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

Abstract

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.