This paper puts forward a first of its kind integration and transparency of Offshore Supply Vessels providing global positioning, fuel analysis and manifest details on the Tengiz mega project. Thus, enabling the project to have a faster execution time. The methods of research and design used a data-driven and action-based methodology.

First, by the integration of disparate data, analysis on verification and then trend analysis to do a higher level of analytics. Machine learning techniques have been researched that when deployed will provide further enhancement to Caspian offshore planning work, that will significantly improve speed and efficiency on major capital projects.

Keywords:
Artificial Intelligence, fuel tank, data mining, operation, Efficiency, database, machine learning, ship, characteristic, real time system
Subjects:
Information Management and Systems, Artificial intelligence
Copyright 2018, Society of Petroleum Engineers
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