Decision support for enhanced oil recovery projects

dc.contributor.advisorGilbert, Robert B. (Robert Bruce), 1965-en
dc.contributor.committeeMemberLake, Larry W.en
dc.creatorAndonyadis, Panosen
dc.date.accessioned2011-02-14T18:12:07Zen
dc.date.accessioned2011-02-14T18:13:04Zen
dc.date.accessioned2017-05-11T22:21:18Z
dc.date.available2011-02-14T18:12:07Zen
dc.date.available2011-02-14T18:13:04Zen
dc.date.available2017-05-11T22:21:18Z
dc.date.issued2010-08en
dc.date.submittedAugust 2010en
dc.date.updated2011-02-14T18:13:05Zen
dc.descriptiontexten
dc.description.abstractRecently, 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.en
dc.description.departmentCivil, Architectural, and Environmental Engineeringen
dc.format.mimetypeapplication/pdfen
dc.identifier.urihttp://hdl.handle.net/2152/ETD-UT-2010-08-1560en
dc.language.isoengen
dc.subjectEnhanced oil recoveryen
dc.subjectOil recoveryen
dc.subjectSurfactant floodingen
dc.subjectPolymer floodingen
dc.subjectAlkali floodingen
dc.subjectCarbonate floodingen
dc.subjectCO2 floodingen
dc.subjectGeotechnical engineeringen
dc.titleDecision support for enhanced oil recovery projectsen
dc.type.genrethesisen

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