Electrical resistance tomography-based multi-modality sensor and drift flux model for measurement of oil–gas–water flow
Abstract
Abstract: This paper proposes a novel method to measure each constituent of an oil–gas–water mixture in a water continuous flow, typically encountered in many processes. It deploys a dual-plane electrical resistance tomography sensor for measuring dispersed phase volume fraction and velocity; a gradiomanometer flow density meter and a drift flux model to estimate slip velocities; with absolute pressure and temperature measurements. These data are fused to estimate constituent volume flow rates. Other commonly used operational parameters can be further derived: water cut or water liquid ratio (WLR) and gas volume fraction (GVF). Trials are described for flow rates of water 5–10 m3 h−1; oil 2–10 m3 h−1 and gas 1–15 m3 h−1. The comparative results are included with published data from the Schlumberger Gould Research flow facility. The paper proposes the use of the described configuration for measurement of volume flow rates in oil–gas–water flows with an absolute error of ±10% within GVF 9%–85% and WLR > 45%.Citation
Rashed, S., Faraj, Y., Wang, M., & Wilkinson, S. (2022). Electrical resistance tomography-based multi-modality sensor and drift flux model for measurement of oil–gas–water flow. Measurement Science and Technology, 33(9), 094006. https://doi.org/10.1088/1361-6501/ac74a1Publisher
IOP PublishingAdditional Links
https://doi.org/10.1088/1361-6501/ac74a1Type
articleDescription
From IOP Publishing via Jisc Publications RouterHistory: received 2022-01-08, revised 2022-05-14, oa-requested 2022-05-16, accepted 2022-05-30, epub 2022-06-14, open-access 2022-06-14, ppub 2022-09-01
Publication status: Published
Funder: University of Chester; doi: http://dx.doi.org/10.13039/100010333
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Except where otherwise noted, this item's license is described as Licence for this article: http://creativecommons.org/licenses/by/4.0