ANSYS: How Oil and Gas Digital Twins Improve Prognostics Health Management

The oil and gas industry is always searching for ways to produce energy at lower costs. To achieve this goal, the industry can apply oil and gas digital twins to various industrial equipment. Physics-based digital twins provide prognostics and health management which enables system optimization and predictive maintenance.

The industry is familiar with sensor-based digital twins that offer users a window to an asset’s current environment, service life and internal/external loads. A physics-based digital twin, however, provides additional insights needed to understand the performance of equipment. Digital twins take sensor data and process it through systems simulations and embedded control software that mimic the reactions of the real-world asset. For instance, the industry can monitor a pipeline and use a digital twin to predict how erosion, corrosion, buckling and fatigue will affect the real-world asset. This data can then be used to optimize future designs, predict maintenance cycles, prevent spills, reduce downtime and improve throughput. In other words, oil and gas digital twins, supported by ANSYS physics-based simulations, are great tools to reduce operating costs and lower the risk of unplanned shutdowns.

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