Home Project-material COMPARATIVE ANALYSIS OF VOID FRACTION CORRELATIONS FOR HIGH VISCOSITY OIL DATA IN HORIZONTAL PIPELINE

COMPARATIVE ANALYSIS OF VOID FRACTION CORRELATIONS FOR HIGH VISCOSITY OIL DATA IN HORIZONTAL PIPELINE

Dept: CHEMICAL ENGINEERING File: Word(doc) Chapters: 1-5 Views: 3

Abstract

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CHAPTER ONE

1 INTRODUCTION

The oil and gas industry is increasingly looking towards unconventional

resources like heavy oil to help satisfy world energy demand as conventional

reserves are continuously depleted due to several years of production and

consumption. Viscous oil hydrodynamic characteristics are different from

conventional oil (light) due mainly to its physical properties .As a result of these

significantly different physical properties, heavy oil is more challenging to

produce and transport. The major implication of these differences is seen in the

design of heavy oil systems as well as in the implementation of technologies

which were mostly developed on the basis of hydrodynamic characteristics of

liquid oil.

High-viscosity oils are discovered and produced all around the world.

High-viscosity or “heavy oil” has become one of the most important future

hydrocarbon resources, with ever-increasing world energy demand and depletion

of conventional oils.

Almost all flow models have viscosity as an intrinsic variable. Two-phase

flows are expected to exhibit significantly different behavior for higher viscosity

oils. Many flow behaviors will be affected by the liquid viscosity, including droplet

formation, surface waves, bubble entrainment, slug mixing zones, and even

three-phase stratified flow. Furthermore, the impact of low-Reynolds-number oil

flows in combination with high-Reynolds-number gas and water flows may yield

new flow patterns and concomitant pressure-drop behaviors.

Void fraction prediction in high viscous liquid is of great importance .This

is because most existing correlations for predicting two phase flow parameters

were developed based on observations from low viscosity liquid gas flows which

have different hydrodynamic features compared to high viscosity liquid gas flows.

Consideration of these prediction models will ensure that pressure drop is

accurately predicted (Oyewole 2009)

2

Water is a low viscosity fluid; syrup is a high viscosity fluid. With oil, like

syrup, as you increase the temperature, the viscosity lowers, meaning it flows

faster, or more easily.

The most common unit of measure for viscosity is the Kinematic viscosity

and this is usually quoted in data sheets at 40°C and 100°C. The commonly used

unit of measure is centistokes but the correct SI unit of measure is mm2/s.

Absolute Viscosity is a measure of a fluid’s internal resistance to flow and

may be thought of as a measure of fluid friction and of the oil’s film strength to

support a load.

Dynamic or Absolute Viscosity: 1 milliPascal second (mPa·s) = 1 centi-Poise

(cP)

1.1 Statement of problem

With the decline of conventional oil reserves, heavy oil with significantly high

viscosity is seen as a major potential resource to meet the world increasing

energy demand .Void fraction prediction in high viscous liquid is of great

importance. This is because most existing empirical correlations for prediction

two phase flow parameters were developed based on observations from low

viscosity liquid-gas flows which have different hydrodynamic features compared

to high viscosity liquid –gas flows. Consideration of these prediction models will

ensure that pressure drop is accurately predicted. This will have significant impact

on the design and specification of downstream facilities.

1.2 Aim

The project aims to carry out an appraisal of existing void fraction correlations

using data for high viscosity oil gas two phase flows in horizontal pipes.

3

1.3 Objectives

1. To compare high viscosity void fraction data with those of prediction from

existing correlations.

2. To carry out a detailed statistical analysis of these correlations.

3. To determine the best performing ones for high viscous oil data.

1.4 Justification

1. Increased growth in global energy consumption.

2. Depleting light resources.

3. Reserves of heavy resources.

4. The need for proper understanding of the behaviour of heavy oil.


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