Recent advances in machine learning and big data analytics, combined with Frank’s TRS proprietary intelligent algorithms, offer a superior method to analyze and utilize the large volumes of data generated by connection make-up operations.
The iCAM® Connection Analyzed Make-up System represents a game-changing disruption in tubular connection analysis and control technology. The iCAM® system’s artificial intelligence engine and machine learning capabilities provide automated evaluation of connection make-up data, offering flexible integration with equipment such as power tongs and CRTs to produce optimal connection integrity and accelerate the make-up process, with the potential to reduce personnel on board.
The iCAM® system draws upon a dynamic trove of data consisting of millions of connection make-ups to positively identify anomalies, including thread and seal interference, dope squeeze, galling and other factors outside of conventional make-up criteria. This enables the iCAM® system to evaluate each connection for proper make-up against more robust and descriptive criteria than possible with traditional OEM rules-based parameters and to do so objectively. The result is a more accurate, reliable, and consistent assessment of tubular connection integrity.
Integrates readily with multiple equipment packages for both land and offshore operations
Available now, everywhere
Potentially reduces personnel on board
Increases well integrity and safety
Improves accuracy, consistency and reliability in connection integrity assessment
Has the potential to increase efficiencies through faster graph disposition
Data-driven recommendations result in fewer rejects and increase connection integrity
When integrated with the DISPLAY™ Digital Application, allows remote, real-time monitoring of the make-up process. Customers can view live and historical data using a web enabled device anywhere in the world
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