AI-Powered Asset Register Automation for a Major LNG Development Project in Qatar

MECIP is currently executing the Asset Register Automation Project in through DIGATEX™, delivering advanced Artificial Intelligence (AI) and Machine Learning (ML) solutions to automate engineering data extraction and asset register development for one of Qatar’s major LNG developments.

The project focuses on automating the Asset Register build process from As-Built engineering documentation by utilizing AI-driven data extraction, intelligent document recognition, rule-based verification, and automated data cleansing technologies. The solution is designed to produce a comprehensive, high-quality asset register with deliverables equivalent to enterprise engineering database standards while significantly reducing manual effort and improving data accuracy.

As part of the project, MECIP is implementing intelligent workflows to extract and validate equipment information, engineering attributes, functional locations, and asset metadata from engineering drawings and technical documents. Advanced verification and quality assurance processes ensure data consistency, completeness, and compliance with the client’s engineering information requirements.

The project also encompasses the automation of Operations & Maintenance (O&M) data enhancement by enriching asset information following As-Built modifications, identifying and resolving data gaps, and maintaining an up-to-date digital asset register throughout the facility lifecycle. This enables continuous synchronization between engineering documentation and operational asset information, supporting long-term asset integrity and lifecycle management.

By combining MECIP’s engineering expertise with DIGATEX™’s AI-powered Engineering Information Intelligence platform, the project establishes a robust digital foundation for asset information governance, engineering data quality, operational efficiency, and future digital transformation initiatives. The solution supports improved maintenance planning, asset reliability, regulatory compliance, and data-driven decision-making across the entire LNG facility lifecycle.