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dc.contributor.authorKeith, Cody D.
dc.date.accessioned2022-07-23T21:03:57Z
dc.date.available2022-07-23T21:03:57Z
dc.date.issued2022-05
dc.identifier.urihttp://hdl.handle.net/11122/12938
dc.descriptionThesis (M.S.) University of Alaska Fairbanks, 2022en_US
dc.description.abstractPolymer flooding has become globally established as a potential enhanced oil recovery method for heavy oils. To determine whether this technology may be useful in developing the substantial heavy oil resources on the Alaska North Slope, a polymer flood field pilot commenced at the Milne Point Unit in August 2018. This study seeks to evaluate the results of the field pilot on a technical and economic basis. A reservoir simulation model is constructed and calibrated to predict the oil recovery performance of the pilot through machine-assisted reservoir simulation techniques. To replicate the early water breakthrough observed during waterflooding, transmissibility contrasts are introduced into the simulation model, forcing viscous fingering effects. In the ensuing polymer flood, these transmissibility contrasts are reduced to replicate the restoration of injection conformance during polymer flooding. Transmissibility contrasts are later reinstated to replicate fracture overextension interpreted in one of the producing wells. The calibrated simulation models produced at each stage of the history matching process are used to forecast oil recovery. These forecasts are used as input for economic analysis, incremental to waterflooding expectations. The simulation forecasts indicate that polymer flooding significantly increases the heavy oil production for this field pilot compared to waterflooding alone, yielding attractive project economics. However, meaningful variations between simulation scenarios demonstrate that a simulation model is only valid for prediction if flow behavior in the reservoir remains consistent with that observed during the history matched period. Critically, this means that a simulation model calibrated for waterflooding may not fully capture the technical and economic benefits of an enhanced oil recovery process such as polymer flooding. Subsequently, the simulation model and economic model are used in conjunction to conduct a sensitivity analysis for polymer flood design parameters, from which recommendations are provided for both the continued operation of the current field pilot and future polymer flood designs. The results demonstrate that a higher polymer concentration can be injected due to the development of fractures in the reservoir. The throughput rate should remain high without exceeding operating constraints. A calculated point-forward polymer utilization parameter demonstrates the decreasing efficiency of the polymer flood at later times in the pattern life. Future projects will benefit from starting polymer injection earlier in the pattern life. A pattern with tighter horizontal well spacing will observe a greater incremental benefit from polymer flooding.en_US
dc.description.sponsorshipU.S. Department of Energy, Office of Fossil Energy - National Energy Technology Laboratory grant DE-FE0031606en_US
dc.description.tableofcontentsChapter 1. Introduction -- Chapter 2. Technical evaluation of polymer flood pilot via reservoir simulation -- Chapter 3. Economic evaluation of polymer flood field pilot -- Chapter 4. Conclusions and recommendations.en_US
dc.language.isoen_USen_US
dc.subjectPolymer floodingen_US
dc.subjectPetroleum engineeringen_US
dc.subjectNorth Slopeen_US
dc.subjectHeavy oilen_US
dc.subjectEnhanced oil recoveryen_US
dc.subjectOil field floodingen_US
dc.subject.otherMaster of Science in Petroleum Engineeringen_US
dc.titleTechnical and economic evaluation of the first ever polymer flood field pilot to enhance the recovery of heavy oils on Alaska's North Slope via machine assisted reservoir simulationen_US
dc.typeThesisen_US
dc.type.degreemsen_US
dc.identifier.departmentDepartment of Petroleum Engineeringen_US
dc.contributor.chairZhang, Yin
dc.contributor.chairAhmadi, Mohabbat
dc.contributor.committeeDandekar, Abhijit
refterms.dateFOA2022-07-23T21:03:58Z


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