Intelligent multiphase flow measurement

The oil and gas industry’s goal of developing high performing multiphase flow metering systems capable of reducing costs in the exploitation of marginal oil and gas reserves, especially in remote environments, cannot be over emphasised. Development of a cost-effective multiphase flow meter to determ...

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Bibliographic Details
Main Author: Ibrahim, Abba A.
Other Authors: Yeung, Hoi
Published: Cranfield University 2009
Subjects:
532
Online Access:http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.512783
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spelling ndltd-bl.uk-oai-ethos.bl.uk-5127832018-05-12T03:24:47ZIntelligent multiphase flow measurementIbrahim, Abba A.Yeung, Hoi2009The oil and gas industry’s goal of developing high performing multiphase flow metering systems capable of reducing costs in the exploitation of marginal oil and gas reserves, especially in remote environments, cannot be over emphasised. Development of a cost-effective multiphase flow meter to determine the individual phase flow rates of oil, water and gas was experimentally investigated by means of low cost, simple and non-intrusive commercially available sensors. Features from absolute pressure, differential pressure (axial), gamma densitometer, conductivity and capacitance meters, in combination with pattern recognition techniques were used to detect shifts in flow conditions, such as flow structure, pressure and salinity changes and measured multiphase flow parameters simultaneously without the need for preconditioning or prior knowledge of either phase. The experiments were carried out at the National Engineering Laboratory (NEL) Multiphase facility. Data was sampled at 250 Hz across a wide spectrum of flow conditions. Fluids used were nitrogen gas, oil (Forties and Beryl crude oil – D80, 33o API gravity) and water (salinity levels of 50 and 100 g/l MgSO4). The sensor spool piece was horizontally mounted on a 4-inch (102mm) pipe, and the database was obtained from two different locations on the flow loop. The ability to learn from ‘experience’ is a feature of neural networks. The use of neural networks allows re-calibration of the measuring system on line through a retraining process when new information becomes available. Some benefits and capabilities of intelligent multiphase flow systems include:  Reduction in the physical size of installations.  Sensor fusion by merging the operating envelopes of different sensors employed provided even better results.  Monitoring of flow conditions, not just flow rate but also composition of components.  Using conventional sensors within the system will present the industry with a much lower cost multiphase meter, and better reliability. Comment [HS1]: I think this word should be measured to make the sentence read correctly.532Cranfield Universityhttp://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.512783http://dspace.lib.cranfield.ac.uk/handle/1826/4082Electronic Thesis or Dissertation
collection NDLTD
sources NDLTD
topic 532
spellingShingle 532
Ibrahim, Abba A.
Intelligent multiphase flow measurement
description The oil and gas industry’s goal of developing high performing multiphase flow metering systems capable of reducing costs in the exploitation of marginal oil and gas reserves, especially in remote environments, cannot be over emphasised. Development of a cost-effective multiphase flow meter to determine the individual phase flow rates of oil, water and gas was experimentally investigated by means of low cost, simple and non-intrusive commercially available sensors. Features from absolute pressure, differential pressure (axial), gamma densitometer, conductivity and capacitance meters, in combination with pattern recognition techniques were used to detect shifts in flow conditions, such as flow structure, pressure and salinity changes and measured multiphase flow parameters simultaneously without the need for preconditioning or prior knowledge of either phase. The experiments were carried out at the National Engineering Laboratory (NEL) Multiphase facility. Data was sampled at 250 Hz across a wide spectrum of flow conditions. Fluids used were nitrogen gas, oil (Forties and Beryl crude oil – D80, 33o API gravity) and water (salinity levels of 50 and 100 g/l MgSO4). The sensor spool piece was horizontally mounted on a 4-inch (102mm) pipe, and the database was obtained from two different locations on the flow loop. The ability to learn from ‘experience’ is a feature of neural networks. The use of neural networks allows re-calibration of the measuring system on line through a retraining process when new information becomes available. Some benefits and capabilities of intelligent multiphase flow systems include:  Reduction in the physical size of installations.  Sensor fusion by merging the operating envelopes of different sensors employed provided even better results.  Monitoring of flow conditions, not just flow rate but also composition of components.  Using conventional sensors within the system will present the industry with a much lower cost multiphase meter, and better reliability. Comment [HS1]: I think this word should be measured to make the sentence read correctly.
author2 Yeung, Hoi
author_facet Yeung, Hoi
Ibrahim, Abba A.
author Ibrahim, Abba A.
author_sort Ibrahim, Abba A.
title Intelligent multiphase flow measurement
title_short Intelligent multiphase flow measurement
title_full Intelligent multiphase flow measurement
title_fullStr Intelligent multiphase flow measurement
title_full_unstemmed Intelligent multiphase flow measurement
title_sort intelligent multiphase flow measurement
publisher Cranfield University
publishDate 2009
url http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.512783
work_keys_str_mv AT ibrahimabbaa intelligentmultiphaseflowmeasurement
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