Jiang Jin

Data Scientist at INGU

Jiang Jin is a Data Scientist at INGU since November 2021, previously serving as a Rail & Transit Engineer at WSP USA from July 2019 to November 2021. Prior industry experience includes a role as a Research Assistant at Penn State University between August 2015 and August 2019, and a Research Engineer position at ENSCO, Inc. from October 2012 to November 2014. Jiang Jin holds a Ph.D. in Civil Engineering from Penn State University (2015-2019) and a Master of Science in Mechanical Engineering from the University of Florida (2010-2012).

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INGU

Currently, inline inspection in the oil and gas sector is a series of staged engineering events, designed to assess the condition of pipeline assets. It is costly, infrequent, and only addresses those lines that are within reach. In fact, it is estimated that 40% of the world’s pipelines are unpiggable. The vulnerabilities between inspections,which are typically years apart, or the inability to conduct inspections at all, puts the world’s aging pipeline infrastructure at risk. In order to address these issues, we have focused on changing the economics, the technology, and the workflow associated with inline inspection. We have introduced the industry’s first self-serve inspection model that eliminates significant engineering and downtime costs. We have developed miniature, multi sensor Pipers® technology that freely flows within any and all active pipelines, regardless of location, condition, material or configuration. This technology is capable of inspecting pipelines as small as 2 inches in diameter, and surveying for leaks, geometric defects, magnetic anomalies, and deposits in a single run. Further, we have reduced the cost of inline inspection by a factor of 10, making it possible for integrity programs to be more present, more often, across all of their assets. Finally, such accessible technology has given us the opportunity to work with a complete range of clients – large and small, private and public – resulting in rich datasets libraries that offer unprecedented contextual analysis and continuous advancement of our data analytics capabilities. Our approach provides clients with uninterrupted access to up-to-date condition-critical data, allowing them to optimize planning, decision-making, and actions.


Headquarters

Calgary, Canada

Employees

11-50

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