When it comes to identifying pipeline integrity risks, midstream operators today have more sensor technology to choose from than ever. When it’s time to analyze the resulting data, however, operators often fall back to tried and true tools such as Microsoft Excel. This typically involves comparing new and earlier test results on spreadsheets to find indications of a pressing threat. Now, however, operators have a new data analysis option, a solution that can help them capitalize on the full business value their pipeline inspections offer.
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.
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.
We are excited to share the most recent progress that has been made to our Polaris release set for launch before the end of the year. Our data science and development teams are busy working through user stories for our Polaris minimally viable product (MVP) release. At the end of May we held our kick off meeting with operators participating in our Private Preview at the Microsoft Technology Center in Houston.
Alignment Business Problem: When evaluating the integrity of a pipeline using inline inspection data, one of the primary challenges the integrity engineer faces is reliably and accurately aligning data from consecutive inspections with other asset information. Without this alignment, both longitudinally along the length of the pipeline and by clock position, it is extremely difficult to make comprehensive comparisons of identified features between multiple Inline Inspections. To correctly handle this comparison, the process used must first align anomalies and do so with a high quantifiable level of statistical confidence.
