higher corrosion damage rates under sour conditions, and (iv) tensile loads due to the buoyed weight.
In light of the new BSEE requirements on load monitoring and data collection for HPHT operations, this paper discusses the major loads in HPHT conditions, and the different predictive analysis models that are available. The paper discusses particularly the load-resistance monitoring and predictive analysis approach with respect to HPHT well integrity. If we monitor the right data, extract the right features, predictive analytics can identify the integrity issues in advance, and procedures can be implemented to maintain the barrier integrity, reliability and thus prevent any fluid leakage.
|File Size||1 MB||Number of Pages||11|