For the majority of pipeline operators struggling to establish the business case for data management, records management, or geographic information systems, a step past the traditional information technology approach of return on investment (ROI) must be made. Traditional information technology value propositions are founded on information efficiencies that, for the most part, are extremely difficult to quantify since the processes are either not presently performed or the effort associated with the existing process has not been measured. Without a baseline of the existing process, a comparative analysis using improved efficiencies cannot be quantified to substantiate a return on investment. Justification of a data management system and its associated benefits in terms of its cost relative to the cost of the data it manages (e.g. ILI, excavation, CIS etc.) is compelling since it is only on the order of 2–10%, but typically even this metric is too general an argument for most pipeline integrity managers to feel comfortable defending. This paper will explore the process required to unearth the value of data management to support pipeline integrity. Many examples and cases will be discussed to back-up the approach to establishing value of data management for pipeline integrity.
BP’s Natural Gas Liquids business unit (NGLBU) has conducted integrity investigation and mitigation activities on its pipelines and has been following this best practice for numerous years. In recent times, NGLBU’s data management initiatives focused on establishing an enterprise Geographic Information System (GIS) coupled tightly with a derivative of the Pipeline Open Data Standard (PODS) data model. During successful implementation of the GIS, an analysis identified gaps in existing data management processes for pipeline integrity information. Consequently, the business unit adopted Baseline Technology’s Pipeline Information Control System (PICS) and its modules to support the pipeline integrity decision-making process on its 9000km of pipeline. The PICS implementation leverages the existing GIS implementation while addressing a number of unresolved data management and integration issues, including: • Integration of inline inspection with excavation results; • Migration of above ground surveys to a common repository; • Integration of multiple inline inspections; • Facilitation of corrosion growth modeling; • Structured process for prioritization of remediation; • Structured process for integration of inline inspections with risk parameters; • Defined data collection, storage, and integration standards. Data management solutions based solely on a GIS require pipeline surveys without explicit positional information to be converted into a common linear reference system (typically chainage or stationing) such that disparate data sets may be overlaid and compared. This conversion, or spatial normalization, process is where much of the data management effort is spent and is often prone to error introduction. Even when small errors are introduced, the normalization process is often performed such that it is not auditable. If the underlying spatial errors are not reported, addressed, and understood, the value of the data integration and any subsequent analysis of the combined data set is questionable.
The SCC (stress corrosion cracking) database was initiated by the CEPA (Canadian Energy Pipeline Association) SCC Working. The current generation of the database has a broad scope, containing detailed data for each and every colony and its associated environmental conditions. The database also includes corrosion and dents amongst other integrity concerns to identify any correlation with SCC and provide a common industry data format to investigate these other integrity issues. The intent of the current version of the database is to provide for the most detailed data entry that one could typically capture at an investigative dig. With the wide acceptance of the current version the CEPA database it is evolving into the industry standard for investigative excavation data. The initial trending results are based on the dataset generated by CEPA member companies, which represents over a thousand investigative excavations. The trend results should only be interpreted broadly at this time, although they do generally support industry’s understanding of SCC. The development and implementation of the CEPA SCC database is premised on the belief, developed through extensive field investigations and laboratory research, that SCC is not a random development, but it initiates and grows at specific locations susceptible to SCC. It is further premised on the belief that such susceptible sites can be generally located by appropriate prioritization techniques. Thus, the objective of the database is to explore correlation among the various operational and environmental variables to improve the current understanding of how to locate SCC, and in particular ‘significant’ SCC, in order that measures can be taken to prevent operational failures and enhance the safety of Canadian pipelines. The need for an industry database regarding SCC was identified by the CEPA SCC working group shortly after its formation 1994. It was apparent that the various companies were collecting the field data from investigative excavations in significantly different formats, only some of which were electronic. The need for a common data structure and data repository to facilitate trending was reinforced numerous times at the Banff Conferences and by the NEB during its inquiry into SCC in 1995/96.
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