The Energy Calendar Allstream Energy Partners

Register Here for the DPSF (Digital Pipeline Solutions Forum) May 18, 19 – Houston

This Event Reminder is Sponsored by:

Midstream Calendar

Digitization, efficient storage, accurate alignment, and improved accessibility of expansive data sets has paved the way for next‐generation data science and advanced analytic methods to optimize and improve asset integrity performance.

Attend DPSF 2022 to learn about newly available systems and applications for virtualization, data management, and cyber-physical applications in the pipeline industry.

The Forum focuses on needs the industry has now to ensure the success of not only digital transformation and applied data science, but also the impact and evolving contribution of “cyber-physical systems” as they propel entirely new capabilities for people and machines.

In particular:

  • Virtual systems and integrity processes
  • Predictive analytics for engineering assessment & decision-making
  • Creating a digital twin of your pipeline
  • Sensor and monitoring data acquisition, curating, communication & analysis
  • Automation of inspection run comparisons and alignment
  • Constraints, interpretability and validation of Machine Learning applications
  • Cyber-systems integration


1. Unlocking Transformational Value
Shahani Kariyawasam, TC Energy
2. Geospatial Technology – The Foundation for Creating a Pipeline Digital Twin
Jeff Allen, Esri
3. Successfully Instituting a Digital Quality Management and Construction Inspection System on the TANAP Project
Ahbay Chand, Petro IT
4. Value Added Pipeline Applications Using High Fidelity Fiber Optic Monitoring & Machine Learning
Steven Koles, Ehsan Jalilian, John Hull, Hifi Engineering
5. Predicting Corrosion Growth Rate Distributions using the IDW and Applied Data Science for Input to Probabilistic Pipeline Assessments
Steven Carrell et al, ROSEN
6. Real Time Networks
Anthony Gilbert, DNV
7. Predictive Corrosion Modelling – Rise of the Machines
Mike Westlund, Parth Iyer, Dynamic Risk
8. Neural Networks for Pipeline Joint Detection
John van Pol, INGU
9. Driving and Optimizing Integrity Performance Using a Comprehensive Digital Twin
Sergiu Lucut et al, TC Energy
10. Digital Transformations Required to Support the Industry 4.0 Era
Brad Eichelberger, DNV
11. How Automated Data Normalization & Alignment Helps Operators Make Better Decisions
Jordan Dubuc, Michael Murray, OneBridge Solutions
12. Finding your match – An improved feature matching process for run comparisons
Joel Anderson, RSI, Craig Champlin, Colarado School of Mines
13. Relational Database Framework for Integrity Management Programs
Martin Glomski, Jeffrey Kornuta, Exponent, Isabelle Poulin, Peter Veloo, PG&E
14. The Benefits & Challenges of Implementing Machine Learning Processes in Support of the Digital Pipeline
Mike Gloven, Pipeline-Risk
15. Improved Pipeline Monitoring, Leak Detection and Compliance using Automated Analysis of Advanced Satellite Data
Peter Weaver, OSK
16. Preventing Common Pitfalls with Monte Carlo Simulations in Pipeline Reliability Engineering
Gabriel Langlois‐Rahme, Miaad Safari, Enbridge Gas
17. Considerations for Developing and Deploying Machine Learning Models for Pipeline Risk and Integrity Assessment
Daryl Bandstra, Shawn Smith, Integral Engineering
18. Addressing Digital – the VirtualTDC
Cliff Johnson, PRCI, John O’Brien, itcSkills

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