Building a Digital Twin for a Global Energy Leader

The Challenge

A global energy supermajor faced significant challenges in managing its vast physical infrastructure, which includes vessels, pipelines, and equipment spread across multiple facilities worldwide. Key issues included:

• Infrastructure Complexity: A massive network of physical assets made it difficult to track equipment status and operational interdependencies.

• Fragmented Asset Information: Critical data was siloed across multiple systems like SAP and historian databases, preventing a unified view of equipment lineage and maintenance history.

• Reactive Maintenance: Without a clear, real-time view of asset health, maintenance was often reactive, leading to risks of unplanned downtime and operational inefficiencies.

Recro's Role & The Solution: Specialized Data Engineering for a Digital Twin

Recro, through our partnership them, provided specialized data engineering expertise to help build the client's advanced Digital Twin platform. Our team was integral to the Production Asset Modeling (PAM) and 3D Contextualization initiatives.

1. Graph-Based Asset Mapping: Our data engineers worked on the core of the solution, which uses a Neo4j graph database to create a digital map of all physical assets. This allows the company to track the "lineage of any equipment" and instantly visualize complex interdependencies.

2. Unified Data Pipeline Development: We engineered the data pipelines that ingest and transform information from disparate sources like SAP and real-time historians, loading it into a Databricks platform for analysis and modeling.

3. Codebase Optimization & Documentation: A key challenge was a complex, 15,000-20,000 line codebase with poor documentation. Our team was instrumental in understanding this system, optimizing it, and creating new documentation to improve maintainability.

The Impact: A New Standard in Asset Intelligence

Our data engineering expertise contributed to a transformative platform that delivered significant operational value.

• Complete Asset Digitization: The project successfully created a comprehensive digital replica of the company's complex physical infrastructure, enabling a single source of truth for all equipment.

• Real-Time Monitoring & Lineage Tracking: The graph database allows operators to instantly trace equipment relationships, identify potential issues like a "valve leakage" digitally, and understand the full operational context of any asset.

• Predictive Maintenance Capabilities: By unifying asset data, the platform enables a shift from reactive to proactive maintenance, allowing the client to track downtime, schedule activities, and optimize costs.

 Enhanced Operational Intelligence: The digital twin provides a sophisticated system for data-driven decision-making, improving safety and efficiency across the energy supermajor's global facilities.