Qualifying ILI Technologies Using an API 1163 Approach Hard Spots as the Example

Abstract API Standard 1163 “In-Line Inspection System Qualification” sets the requirements for operators to define the scope of the inspection, its goal(s) and validate that a system has met the intent of the inspection. As part of the Integrity Management Program (IMP), an operator often faces the need to bring a new technology or and known technology from a new provider. Over the years, a process was developed with the intent to reduce the learning curve for both the service provider and the operator and reduce the risk of using an unfamiliar technology and/or vendor. Some of the risks that operators experienced in the past were the pace to which trust in the In-Line Inspection (ILI) tool can be built, the challenge in understanding if the results are truly representative of the total population of features to be managed, first run success and reporting. The process leverages the requirements laid out in API STD 1163 to define three stages to the qualification: 1. Audit that included testing demonstration of all aspects of the tool or the vendor capacity to meet the goal of the inspection and the reporting deliverables. 2. Performance demonstration that the tool can meet the service provider’s claim. 3. A first inspection to provide overall confidence that the tool does function as intended which includes field validation and all requirements sets by both parties. The paper will walk through these 3 steps by showing how an operator can apply it to the identification of a capable ILI technology to inspect pipelines for hard spots. It will include the audit process and how specific requirements were developed when needed. How a series of pull through tests were organized to understand the tool performance based on a known dataset of hard spots. Finally, how a ‘run-off’ in a pipeline segment was set up to complete the validation with a series of digs that were compared to each service provider’s ILI tool to validate Probability of Detection (POD), Probability of Identification (POI), and sizing accuracy (SA). Observations, lessons learned, and recommendations will be drawn from the example to inform other operators on considerations to include in their ILI qualification processes.