Practical Application Of AI To Transform Pipeline Integrity Management

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Management and operating teams, across all industries, but especially inside asset management organizations, must increasingly rely on data-driven assessment and analytics for decision making. Clearly, inefficiency and ineffectiveness associated with manual or poorly optimized business processes and fragmented business management Infrastructures is a barrier to formulating the safest, most efficient and cost effective asset management and operational decisions. According to Deloitte’s digital maturity analysis, the midstream industry and specially the pipeline sector is in its lowest stages of digital adoption (first 20-30% progress).

Product Number: 51323-19039-SG

Author: Pankaj Tandon

Publication Date: 2023

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Midstream pipeline integrity teams face continual challenges from deteriorating conditions such as corrosion that can impact their transmission infrastructure. In order to maintain compliance with federal and state regulations, and preserve continuity of operations, operators must integrate across several data sources in their maintenance plans.

This paper will illustrate how Praemia™ Inc. software equips operators with planning tools to better address the dynamic nature of integrity management activities. Powerful analytics incorporate assessment and risk analysis for efficient prioritization of mitigating and remediating measures while balancing system risk and system budget, resulting in safe, cost effective and efficient integrity decisions.

Artificial Intelligence (AI) and Machine Learning (ML) technologies have been applied for years in many industrial fields, but for the pipeline industry, the concept is still relatively new and mysterious. This paper will demystify AI for the midstream pipeline integrity sector with one practical application to dramatically enhance condition assessment, prevention and remediation activities scheduling and transform the way operators can address regulatory and asset decay challenges.