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"Adoption of big data analytics for energy pipeline condition assessmen" by Muhammad Hussain, Tieling Zhang et al.

Due to complexity, the oil and gas industry use various sensors to collect data for analysis to maintain the safety and integrity of pipelines and associated infrastructures. There is an enormous amount of data available to conceal crucial information, including precursor data on failure modes and knowledge that may be analyzed. The availability of large amounts of data has enabled the development of analytical tools that integrate methods like predictive analytics using different decision-making models, artificial intelligence (AI), and machine learning. These tools are crucial for managing pipeline conditions, preventing unwarranted failures, enhancing asset performance, availability, and decision-making. Big data analytics enables energy companies to implement a proactive approach to pipeline condition assessment. By integrating real-time data from sensors embedded in pipelines, weather conditions, and maintenance records, it becomes possible to detect potential issues and predict a ....

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