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Activity Number:
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28
- Computation, Design, and Quality Assurance of Physical Science and Engineering Applications
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Type:
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Contributed
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Date/Time:
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Sunday, August 8, 2021 : 1:30 PM to 3:20 PM
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Sponsor:
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Section on Physical and Engineering Sciences
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Abstract #317747
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Title:
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Statistical Analysis of Oil and Gas Pipelines to Predict Pipe Grade Using Power BI
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Author(s):
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William V Harper* and Thomas A Bubenik and Tara P McMahan and Benjamin R Hanna and Steven J Polasik and Adriana P Nenciu and Stacy G Hickey and David J Stucki
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Companies:
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DNV and DNV and DNV and DNV and DNV and Otterbein University and DNV and Otterbein University
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Keywords:
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Oil;
Gas;
Pipeline;
Pipe Grade;
PHMSA
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Abstract:
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Oil and gas transmission pipelines are comprised of steel segment (joints) with lengths of about 40 feet. A key property of a joint is specified grade (minimum material and mechanical properties). For some pipe, the grade is no longer known. The Pipeline and Hazardous Materials Safety Administration (PHMSA) has tightened regulations leading to the need to estimate joint grade from destructive and non-destructive testing. PHMSA developed the revisions to address the recommendations made by the National Transportation Safety Board (NTSB). The NTSB highlighted the importance of using accurate material properties to determine the integrity of pipelines. GradeIt is a Power BI app that provides a statistical grade estimation for joints based on measured values of yield strength. The fidelity of the grade estimation relies on the number of data points, as there may be multiple yield strength measurements for each joint. GradeIt uses statistical methods to estimate grade as well as a user-defined level of conservatism. GradeIt introduces new metrics to quantify the quality of the overall population grade relative to the assumption of differing pipe grades.
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Authors who are presenting talks have a * after their name.
