J. Lovell, O. Kulbrandstad, A. Haun, J.H. Alzate
MIcroSilicon,
United States
Keywords: spectroscopy, IoT, Energy
Summary:
In the context of chemical processes, an inability to measure a certain component in real-time creates challenges and, perhaps opportunities, for optimization. This has proven true in aspects of the chemical management of flow assurance in the oilfield, wherein asphaltenic particles precipitate and cause significant fouling and obstruction to flow. The oilfield industry has developed measurement techniques on aspects of asphaltenes in solution, but has not previously been able to make online measurements pertinent to the asphaltene itself. This changed with the discovery that a real-time measurement of fluid paramagnetism could be used to infer asphaltene conveyance. Spectroscopic devices have now been deployed in US Land, Canda, Middle East, Central America and Offshore Gulf of Mexico. The overall spectrum is transmitted by the IoT software to the cloud where machine learning is used to extract information needed for robust flow assurance. One surprise is that the measurement turns out to be quite dynamic. For example, the asphaltene might alternatively deposit inside a pipe and then slough off, which gives a sinusoidal variation in the spectral amplitude. Wells can give a characteristic dynamic pattern in the few days before the wellhead completely seizes up due to deposition, which gives significantly earlier warning than can be seen from pressure gauges. Operators are gaining confidence in the measurement and beginning to incorporate the digital data into control loops to optimize their chemical management process. Real-time paramagnetic measurements also have applicability to fouling and deposition within surface refineries and chemical plants. The combination of quantum chemical paramagnetic sensing, combined with real-time IOT, cloud storage and machine learning led to the sensor winning the iChemE Global Research and ADIPEC Best Innovation awards in 2021.