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Advancements in Foam Flow Modeling for Efficient Gas Well Production

This project, a collaborative effort between RPSEA and six major companies, aims to enhance the understanding of foam flow as an artificial lift method in tight, deep gas wells. Objectives include collecting experimental data on various foams, developing models to predict pressure drop, and establishing guidelines for surficant use. Currently, students from The University of Tulsa are engaged in large and small scale experiments. Future work will focus on building models to estimate gas holdup, liquid loading inception, and pressure drops in foam flow conditions.

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Advancements in Foam Flow Modeling for Efficient Gas Well Production

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  1. Foam Flow Projects Mohan Kelkar and Cem Sarica The University of Tulsa

  2. Outline • Introduction • Background • Objectives • Current Status • Future Work

  3. 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

  4. 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

  5. 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

  6. Current Status • One graduate student and two undergraduate students working on the project • Ayantayo Ajani – PhD Student • Chance Brashears • DhiyaShukri

  7. 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

  8. Current Status … • We have collected data in large scale facility for five different surfactants • We have collected data in small scale facility for five different surfactants • We have examined the effect of brine and temperature on some representative samples • We have just started the modeling process

  9. Future Work • 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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