Pipeline Integrity Management and Data Science Blog

Crack Fatigue Analysis as a Cloud Service

The more time we spend with our clients the more we learn they are reliant on spreadsheets. To this point, we’ve jokingly considered changing our mission from “Predict pipeline failures, save lives and protect the environment… with the assistance of Machine Learning” to “We eliminate legacy Microsoft Excel spreadsheets”. Of course, all joking aside, we want to enable integrity management teams to spend their time doing high-value engineering. The latest Microsoft Excel sheet we have replaced is a customer’s version of a Crack Fatigue Analysis based on the modified Ln-Sec equation for cracks in pressurized pipelines.

Data Ingestion and Normalization – Machine Learning accelerates the process

If you have ever looked through 20 years of inline inspection tally sheets, you will understand why it takes a machine learning technique (e.g. random forest, Bayesian methods) to ingest and normalize them into a database effectively. It would be a monumental task if attempted manually by a human … not to mention the risk of endless errors. However, by training a machine learning data classifier on enough log data, this task becomes the perfect scenario where data science can drastically improve integrity management practices.

OneBridge on the Money Answers Show with Jordon Goodman

Episode Description Dwayne Kushniruk,Tim Edward, and Brandon Taylor, from OneBridge Solutions, a subsidiary of OneSoft Solutions, talk with host Jordan Goodman about OneBridge Solutions game changing approach to helping predict and eliminate potential oil and gas pipeline problems. Through the power of big data and machine learning, OneSoft’s new SaaS approach to anticipating and preventing pipeline failures has the potential to be a game changer in the fuel industry. Kushniruk, Edwards and Taylor explain their company’s innovative high powered approach and the investment opportunities offered.