Asset Lifecycle Management in the Gas Industry: The Role of BIM and Digital Twins
BIM Leaders LTD BIM Leaders LTD
BIM Case Studies
August 14, 2025

Asset Lifecycle Management in the Gas Industry: The Role of BIM and Digital Twins

In the gas sector, precision, safety, and efficiency are non-negotiable. That’s why BIM Leaders LTD integrates Building Information Modelling (BIM) and Digital Twins to deliver complete asset lifecycle management – from design and construction to operation and modernization.
The use of Building Information Modelling (BIM) and Digital Twins for improving long-term asset management is highly relevant and important, especially in industries such as energy, infrastructure, and manufacturing. Both technologies assist not only in design and construction but also in the effective management of assets throughout their lifecycle.

Let’s explore how BIM and Digital Twins can help enhance long-term asset management by reducing failures and optimizing performance.

1. Integration and Accessibility of Data

BIM allows the collection of all asset data into a single digital model that contains not only graphical information but also details about components, materials, lifecycle stages, and even maintenance history.

This makes data accessible to all process participants (engineers, designers, project managers, and operators), ensuring better coordination and quick decision-making.

This reduces the risk of misunderstandings between teams, helps promptly identify clashes and errors between systems, and provides the ability to monitor asset conditions in real-time, allowing quicker responses to any changes.

2. Digital Twins: Real-Time Monitoring

A Digital Twin is a virtual representation of a physical object or system. In asset management, Digital Twins provide an accurate depiction of how infrastructure or equipment operates based on data from sensors and monitoring systems.

They allow continuous monitoring of asset conditions in real-time, enabling all involved parties to respond quickly to any necessary adjustments. This approach helps reduce the risk of unforeseen failures and extends the lifespan of equipment through proactive maintenance.

3. Predicting Failures and Breakdowns

Thanks to the integration of Digital Twin data and monitoring systems within BIM, it is possible to analyze and predict potential equipment failures or breakdowns.

This allows for planning necessary repairs or replacements in advance and helps minimize the risk of accidents, reducing the need for urgent and costly repairs. Proactive maintenance helps prevent unplanned downtime and improves overall asset efficiency.

4. Optimizing Performance

With BIM and Digital Twins, not only can failures be predicted, but the operation of equipment can also be actively optimized. Since all data about assets, their maintenance, and performance is available in real-time, adjustments or processes can be made quickly to achieve maximum efficiency.
For gas compressor stations, for example, the operation of compressors can be optimized by controlling their load and predicting the best operating modes.

5. Improved Maintenance and Repair Planning

BIM and Digital Twins not only provide monitoring of current asset conditions but also help plan their maintenance based on real data.
This approach reduces downtime, optimizes maintenance and repair processes, and allows for more efficient resource planning, which is crucial for maintaining operational assets in optimal condition throughout their entire lifecycle.

6. Cost Reduction and Increased Resilience

Thanks to precise monitoring and forecasting of asset conditions, overall maintenance and repair costs can be reduced while increasing asset longevity.
An important advantage is the improvement of infrastructure resilience, as Digital Twins allow assets to adapt to changing conditions, preventing potential hazardous situations.

7. Resource Savings

When all data is collected into a single model and available for analysis, the need for unnecessary resources, such as additional checks or error corrections, is reduced. Additionally, the likelihood of rework or task duplication is decreased, which optimizes asset management processes.

8. Improved Safety

Digital Twins and the use of BIM models are used for monitoring safety at gas facilities. They allow the assessment of risks to people and the environment, such as the likelihood of gas leaks or other hazardous situations that may occur during operation.
This allows for a quick response to potential threats and the prevention of accidents.

9. Holistic Asset Management

Thanks to the integration of BIM and Digital Twins, companies are able to monitor and manage assets at all stages of their lifecycle, from design and construction to operation and modernization.
All data – from materials and structural elements to operational and maintenance parameters – is integrated into a single system, allowing for more informed and reasoned management.

10. Enhanced Collaboration Across Teams

One of the key advantages of BIM and Digital Twins is the improvement in collaboration between different teams involved in asset management.
Since all data is integrated into a single platform, stakeholders from various disciplines - such as engineering, operations, and maintenance – can collaborate more effectively.

This centralized information hub ensures that everyone has access to the latest updates, reducing silos and facilitating quicker decision-making. Cross-functional teams can now work together seamlessly, with real-time data and shared goals.

11. Energy Efficiency and Sustainability

BIM and Digital Twins not only help in asset management but also contribute significantly to energy efficiency and sustainability efforts. For example, the ability to continuously monitor the performance of assets allows for energy optimization.
Digital Twins can simulate different operating conditions and help determine the most energy-efficient modes for equipment. In the long term, this can lead to reduced energy consumption, lower operational costs, and a smaller carbon footprint – aligning with global sustainability goals.

12. Scalability and Adaptation to Future Technologies

The adaptability of BIM and Digital Twins also plays a crucial role in future-proofing asset management strategies.
As new technologies emerge, these digital models can easily integrate additional data or tools without disrupting existing processes. Whether it's incorporating new sensors, adopting advanced AI-driven analytics, or utilizing the Internet of Things (IoT), the digital twin ecosystem can grow and evolve.

This makes it easier for gas industry companies to keep pace with technological advancements and continuously optimize asset performance.

13. Regulatory Compliance and Reporting

In industries like energy and gas, regulatory compliance is a major concern. BIM and Digital Twins assist in ensuring that assets comply with safety standards, environmental regulations, and industry-specific codes.

By maintaining accurate and up-to-date digital records of assets, companies can easily generate reports and audits to prove compliance. This also helps streamline inspections and facilitates the certification process, which is often cumbersome and time-consuming when relying on traditional methods.

14. Improved Asset Condition Monitoring and Remote Diagnostic

Beyond basic monitoring, the integration of real-time sensor data into BIM and Digital Twins allows for detailed condition monitoring and even remote diagnostics. For example, equipment can be monitored from a control center, and operators can troubleshoot issues without needing to be physically present at the site.
This not only saves time but also minimizes disruptions to operations, especially in remote or hazardous locations where on-site access may be limited.

15. Long-Term Asset Performance Analytics

Another significant benefit of BIM and Digital Twins is the ability to leverage long-term asset performance data for predictive analytics. Over time, as more data is collected, machine learning algorithms can be applied to predict long-term trends and potential performance degradation.

This predictive capability ensures that maintenance schedules and replacement cycles are always aligned with the real condition of assets, avoiding premature replacements or unnecessary downtimes.

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