Leveraging FMMEA for Digital Twin Development: A Case Study on Intelligent Completion in Oil and Gas

Area of Science:

• Digital Engineering
• Risk Management
• Oil and Gas Industry

Background:

• Digital Twins (DTs) are advancing the Oil and Gas (O&G) sector by enabling asset monitoring and optimization.
• Traditional risk assessment methods like FMEA/FMECA lack specific guidelines for complex system failures.
• Identifying potential failure modes is crucial for robust DT implementation.

Purpose of the Study:

• To introduce a novel Failure Modes, Mechanisms, and Effects Analysis (FMMEA) framework for early-stage DT development.
• To provide specific guidelines for analyzing failures in complex O&G systems.
• To enhance prognostic health management and failure prediction within DTs.

Main Methods:

• Development of the FMMEA framework tailored for DTs.
• Integration of failure mechanism analysis into the DT lifecycle.
• Adaptation of risk prioritization metrics (e.g., DPR over RPN) for complex systems.
• Case study application on an intelligent completion system DT.

Main Results:

• The FMMEA framework effectively identifies and assesses failures during DT development.
• Mechanism-oriented failure analysis improves predictive capabilities.
• The proposed DPR metric offers a more suitable risk prioritization for complex systems.
• The case study demonstrated enhanced prognostic health management and transparency.

Conclusions:

• The FMMEA framework provides a structured approach to failure analysis in DT development.
• Focusing on failure mechanisms is essential for accurate prediction and management.
• The framework improves the reliability and transparency of DTs in the O&G industry.