Optimization of Suitable Measurement Position Through Fluid Dynamics in Early Kick Detection

Sun, Hehui; Lao, Liyun; Li, Dengyue; Tao, Qinglong; Ma, Hong; Li, Huaiyu; Song, Changhong

doi:10.2523/19528-ms

Cited by 4 publications

(1 citation statement)

References 1 publication

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, their applicability is limited to water-based drilling fluid [23]. It has been reported that the accuracy of electromagnetic flowmeters for early kick detection can be improved by installation in a V-shaped flowline segment on the outlet flow path as challenges with transient large flow passage and solids deposition were resolved [24].…”

Section: Surface Sensors For Early Kick Detectionmentioning

confidence: 99%

Advances in Well Control: Early Kick Detection and Automated Control Systems

Olamigoke¹,

James²

2022

Drilling Engineering and Technology - Recent Advances New Perspectives and Applications

View full text Add to dashboard Cite

The devastating impact of the Macondo blowout incident has underscored the need for effective well barriers, early kick detection systems, and increased automation of well-control operations toward successful drilling and completion operations particularly in deep offshore environments. Early kick detection systems should be capable of detecting a gas influx both during drilling and tripping operations regardless of the drilling fluid system with minimal false-negative alarms, while automated control systems regain well-control eliminating delays or omissions due to human error. In this chapter, developments in the deployment of early kick detection and automated control systems in conventional and managed pressure drilling operations are reviewed. We discuss the use and placement of surface sensors such as the Coriolis flowmeter, smart flowback fingerprinting when the rig pumps are off, real-time gas monitoring along the marine riser and downhole measurements complimented with machine learning algorithms for early kick detection. We then focus on the application of automated well-control systems for managed pressure drilling operations for which gas kicks are circulated without stopping the pumps or shutting in the well and in conventional well operations requiring intelligent tool joint space-out prior to well shut in especially for deep offshore operations.

show abstract

Section: Surface Sensors For Early Kick Detectionmentioning

confidence: 99%

Advances in Well Control: Early Kick Detection and Automated Control Systems

Olamigoke¹,

James²

2022

Drilling Engineering and Technology - Recent Advances New Perspectives and Applications

View full text Add to dashboard Cite

show abstract

Realtime Application of Early Kick and Loss Detection (EKLD) for the Entire Drilling Operation

Zhang,

Samuel

2024

SPE Eastern Regional Meeting

View full text Add to dashboard Cite

In drilling operations, deploying a real-time monitoring and detection model to identify early kick and loss events is essential for ensuring safety and achieving operational success. The model presented has the capability to accurately recognize various phases of the drilling process—such as active drilling, tripping in, reaming, and tripping out—from the available real-time data. Furthermore, the system must detect kick/loss events across all phases accordingly, providing operators with meaningful and reliable results. Using a smart drilling phase detection algorithm in real-time, then applying unique early kick/loss detection according to the drilling activity to achieve EKLD for the entire drilling operation. Additionally, the monitoring system is designed to address the challenge of performing complex calculations in real time, ensuring that there is no lag in the system's responsiveness. The model was validated and evaluated using real-time drilling data directly from the rig in real-time, covering the entirety of drilling operations. Field testing demonstrated its effectiveness in detecting both kick and lost circulation events across all phases of drilling, applicable especially for real-time monitoring. A comprehensive performance comparison with traditional kick detection models was conducted. This comparison shows that the model is more suitable for all phases of drilling activities, by having its unique detection and validation algorithms tailored for each activity. In conclusion, the model stands out for its ability to effectively detect kicks and losses throughout the entire drilling operation, across various drilling phases, as well as its capability to process all data in real time. The model presented in this paper represents one of the first advanced systems capable of processing real-world drilling data for the entire drilling operation. It achieves accurate and timely detection of early kicks and losses in real-time while minimizing false alarms.

show abstract

Reducing False Alarms for Early Kick and Loss Detection (EKLD) in Real-Time Application Using Knowledge-Assisted Case-Based Reasoning

Zhang,

Samuel

2024

Adipec

View full text Add to dashboard Cite

Recent advancements in Early Kick and Loss Detection (EKLD) have leveraged various sensor information in real-time for detection and time-series trend analysis. However, the increase in data and complexity has led to a higher rate of false alarms, undermining the reliability and usability of the system. In this study, we developed a Knowledge-Assisted Case-Based Reasoning (KACBR) approach by integrating historical data with contextual knowledge to reduce the false alarm rate while maintaining detection capabilities. The expert system employs a hybrid methodology that combines the structured domain knowledge from Knowledge-Based Expert Systems (KBES) with the flexibility, robustness, and adaptability of Case-Based Reasoning (CBR). The model was validated and evaluated using real-time drilling data from the field. Employing the hybrid approach developed in this study, significantly reduced the overall false alarm rate while maintaining high performance in event detection. Field testing in real-time confirmed the system's effectiveness in detecting both kick and lost circulation events across all drilling phases without compromising the speed of real-time monitoring. Comparative analysis with traditional kick and loss detection methods and statistical trend-analysis-based systems revealed that the Knowledge-Assisted Case-Based Reasoning (KACBR) approach excels in reducing false alarms and maintaining detection reliability.

show abstract

Optimization of Suitable Measurement Position Through Fluid Dynamics in Early Kick Detection

Cited by 4 publications

References 1 publication

Advances in Well Control: Early Kick Detection and Automated Control Systems

Advances in Well Control: Early Kick Detection and Automated Control Systems

Realtime Application of Early Kick and Loss Detection (EKLD) for the Entire Drilling Operation

Reducing False Alarms for Early Kick and Loss Detection (EKLD) in Real-Time Application Using Knowledge-Assisted Case-Based Reasoning

Contact Info

Product

Resources

About