(370g) Experimental Validation of Methods for Optimizing Remaining Useful Life (RUL)

Typically, production optimization requires larger flowrates and more extreme process conditions, which has a negative impact on the remaining useful life (RUL) of the process equipment. RUL is usually defined as the time that an asset, like a valve for example, is likely to operate before it requires maintenance. Clearly, there is a trade-off if one wants to maximize both production and RUL. The question that arises is: Is there a way to counterbalance these effects in an optimal operational strategy? Recently, [1] - [6] proposed methods that integrate equipment condition monitoring and prognostics into the process optimization problem. By applying a robust economic optimization strategy that incorporates erosion models, the authors were able to steer plant degradation actively during the simulations, preventing violation of health-critical constraints, while optimizing plant production.

In order to validate the proposed methods in a more realistic scenario, a lab rig has been designed, in which production optimization and accelerated life testing of critical components can be carried out. The rig set-up is based on an oil production system, a gas-lift oil well network. In the system, a mixture of water, mud/sand slurry and air is used for degrading an intrusive eroding probe in three “wells” in parallel. The eroding probe is made of plaster in order accelerate the visualization of the erosion effects.

This work describes the step-by-step development of the lab rig, starting on the design phase, going through the determination of the eroding material and finally discussing the set-up of the erosion measurement equipment, which is based on image analysis. Finally, preliminary results of the erosion models, which need to be included in robust economic optimization strategy, are presented.

[1] Adriaen Verheyleweghen, Julie Marie Gjøby, and Johannes Jäschke. “Health-aware operation of a subsea compression system subject to degradation”. In Computer Aided Chemical Engineering, volume 43, pages 1021–1026. Elsevier, 2018.4

[2] Adriaen Verheyleweghen and Johannes Jäschke. “Oil production optimization of several wells subject to choke degradation”. IFAC-PapersOnLine, 51(8):1–6,2018.5

[3] Adriaen Verheyleweghen and Johannes Jäschke. “Framework for combined diagnostics, prognostics and optimal operation of a subsea gas compression system”. IFAC-PapersOnLine, 50(1):15916–15921, 2017.2

[4] Adriaen Verheyleweghen and Johannes Jäschke. “Health-aware operation of a subsea gas compression system under uncertainty”. Foundations of Computer Aided Process Operations/Chemical Process Control,2017.3

[5] Teresa Escobet, Vicenç Puig, and Fatiha Nejjari. “Health aware control and model-based prognosis”. In 2012 20th Mediterranean Conference on Control & Automation (MED), pages 691–696. IEEE, 2012

[6] Eduardo Bento Pereira, Roberto Kawakami Harrop Galvão, and Takashi Yoneyama. “Model predictive control using prognosis and health monitoring of actuators”. In 2010 IEEE international symposium on industrial electronics, pages 237–243. IEEE, 2010.6T