Driving Flow Assurance Through Effective KPI Setting, Analytics and Digital Twins

In the past, when oil prices were higher, upstream producers were very focused on managing their assets for maximum production volume. However, in the current and forecast business environment, there is a much greater need to manage for value. Maximum value is not always maximum flow; this can sometimes lead to value destruction. So what does managing for value mean for an upstream producer?

It’s much easier to cut costs than to grow revenues, yet in many cases revenue growth has the biggest potential to impact return on capital employed. Costs can’t be ignored but the main thrust should be on growth and the most cost effective investment strategy to get you there. One such value hotspot that is a key growth pathway for enhanced production is flow assurance in pipelines and networks.

The formation of hydrates is a major concern for maintaining integrity of pipeline flow which itself is the life blood of the profitability of an upstream system. The threat to flow assurance is particularly high in offshore or deepwater operations where fluids can cool to particularly low temperatures, introducing the real threat of rapid solids formation in the flowline or in the producing facilities. This can result in decreased production levels, equipment damage, safety issues, and even plant shutdown. To prevent or mitigate these risks, operators often inject chemical inhibitors into the hydrocarbon flow.

With the help of field data and digital twin technology, inhibitor dosing can easily become a dynamic process that allows for more sustainable production optimization. The key is a digital twin that mirrors the present in terms of the pipelines and networks, including wells, chokes, flowlines and a wide range of processing equipment, and which performs its calculations in compositional mode with a rigorous thermodynamic engine. With this capability, it is able to solve for the composition of all the phases and their flowrates, allowing for full reconstruction of the flow and production conditions across the whole network.

Any modification of production conditions can be tested and evaluated holistically through the simulation of the new operating scenario in the digital twin before being implemented. Well-informed decision-making and operations optimization therefore becomes a simple routine evaluation of KPIs and operating parameters, against which current operations and new operating strategies can be monitored and tested.