Steven is currently the President & CEO of Hifi Engineering, a fiber optic sensing technology company (partly owned by Enbridge, Cenovus, and BDC). Hifi possesses over 50 patents on specialized fiber optic technology, and artificial intelligence / machine learning based software algorithms, designed for preventative pipeline leak detection.
Prior to Hifi, Steven was acting CFO at Steeper Energy, an alternative energy company, President & CEO of Hemisphere GPS, which provided machine control / automation solutions, Vice President & General Manager at AOL (Time Warner) Canada, where he headed up the Service businesses for Canada, and Group Telecom as Senior Vice President Marketing & Sales. Steven has also held several management positions at TELUS Corporation.
Steven Koles has served on boards and in advisory capacities with such organizations as Hifi Engineering, VentMeter Technologies, Hemisphere GPS, Qwick Media, and Route 1. He is a graduate from both the Faculty of Business at the University of Alberta, as well as the Executive Management Program at the University of Western Ontario’s Richard Ivey School of Business. Steven has also received his ICD designation from the Institute of Corporate Directors through the University of Toronto and University of Calgary.
Virtual Pipeline Summit 30 Jun
Value Added Pipeline Applications Using High Fidelity Fiber Optic Monitoring & Machine Learning
President & CEO, Hifi Engineering, Canada
Distributed fiber optic sensing has been gaining significant momentum in pipeline industry adoption. The primary application of this technology has been in preventative leak detection. However, new value-added applications are now emerging with potential to deliver extra value to the pipeline operators, over and above leak detection.
Different fiber optic sensing technologies exist which can be appropriately positioned for various applications. One of these specialized fiber optic sensing approaches is known as high fidelity distributed sensing (HDS) which uses a different interferometry to achieve very high signal-to-noise ratio (SNR). Along with high SNR, HDS also provides integrated acoustics, temperature and strain/vibration, and is optimized to do so over long distances without degradation of fidelity. This makes the HDS technology particularly appropriate for preventative pipeline leak detection as well as a number of other value-added applications.
Case studies will be provided to showcase the value of using artificial intelligence and machine learning to explore new frontiers in pipeline monitoring; including a variety of “value added” applications such as flow anomaly detection, flow rate, pressure, and density estimation. Other applications such as pig, vehicle, and train detection, tracking and analysis will also be presented.