• Login
    • Submit
    View Item 
    •   Repository Home
    • UT Electronic Theses and Dissertations
    • UT Electronic Theses and Dissertations
    • View Item
    • Repository Home
    • UT Electronic Theses and Dissertations
    • UT Electronic Theses and Dissertations
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Decision support for enhanced oil recovery projects

    Icon
    View/Open
    ANDONYADIS-THESIS.pdf (18.19Mb)
    Date
    2010-08
    Author
    Andonyadis, Panos
    Share
     Facebook
     Twitter
     LinkedIn
    Metadata
    Show full item record
    Abstract
    Recently, oil prices and oil demand are rising and are projected to continue to rise over the long term. These trends create great potential for enhanced oil recovery methods that could improve the recovery efficiency of reservoirs all over the world. The greatest challenges for enhanced oil recovery involve the technical uncertainty with design and performance, and the high financial risk. Pilot tests can help mitigate the risk associated with such projects; however, there is a question about the value of information from the tests. Decision support can provide information about the value of an enhanced oil recovery project, which can assist with alleviating financial risk and create more potential opportunities for the technology. The first objective of this study is to create a new simplified method for modeling oil production histories of enhanced oil recovery methods. The method is designed to satisfy three criteria: 1) it allows for quick simulations based on only a few physically meaningful input parameters; 2) it can create almost any potential type of realistic production history that may be realized during a project; and 3) it applies to all nonthermal enhanced oil recovery methods, including surfactant-polymer, alkali-surfactant polymer, and CO₂ floods. The developed method is capable of creating realistic curves with only four unique parameters. The second objective is to evaluate the predictive method against data from pilot and field scale projects. The evaluations demonstrate that the method can fit most realistic production histories as well as provided ranges for the input parameters. A sensitivity analysis is also performed to assist with determining how all of the parameters involved with the predictive method and the economic model influence the forecasted value for a project. The analysis suggests that the price of oil, change in oil saturation, and the size of the reservoir are the most influential parameters. The final objective is to establish a method for a decision analysis that determines the value of information of a pilot for enhanced oil recovery. The analysis uses the predictive method and economic model for determining economic utilities for every potential outcome. It uses a decision-based method to ensure that the non-informative prior probability distributions have an unbiased, consistent, and rational starting point. A simple example demonstrating the process is discussed and it is used to show that a pilot test provides some valuable information when there is minimal prior information. For future work it is recommended that more evaluations are performed, the decision analysis is expanded to include more input parameters, and a rational and logical method is developed for determining likelihood functions from existing information.
    Department
    Civil, Architectural, and Environmental Engineering
    Description
    text
    Subject
    Enhanced oil recovery
    Oil recovery
    Surfactant flooding
    Polymer flooding
    Alkali flooding
    Carbonate flooding
    CO2 flooding
    Geotechnical engineering
    URI
    http://hdl.handle.net/2152/ETD-UT-2010-08-1560
    Collections
    • UT Electronic Theses and Dissertations

    Related items

    Showing items related by title, author, creator and subject.

    • Experimental investigation of the effect of increasing the temperature on ASP flooding 

      Walker, Dustin Luke (2011-12)
      Chemical EOR processes such as polymer flooding and surfactant polymer flooding must be designed and implemented in an economically attractive manner to be perceived as viable oil recovery options. The primary expenses ...
    • Development of an equation-of-state thermal flooding simulator 

      Varavei, Abdoljalil (2009-05)
      In the past thirty years, the development of compositional reservoir simulators using various equations of state (EOS) has been addressed in the literature. However, the development of compositional thermal simulators ...
    • Assess the risk of extreme floods : case study : Houston, Texas 

      Gao, Yang, M.S. in Engineering; 0000-0002-4499-8592 (2018-01-26)
      The catastrophic flooding caused by the Hurricane Harvey, ranked as the third 500-year floods in three years in Houston Area, has inflicted nearly $200 billion in damage. The traditional Hydro-Economical Model of a specific ...
    University of Texas at Austin Libraries
    • facebook
    • twitter
    • instagram
    • youtube
    • CONTACT US
    • MAPS & DIRECTIONS
    • JOB OPPORTUNITIES
    • UT Austin Home
    • Emergency Information
    • Site Policies
    • Web Accessibility Policy
    • Web Privacy Policy
    • Adobe Reader
    Subscribe to our NewsletterGive to the Libraries

    © The University of Texas at Austin

    Browse

    Entire RepositoryCommunities & CollectionsDate IssuedAuthorsTitlesSubjectsDepartmentThis CollectionDate IssuedAuthorsTitlesSubjectsDepartment

    My Account

    Login

    Information

    AboutContactPoliciesGetting StartedGlossaryHelpFAQs

    Statistics

    View Usage Statistics
    University of Texas at Austin Libraries
    • facebook
    • twitter
    • instagram
    • youtube
    • CONTACT US
    • MAPS & DIRECTIONS
    • JOB OPPORTUNITIES
    • UT Austin Home
    • Emergency Information
    • Site Policies
    • Web Accessibility Policy
    • Web Privacy Policy
    • Adobe Reader
    Subscribe to our NewsletterGive to the Libraries

    © The University of Texas at Austin