Knowledge Discovery for Classification of Three-Phase Vertical Flow Patterns of Heavy Oil from Pressure Drop and Flow Rate Data

المؤلفون المشاركون

Bannwart, Antonio C.
Serapião, Adriane B. S.

المصدر

Journal of Petroleum Engineering

العدد

المجلد 2013، العدد 2013 (31 ديسمبر/كانون الأول 2013)، ص ص. 1-8، 8ص.

الناشر

Hindawi Publishing Corporation

تاريخ النشر

2012-12-19

دولة النشر

مصر

عدد الصفحات

8

التخصصات الرئيسية

علم المواد والمعادن

الملخص EN

This paper focuses on the use of artificial intelligence (AI) techniques to identify flow patterns acquired and recorded from experimental data of vertical upward three-phase pipe flow of heavy oil, air, and water at several different combinations, in which water is injected to work as the continuous phase (water-assisted flow).

We investigate the use of data mining algorithms with rule and tree methods for classifying real data generated by a laboratory scale apparatus.

The data presented in this paper represent different heavy oil flow conditions in a real production pipe.

نمط استشهاد جمعية علماء النفس الأمريكية (APA)

Serapião, Adriane B. S.& Bannwart, Antonio C.. 2012. Knowledge Discovery for Classification of Three-Phase Vertical Flow Patterns of Heavy Oil from Pressure Drop and Flow Rate Data. Journal of Petroleum Engineering،Vol. 2013, no. 2013, pp.1-8.
https://search.emarefa.net/detail/BIM-495398

نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)

Serapião, Adriane B. S.& Bannwart, Antonio C.. Knowledge Discovery for Classification of Three-Phase Vertical Flow Patterns of Heavy Oil from Pressure Drop and Flow Rate Data. Journal of Petroleum Engineering No. 2013 (2013), pp.1-8.
https://search.emarefa.net/detail/BIM-495398

نمط استشهاد الجمعية الطبية الأمريكية (AMA)

Serapião, Adriane B. S.& Bannwart, Antonio C.. Knowledge Discovery for Classification of Three-Phase Vertical Flow Patterns of Heavy Oil from Pressure Drop and Flow Rate Data. Journal of Petroleum Engineering. 2012. Vol. 2013, no. 2013, pp.1-8.
https://search.emarefa.net/detail/BIM-495398

نوع البيانات

مقالات

لغة النص

الإنجليزية

الملاحظات

Includes bibliographical references

رقم السجل

BIM-495398