Big Data Metocean Analytics for Oil and Gas Logistics Planning

• Main Author: Badarudin, Suhaila
• Format: Final Year Project
• Language: English
• Published: IRC 2019
• Subjects: Q Science (General)
• Online Access: http://utpedia.utp.edu.my/20961/1/SUHAILA%20BADARUDIN%2022960.pdf; http://utpedia.utp.edu.my/20961/
• Institution: Universiti Teknologi Petronas

Metocean is an important aspect when dealing with logistics for an Oil and Gas industry. Due to the nature of Metocean being a Big Data, it is getting hard to keep track and to monitor it manually. As most of the activities for the Oil and Gas industry are highly affected by the weather conditions, an automated solution should be developed to monitor crucial weather information to assist in Oil and Gas logistics planning activities. Therefore, this project is focusing on the development of a predictive and descriptive dashboard incorporated with Metocean analytics for the Oil and Gas Industry. The dashboard is being built by using a data visualization tool called Power BI and it also incorporates Python Machine Learning for extensive visualization. All Metocean data will be stored in a database created using MongoDB. This project is expected to help the logistics team in the Oil and Gas industry to conduct an effective logistics planning using the dashboard that incorporates descriptive and predictive analytics.