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    Evaluation of CO2 Injection in Shale Gas Reservoirs through Numerical Reservoir Simulation and Supervised Machine Learning

    Mansi MKA 2023 Public.pdf (2.615Mb)
    Access Status
    Open access
    Authors
    Mansi, Moataz Khamees Abdelfattah
    Date
    2023
    Supervisor
    Sam Xie
    Christopher Lagat
    Type
    Thesis
    Award
    MPhil
    
    Metadata
    Show full item record
    Faculty
    Science and Engineering
    School
    WASM: Minerals, Energy and Chemical Engineering
    URI
    http://hdl.handle.net/20.500.11937/91978
    Collection
    • Curtin Theses
    Abstract

    CO2 geological storage is an important means to decarbonize the economy, but also expensive in field applications. CO2 injection into shale gas reservoirs can significantly increase the economic incentive by enhancing shale gas production through CO2 preferential adsorption in shales. This work presents a practical framework to evaluate and predict the CO2 adsorption process and CH4 production in shales through a combination of numerical reservoir simulation and supervised machine learning.

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