Pumping smarter via analytics and artificial intelligence
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Corie J. Allemand
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Corie Allemand
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Abstract

Midstream operators across the world can benefit from deploying sophisticated software technologies, especially analytics, AI, and machine learning. Properly applied, these technologies can improve and optimize pumping operations in terms of load management, power consumption, and scheduling.

This paper will introduce the “digital twin” concept. Enhancing the digitalization of pump stations and pipelines, plus adding more operational and scheduling intelligence, midstream operators can better align and fine-tune a facility’s power consumption and pump performance with the different batches of products moving through their pipelines.

Pipeline control centers already monitor vast amounts of data from their operations. This large amount of data must be transformed into smart data, increasing the operating visibility of pump stations, control room operators can drill down further to more closely monitor a pumping station’s equipment performance and set operating alerts should performance parameters be exceeded.

Software solutions can uncover anomalous behaviors in pump station equipment, it can issue alerts when they occur. These can trigger prescriptive or preventive maintenance before problems occur that could disrupt the pumping station’s operations or, worse, endanger the environment or personnel safety.

It’s also possible to tie-in the data to a conditioning monitoring maintenance program that only services equipment when its performance degrades, indicating maintenance is needed. This approach can save costly dispatches of technicians for routine scheduled maintenance, which equipment might not require. It can also save on spare parts, enabling a reduction in spare part inventories with a shift to just-in-time part deliveries.  

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