Foam flow projects
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Foam Flow Projects. Mohan Kelkar and Cem Sarica The University of Tulsa. Outline. Introduction Background Objectives Current Status Future Work. Introduction. Foam flow is the most suitable artificial lift method for many tight, deep, gas wells

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Foam Flow Projects

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Foam flow projects

Foam Flow Projects

Mohan Kelkar and Cem Sarica

The University of Tulsa


Outline

Outline

  • Introduction

  • Background

  • Objectives

  • Current Status

  • Future Work


Introduction

Introduction

Foam flow is the most suitable artificial lift method for many tight, deep, gas wells

No correlation exists for pressure drop prediction in foam flow

Need a model to correctly predict the rate-pressure drop relationship under foam flow conditions

Need to know the limits of foam flow application


Background

Background

This project is a joint effort between funding by RPSEA and six companies

The six member companies are: Chevron, Marathon, Shell, ConocoPhillips, Nalco, and MultiChem

The Project got officially kicked off in December, 2010 and have been extended through December of 2014


Objectives of the project

Objectives of the Project

  • Collect experimental foam flow data under controlled conditions for two different tubing sizes and five different foams

  • Measure surface tension, viscosity and foam stability

  • Develop comprehensive correlation to predict pressure drop under foam flow conditions

  • Develop guidelines for using appropriate concentration of surfactant as well as minimum gas-liquid ratios

  • Validate the model by comparing the results with field data provided by participating companies


Current status

Current Status

  • Three graduate students are working or have worked on the project

    • Shu Luo – PhD Student, (finished Dec 2013)

    • Ayantayo Ajani – PhD Student

    • Anton Skopich – MS Student (finished Dec 2012)


Current status1

Current Status …

  • The project is divided into three phases

    • Experimental data in large scale facility

    • Experimental data in small scale facility

    • Modeling of the data


Current status2

Current Status …

  • We have collected data in large scale facility for three different surfactants and at various concentrations

  • We have collected data in small scale facilities for three surfactants at various concentrations. In addition, we have also collected data including effects of brine concentration and temperature

  • A new definition of liquid loading is introduced and a new method to predict liquid loading has been proposed. The method is validated with large amount of field data.


Future work

Future Work

  • Data will be collected on two additional surfactants in both small scale and large scale facilities

  • Model will be built to estimate gas holdup in large scale facility based on small scale data

  • Model will be built to understand the inception of liquid loading under foam flow

  • Model will be built to estimate pressure drop for foam flow conditions


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