Oil & Gas, Research

iPIPE Advances Risk Management with Machine Learning

The intelligent Pipeline Integrity Program (iPIPE) has partnered with Pipeline-Risk to advance optimization of pipeline risk management and prevent incidents. Pipeline-Risk uses machine learning to analyze pipeline integrity data and quantify risk that informs mitigation decisions.

The joint offering is a web-based machine learning platform and the research will determine if existing data are sufficient to identify useful patterns, measure data influence, and learn and validate threat models.

“Pipeline-Risk is a great addition to our portfolio addressing prevention,” said Darren Schmidt, iPIPE Program Director at the Energy & Environmental Research Center (EERC). iPIPE offers technology partners the unique opportunity to gain real-life demonstration experience working with oil and gas providers on the actual technologies they need to increase efficiency, reduce cost, and reduce risk for pipeline leaks. By partnering with iPIPE, Pipeline-Risk is expecting to see positive outcomes while assessing the validity and value of machine learning-based processes and methods for gathering system operators and improved pipeline integrity.

iPIPE is an industry consortium focusing on the advancement of near-commercial, emerging technologies to prevent and detect pipeline leaks. iPIPE is led by the Energy & Environmental Research Center (EERC) at the University of North Dakota and sponsored by the North Dakota Oil and Gas Research Program. Industry partners include Energy Transfer LP, DCP Midstream, Enbridge, Equinor, Goodnight Midstream, Hess, Marathon Petroleum Logistics, ONEOK, and TC Energy. For more information about joining one of the most innovative programs in the pipeline industry, contact the EERC or visit www.ipipepartnership.com.

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