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