Making Midstream future-ready: Perform condition monitoring and avoid costly shutdowns

Making Midstream future-ready: Perform condition monitoring and avoid costly shutdowns

December 12, 2023
Time to read: 8 minutes
Yorinde Lokin-Knegtering

The midstream sector is responsible for moving so much product that even slight deviations from optimal operational parameters could cost operators dearly – not to mention the potential losses, and in the worst-case scenario, total shutdown caused by equipment failure.

In a previous blog post, we talked about how digital twin technology can specifically help midstream operators get value from big data, improve equipment performance, run simulations and help solve challenges from ESG and emissions to fully engage in the energy transition. Read more about transforming midstream operations with a digital twin here.  

Now, we’re ready to zoom in and focus on what digital twins can do for midstream operators who want to solve the challenge of condition monitoring for storage facilities and pipelines – and more importantly, the value that can be gained by moving from a reactive to proactive asset management strategy.


Onshore and offshore, aging infrastructure poses a significant risk to midstream operations' safety, reliability, and efficiency.

Aging pipeline infrastructure comes at a high price, with pipeline incidents between 2001 and 2020 causing as much as USD 10.7 billion worth of damages during the time period.

Source: IoT Use Case for Gas Pipeline Monitoring | IoT Sources

On top of this, onsite and day-to-day challenges faced by operators include everything from technical issues (material/weld/equipment failure and corrosion) to the human factor (incorrect operation and miscommunications) and natural causes (like harsh weather conditions).

And the consequences can be far-reaching:

  • Severe environmental damage to wildlife and ecosystems
  • Costly production loss through product leakage, pipeline ruptures, and equipment failure
  • Unexpected shutdowns that impact product delivery
  • Increasing vulnerability to accidents and natural disasters


Condition monitoring in a digital twin offers a new way to deal with both short- and long-term challenges for midstream operators. Condition monitoring means the collection and analysis of data from sensors, on-site IoT devices, and historical data to regularly assess the health and performance of equipment and assets.  

By combining this information with a virtual replica of the asset/equipment and adding advanced Machine Learning and AI models, a digital twin can detect performance anomalies, predict potential issues, and recommend optimal maintenance strategies based on the actual condition and performance of a facility or pipeline.

With condition monitoring in a digital twin, midstream operators now have a way to:

Move from reactive to proactive and even predictive maintenance by identifying first-priority equipment for repairs and service and making sure the right equipment is procured and in stock.

Monitor pipelines, pumps, compressors, valves, tanks, and other components and devices for component degradation.

Visualisethe health and status of each asset and piece of equipment within the midstream network.

Track failures across processing facilities and pipelines, and use historical and real-time data to study trends and predict future failures.

Develop inspection programs and schedule these for multiple maintenance and operations teams in a single digital environment, making sure that conflicting work doesn’t occur in the same area at the same time.

Set alarms for operational parameters to discover signs of damage, leakage or other risks.

Mitigate human errors like mismarking pipelines before excavation work and opening a wrong valve by giving users one place to plan and report back on daily activities.

Train operators in a safe virtual environment through the simulation of different operational scenarios.

Monitor equipment remotely even when physical access to a site is limited.

Real-world use case

For a booster gas compressor (BGC), it was possible to calculate the estimated remaining useful life (RUL) and detect anomalous operating conditions several days prior to a defect being detected by the maintenance crew on the discharge cooler.

RUL estimation BGC
Anomaly detection BGC

Anomaly detection BGC motor trip

No anomaly detected in the trend indicating healthy BGC state

This use case helps us confirm the following benefits of a dynamic digital twin for real-time condition monitoring:

  • Detection of anomalous behavior of equipment as soon as possible.
  • Insightful overviews of trends and alerts that provide operational decision support.
  • Estimation of remaining useful life (RUL) that helps improve planning for maintenance downtime, maintenance scheduling, and more efficient use of equipment.
  • Optimal production and stable operation for a smarter, safer, and greener tomorrow.


By adopting the more proactive and predictive ways of working offered by a digital twin, midstream operators can move beyond reactive measures that are often too late and ineffective. A digital twin helps you see the future and prevent the past, providing a rich overview of the information you need to make the most informed and data-driven decisions for operations and maintenance.

Five ultimate impact areas of condition monitoring for midstream operators:

  1. Avoid costly and unexpected shutdowns through proactive maintenance. For one major energy operator, our digital twin technology, Kognitwin, resulted in a reduction of unplanned shutdowns saving 1-2 M USD/year.

  2. Identify maintenance patterns and root causes to implement long-term improvement strategies, resulting in procurement cost savings of up to 30% for maintenance turnaround planning.

  3. Give operators, maintenance teams and engineers instant and continuous insights into maintenance priorities. Reducing the time needed to search for information and create work packages can save up to 4 hours per worker each week, freeing up the workforce to focus on more value-adding tasks.

  4. Execute realistic risk assessments through simulation capabilities, without visiting the site. Midstream operators can expect to save up to 20% in engineering costs.

  5. Detect deviations and at-risk components immediately. For condition monitoring, Kognitwin helped detect potential errors in advance with 30% of alarms giving an early warning flag at least 15 minutes before the alarm.

See for yourself

Contact us for a demo of our solutions – let’s tackle your midstream challenges together.

About the author

Making Midstream future-ready: Perform condition monitoring and avoid costly shutdowns

Yorinde Lokin-Knegtering

Growth Manager Americas

View LinkedIn profile

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