TOWARD A QUANTIFIED RISK ASSESSMENT APPROACH. Mari Shironishi Pipeline Integrity Manager

Transcription

1 TOWARD A QUANTIFIED RISK ASSESSMENT APPROACH Mari Shironishi Pipeline Integrity Manager

2 Overview 1. What is Risk? 2. Our Background Story 3. Reliability Based Design & Assessment 4. Lessons Learned / Road Ahead

3 What is Risk? In summary, risk assessment is a mental model that is useful to frame decision making. It is not something that is real or absolute. By definition it is fuzzy and imprecise. For this reason, decision making based on risk assessment needs to 1) acknowledge this fact; and 2) consider a broad range of factors. REASONABLY PRACTICABLE A HELP OR A DISTRACTION IN ENSURING PUBLIC SAFETY? Jan Hayes* RMIT University, Victoria, Australia Richard McDonough GPA Engineering, South Australia, Australia Presented at the 21st Joint Technical Meeting, 1-5 May 2017, Colorado Springs, Colorado

4 Quantification Efforts Risk Assessment: Evaluation (modeling) of chance of failure and its consequence Risk Management: Optimized resource allocation based on Risk Assessment

5 Overview 1. What is Risk? 2. Our Background Story 3. Reliability Based Design & Assessment 4. Lessons Learned / Road Ahead

6 Relative Model for TIMP Baseline Assessments Code compliant Algorithm using weighting factors Based on attributes and operation data Primarily a prioritization tool Manual feedback Validation limited and difficult Question: How do we ever know it s working????

7 Risk Assessment Above all, risk assessment must be confidence building Integrity from Latin integer: whole

8 New Risk Assessment Concept what do we want in new approach? Complexity reflects assessment results Transparency Modular modeling Consistency and repeatability Where to Start? There is no single correct way

9 Risk Matrix Index Model SME Fault Tree Statistics Models Bayesian Modeling Reliability Based Rapid Analysis Aggregate large data Good for complex interaction Wide use in PSM world Good for historic rates Probability includes uncertainty Estimation of uncertainties Easily Understood Subjective threat factors Good for ancestral knowledge Good for complex interaction Good for high freq. data Good for scarce data Target has been researched & established Compare simple relationships Rapid data aggregation Cross experience/ Disciplines Leverage experience & intuition Critical to engineering analysis Improves with more data Distribution of data able to handle range of data Visualize Results Very Subjective Subjective Cross experience/ Disciplines Significantly Objective Subjective development Time dependent analysis Subjective & High Level Limited interactive threats SMEs often underestimate risk Limited to small domains Not app. for rare event Limited realworld applicability Requires rich data Manually intensive Limited repeatability Time consuming Limited interactive threats Need skill to defend/react Complex calculation Not app for complex syst.

10 Critical Review of Integrity Program Main assessment method: In-Line Inspection ~70% of transmission mileage Rich data Some quantified analysis repair criteria Probability of Exceedance

11 Probability of Exceedance Leakage Graph Pipeline A Pipeline B Pipeline C Pipeline D Pipeline A Anomalies Pipeline B Anomalies Pipeline C Anomalies Pipeline D Anomalies 90 REPAIR Wall Loss (%) Probability

12 Probability of Exceedance Leakage Graph Pipeline A Pipeline B Pipeline C Pipeline D Pipeline A Anomalies Pipeline B Anomalies Pipeline C Anomalies Pipeline D Anomalies Wall Loss (%) REPAIR Probability 20

13 Pilot Project Good approach for ILI data Tool Performance Able to evaluate uncertainties Limited Scope Mainly Corrosion evaluation 2 pipelines Reliability Based Design & Assessment (RBDA)

14 Overview 1. What is Risk? 2. Our Background Story 3. Reliability Based Design & Assessment 4. Lessons Learned / Road Ahead

15 Reliability Based Approach Risk = Chance of Failure x Consequence of Failure Risk Chance of Failure = Consequence of Failure Reliability = 1 - Risk Consequence of Failure Used with permission

16 Reliability Based Assessment Process Flow (Corrosion) Used with permission

17 Defect Assessment pipe properties and dimensions Frequency maximum operating pressure measurement uncertainty inspection measurements corrosion model test results Prob. Density Test Results Yield Stress Flaw Depth Model Results Failure Rate (/km year) Time (years) repeated inspections Prob. Desnity Growth Rate Used with permission

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20 Not One Size Fits All Used with permission

21 Target All Combined Seismic Liquefaction Equipment Impact Used with permission

22 Vision: Quantified Risk Across Business Units Used with permission

23 Overview 1. What is Risk? 2. Our Background Story 3. Reliability Based Design & Assessment 4. Lessons Learned / Road Ahead

24 Benefits Challenges Promoted discussions Transparency Clarity on improvement needs Target Path forward Integration Consensus Confidence Integration Consensus Consistency Defining limits how much risk is acceptable?

25 Risk Matrix Rapid Analysis Easily Understood Compare simple relationships Visualize Results Subjective & High Level Index Model Aggregate large data Subjective threat factors SME Fault Tree Statistics Models Good for complex interaction Good for ancestral knowledge Wide use in PSM world Good for complex interaction Good for historic rates Good for high freq. data Bayesian Modeling Probability includes uncertainty Good for scarce data Rapid data Cross Leverage Critical to Improves aggregation experience/ experience & engineering with more Integrated Approach Disciplines intuition analysis data Very Subjective Limited interactive threats Manually intensive Subjective SMEs often underestimate risk Limited repeatability Cross experience/ Disciplines Limited to small domains Time consuming Significantly Objective Not app. for rare event Limited interactive threats Not app for complex syst. Subjective development Limited realworld applicability Need skill to defend/react Reliability Based Estimation of uncertainties Target has been researched & established Distribution of data able to handle range of data Time dependent analysis Requires rich data Complex calculation

26 Summary In summary, risk.... is fuzzy and imprecise. For this reason, decision making based on risk assessment needs to 1. acknowledge this fact; and 2. consider a broad range of factors. There are a thousand ways to kneel and kiss the ground ~Rumi