Borehole Flow Monitoring using a Non-intrusive Passive Distributed Acoustic Sensing (DAS)
- Daniel Clark Finfer (Silixa Ltd) | Veronique Mahue (Silixa Ltd) | Sergey Shatalin (Silixa Ltd) | Tom Parker (Silixa Ltd) | Mahmoud Farhadiroushan (Silixa Ltd)
- Document ID
- Society of Petroleum Engineers
- SPE Annual Technical Conference and Exhibition, 27-29 October, Amsterdam, The Netherlands
- Publication Date
- Document Type
- Conference Paper
- 2014. Society of Petroleum Engineers
- ProductionÂ monitoring, Flow surveillance, Fiber optics
- 7 in the last 30 days
- 423 since 2007
- Show more detail
- View rights & permissions
|SPE Member Price:||USD 8.50|
|SPE Non-Member Price:||USD 25.00|
Historically in-well flow measurement has been challenged by downhole power requirements and post-installation inflexibility. Distributed acoustic sensing makes it possible to monitor the acoustic field along the entire length of a standard fiber optic cable, and therefore facilitate flow monitoring without any downhole electric power requirements. Further, the distributed nature of such systems enables post-installation adaptability as the production profile evolves. Partly as a result of this flexibility, distributed acoustic sensors have now started to gain momentum as a recognized solution for in-well flow surveillance.
In this paper, Silixa will present recent development work showing how distributed technology can enable high accuracy flow monitoring. Emerging results will be used to show how array processing of flow noise can be used to develop production data. Examples from the laboratory will be used to demonstrate these advanced techniques. It will be seen that advanced signal processing can be combined with knowledge concerning the physics of fluid-acoustic interactions to make determinations concerning the flow within a well. Finally, it will be shown that there exists strong promise for this upstream technology in a broad variety of well-types.
Effective in-well flow surveillance is fundamental to long-term field management. Flow data accumulated over time concerning the flow conditions within wells can help to identify regions exhibiting non-optimal production, which in turn can drive decisions concerning intervention and work-overs. Further, for injection wells, real-time feedback concerning downhole flow conditions can allow for varying of injection rate, which can facilitate greater producer efficiency and longer reservoir lifetime. It is however challenging to obtain well performance data which spans an extended time period or expansive length scale. Wireline production logging tools (PLT’s), for instance, can be used to perform in-well surveillance. However, PLT’s are expensive to operate, require the use of potentially-risky interventions, and provide only limited information along horizontal wells as a result of variable flow regimes. Further, the data gathered from a PLT represents a temporal “snap-shot” of well performance, which may not necessarily be highly precise in terms of flow rate. Additionally, PLT data does not provide information on temporal fluctuations seen during long-term production. Fixed-position permanent in-well flow meters can provide long-term surveillance capability which can be used to understand the fluctuations of total well performance with time. However, such devices can provide flow information from a single point only, and so are limited in their ability to deliver detail concerning the way in which zonal activity varies as the production profile evolves.
Distributed fiber optic sensors make it possible to monitor data gathered over time from along the entire length of a well. Distributed temperature sensor (DTS) technology, which is capable of measuring the temperature at every point along a fiber optic cable, has been in use for around two decades (e.g. Smolen & van der Spek, 2003). In those cases where the DTS unit is sufficiently sensitive to allow thermal effects accompanying flow phenomena to be observed, the temperature traces can be used to collect information concerning zonal production. DTS data however can be challenging to interpret in multi-phase situations and in highly deviated and horizontal wells.
|File Size||1 MB||Number of Pages||9|