This webinar discussed how to effectively simulate CO2 EOR processes by highlighting how CMG's dynamic modelling tools support the successful implementation of CO2 EOR processes.
Carbon Dioxide Enhanced Oil Recovery (CO2 EOR) addresses the decades long challenge of declining oil production while effectively reducing Greenhouse Gas Emissions (GHG). The strategic deployment of CO2 EOR projects requires an assessment of incremental oil recovery, including several economic factors and a performance model. Traditionally, performance models use the empirical and semi-analytical approaches which provide a quick assessment on a large scale; however, these models lack several important CO2 EOR mechanisms thereby reducing the accuracy of results. By applying advanced reservoir modelling, you will effectively model the CO2 EOR process and accurately predict incremental oil recovery.
Recent computer technology advances enable the application of dynamic modelling for the design of CO2 EOR processes or any other EOR technique. In fact, successful CO2 EOR implementation requires a simulation model that captures all the physics and important mechanisms, including: multiphase solubility, miscible displacement, three-phase flow, and rock-fluid interactions, etc. A dynamic reservoir model will help you understand how the physics and/or mechanisms impact performance, and provides the opportunity to run sensitivity, optimization, and uncertainty analysis to evaluate different operating strategies, such as well injection patterns and injection rates. By combining a dynamic reservoir model with CMOST AI, you will be able to select the optimum design based on your company’s field development strategies for CO2 EOR projects.
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