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dc.contributor.advisorThomas Herring.en_US
dc.contributor.authorŞahin, Sedar Cihanen_US
dc.contributor.otherMassachusetts Institute of Technology. Department of Earth, Atmospheric, and Planetary Sciences.en_US
dc.date.accessioned2013-06-17T19:54:13Z
dc.date.available2013-06-17T19:54:13Z
dc.date.copyright2013en_US
dc.date.issued2013en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/79299
dc.descriptionThesis (S.M. in Geophysics)--Massachusetts Institute of Technology, Dept. of Earth, Atmospheric, and Planetary Sciences, 2013.en_US
dc.descriptionCataloged from PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references (p. 92-97).en_US
dc.description.abstractInSAR has been developed to estimate the temporal change on the surface of Earth by combining multiple SAR images acquired over the same area at different times. In the last two decades, in addition to conventional InSAR, numerous multiple acquisition InSAR techniques have been introduced, including permanent scatterer (PS) (Ferretti et al., 2001) and small baseline subset (SBAS) (Berardino et al., 2002). Stanford method for persistent scatterers (StaMPS) (Hooper, 2006) is another multiple acquisition method that has been developed for estimating ground deformation and differs from the permanent scatterer technique through the method used for pixel selection. In this project, we used the SBAS method to detect the surface deformation over a hydrocarbon reservoir in Adiyaman Providence, Turkey. The SBAS technique is performed on combinations of SAR images that are characterized by small orbital distances with large time intervals. By applying singular value decomposition (SVD), the temporal sampling rate is increased and those subsets are connected. We applied the SBAS method to five ALOS-PALSAR fine-beam dual (FBD) mode images, and removed the topographic phase by using a 3 arc-sec SRTM digital elevation model (DEM). The atmospheric artifacts are determined and filtered out based on available spatial and temporal information on processed data. Our analysis has revealed that due to the effective mitigation measures taken by the oil company, the maximum observed LOS displacement velocity in the oil field is 5 mm/yr with a likely uncertainty of a similar magnitude in the period of 2007-2010. The high uncertainty estimate is due to the other spatially correlated signals of similar and larger magnitude seen in regions outside of the oil field.en_US
dc.description.statementofresponsibilityby Sedar Cihan Sahin.en_US
dc.format.extent97 p.en_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsM.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectEarth, Atmospheric, and Planetary Sciences.en_US
dc.titleSurface deformation analysis over a hydrocarbon reservoir using InSAR with ALOS-PALSAR dataen_US
dc.title.alternativeSurface deformation analysis over a hydrocarbon reservoir using Interferometric Synthetic Aperture Radar with Advanced Land Observing Satellite-Phased Array type L-band Synthetic Aperture Radar dataen_US
dc.typeThesisen_US
dc.description.degreeS.M.in Geophysicsen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Earth, Atmospheric, and Planetary Sciences
dc.identifier.oclc847522084en_US


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