The application of big data analytics, artificial intelligence, and machine learning to solving challenging problems is ever-increasing in the oil and gas industry. These techniques have already been proven to be powerful tools that can not only improve safety and reliability but can also provide more consistent and accurate decision-making capabilities as compared to conventional methods. This paper will detail a real-world application of big data analytics and machine learning to the tubular connection make-up process, realizing significant benefits over traditional human-evaluated methods. While the focus of the paper will be on a single application, similar approaches may be beneficial to other applications and other industries, achieving similar benefits.

Keywords:
data mining, anomaly, artificial intelligence, effective tool, shoulder point, technician, application, big data, accuracy, connection evaluation
Subjects:
Information Management and Systems, Data mining, Artificial intelligence
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