In Line Inspection Data Analysis for Pipeline Integrity Management

In-line inspection (ILI) technology has been in widespread use approximately 30 years and has become the preferred method used by pipeline operators to ensure the integrity of their pipeline assets. This pioneer training course is aimed at improving accuracy and reliability in the application, interpretation, and evaluation of data acquired from in-line inspection devices. The course presents practical methods of risk-based ILI technology as applied to pipeline integrity problems. The course is highly interactive, and takes the forms of lectures, workshops, case studies, and discussions.

Course Objectives

Upon successful completion of this course, the delegates will be able to:

• Understand the basics of acquiring and interpreting ILI data when assessing pipeline integrity and safety
• Gain a working knowledge of the basics of the engineering approach to ILI data extraction, mining, fusion, and analysis
• Acquire essentials of the current international codes that regulate ILI systems quality (API 1163, NACE Standard RP 0102-2002, NACE 35100, ASNT ILI-PQ 2005) and how to use them on a daily basis

Agenda

Day 1

Introduction - Problems Discovered During Integrity Management Program (IMP)

Inspections and Pipeline Accident Investigations Critical Knowledge Gaps in Current ILI Technology

• Holistic analysis of ILI data – key element in a successful pipeline integrity management program
• ILI data analysis terminology
• Defects: main threats and localities of pipeline loss of integrity

Types and Classification of Pipeline Defects

• Pipeline defects and remaining life
• Structural reliability and performance risk of pipelines with defects
• Basics of ILI technology

Day 2

ILI – Most Important Single Method of Pipeline Diagnostics

• Contemporary methods of ILI
• Four stages of ILI technology
• Three possible outcomes of ILI
• International ILI qualification standards: an overview

Comprehensive Review and Analysis of Existing International Standards

• API 1163, NACE Standard RP 0102-2002, NACE 35100, ASNT ILI- PQ 2005
• Selection of an ILI system (API 1163, RP 0102-2002, RP 35100)
• Operational characteristics & constraints (API 1163, NACE)
• ILI system performance specification (API 1163)

Day 3

ILI Systems Performance Verification (API 1163) Basics of Holistic Ili Acquisition, Mining, Analysis, and Management

• ILI as a measurement system
• Main sources of variability in ILI measurements
• Typical ILI results
• Seven basic ILI performance quality metrics
• Probability of true detection (PTD)
• Probability of true location/positioning
• Probability of true identification/discrimination (PTI)
• Defect sizing accuracy metrics
• ILI system measurement and verification models
• Flow chart of holistic analysis of ILI results
• Solving the problem of missing and false ILI data
• Calibration of ILI tools and results of runs
• Field verification of ILI data
• Number of confirmatory digs needed for corroboration of the ILI data
• Contractual criteria for defect reports
• ILI quality management
• Cost/benefit analysis of ILI technology

Day 4

Workshop #1: Working Examples of Total Analysis of ILI Data

Implementation of ILI Analysis Output in Risk-Based Pipeline IMPs

• Manual for the IMP manager: from holistic ILI data to IMP activities
• Assessment of rupture pressure (B31mod, Shell, Battelle, DNV, etc.)
• Defect-growth models
• Corrosion
• Stress corrosion
• Low-cycle fatigue cracks
• Interaction rules
• Fitness-for-purpose assessment
• Remaining lifetime
• Planning the next ILI

Day 5

Case Studies: Application of Prima Software

WORKSHOP # 2: RISK-BASED PRIORITIZATION OF PIPELINE SEGMENTS WITH DEFECTS FOR MAINTENANCE/REPAIR: MAKING CLEVER DECISIONS ON ACTIONABLE ANOMALIES ROLE OF THE HUMAN FACTOR IN ILI TECHNOLOGY

Influence of ILI-Induced Human Errors on Pipeline Safety and Reliability

• Personnel education, qualification, certification, training and experience requirements (as per ASNT ILI PQ requirements)

Existing Approaches to Quantitative Assessment of Human Factors/Errors

• Repeatability and reproducibility of ILI and field-verification measurements
• Interaction of pipeline operators, ILI vendors, and regulatory bodies

Understanding ILI Tool Data Submitted By Vendors

• Information exchange flow between operator and vendor before, during, and after ILI
• Regulators and ILI quality
• ILI tender issues