Multiphase flow occurs in almost all oil and gas wells and production installations. The past three decades have seen intense efforts to develop empirical correlations and modelling tools to improve the ability to predict multiphase-flow behaviour with greater accuracy. The empirical approach typically involves flowing fluids at carefully measured flow rates through a pipe, observing the flow pattern, and measuring liquid holdup and pressure drop. Using the measured data, empirical correlations are developed for predicting flow patterns, liquid holdup, and friction factor, and a pressure gradient equation is developed that uses these empirical correlations.

In its operations on Al-Khalij field, which is operated under a Production Sharing Agreement (PSA) with Qatar Petroleum (QP), Total E&P Qatar experience multiphase flow in main production lines, with a resulting pressure loss which has to be accurately predicted.

As part of the Qatar Science & Technology Park (QSTP), Total Research Centre - Qatar (TRC-Q) has research collaborations with different partners. In this work, we present the results of a joint research project between the Petroleum Engineering program at Texas A&M University in Qatar and the Smart Metering Project team from TRC-Q.

A literature review of available multiphase flow correlations has been performed first. Secondly, limitations and range of applicability of these correlations were evaluated. We then identified the most applicable correlation to specific conditions of a pipeline in Qatar's Al-Khalij field. This included gas-oil-water flow in a large-diameter multi-kilometre-long pipeline which passes through a hilly terrain (slightly deviated from horizontal). Our Analyses show that Beggs and Brill set of equations estimates pressure gradient with the least error among other correlations for these conditions. To improve the correlation's accuracy, we divided the pipeline into several segments with an optimum length to minimize the error and ensure computation efficiency. We developed a code to implement this correlation to simulate the multiphase flow inside the pipe. We could obtain pressure and phase flow rates along the pipeline. Also, a sensitivity analysis of some key parameters was performed. The model provided good agreement with measured pressure at the end of the pipeline.


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