Clarion’s Digital Pipeline Solutions Forum

Clarion’s Digital Pipeline Solutions Forum

Date(s) - May 18, 2022 - May 19, 2022
All Day MST

Royal Sonesta Houston

Dynamic Risk

Dynamic Risk is pleased to announce our participation in the Digital Pipeline Solutions Forum presented by Clarion Technical Conferences in Houston, TX. The event will take place from May 18-19 at the Royal Sonesta Hotel.

The Digital Pipeline Solutions Forum (DPSF) is the first colloquium of its kind to address how the 4th Industrial Revolution – a new era that builds and extends the impact of digitization in new and unanticipated ways – will indelibly change the pipeline sector in terms of its daily operations and management.

This forum aims to create a greater understanding of the 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” involving entirely new capabilities for people and machines.

Presentation: Predictive Corrosion Modeling – Rise of the Machines
Date & Time: Wednesday, May 18th at 4:00 P.M. CST

Pipeline operators regularly employ risk-based inspection (RBI) decision-making to prioritize expenditures. The goal when using an RBI process to drive asset integrity is always a reduction of risk to as low as reasonably practicable (ALARP). Traditional corrosion risk modeling is done in one of two ways – qualitative or quantitative. The qualitative algorithm involves assigning numerical scores which represent failure susceptibility to factors that are known to influence internal and external corrosion propagation on pipelines. This includes factors such as external coating type, soil type, maintenance pigging, chemical inhibition programs, and so on. The quantitative algorithm typically evaluates pipeline inspection data using a probability of exceedance (POE) method to generate a probability of failure (POF) for each metal loss anomaly reported by the pipeline inspection tool.

This presentation will showcase a machine-learning (ML) approach to predict areas and the extent of metal loss corrosion in an effort to quantify qualitative risk factors such as prevention and mitigation (P&M) activities. The results showed promise with high accuracy and 90% confidence for axial location and depth of both internal and external metal loss anomalies. This, in turn, combined with the corrosion growth analysis can help pipeline operators develop robust, yet accurate long-term mitigation plans for their pipeline assets while prioritizing the risk-reduction achieved by implementing additional P&M measures. Supporting cases are discussed to help explain the intended use of this algorithm and the interpretation of the results.

Paper Authors:
Mike Westlund, Director, Integrity Services, Dynamic Risk
Parth Iyer, Senior Integrity Engineer, Dynamic Risk

Dynamic Risk will be showcasing our industry-leading pipeline risk management software solutions at booth #12 during this event.
If you have any questions or would like to be connected with one of our participating team members, please contact Tracey Murray at:

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