Pipeline Integrity Management and Data Science Blog

With AI, zero failure is more than a pipe dream

Everyone in our business knows—or ought to know—about the pipeline maintenance crisis that puts billions of dollars, lives, property, and the reputation of midstream oil & gas industry at risk, leading some in the public to call it a “ticking timebomb.” Statistics indicate tens of thousands of miles of pipes decades beyond their predicted end-of-life, scattered so wide and buried so deep that just finding them on a map can be a problem.

Cognitive Integrity Management™ 3.0 General Availability

This week we officially released Cognitive Integrity Management™ 3.0, (“CIM 3.0”), which was developed under the product codename Polaris. The product team has been working tirelessly with SME’s from our participating pipeline operators during our private preview to ensure the solution applies horizontally across most operators. Starting at the end of May, each week these SME’s provided us operational data from their existing systems, assisted to validate CIM features, and confirmed the accuracy of the results.

Disrupting the ingestion, feature alignment and classification process

During our time in the Microsoft Accelerator, Data Science, and Machine Learning cohort, we interviewed a few folks working in integrity management for pipeline operators to ask them to describe some of their most difficult challenges. We anticipated it would range from dealing with silos of data to spatially integrating risk data. However, we were surprised to learn that they simply wanted a solution that would accurately align features (welds, anomalies, valves, etc.