| Autor: |
John Lovell, Dalia Salim Abdallah, Rahul Mark Fonseca, Mark Grutters, Sameer Punnapala, Omar Kulbrandstad, Daniel Meza, Jorge Baez |
| Rok vydání: |
2021 |
| Zdroj: |
Day 3 Wed, November 17, 2021. |
| Popis: |
Asphaltene deposition presents a significant flow assurance to oil production in many parts of the Middle East and beyond. Until recently, there had been no intervention-free approach to monitor deposition in the asphaltene affected wells. This prompted ADNOC to sponsor MicroSilicon to develop of an intervention less real-time sensor device to monitor asphaltene deposition. This new state-of-the-art device is currently installed and automatically collecting data at the wellhead and nearby facilities of an ADNOC operated field. Historic ways of measuring asphaltene in oil relied upon laboratory processes that extracted the asphaltene using a combination of solvents and gravimetric techniques. Paramagnetic techniques offer a potentially simpler alternative because it is known that the spins per gram of an oil is a constant property of that oil, at least when the oil is at constant temperature and pressure. Taking the device to the field means that any interpretation needs to be made independent of these properties. Additionally, the fluid entering the sensor is multiphase and subject to varying temperature and pressure which raises challenges for the conversion of raw spectroscopic data into asphaltene quantity and particle size. These challenges were addressed with a combination of hardware, software and cloud-based machine learning technologies. Oil from over two dozen wells has been sampled in real-time and confirmed that the asphaltene percentage does not just vary from well to well but is also a dynamic aspect of production, with some wells having relatively constant levels and others showing consistent variation. One other well was placed on continuous observation and showed a decrease in asphaltene level following a choke change at the surface. Diagnostic data enhanced by machine learning complements the asphaltene measurement and provides a much more complete picture of the flow assurance challenge than had been previously been available. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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