Automated Influx and Loss Detection System Based on Advanced Mud Flow Modeling
- Aurore Lafond (Schlumberger) | Florian Leblay (Schlumberger) | Ghislain Roguin (Schlumberger) | Maurice Ringer (Schlumberger)
- Document ID
- Society of Petroleum Engineers
- SPE Annual Technical Conference and Exhibition, 30 September - 2 October, Calgary, Alberta, Canada
- Publication Date
- Document Type
- Conference Paper
- 2019. Society of Petroleum Engineers
- Managed Pressure Drilling, Kick and Losses, Pump Efficiency, Well Control, Automation
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- 172 since 2007
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Maintaining well control is one of the most important considerations of any drilling operation, and early detection of formation fluid influx or mud losses is vital to safe drilling.
Today's gain and loss detection tends to trigger too many false alarms; major improvements in reliability (few to no false alarms) and reactivity (no missed events) are needed without being user dependent. The new developed system optimizes both accuracy and efficiency. This system maintains a false alarm rate lower than current system, while detecting influxes or losses as low as 40 gal. It applies also to a wide variety of configuration: deepwater, managed pressure drilling, land rig operations, etc. This performance is achieved through a new flow-modeling processes combined with automated settings, real-time quality control and guided, intuitive software interfaces. From a purely user-dependent system, the new kick detection software is now based on automated processes, ensuring repeatable and optimal detection performances while minimizing risks of human error. The detection of abnormal flow conditions in the well relies on the comparison of predicted and measured flow at the exit of the well. The improvements of the flow modeling, such as new, calibrated pump-efficiency models based on the isothermal modeling of the pumps, increase the robustness and the reactivity of the detection system. The presented case studies allow quantifying improvements of the kick detection performance between the existing system and the new version, benchmarking both the influx-detection reactivity and the system reliability. Kick detection charts used in the study represent a new way of illustrating detection performances.
|File Size||1 MB||Number of Pages||11|
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