Data fusion framework for sand detection in pipelines

A. Abdelgawad, Zaher Merhi, Mohamed Elgamel, Magdy Bayoumi, Amal Zaki

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

Reliable sand detection is an important component of oil production system. In practice, produced sand in oil pipelines poses a serious problem in many production situations, since a small amount of sand in the produced fluid can result in significant erosion in a very short time stage. A new data fusion framework for sand detection in pipeline is presented. The framework is collecting data from oil pipeline using acoustic sensors (SENACO AS100) and Flow Analyzer (MC-II) in real time. The framework combines two modules: a wireless receiving and transmission (ReT) module and a data fusion module (DaF). The ReT module implementation is based on TinyOS and Crossbow MICAz motes. In order to optimize between the complexity and accuracy needs, DaF module is implemented using two methods; Fuzzy Art (FA) and Maximum Likelihood Estimator (MLE). The results show the efficient number of sensors needed and compare between FA and MLE redundant.

Original languageEnglish
Title of host publication2009 IEEE International Symposium on Circuits and Systems, ISCAS 2009
Pages2173-2176
Number of pages4
DOIs
StatePublished - 2009
Event2009 IEEE International Symposium on Circuits and Systems, ISCAS 2009 - Taipei, Taiwan, Province of China
Duration: May 24 2009May 27 2009

Publication series

NameProceedings - IEEE International Symposium on Circuits and Systems
ISSN (Print)0271-4310

Conference

Conference2009 IEEE International Symposium on Circuits and Systems, ISCAS 2009
Country/TerritoryTaiwan, Province of China
CityTaipei
Period05/24/0905/27/09

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