Automated Alarms for Smart Flowback Fingerprinting and Early Kick Detection

Autor: Sven Haberer, Bente Bjelland, Tarab H. Ali, Ian P. Says, Olav Helgesen, Max Liang, Charles C. Ubaru, Moray L. Laing
Rok vydání: 2013
Předmět:
Zdroj: All Days.
DOI: 10.2118/163474-ms
Popis: Recent events and studies show that wellbore stability and geopressure events continue to plague the oil industry with issues that affect the safety of people and the environment. In addition, events such as kicks and lost circulation also create significant loss of time and productivity, commonly referred to as non-productive time (NPT). Deepwater studies have shown NPT related to kicks, and lost circulation can amount to 4.5% of the total well construction time. Consequently, early kick and lost circulation detection is crucial to eliminating detrimental effects on human and environmental safety, in addition to minimizing NPT. Kicks frequently happen during connections, and flowback fingerprint monitoring has been used for more than a decade across the industry to aid in kick detection. However, setting alarm thresholds and identifying abnormal flowbacks has been a manual process that relies heavily on the experience and intuition of the engineer who performs this critical safety monitoring. This manual process frequently misses early signs of influx, and thus greatly increases the well remediation time. This publication focuses on the development and deployment of an automated flowback monitoring technology. The new solution aids drillers and drilling engineers by generating intelligent alarms relevant to current well conditions for early kick and loss detection, which can result in detecting kicks up to one connection earlier than the existing manual method. This paper demonstrates the benefits of Smart Flowback Fingerprinting over existing practices and how it can significantly reduce safety risks and NPT.
Databáze: OpenAIRE