In order to comply with industry regulations and optimize pipeline operational expenditures, pipeline operators employ a Risk Based Inspection (RBI) process. This process:
- Produces a relative quantitative risk ranking of pipeline assets that can be used to allocate budget for integrity activities based on the inspection and monitoring data.
- Enables pipeline operators to use the latest asset integrity data to improve the RBI algorithm with each iteration, thus enabling continuous improvements.
- Assists pipeline operators to generate Long Range Forecasts (LRFs) for specific assets based on their perceived integrity risk and potential cost to lower it.
Figure 1.0: Typical RBI Process
Modern pipeline operator RBI implementations often focus on inspection cycles rather than prioritizing prevention activities, such as maintenance of Cathodic Protection (CP) to prevent external corrosion. As a result, pipeline operators often find themselves in an inspect-and-repair cycle that is reactive in nature. Furthermore, risk models traditionally based on the likelihood of failure and consequence of failure, are subject to interpretation in order to be effective. Risk results, developed to provide an understanding of the potential for failure prior to the next inspection may not provide adequate context to evaluate the performance and benefit of threat prevention and mitigation programs over time.
A methodology focusing on the mitigation of External Corrosion, that provides focus on the interpretation of risk results in a context that allows operators to better prioritize threat prevention activities and optimize integrity expenditures is outlined in the following:
1. Select Pipeline Segment that requires analysis
The process starts with selecting a pipeline segment that will be the subject of the assessment. Typically, operators will perform a risk assessment on all pipeline segments at least on an annual basis.
2. Compile and review In-line Inspection (ILI) data for Pipeline Segment
Compile the available high-resolution metal loss ILI data necessary for a Probability of Exceedance (POE) calculation.
3. Calculate POE based on compiled ILI data
Calculate a POE value for each reported external metal loss anomaly on the pipeline segment. The determination of probability of exceedance, based on an analysis of ILI data, is predicated on the concept that the size of an anomaly, as measured by an ILI tool, represents only an estimate of the anomaly’s true size. This true size is represented as a probability distribution, whose characteristics are a function of measurement error that is characteristic of the ILI tool. By accounting for ILI measurement error, any individual ILI anomaly may be expressed as a normal probability distribution having a mean and a standard deviation.
4. Calculate SME Score for pipeline Segment
Calculate a Subject Matter Expert (SME) score for the pipeline segment based purely on integrity program and pipeline attribute data. The purpose of this score is to scale the estimated Corrosion Growth Rate (CGR) value with relevant knowledge on the effectiveness of the external corrosion (EC) mitigation systems in place for the pipeline segment. The contributing factors and the overall score can be calibrated and scaled based on the risk tolerance of the user, and will vary from operator to operator. Other corrosion growth rate factors that may affect this POE value and the associated time to grow to critical depth may be provided by subject matter experts (SME’s) for consideration. These include:
- Soil Type
- Coating Type
- CP System Operations
- Coating Quality
- Pipeline and Coating Age
- Failure History
- DC Interference susceptibility
- AC Interference susceptibility
- Shorted Casing susceptibility
5. Calculate Probability of Failure (PoF)
Calculate the probability of failure for the pipeline segment for the selected year of analysis by calculating the POE for the inspection year, and adjusting the CGR by the SME score. The CGR is adjusted based on the SME Score because the SME score represents the impact of any compromised pre-existing mitigation programs on the pipeline segment.
6. Calculate Time to Non-compliance
Calculate the estimated time to non-compliance to specified criteria as per the operator’s risk tolerance using the SME Score and CGR from Step 4, and the POE from Step 3.
7. Calculate Consequence of Failure
Calculate the consequence of failure based on the pipeline operating company’s consequence assessment algorithm.
Dynamic Risk has developed an algorithm based on the aforementioned 7-step methodology which provides significant benefit to pipeline operators, including:
- Freedom to leverage integrity program, operational, and mitigation data and subject matter expertise to produce more realistic probability of failure results.
- Ability to focus on preventative mitigation activities in addition to maintaining an inspection interval as a means of risk-reduction.
- Ability to forecast costs for mitigation and inspection activities based on estimated time to non-compliance calculations.
For additional information on how our technology enabled solutions leverage risk-based results to optimize efficient and effective pipeline integrity management programs, please reach out to us at firstname.lastname@example.org
About the Author:
Parth Iyer M.Sc., P.Eng
Parth, a Pipeline Integrity Engineer at Dynamic Risk, is a Professional Engineer registered with Association of Professional Engineers and Geoscientists of Alberta (APEGA), and a member of the National Association of Corrosion Engineers (NACE) with Cathodic Protection Technician certification. Parth has been in this industry for over 8 years, during which he has developed many pipeline Integrity Management Programs, Safety and Loss Management Systems, Risk Algorithms, and Quality Control protocols for integrity data. Parth has been involved as a Subject Matter Expert in external corrosion and cathodic protection on many pipeline construction and integrity projects, and has conducted integrity program reviews with technical services and field operations directly. Parth’s expertise has also enabled him to be involved in various high-profile due diligence reviews for pipeline operator mergers and acquisitions.