NDLI: Pipeline Data Analytics: Enhanced Corrosion Growth Assessment Through Machine Learning

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Volume 1: Pipeline and Facilities Integrity

Modeling Pipeline Metal Loss Defects at Tool Speed

Failure Assessment of the Gas Pipeline by Considering the Geometric Constraint Effect

Identifying Stress Concentrations on Buried Steel Pipelines Using Large Standoff Magnetometry Technology

Directional Caliper Tool Development

Validate Crack Assessment Models With In-Service and Hydrotest Failures

Non-Contact Geomagnetic Localization of Pipeline Defects Using Empirical Mode Decomposition and Magnetic Gradient Tensor

Evaluation of Corrosion Growth Prediction Methodologies Using Burst Pressure Comparisons From Repeated In-Line Inspections

An Investigation Into the Benefits of Employing Multiple Assessments Methods for High Risk Pipelines

EMAT As a Basis for a Comprehensive System Wide Crack Management Program

Structure Assessment Using Instrumented Indentation: Strength, Toughness and Residual Stress

Operational Experiences With Axial Strain Inline Inspection Tools

Do You Have Wrinkles? A Strain- and Stress-Based Approach for the Assessment of Wrinkles Reported by In-Line Inspection

In-Line Inspection in Lieu of Hydrostatic Testing for Low Frequency Electric Resistance Welded Pipe

Implementation of a New Tool for Pipelines Integrity Evaluation: A Correlation Between Local Strains and Hardness

A Sensitivity Study: Effects of Toughness Values on Fatigue Crack Growth Analysis of Just-Survived Flaws Following a Pressure Test

Exceeding Limitations: Ultrasonic Crack Inspections Become Feasible for Liquid Natural Gases

Breathing New Life to Aging Pipeline Infrastructure Using Unique Wireline Inspection Techniques and Pipe-Lining Technology

Achieving North American Record for Longest Intelligent Inspection of a Natural Gas Pipeline

Development of Pinhole Corrosion Management Using MFL

Understanding Quantitative Performance of Large Standoff Magnetometry in Detecting Live Gas Pipeline Anomalies With Stress Estimation

The Future of In-Line Inspection: Free-Floating Smart Sensors

Validation of Computed Tomography Technology for Pipeline Inspection

Criticality Level Assessment From ILI Data

A Case Study on Potential SCC Management Using 10-Inch EMAT ILI

An Investigation on Microstructural Evolution of X70 Steel Pipe During Hot Induction Bending

Corrosion Growth Modeling by Learning a Dynamic Bayesian Network From Multiple In-Line Inspection Data

Adaptive Ultrasonic Imaging of Electric Resistance Welded Pipeline Seams

Interaction Rule Guidance for Corrosion Features Reported by ILI

An Investigation of the Load Carrying Capacity of Pipelines Under Accidental and Longitudinal Moving (Sliding) Loads

Fitness for Service Analysis of the Circumferential Extent of Corrosion in Pipelines

Application of Wide-Band Ultrasound for the Detection of Angled Crack Features in Oil and Gas Pipelines

Calibration of a Nondestructive Toughness Tester (NDTT) for Measuring Fracture Toughness of Pipeline Steel

Understanding Pipeline Strain Conditions: Case Studies Between ILI Axial and ILI Bending Measurement Techniques

Using Finite Element Analysis to Prioritize ILI Calls for Combined Features: Dents in Bends

Ultrasonic NDE Technology Comparison for Measurement of Long Seam Weld Anomalies in Low Frequency Electric Resistance Welded Pipe

Vibration and Fatigue Failures at Pipeline Facilities

Microwave Sensor Array for Corrosion Prediction in Steel Tank Bottoms

Risk-Based Integrity Decision Making for Lateral Piping

Advanced EMAT Crack Tool for Unpiggable Pipelines

Remaining Strength in Pressure Vessels With Pitting Type Metal Loss: Part 1

Root Cause Analysis of an Above-Ground Pipeline With Stress Corrosion Cracking

Condition Assessment for Optimizing Gasunie’s Network Improvement Program (GNIP)

Evaluation of Burst Pressure of Corroded Pipe Segments Using Three-Dimensional Finite Element Analyses

An Approach to Engineering Critical Assessment of Assets That Cannot Be Inline Inspected

Reactivating a Legacy Pipeline: Simulating ILI Run Behavior, Operation Optimization, and Project Challenges

Uncertainty Quantification of Nondestructive Techniques to Verify Pipeline Material Strength

An Analysis Model and its Practical Applications in PG&E Gas Transmission Pipeline Strength Test Projects

Pipeline Data Analytics: Enhanced Corrosion Growth Assessment Through Machine Learning

Do We Need a Safe Excavation Pressure for Dented Pipelines: How Should it Be Defined?

Analysis of the National Energy Board Pipeline Integrity Performance Measures Data

A Method to Analyze the Impact of Inline Inspection Accuracy on Integrity Management Program Planning of Pipelines

Overcoming Difficult to Inspect Multi-Diameter, Low Pressure Gas Transmission Pipeline Challenges

An ILI Based Program That Prevents Reoccurrence of Post ILI Failures Seen in Industry

Development of an Industry Test Facility and Qualification Process for ILI Technology Evaluation and Enhancements: Performance Evaluation Phase

Colonial Scout: A Powerful Web Map Solution Designed As the Data Messenger for Colonial Pipeline Company

Liquid Pipeline Location Specific Cyclic Pressure Determination

Threshold Geometrical Dimensions of Stage II Cracks Versus Required Resolution of Crack-Detection Techniques

Integration of Data From Multiple In-Line Inspection Systems to Improve Crack Detection and Characterization

A More Accurate and Precise Method for Large Metal Loss Corrosion Assessment

An Authoritative Comparison of Remaining Life Assessments for Pipeline Dents

Assessment of Pipeline Spiral Weld Cracks Subjected to Internal Pressure

Development and Experiences of a Circumferential Stress Corrosion Crack Management Program

Differences in Near-Neutral pH Crack Growth Behavior Between Oil Pipelines and Gas Pipelines and Corresponding Crack Growth Mitigation Strategies

High pH Crack Growth Sensitivity to Underload-Type of Pressure Fluctuations

Study on Transition of Stress Corrosion Cracking to Sharp Edge Corrosion for a Liquids Pipeline

Experimental-Numerical Assessment of Vintage Pipe and Girth Weld With a Geometrically Complex Corrosion Feature

Algorithms for the Strain Based Analysis of Dented Pipelines

Evaluation of the Fatigue Crack Growth Behavior by Experiments and Numerical Simulations on Full-Size Pipeline Steels

Some Factors Affecting Initiation of Stress Corrosion Cracking of an X80 Pipe Steel in Near-Neutral pH Environment

Complex Circumferential Stress Corrosion Cracking: Identification, Sizing and Consequences for the Integrity Management Program

Crack Shape Development for Leak-Before-Break Analysis in Pipelines

Implementation of Reliability-Based Criteria for Corrosion Assessment

Study of Safe Dig Pressure Level for Rock Dents in Gas Pipelines

Improving the Accuracy of Traditional Dent Fatigue Analysis: A Method for Quantifying the Initial Damage Caused by Dent Formation

Evaluation of Crack Growth and Material Toughness Effects on Probability of Pipeline Failure

Influence of Mean Load Pressure Fluctuations on Crack Growth Behavior in Steel Pipelines

Fracture Toughness Testing and its Implications to Engineering Fracture Mechanics Analysis of Energy Pipelines

Determining Pipeline Depth of Cover at River Crossings by Data Integration

Buried Pipe Span Ovality Assessment

Effect of Residual Stress or Plastic Deformation History on Fatigue Life Simulation of Pipeline Dents

Volume 2: Pipeline Safety Management Systems; Project Management, Design, Construction, and Environmental Issues; Strain Based Design; Risk and Reliability; Northern Offshore and Production Pipelines

Volume 3: Operations, Monitoring, and Maintenance; Materials and Joining

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Pipeline Data Analytics: Enhanced Corrosion Growth Assessment Through Machine Learning

Content Provider	The American Society of Mechanical Engineers (ASME) Digital Collection
Author	Smith, Michael Cronjaeger, Stefan Ershad, Navid Nickle, Randy Peussner, Matthias
Copyright Year	2018
Abstract	Effective integrity management of a corroded pipeline requires a significant quantity of data. Common data sources include in-line inspection (ILI), process monitoring, or external surveys. The key challenge for an integrity engineer is to leverage the data to understand the level of corrosion activity along the pipeline route, and make optimal decisions on future repair, mitigation and monitoring. This practice of gaining business insights from historical datasets is often referred to as ‘data analytics’. In this paper, a single application of data analytics is investigated — that of improving the estimation of corrosion growth rates (CGRs) from ILI data. When two or more sets of ILI data are available for the same pipeline, a process known as ‘box matching’ is typically used to estimate CGRs. Corresponding feature ‘boxes’ are linked between the two ILIs and a population of CGRs is generated based on changes in reported depth. While this is a well-established technique, there are uncertainties related to ILI sizing, detection limitations, and data censoring. Great care is required if these uncertain CGRs are used to predict future pipeline integrity. A superior technique is ‘signal matching’, which involves the direct alignment, normalization and comparison of magnetic flux leakage (MFL) signals. This delivers CGRs with a higher accuracy than box matching. However, signal matching is not always feasible (e.g. when conducting a cross-vendor or cross-technology comparison). When box matching is the only option for a pipeline, there is great value in understanding how the box matching CGRs can be improved in order to more closely resemble those from signal matching. This limits the extent to which uncertainties are propagated into any subsequent analyses, such as repair plan generation or remaining life assessment. Given their relative accuracy, signal matching CGRs can be utilized as a ‘ground truth’ against which box matching results can be validated. This is analogous to the ILI verification process, where in-field measurements (e.g. with laser scan) are used to validate feature depths reported by an ILI. By extension, a model to estimate CGRs following a box matching analysis can be trained with CGRs from a signal matching analysis, using supervised machine learning. The outcome is an enhanced output from box matching, which more closely resembles the true state of corrosion growth in a pipeline. Through testing on real pipeline data, it is shown that this new technique has the potential to improve pipeline integrity management decisions and support economical, safe and compliant operation.
Sponsorship	Pipeline Division
File Format	PDF
ISBN	9780791851869
DOI	10.1115/IPC2018-78364
Volume Number	Volume 1: Pipeline and Facilities Integrity
Conference Proceedings	2018 12th International Pipeline Conference
Language	English
Publisher Date	2018-09-24
Publisher Place	Calgary, Alberta, Canada
Access Restriction	Subscribed
Subject Keyword	Leakage Process monitoring Magnetic flux Uncertainty Pipelines Pipeline integrity management Inspection Maintenance Corrosion Lasers Remaining life assessment Machine learning Signals Engineers Performance Pipeline integrity Testing
Content Type	Text
Resource Type	Article

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